Nuclear Cardiac Imaging: Principles and Applications [6 ed.] 0190095652, 9780190095659

Citation preview

 

N UC L E A R CA RDI AC I MAGI NG

 

 

NUCLEAR CARDIAC IMAGING Principles and Applications SIXTH EDITION

Ami E. Iskandrian and Fadi G. Hage

 

Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and certain other countries. Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America. © Oxford University Press 2024 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above. You must not circulate this work in any other form and you must impose this same condition on any acquirer. CIP data is on file at the Library of Congress ISBN 978–​0–​19–​009565–​9 DOI: 10.1093/​med/​9780190095659.001.0001 This material is not intended to be, and should not be considered, a substitute for medical or other professional advice. Treatment for the conditions described in this material is highly dependent on the individual circumstances. And, while this material is designed to offer accurate information with respect to the subject matter covered and to be current as of the time it was written, research and knowledge about medical and health issues is constantly evolving and dose schedules for medications are being revised continually, with new side effects recognized and accounted for regularly. Readers must therefore always check the product information and clinical procedures with the most up-​to-​date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulation. The publisher and the authors make no representations or warranties to readers, express or implied, as to the accuracy or completeness of this material. Without limiting the foregoing, the publisher and the authors make no representations or warranties as to the accuracy or efficacy of the drug dosages mentioned in the material. The authors and the publisher do not accept, and expressly disclaim, any responsibility for any liability, loss, or risk that may be claimed or incurred as a consequence of the use and/​or application of any of the contents of this material. Printed by Integrated Books International, United States of America

 

To our wives, Sulaf Hage, MS, MD, and Greta P. Iskandrian, MD And to our children, their spouses and children (our grandchildren) Alexander, Gabrielle, and Diana Hage Basil Iskandrian and Kimberly Iskandrian (Szabba, Luca, and Roan) Susan Buckingham, MD, and Brendhan Buckingham, MD (Ella, Lilia, Ava, and Ian) Kristen Connell, PhD, and Brian Connell (Beatrice and Simone)

 

 

CONTENTS

Preface Contributors

ix xi

SECTION I.  HISTORICAL, TECHNICAL, AND PHYSIOLOGIC CONSIDERATIONS 1. NUCLEAR CARDIOLOGY: HISTORY AND MILESTONES

3

13

38

61

87

126

Milena J. Henzlova, Sean R. McMahon, and W. Lane Duvall 7. ARTIFACTS

152

171

Henry Gewirtz 187

Heinrich R. Schelbert

Juliana Brenande de Oliveira Brito, Gary R. Small, Kathryn J. Ascah, R. Glenn Wells, and Terrence D. Ruddy

Gregory S. Thomas and L. Samuel Wann

338

17. ROLE OF PET IN DIAGNOSIS AND RISK ASSESSMENT IN PATIENTS WITH KNOWN OR SUSPECTED CAD

357

18. NUCLEAR CARDIAC IMAGING IN WOMEN

379

19. MYOCARDIAL VIABILITY ASSESSMENT BY NUCLEAR TECHNIQUES

398

SECTION III.   ROLE OF NUCLEAR IMAGING BEYOND CAD 20. IMAGING DYSSYNCHRONY

425

Alessia Gimelli and Riccardo Liga

10. MEASUREMENT OF MYOCARDIAL BLOOD FLOW BY SPECT 208

11. TREADMILL EXERCISE TESTING

16. EVALUATION OF PATIENTS WITH CHEST PAIN IN THE EMERGENCY DEPARTMENT

Vasken Dilsizian, Ines Valenta, and Thomas H. Schindler

SECTION II.  DIAGNOSIS AND RISK ASSESSMENT

9. MEASUREMENT OF MYOCARDIAL BLOOD FLOW BY PET

322

Viviany R. Taqueti and Ana Carolina do A. H. de Souza

William A. Van Decker

8. REGULATION OF MYOCARDIAL BLOOD FLOW

15. SPECT MPI AND RISK ASSESSMENT BEFORE NON-​ CARDIAC SURGERY

Christiane Wiefels, Brian A. Mc Ardle, Jennifer M. Renaud, Robert A. deKemp, Rob S. B. Beanlands, and Steven Promislow

Steven Port 6. GATED SPECT MPI: IMAGING PROTOCOLS AND ACQUISITIONS; PROCESSING AND QUANTIFICATION

303

Alberto Cuocolo, Emilia Zampella, Valeria Gaudieri, and Roberta Assante

Elona Rrapo Kaso and Jamieson M. Bourque

Ran Klein, Robert A. deKemp, Benjamin Rotstein, and Keiichiro Yoshinaga 5. RADIONUCLIDE ANGIOGRAPHY

14. SPECT MPI FOR RISK ASSESSMENT IN SPECIAL GROUPS: DIABETES MELLITUS, KIDNEY TRANSPLANT, LIVER TRANSPLANT, ASYMPTOMATIC, OBESE

Daniel C. Fisher and Lawrence M. Phillips

James R. Galt, Ernest V. Garcia and Ji Chen 4. KINETICS OF CONVENTIONAL AND NEW CARDIAC RADIOTRACERS

280

Javier Gomez and Rami Doukky

Paul H. Murphy and James R. Galt 3. SPECT AND PET INSTRUMENTATION: CONVENTIONAL AND NEW

250

Efstathia Andrikopoulou, Ami E. Iskandrian, and Fadi G. Hage 13. DIAGNOSIS AND RISK ASSESSMENT WITH SPECT MPI

Barry L. Zaret and Frans J. Th. Wackers 2. RADIATION PHYSICS AND RADIATION SAFETY

12. PHARMACOLOGIC STRESS TESTING

21. IMAGING MYOCARDIAL INNERVATION BY SPECT AND PET

445

Mark I. Travin 22. IMAGING SARCOID HEART DISEASE 230

David G. Rosenthal and Paco E. Bravo

466

 

23. IMAGING AMYLOID HEART DISEASE

481

John P. Bois, Martha Grogan, and Panithaya Chareonthaitawee 24. IMAGING INFECTION OF VALVES AND DEVICES

495

511

Sina Tavakoli and Mehran M. Sadeghi 26. RADIONUCLIDE IMAGING IN HEART FAILURE

531

Daniel Shpilsky and Prem Soman

543

Matthew E. Harinstein and Raymond Russell, III

viii

36. NUCLEAR CARDIOLOGY REPORT GENERATION

698

709

582 38. STATISTICS IN NUCLEAR IMAGING

729

Charity J. Morgan and Anastasia M. Hartzes 596

39. NUCLEAR IMAGING IN DEVELOPING COUNTRIES

742

Amalia Peix, Diana Paez, Joao V. Vitola, Pilar Orellana, and Maurizio Dondi 610

SECTION VI.   OVERVIEW 40. ESSENTIALS OF NUCLEAR CARDIAC IMAGING: ASK THE EXPERTS

624

Ahmed Aljizeeri and Mouaz H. Al-​Mallah 32. NUCLEAR IMAGING IN CARDIO-​ONCOLOGY

686

Andrew J. Einstein

Ravi Venkatesh and Saurabh Malhotra 31. THE ROLE OF NUCLEAR CARDIOLOGY IN THE MANAGEMENT OF CARDIOVASCULAR DISEASES IN PATIENTS LIVING WITH HIV

Robert C. Hendel, Minnsun K. Park, and Gursukhmandeep S. Sidhu

37. RADIATION CONSIDERATIONS IN IMAGING

Robert J. H. Miller and Piotr J. Slomka 30. NUCLEAR IMAGING IN PATIENTS WITH SERIOUS ARRHYTHMIAS

673

Wael A. AlJaroudi

Philipp A. Kaufmann, Oliver Gaemperli, and Ronny R. Buechel 29. ARTIFICIAL INTELLIGENCE AND NUCLEAR IMAGING

34. PHYSICIAN CERTIFICATION AND LABORATORY ACCREDITATION

Timothy F. Christian

Arnold C. T. Ng, Victoria Delgado, and Jeroen J. Bax 28. HYBRID IMAGING: SPECT/CCTA, PET/​MR, AND SPECT CALCIUM SCORE: WHEN AND WHY?

SECTION V.  CHALLENGES FOR NUCLEAR CARDIOLOGY

35. NUCLEAR CARDIOLOGY GUIDELINES AND APPROPRIATE USE CRITERIA: AMERICAN COLLEGE OF CARDIOLOGY, AMERICAN HEART ASSOCIATION, AND EUROPEAN SOCIETY OF CARDIOLOGY

SECTION IV.  ADVANCES IN NUCLEAR CARDIAC IMAGING 27. EVOLVING ROLE OF ECHOCARDIOGRAPHY, CARDIAC CT, AND CARDIAC MRI IN CAD

655

Sara L. Partington and Sharmila Dorbala

Thomas H. Schindler, Soraya El Ghannudi, and Alessio Imperiale 25. IMAGING CARDIAC AND VASCULAR INFLAMMATION

33. RADIONUCLIDE IMAGING IN PATIENTS WITH CONGENITAL HEART DISEASES

636

757

Ami E. Iskandrian, Fadi G. Hage, Pradeep Bhambhvani, and Ernest V. Garcia Index

781

 

PREFACE

W

e are pleased to bring you the sixth edition of Nuclear Cardiac Imaging: Principles and Applications. In keeping with the tradition of the first edition of this book, which was published 35 years ago, and the subsequent editions, we strived to give you a book that is comprehensive, up to date, relevant, and yet easy to read. We believe this edition will remain the ultimate reference on nuclear cardiology for the coming years. While planning this edition, we appreciated the many advances and innovations that have occurred in the field since the last edition. Rather than updating the prior edition we put together an almost completely new book. A few chapters have been updated, some have been deleted, others have been combined with completely new content by different authors, and many are brand new. In doing so, we have listened to our readers who wanted us to retain the acclaimed features of the prior editions, which made the book a huge success, while simultaneously making changes to the organization and content to reflect the astounding developments in nuclear cardiology. Each chapter in the book is written by a leader in nuclear cardiology. Every chapter starts with 10 key points that summarize the important information within the chapter. Each chapter is enriched with plenty of tables, colored figures, and highly relevant references. The book has an online version that includes downloadable figures and videos. We are indebted to the authors for their sacrifices, especially during the COVID pandemic, when this work was being done; they were all selected because of their excellence and enormous contributions to our field. We have asked the authors not to shy away from controversy and to express their views in an open and transparent manner. Both of us have read all the chapters in their entirety and provided the authors with feedback while writing. While we tried our best to make the chapters consistent with each other and with the prevailing literature, we wanted the reader to appreciate the constantly evolving nature of some topics and to retain the honest assessment and views of the authors. For that reason, some overlap or repetition is unavoidable and may actually be healthy. While all the credit

goes to the individual authors, the errors that remain are entirely ours. It was our pleasure to work on this book day in and day out with such a distinctive group of professionals who made our job so much easier. The book is divided into six sections. The first section has seven chapters dealing with historical, technical, and physiologic considerations (Chapters 1–​7). The second section has 12 chapters dealing with diagnosis and risk assessment (Chapters 8–​19). The third section has seven chapters that address the role of nuclear imaging beyond coronary artery disease (Chapters 20–​26). The fourth section has seven chapters on advances in nuclear cardiac imaging (Chapters 27–​33). The fifth section consists of six chapters that deal with challenges for nuclear cardiology (Chapters 33–​39). The sixth and last section consists of just one chapter, which provides an overview of the book. Chapter 40 provides the essentials of nuclear cardiac imaging as a reference to the reader by answering 26 questions encountered by practitioners in the field on a regular basis. A new aspect to this edition is a Companion Atlas, which will help readers apply the knowledge they acquired from the chapters. The Atlas has chapters that mirror those included in the book. Some chapters include case presentations with a wealth of multimodality images to ground the topics in clinical care. Others consist of multiple-​choice questions and discussions to help solidify the knowledge gained. We recommend reading the book chapter first in its entirety before moving on to the corresponding chapter in the Atlas for maximum benefit. The last chapter in the Atlas is a self-​ assessment tool on the content of the book. This chapter consists of 40 questions followed by multiple-​choice answers. These questions were contributed by the authors of the chapters and are followed by a quick discussion. For full discussion, please refer back to the respective chapters. We could not have edited this book without the unwavering support of our families. We are grateful for their many sacrifices and especially for allowing us to carry this monumental effort to its fruition. This book benefits from our professional and personal interactions with our trainees and colleagues who have helped transform this book into a

 

bridge between understanding principles and applying them in clinical care. Our thanks are extended to the superb team at Oxford University Press and especially to Katie Lakina and Gnanambigai Jayakumar for their invaluable efforts. Lastly, we would like to acknowledge three giants of the field who passed away while working on this book: Drs. Barry L. Zaret (Chapter 1), Keiichiro Yoshinaga (Chapter 4) and Henry Gewirtz (Chapter 8). May their souls rest in peace and their memory remain alive, in part through their enormous contributions to nuclear cardiology.

x

We believe this edition of the book will be of great interest and a reference standard to trainees in imaging, especially nuclear cardiology; those who perform and interpret these images regardless of their specialty, place of work, and affiliations; and also those who use these images for patient care. We hope that you will enjoy and benefit from reading this book as much as we did in bringing it to you. Fadi G. Hage, MD, FACC, MASNC Ami E. Iskandrian, MD, MACC, MASNC

 

CONTRIBUTORS

Wael A. AlJaroudi, MD, EMBA, FACC, FASNC Professor of Medicine Wellstar Health Medical College of Georgia Augusta, Georgia, USA Ahmed Aljizeeri, MBBS King Abdulaziz Cardiac Center, Riyadh, Kingdom of Saudi Arabia King Saud bin Abdulaziz University for Health Sciences—​Riyadh, Kingdom of Saudi Arabia King Abdullah International Medical Research Center—​Riyadh, Kingdom of Saudi Arabia Mouaz H. Al-​Mallah, MD, Msc Beverly B. and Daniel C. Arnold Distinguished Chair, Professor of Cardiology, Houston Methodist Academic Institute and Professor of Medicine, Weill Cornell Medicine. Director, Cardiovascular PET, Houston Methodist DeBakey Heart and Vascular Center, Houtson, Texas, USA Efstathia Andrikopoulou, MD, MBA, FACC Assistant Professor of Medicine, Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA Kathryn J. Ascah Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada Roberta Assante, MD, PhD Department of Advanced Biomedical Sciences, School of Medicine, University of Naples Federico II, Naples, Italy Jeroen J. Bax, MD, PhD Department of Cardiology, Leiden University Medical Centre, Leiden, The Netherlands

Rob S. B. Beanlands, MD, FRCP(C), FACC, MASNC, FCCS Deputy Director General, University of Ottawa Heart Institute Professor of Medicine—Division of Cardiology and Distinguished Chair in Cardiovascular Imaging Research University of Ottawa, Ontario, Canada Pradeep Bhambhvani, MD Professor of Radiology The University of Alabama at Birmingham Birmingham, Alabama, USA John P. Bois, MD Associate Professor of Medicine, Mayo Clinic, Rochester, Minnesota, USA Jamieson M. Bourque, MD, MHS Professor of Medicine and Radiology, Medical Director of Nuclear Cardiology and the Stress Laboratory, Medical Director of Echocardiography, University of Virginia, Charlottesville, Virginia, USA Paco E. Bravo, MD Divisions of Nuclear Medicine and Cardiothoracic Imaging, Department of Radiology, and Division of Cardiology, Department of Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA Juliana Brenande de Oliveira Brito Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada Ronny R. Buechel, MD Deputy Director and Professor, University Hospital Zurich, Department of Nuclear Medicine, Cardiac Imaging, Zurich, Switzerland

 

Panithaya Chareonthaitawee, MD Professor of Medicine, Director of Nuclear Cardiology, Mayo Clinic, Rochester, Minnesota, USA

W. Lane Duvall, MD, FASNC Director of Nuclear Cardiology, Hartford Hospital, Hartford, CT, USA

Ji Chen, PhD Head of Engineering, Acelerate San Francisco Bay Area

Andrew J. Einstein, MD, PhD, FACC, FAHA, MASNC, MSCCT, FSCMR Professor of Medicine (in Radiology) Director, Nuclear Cardiology, Cardiac CT, and Cardiac MRI Director, Advanced Cardiac Imaging Fellowship Seymour, Paul and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center/NewYork-Presbyterian Hospital New York, New York, United States of America

Timothy F. Christian, MD, MPA DeMatteis Research Center/​St Francis Hospital, Roslyn, New York, USA Alberto Cuocolo Department of Advanced Biomedical Sciences, School of Medicine, University of Naples Federico II, Naples, Italy Robert A. deKemp, PhD Head Imaging Physicist, University of Ottawa Heart Institute, Ottawa, Ontario, Canada Victoria Delgado, MD, PhD Department of Cardiology, Leiden University Medical Centre, Leiden, The Netherlands Ana Carolina do A. H. de Souza, MD, PhD Cardiovascular Imaging Program, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA Vasken Dilsizian, MD Chief, Division of Nuclear Medicine, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA

Soraya El Ghannudi, MD, PhD Departments of Radiology and Nuclear Medicine, Nouvel Hôpital Civil—​University Hospitals of Strasbourg, Strasbourg, France Daniel C. Fisher, MD Director, Stress Nuclear Laboratory, Bellevue Hospital, New York, USA Oliver Gaemperli, MD, FESC Professor, Consultant Cardiologist, HeartClinic Zurich AG, Hirslanden Hospital, Zurich, Switzerland, EU James R. Galt, PhD Professor of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA Ernest V. Garcia, PhD, FASNC Professor of Radiology and Imaging Sciences (Retired) Emory University School of Medicine, Atlanta, Georgia, USA

Maurizio Dondi, MD Division of Human Health, International Atomic Energy Agency, Vienna, Austria

Valeria Gaudieri, MD, PhD Department of Advanced Biomedical Sciences, School of Medicine, University of Naples Federico II, Naples, Italy

Sharmila Dorbala, MD, MPH Director of Nuclear Cardiology, Professor of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

Henry Gewirtz, MD† Professor of Medicine, Harvard Medical School Boston, Massachusetts, USA

Rami Doukky, MD, MSc, MBA, FASNC Chairman, Division of Cardiology Cook County Health, Chicago, Illinois, USA

xii

Alessia Gimelli, MD, FESC Head of Nuclear Cardiology Lab, Imaging Department, Fondazione Toscana Gabriele Monasterio, Pisa, Italy Javier Gomez, MD Division of Cardiology, Cook County Health, Chicago, Illinois. USA

 

Martha Grogan, MD Associate Professor of Medicine, Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA Fadi G. Hage, MD, FACC, FAHA, FSCCI, MASNC Professor of Medicine, Cardiovascular Disease, University of Alabama at Birmingham and the Birmingham VA Medical Center, Birmingham, Alabama, USA Matthew E. Harinstein, MD, MBA SVP, COO, Associate CMO, UPMC International, Associate Professor of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA Anastasia M. Hartzes, PhD Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA Robert C. Hendel, MD, MACC, MASNC Professor of Medicine and Radiology, Tulane University School of Medicine, New Orleans, Louisiana, USA Milena J. Henzlova, MD, PhD Mount Sinai Medical Center New York, NY, USA Alessio Imperiale, MD, PhD Department of Nuclear Medicine and Molecular Imaging, Institut de Cancérologie de Strasbourg Europe (ICANS), Strasbourg, France Ami E. Iskandrian, MD, MACC, MASNC Professor Emeritus Heersink School of Medicine, University of Alabama at Birmingham Birmingham Alabama, USA

Saurabh Malhotra, MD, MPH Director of Advanced Cardiac Imaging, Cook County Health, Chicago, Illinois, USA Brian A. Mc Ardle, MD Clinical Assistant Professor, University of British Columbia, Victoria, British Columbia, Canada Sean R. McMahon Division of Cardiology, Hartford Hospital, Hartford Heart and Vascular Institute, Hartford, CT, USA Robert J. H. Miller, MD, FRCPC, FACC Clinical Associate Professor, University of Calgary, Calgary, Alberta, Canada Charity J. Morgan, PhD Professor, The University of Alabama at Birmingham Birmingham, AL, USA Paul H. Murphy, PhD Professor Emeritus of Radiology, Baylor College of Medicine, Houston, Texas, USA Arnold C. T. Ng, MBBS, PhD Department of Cardiology, Princess Alexandra Hospital, University of New South Wales, Australia Pilar Orellana, MD Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, International Atomic Energy Agency, Vienna, Austria Diana Paez, MD, MSc, Ed. Head of the Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, International Atomic Energy Agency, Vienna, Austria

Philipp A. Kaufmann, MD Professor and Chairman, Department of Nuclear Medicine, University Hospital Zurich, Zurich, SZ

Minnsun K. Park, MD Cardiology Fellow, Tulane University School of Medicine, New Orleans, Louisiana, USA

Ran Klein Imaging Physicist, The Ottawa Hospital Ottawa, Ontario, Canada

Sara L. Partington, MD Assistant Professor of Clinical Medicine, Hospital of the University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA

Riccardo Liga, MD, PhD, FESC University of Pisa and University Hospital of Pisa, Pisa, Italy

CONTRIBUTORS

 

Amalia Peix, MD, MSc, PhD Nuclear Cardiologist, Master in Cardiac Magnetic Resonance Francisco Vittoria University Spain, Institute of Cardiology and Cardiovascular Surgery, La Habana, Cuba

Mehran M. Sadeghi, MD Professor of Medicine (Cardiology), Yale School of Medicine, New Haven, Connecticut, USA Physician, VA Connecticut Healthcare System, West Haven, Connecticut, USA

Lawrence M. Phillips, MD Associate Professor of Medicine, Leon H. Carney Division of Cardiology, NYU Grossman School of Medicine, New York USA

Heinrich R. Schelbert, MD, PhD Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California at Los Angeles, Los Angeles, California, USA

Steven Port, MD AdvocateAuroraHealth, Aurora Cardiovascular Services, Milwaukee, Wisconsin, USA Steven Promislow, MD, FRCPC Assistant Professor of Medicine Department of Internal Medicine, Section of Cardiology University of Manitoba Winnipeg, Manitoba, Canada Jennifer M. Renaud, MSC Research Scientist, INVIA Medical Imaging Solutions, Ann Arbor, Michigan, USA David G. Rosenthal, MD, FACC, FHRS Swedish Medical Center, Seattle, Washington, USA Benjamin Rotstein, PhD Associate Professor and Scientist University of Ottawa and University of Ottawa Heart Institute, Ottawa, Ontario, Canada Elona Rrapo Kaso, MD Division of Cardiovascular Medicine and the Cardiac Imaging Center, Departments of Medicine and Radiology, University of Virginia Health System, Charlottesville, Virginia, USA

Thomas H. Schindler, MD, PhD Professor of Radiology and Medicine; Mallinckrodt Institute of Radiology, Division of Nuclear Medicine, Washington University in Saint Louis, School of Medicine, Saint Louis, Missouri, USA Daniel Shpilsky, MD Division of Cardiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA Gursukhmandeep S. Sidhu, MD University of Illinois Chicago, Chicago, Illinois, USA Piotr J. Slomka, PhD Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-​ Sinai Medical Center, Los Angeles, CA, USA Gary R. Small Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada Prem Soman, MD, PhD Professor of Medicine, and Clinical and Translational Science, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA

Terrence D. Ruddy, MD, FRCPC, FACC, FAHA, FCCS, FSNMMI, MASNC Consulting Cardiologist, Division of Cardiology, Professor of Medicine and Radiology,University of Ottawa Heart Institute, Ottawa, Ontario, Canada

Viviany R. Taqueti, MD, MPH Cardiovascular Imaging Program, Brigham and Women’s Hospital and Cardiology Division, VA Boston Healthcare, Harvard Medical School, Boston, Massachusetts, USA

Raymond Russell, MD, PhD, MASNC, FACC Professor of Medicine, Institution Alpert Medical School of Brown University, Providence, Rhode Island, USA

Sina Tavakoli, MD, PhD Assistant Professor and Chief of the Division of Cardiothoracic Imaging, Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

xiv

 

Gregory S. Thomas, MD, MPH, FACC, MASNC MemorialCare Health System, Fountain Valley, California, USA; Division of Cardiology, University of California, Irvine, California, USA Mark I. Travin, MD, FACC, MASNC Division of Nuclear Medicine, Professor of Clinical Radiology and Clinical Medicine, Montefiore Medical Center. Albert Einstein College of Medicine, Bronx, New York, USA Ines Valenta, MD Research Associate; Mallinckrodt Institute of Radiology, Washington University in Saint Louis, School of Medicine, Saint Louis, Missouri, USA William A. Van Decker, MD Professor of Medicine, Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania, USA Venkatesh Ravi, MD, FACC, FHRS Clinical Cardiac Electrophysiologist, Adjunct Clinical Assistant Professor, Saint Francis Health System, Tulsa, Oklahoma, USA, Chicago, Illinois, USA Joao V. Vitola, MD, PhD Quanta Diagnóstico & Terapia, Curitiba, Brazil Frans J. Th. Wackers, MD, PhD Professor Emeritus of Diagnostic Radiology and Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA

CONTRIBUTORS

L. Samuel Wann, MD Clinical Professor of Cardiovascular Medicine, University of New Mexico Santa Fe, New Mexico R. Glenn Wells Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada Christiane Wiefels, MD, PhD Assistant Professor of Medicine, Department of Medicine, Division of Nuclear Medicine, University of Ottawa, Canada Keiichiro Yoshinaga, MD, PhD† Team leader at the Department of Molecular Imaging and Theragnostic, National Institute of Radiological Sciences, Chiba, Japan Emilia Zampella Department of Advanced Biomedical Sciences, School of Medicine, University of Naples Federico II, Naples, Italy Barry L. Zaret, MD† Robert W. Berliner Professor Emeritus of Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA

 

 

I. HISTORICAL, TECHNICAL, AND PHYSIOLOGIC CONSIDERATIONS

 

 

1. NUCLEAR CARDIOLOGY HI STO RY A ND M I LESTONES

Barry L. Zaret and Frans J. Th. Wackers

K EY P OIN TS 1. The initial application of radioisotopes to cardiac studies occurred in the mid-​1920s. 2. Ventricular function was evaluated in the 1960s and 1970s by first-​pass and equilibrium techniques. 3. Myocardial stress perfusion imaging was first performed using potassium-​43 and exercise in 1973. 4. Stress imaging rapidly evolved thereafter with new tracers (thallium-​201 and technetium-​ 99m-​labeled agents) and from planar to SPECT approaches. 5. Perfusion imaging rapidly proved its value diagnostically and in assessing prognosis. 6. Acute infarct imaging reached its peak use in the 1970s but is now no longer employed. 7. Advances in hybrid imaging, combining computed tomography with radionuclide imaging, have recently allowed attenuation correction as well as providing the combination of anatomic and physiologic data. 8. PET myocardial perfusion studies have recently become a standard approach for evaluating myocardial perfusion, absolute quantification of coronary blood flow, and coronary flow reserve. 9. PET FDG studies of cardiac sarcoidosis have recently been established as a new approach for defining myocardial inflammation.

10. New cardiac-​centered SPECT systems provide high-​sensitivity, high-​resolution studies, allowing for radiation dose reduction and high-​quality imaging studies. AB B R E v IAT IONS ERNA FDG (F-​18) FPRNA LV LVEF MI PET PYP RVEF SPECT Tc-​99m

equilibrium radionuclide angiocardiography fluorodeoxyglucose first-​pass radionuclide angiocardiography left ventricular left ventricular ejection fraction myocardial infarction positron emission tomography pyrophosphate right ventricular ejection fraction single-​photon emission computed tomography technetium-​99m

Nuclear cardiology is generally considered a clinical sub­ specialty of the past four decades. However, the field has its roots in earlier times. This chapter focuses on these historical roots as they have evolved into the present era. Space constraints mandate focusing solely on the highlights. Apologies to the many highly productive investigators and laboratories whose contributions helped the field grow to its current level, but who could not be included.

 

HEA RT FUNCTI O N AN D CI RCULATO RY DY NA M ICS

for imaging with the sodium-​iodide crystal of the Anger camera. Early pioneers in the field (such as Joseph Kriss) demonstrated the ability to visualize cardiac structures The initial application of radioisotopes to the study of circu- from rapid sequential radionuclide images following in5,6 lation occurred in the mid-​1920s (Table 1.1). A renowned jection of a bolus of Tc-​99m–​labeled radiotracers. From cardiology investigator of that era, Hermann Blumgart, in these serial images, a number of inferences could be made an elegant series of studies employing radon gas dissolved concerning cardiac pathophysiology and cardiac chamber in saline as the radionuclide marker and a modified Wilson and great vessel size. Following these qualitative studies, cloud chamber as the radiation detector, measured central quantitative techniques were developed for measuring left circulation transit times in humans (Figure 1.1).1 These and right ventricular ejection fraction as well as the degree 7,8 studies, which were well ahead of their time, resulted in of left-​to-​right intracardiac shunting. For over a decade, substantial improvement in the general understanding of first-​pass approaches to assess ventricular ejection fraccardiovascular function in a variety of disease states. They tion were widely used. Extensive studies were subsequently were early forerunners of the studies of the 1950s and performed by many laboratories, particularly by Jones at al. 1960s, in which substantial attention was given to hemo- at Duke and by Zaret et al. at Yale, establishing efficacy and 9–​12 dynamic characterization of both health and human disease clinical utility. In 1971, the principle of electrocardiographic gating of states. Blumgart’s laboratory in Boston also served as fertile the stable radiolabeled (equilibrium) blood pool to evalground for training the next generation of cardiovascular uate cardiac performance was first proposed by Zaret and investigators. 13,14 This forerunner of current ERNA Not until the 1940s did Myron Prinzmetal build on this Strauss (Table 1.2). required separate manual gating of the end-​systolic and concept for potential clinical use, employing a simple sodium iodide probe to record transit of radiolabeled albumin end-​diastolic phases of the cardiac cycle for subsequent through the central circulation. Prinzmetal, a practicing measurement of LVEF and assessment of regional function. cardiologist, made important clinical observations using This was a cumbersome and time-​consuming procedure. nonimaging Geiger tubes and scintillation detectors in However, once efficacy had been established, it was only a a procedure called “radio-​cardiography” to define car- short time before automation of this technique occurred. diac output, pulmonary blood volume, and pulmonary Michael V. Green demonstrated in 1975 that by using relatively simple computerized techniques, the entire cardiac transit time.2 However, the major impetus for the development of nu- cycle could be visualized in an endless loop display with clear medicine technology occurred in the 1960s when Hal automated calculation of ventricular ejection fraction and 15 O. Anger, working in Berkeley, California, developed the visualization of the entire ventricular volume curve. For first practical widely used high-​resolution dynamic imaging over a decade, this technique was the standard for measdevice, the gamma (Anger) camera.3 At about the same uring ventricular function noninvasively. In 1977, Borer time radiochemists Walter Tucker and Margaret Greene, et al. at the National Institutes of Health first reported at the Brookhaven National Laboratories, invented the Tc-​ combining ERNA with supine bicycle exercise to evaluate 99m generator.4 Tc-​99m, because of the emitted energy at regional and global LV function under stress conditions in 140 keV, was a readily available radiotracer ideally suited coronary artery disease as well as other disease states, such as valvular heart disease.16 In large part, echocardiography has superseded ERNA in this context. However, for precise TA B LE 1.1   MA JO R A DvA N CE S : B EF O RE 1 9 7 0 and reproducible serial measurements of LVEF, such as required for monitoring cardiotoxicity in patients receiving Decade Investigator Advance chemotherapy, the radionuclide technique remains the pro1920s H. Blumgart Circulation times with radioisotopes cedure of choice.17 1940s M. Prinzmetal Radiocardiography Newer evolutionary advances in assessment of ventric1960s E. A. Carr Perfusion imaging in experimental MI ular function involve SPECT studies of global myocardial motion on perfusion images or endocardial borders on E. A. Carr Hot spot imaging in experimental MI equilibrium cardiac blood pool images. This allows a more W. Tucker, M. Greene Tc-​99m generator comprehensive assessment of right and left ventricular H. O. Anger Development of scintillation camera global and regional function.18 At present, with the marked J. Kriss Quantitative FPRNA advances in gated SPECT perfusion studies, ventricular 4

S E C T I O N I . H istorical , T echnical

 

Figure 1.1  Hermann L. Blumgart, MD (right), and Soma Weiss, MD (left), with a prototype of the Blumgart–​Yens cloud chamber detector.

TABLE 1 . 2   M A J O R A DvA N CES : 1 9 7 0 – 2 ​ 000 Date

Investigators

Advance

1971

B. Zaret, H. W. Strauss

ECG gating of cardiac blood pool in humans (ERNA) for LVEF and regional wall motion abnormality

1973

B. Zaret, H. W. Strauss

Exercise perfusion imaging (K-​43) in humans

1970s–​1980s

H. Schelbert, R. Jones, B. Zaret

Quantitative FPRNA for LVEF, RVEF

1973

E. Lebowitz

Development of Tl-​201

1974

R. Parkey, J. Willerson F. Bonte

Hot spot imaging of acute MI with Tc-99mPYP

1976

F. Wackers

Imaging acute MI with Tl-​201

1976

B. Khaw, E. Haber

Antibody imaging of acute MI

1977

J. Borer

Exercise ERNA

1977

G. Beller, G. Pohost

Tl-​201 redistribution

1978

K. L. Gould, M. Verani

Pharmacologic stress imaging

1980s–​1990s

Multiple

Development of Tc-​99m perfusion imaging agents

1980s–​1990s

D. Kuhl, R. Edwards, G. Hounsfield

Development of SPECT

1986

J. Tillisch, H. Schelbert

PET viability

1980s–​1990s

R. Bonow

SPECT viability

1990s and after

Multiple, in particular G. A. Beller, D. Berman, R. Hachomovitch, L. Shaw, A. Iskandrian

Studies of prognosis with nuclear cardiology

1990s

Multiple, in particular E. Garcia, J. Galt, S. Cullom, E. Ficaro, B. Tsui

Development of attenuation correction

1995

J. Narula, B. Khaw

Vascular plaque imaging

1998

H. Blankenberg, H. W. Strauss

 

also able to establish direct relationships between perfusion patterns and location and severity of coronary stenosis on contrast coronary angiography. Following the initial observations, subsequent clinical studies demonstrated the utility of this approach, again using K-​43 and the rectilinear M YOC A R DIA L PERFUSI O N I MAG I N G scanner, in assessing the patency of bypass grafts following cardiac surgery22 and the presence of false-​positive exercise In the early 1960s, Carr, in a pioneering set of experiments, ECG tests.23 These studies, which set the stage for the rapid demonstrated the accumulation of radioactive potassium development of the field, clearly employed a suboptimal raand other radioactive potassium analogs, such as cesium dioactive tracer in the form of K-​43. Its high-​energy specand rubidium, in the myocardium of experimental animals trum, which was not a problem for the rectilinear scanner, (Figure 1.2).20 He also demonstrated that under conditions was a significant problem for the gamma camera. Of note, of acute coronary ligation, the uptake of these radioactive this same group demonstrated in the early 1970s that tracers in the evolving infarct zone was decreased compared with appropriate pinhole collimation and shielding, one to normal regions. However, it was not until 1973 that the could obtain acceptable planar cardiac images using these possibility of imaging the site and extent of myocardial is- high-​energy, positron-​emitting agents and a conventional chemia was demonstrated by combining physical exercise (Anger) gamma camera.24 Thereafter, Lebowitz et al.25 introduced the potasstress with static cardiac imaging (see Table 1.2). These initial studies, performed in humans by Zaret and Strauss sium analog thallium-​201 (Tl-​201) as a new radiotracer at Travis Air Force Base in California, established the par- for imaging. The ease of using the lower-​energy Tl-​201 adigm of imaging ischemia induced by treadmill exercise with the gamma camera was a major breakthrough in the stress, and intravenous injection of potassium-​43 (K-​43) at development of nuclear cardiology as a clinically viable peak exercise, followed by imaging with a rectilinear scanner methodology. In 1975, Pohost and Beller26 defined the as the imaging device (Figure 1.3).21 This relatively simple phenomenon of myocardial redistribution on thallium observation established the clinical and physiologic basis imaging. This allowed the use of a single radionuclide of nuclear cardiology and stress imaging as it is practiced stress injection and subsequent sequential imaging during today. These investigators thus demonstrated a character- resting state to evaluate normalization of initially hetistic pattern of relatively decreased perfusion in a stress-​ erogeneous radiotracer uptake, thereby indicating stress-​ induced ischemic area and homogeneous radioactive tracer induced ischemia. In the late 1970s, Gould, who had distribution in the same area under resting conditions. The already made important contributions to understanding physical properties of K-​43 (i.e., relatively high radiation ex- the pathophysiologic basis of myocardial perfusion imposure and rapid myocardial washout) mandated separate aging, developed the concept of blunted coronary flow reinjections for rest and stress studies. The investigators were serve, in the presence of a functionally significant stenosis, function is routinely evaluated concomitantly with assessment of myocardial perfusion, and this has frequently obviated the need for separate studies.19

Figure 1.2  Experimental anterior MI in a dog. (Left) Cesium-​131 rectilinear scan of the intact animal. A large anteroapical defect, corresponding to the

site of infarction, is visualized. (Right) A scan of the excised heart shows an extensive area of necrosis in the anterior wall, without cesium-​131 uptake.

6

S E C T I O N I . H istorical , T echnical

 

Figure 1.3  Rest and post-​exercise rectilinear scans of a patient with exercise-​induced ischemia. (Left) Homogeneous K-​43 cardiac uptake at rest. (Right)

Post-​exercise K-​43 scan, showing a defect in the inferoapical area.

by using vasodilator pharmacologic stress as opposed to physical exercise stress.27 Pharmacologic vasodilation was initially achieved with dipyridamole. However, Verani et al.28 demonstrated in 1990 that comparable diagnostic images could be obtained by direct intravenous infusion of adenosine. More recently, attention has turned to specific adenosine receptor agonists, with focus on the adenosine A2a receptor.29 For patients who cannot tolerate adenosine because of bronchospastic disease, dobutamine was introduced as a stressor, comparable to its use in stress echocardiography.30 These advances expanded the utility of stress perfusion imaging to individuals unable to exercise adequately. In the same decade (1976), Wackers et al.31 in Amsterdam demonstrated the utility of resting bedside Tl-​201 imaging for detecting acute MI. This study was a forerunner to current imaging approaches in the emergency department setting. The late 1980s and 1990s saw the development of Tc-​ 99m–​labeled perfusion imaging agents as important new radiopharmaceuticals for identifying myocardial ischemia and MI. The initial two agents were Tc-​99m–​labeled sestamibi and teboroxime.32–​34 Whereas sestamibi has survived and remains a major clinical tracer today, teboroxime is no longer employed because of the very rapid washout of teboroxime from the myocardium. Consequently, for purposes of imaging ischemia clinically, it remains a suboptimal agent when imaging is performed with conventional SPECT cameras. In the mid-​1990s, tetrofosmin became available as an alternative to sestamibi for perfusion imaging.35 N uclear C ardiology : H istory & M ilestones

The Tc-​99m–​labeled myocardial perfusion agents are of clinical importance because due to the optimal energy of emitted photons and the ability to use higher doses, the quality of SPECT imaging is consistently better. However, the optimal perfusion imaging agent has not been defined as yet. Such an agent should, compared to Tc-​99m as the radionuclide, provide better myocardial uptake and kinetic characteristics (i.e., linearity of uptake over a wide range of myocardial blood flow), without excessive subdiaphragmatic tracer accumulation. PET imaging with rubidium-​82 is increasingly used in many laboratories. Rubidium-​82 PET images are consistently of good quality, even in obese patients, and allow for quantification of regional myocardial blood flow.36 PROGNOS IS In the 1970s, as the field was developing, it focused primarily on diagnostic issues. This could be called the “decade of discovery.” Subsequent decades have focused on functional assessment and prognosis in patients with already identified cardiovascular disease. The field entered an important new area when the unique prognostic potential of nuclear cardiology was demonstrated in elegant and meticulous detail. In 1983, Gibson and Beller37 first established the prognostic value of thallium imaging following MI. Thereafter, numerous studies by major laboratories have defined its prognostic value in both acute and chronic coronary artery disease.38 An important observation is also

 

the favorable outcome in patients who have normal stress myocardial perfusion images. Although the number of investigators involved in this field of research is large, the seminal contributions of Berman and Hachomovitch and their colleagues at Cedars-​Sinai39,40 and Iskandrian and colleagues in Philadelphia41,42 are particularly noteworthy. No other imaging discipline has demonstrated the same rigorous and comprehensive approach to the assessment of noninvasive risk stratification that has been displayed by nuclear cardiology.

situations where apoptosis is an expected pathophysiologic event.50 v IAB ILIT Y

Nuclear cardiology was the first imaging field to focus intensively on the definition and identification of dysfunctional, but viable, myocardium in coronary artery disease. This work proceeded using a variety of radioactive tracers and technologies. In the 1980s, the UCLA group under the leadership of Schelbert used the glucose analog fluorine-​18 (F-​18)-​fluorodeoxyglucose (FDG) INFA R CT IM AG I N G to identify viable myocardium.51 Thereafter, numerous In parallel with the development of perfusion imaging investigations demonstrated the phenomenon of increased (“cold spot imaging”), great interest developed in identi­ glucose accumulation in dysfunctional, yet viable, presumfying areas of acute necrosis with radioactive tracers that ably hibernating myocardium. This imaging approach has would be incorporated into acute infarct zones (“hot predominately involved PET. However, work with new spot imaging”). Much as with perfusion imaging, these cameras that allow imaging of positron agents with SPECT advances were heralded by earlier experimental work, and coincidence detectors, as well as more widespread once again by Carr et al.43 The first important studies in availability of PET cameras, may substantially broaden this humans were by Holman et al. (1974),44 who used Tc-​ area of investigation in the future. In 1988 Kiat, Berman, 52 labeled tetracycline to define zones of acute MI. This par- and colleagues at Cedars-​Sinai suggested that 24-​hour ticular tracer, however, was complex in preparation with delayed thallium imaging also could be used to define visignificant limitations. Shortly thereafter, Willerson, ability. Bonow in 1990 realized that myocardial uptake Parkey, and Bonte45 in Dallas, Texas, reported the utility of thallium-​201 after injection at rest also indicated myof imaging acute MI with Tc-​99mPYP. Then, great in- ocardial viability with intact sodium–​potassium pump. terest arose in defining acute MI of both right and left Thereafter, the 1990s saw an explosion of studies evaluating ventricles by dual isotope imaging with thallium-​201 and resting reinjection thallium imaging for identifying viable 53 Tc-​99mPYP.46 However, it became clear that there were myocardium in states such as hibernation. Both the PET time constraints involving how one could use this tech- approach with FDG and the SPECT approach with thalnique in a clinically meaningful sense. As a result, this lium have been used as gold standards for assessing viable myocardium. However, additional work has demonstrated, technique has not survived. 47 In the late 1970s, Khaw and Haber demonstrated for based on quantitative techniques, that the Tc-​99m–​labeled the first time that a radiolabeled specific antibody against agents sestamibi and tetrofosmin also may be employed for 54 cardiac myosin could be used to define acute myocardial ne- identifying viable myocardium. crosis and MI. These studies were designed initially based on biologic rather than clinical principles. Elegant in vitro C AR DIAC INF LAMMAT ION AND and subsequent experimental studies preceded application INF ILT R AT Iv E DIS E AS E to humans. Thereafter, antimyosin imaging, using indium-​ 111 as the radioactive marker, was employed in the study of MI, myocarditis, and cardiac transplant rejection.48 In recent years, cardiac imaging has focused also on Regrettably, at the present time antimyosin imaging is also identifying myocardial inflammation, particularly in cardiac sarcoidosis, using F-​18 FDG PET imaging.55 This techno longer utilized. More recently, Tc-​99m–​labeled annexin-​V has been nique is now employed in diagnosis and may also have a role developed for defining varying states of myocyte death, in monitoring therapy. It also establishes a paradigm for use including apoptosis (programmed cell death) as well as in other inflammatory diseases. Of the cardiac infiltrative ischemic necrosis.49 This agent has been demonstrated in cardiomyopathies, transthyretin cardiac amyloidosis can be zones of acute infarction as well as experimental and clinical diagnosed early with high sensitivity and specificity, using 8

S E C T I O N I . H istorical , T echnical

 

bone avid radiotracers such as Tc-​99mPYP, Tc-​99mDPD, or Tc-​99mHMDP, by either planar or SPECT imaging.56

and microPET systems has been a substantial advance, thereby allowing imaging of small animals such as mice and rats.64 Use of microinstrumentation allows nuclear imaging to enter the realm of contemporary molecular research.

INS TR UM ENTATI O N Many of the current and future advances in perfusion imaging have been and will be dependent on advanced instrumentation. The field has moved dramatically from the ancient rectilinear scanner through an era of planar single crystal camera imaging and now into an era of advanced SPECT imaging. The advances in SPECT imaging have involved both instrumentation development and computer software for reconstruction, display, and quantitative analysis. The multiheaded SPECT systems have been a substantial improvement. The recognition of substantial degradation in SPECT images due to both attenuation and scatter has led to the development of major new corrective approaches to address both of these issues.57,58 Although there is no consensus as to the best technique for attenuation and scatter correction, clearly this is an important advance. Of particular importance is the recent technology of high-​sensitivity SPECT cameras.59 Several new SPECT systems with multiple cardiac-​centered direct-​conversion, solid-​state detectors, using cadmium-​zinc-​telluride (CZT) or pixelated scintillation crystals, combined with novel collimation, represent a significant advance in instrumentation. These camera systems optimize image quality and improve diagnostic accuracy while reducing acquisition time and patient radiation exposure. Whereas the initial interpretive techniques involved visual assessment of images, the importance of image quantification is well now recognized and has improved reproducibility of interpretation and quantification of image abnormalities. Software programs developed at Cedars-​ Sinai, Emory, Yale, and other institutions are being employed widely for direct quantification and automated analysis with a variety of displays, including polar maps.60–​62 Such quantification forms an important basis for the future of the field. In addition, the combination of perfusion imaging and electrocardiogram gating has allowed attainment of the long-​established goal of defining perfusion and function from a single study. The use of hybrid cameras that combine computed x-​ray tomography with either SPECT or PET imaging has been a major recent advance.63 With combined imaging it is possible to have attenuation correction, precise anatomic image co-​registration, assessment of coronary calcification, and physiologic imaging defined by radionuclide studies. The development of microSPECT N uclear C ardiology : H istory & M ilestones

ME TAB OLIC IMAGING Whereas metabolic imaging has been associated primarily with F18-​FDG imaging of viable myocardium, other specific radioactive tracers involving both PET and SPECT have been employed. Particularly in Japan, SPECT imaging using radioiodinated fatty acids has been performed for over a decade.65 These agents have been used to define viable myocardium and ischemic myocardium. As yet, predominately because of reasons surrounding the widespread lack of availability of iodine-​123, this set of approaches has not been widely used throughout the world. Nevertheless, fatty acid imaging with both fatty acid analogs that are relatively trapped within the myocardium to allow optimal imaging and other agents whose period of residence within the myocardium is somewhat limited may find use in the field. More recently, fatty acid imaging has been demonstrated to have a potential use as an ischemic memory agent. Initial studies have demonstrated the potential for defining ischemic events in humans hours after their occurrence.66 Further work in this area should be forthcoming. PET imaging of metabolism, in addition to F18-​FDG, has involved radioactive C11-​acetate and free fatty acids (C11-​palmitate). However, FDG appears to be the agent that has been and will continue to be used most widely. In addition, its widespread use in the field of oncology imaging will ensure its continued availability. F U T U R E IMAGING AGE NT S / ​M OLE C U L A R IMAGING Nuclear cardiology is entering a new era in which imaging strategies will be based on the paradigms of molecular and cell biology, as opposed to the classic paradigms of physiology and pathophysiology that have heretofore dominated the field (Table 1.3).67 Use of these new paradigms should allow imaging to partner effectively with contemporary science. Already substantial advances have occurred with respect to imaging plaque and lesion vulnerability within the vasculature, aortic aneurysm activity, defining the presence of active angiogenesis, defining matrix metalloproteinase activity within vasculature and myocardium, and imaging of

 

gene product.68–​71 In addition, nuclear imaging techniques have been proven suitable for imaging stem cell traffic.71 The field of vascular imaging began in 1995 with the demonstration by Khaw and Narula72 that atherosclerotic lesions in the aorta of rabbits could be imaged using antibody Z2D3 raised against rapidly dividing smooth muscle cells. R ECOGNITION AS A SUBSPECI ALTY As nuclear cardiology developed, there was an intense and at times acrimonious interaction between the fields of nuclear medicine and cardiology, both of which claimed paternal primacy. In 1993 the American Society of Nuclear Cardiology (ASNC) was founded by Leppo, Wackers, and colleagues and formally incorporated.73 ASNC provided the field with the stature of a significant professional society and also established its advocacy role for nuclear cardiology on an international basis. Shortly thereafter, national and international meetings were established that focused solely on nuclear cardiology. In January 1994 the Journal of Nuclear Cardiology (JNC) was first published, with Zaret as first editor-​in-​chief. The journal has provided an additional focused vehicle for the dissemination of experimental and clinical nuclear cardiology and has been a stimulus for development of the field. TA B LE 1.3   MA JO R A DvA N CE S : 2 0 0 0 A N D B EYO N D Authors

Advance

Multiple

Development of molecular imaging

Multiple

Development of hybrid imaging systems

Multiple

Development of microSPECT and microPET systems

Multiple (H. Schelbert, M. DiCarli, K. L. Gould, R. Beanlands)

Establishment of PET myocardial perfusion studies

Multiple

Imaging myocardial and vascular inflammation with FDG

Multiple

Development of high-​sensitivity, high-​resolution solid-​state SPECT systems

Multiple (particularly E. Garcia, T. Faber, P. Slomka, G. Germano, F. Wackers, Y. H. Liu)

Development of effective quantitative software, automation, and quantitative approach to multimodality imaging

A. Einstein

Awareness of the need to develop strategies of radiation dose reduction

10

TA B LE 1 .4   S TE PS IN E S TAB L IS H IN G N U CL E AR CARD IO L O G Y AS A S U B S PE CIALTY 1993

American Society of Nuclear Cardiology formed

1994

Journal of Nuclear Cardiology first published

1995

Certification Board of Nuclear Cardiology formed and gives first certification exam

1998

Intersocietal Commission for the Accreditation of Nuclear Laboratories formed and accredits first laboratory

In addition, under the guidance of Wackers, in 1996 the Certification Board of Nuclear Cardiology was formally established and offered its first certification examination. This has continued annually and is a well-​established benchmark for the clinical practice of nuclear cardiology. In 1997, again through the vision of Wackers, the Intersocietal Commission for the Accreditation of Nuclear Laboratories was established to accredit nuclear cardiology laboratories, and in 1998 the first laboratory was accredited. This, too, was an important landmark in establishing the serious emphasis on quality within the field (Table 1.4). R E F E R E NC E S 1. Blumgart HL, Weiss S. Studies on the velocity of blood flow. VII. The pulmonary circulation time in normal resting individuals. J Clin Invest. 1927;4:399. 2. Prinzmetal M, Corday E, Sprizler RJ. Radiocardiography and its clinical applications. J Am Med Assoc. 1949;139:617. 3. Anger HO, Van Dyke DC, Gottschalk A, et al. The scintillation camera in diagnosis and research. Nucleonics. 1965;23:57. 4. https://​en.wikipe​dia.org/​wiki/​Tec​hnet​ium-​99m_​ge​nera​tor 5. Kriss JP, Yeh SH, Farrer PA, et al. Radioisotope angiocardiography. J Nucl Med. 1966;7:367. 6. Kriss JP, Enright LP, Hayden WG, et al. Radioisotopic angio-​ cardiography: Wide scope of applicability in diagnosis and evaluation of therapy in diseases of the heart and great vessels. Circulation. 1971;43:792. 7. Schelbert HR, Verba JW, Johnson AD, et al. Nontraumatic determination of left ventricular ejection fraction by radionuclide angiocardiography. Circulation. 1975;51:902. 8. Askenazi J, Ahnberg DS, Korngold E, et al. Quantitative radionuclide angiocardiography: Detection and quantitation of left-​to-​right shunts. Am J Cardiol. 1976;37:382. 9. Jones RH, Floyd RD, Austin EH, et al. The role of radionuclide angiocardiography in the preoperative prediction of pain relief and prolonged survival following coronary artery bypass grafting. Ann Surg. 1983;187:743. 10. Pryor DD, Harrell FE, Lee KI, et al. Prognostic indicators from radionuclide angiography in medically treated patients with coronary artery disease. Am J Cardiol. 1984;53:18. 11. Marshall RC, Berger HJ, Costin JC, et al. Assessment of cardiac performance with quantitative radionuclide angiocardiography: Sequential left ventricular ejection fraction, normalized left ventricular ejection rate, and regional wall motion. Circulation. 1977;56:820.

S E C T I O N I . H istorical , T echnical

 

12. Reduto LA, Berger HJ, Cohen LS, et al. Sequential radionuclide assessment of left and right ventricular performance following acute transmural myocardial infarction. Ann Intern Med. 1978;89:441. 13. Strauss HW, Zaret BL, Hurley PJ, et al. A scintiphotographic method for measuring left ventricular ejection fraction in man without cardiac catheterization. Am J Cardiol. 1971;28:575. 14. Zaret BL, Strauss HW, Hurley PJ, et al. A noninvasive scintiphotographic method for detecting regional ventricular dysfunction in man. N Engl J Med. 1971;284:1165. 15. Green MV, Ostrow HG, Douglas MA, et al. High temporal resolution ECG-​gated scintigraphic angiocardiography. J Nucl Med. 1975;16:95. 16. Borer JS, Bacharach SL, Green MV, et al. Real-​time radionuclide cineangiography in the non-​invasive evaluation of global and regional left ventricular function at rest and during exercise in patients with coronary artery disease. N Engl J Med. 1977;296:839. 17. Schwartz RG, McKenzie WB, Alexander J, et al. Congestive heart failure and left ventricular dysfunction complicating doxorubicin therapy: A seven-​year experience using serial radionuclide angiocardiography. Am J Med. 1987;82:1109. 18. Corbett JR. Tomographic radionuclide ventriculography: Opportunity ignored? J Nucl Cardiol. 1994;1:567. 19. Sharir T, Germano G, Kavanagh PB, et al. Incremental prognostic value of post-​stress left ventricular ejection fraction and volume by gated myocardial perfusion single photon emission computed tomography. Circulation. 1999;100:1035. 20. Carr EA, Walker BJ, Bartlett J. The diagnosis of myocardial infarct by photo scanning after administration of cesium-​131. J Clin Invest. 1963;42:922. 21. Zaret BL, Strauss HW, Martin MD, et al. Noninvasive regional myocardial perfusion with radioactive potassium: Study of patients at rest with exercise and during angina pectoris. N Engl J Med. 1973;288:809. 22. Zaret BL, Martin ND, McGowan RL, et al. Rest and exercise potassium-​43 myocardial perfusion imaging for the noninvasive evaluation of aortocoronary bypass surgery. Circulation. 1974;40:688. 23. Zaret BL, Stenson RE, Martin ND, et al. Potassium-​43 myocardial perfusion scanning for the noninvasive evaluation of patients with false-​positive exercise tests. Circulation. 1973;48:1234. 24. Martin ND, Zaret BL, Strauss HW, et al. Myocardial imaging using 43K and the gamma camera. Radiology. 1974;112:446. 25. Lebowitz E, Greene MW, Bradley-​Moore P, et al. 201Tl for medical use. J Nucl Med. 1973;14:421. 26. Pohost GM, Zir LM, Moore RH, et al. Differentiation of transiently ischemic from infarcted myocardium by serial imaging after a single dose of thallium-​201. Circulation. 1977;55:294. 27. Gould KL. Noninvasive assessment of coronary stenosis by myocardial perfusion imaging during pharmacological vasodilation. I. Physiologic basis and experimental validation. Am J Cardiol. 1978;41:267. 28 Verani MS, Mahmarian JJ, Hixson JB, et al. Diagnosis of coronary artery disease by controlled coronary vasodilation with adenosine and thallium-​201 scintigraphy in patients unable to exercise. Circulation. 1990;82:80. 29. Iskandrian AE, Bateman TM, Belardinelli L, et al. Adenosine versus regadenoson comparative evaluation in myocardial perfusion imaging: Results of the ADVANCE phase 3 multicenter international trial. J Nucl Cardiol. 2007;14:645. 30. Geleijnse ML, Elhendy A, Fioretti PM, et al. Dobutamine stress myocardial perfusion imaging. J Am Coll Cardiol. 2000;36:2017. 31. Wackers FJ, Sokole EB, Samson G, et al. Value and limitations of thallium-​201 scintigraphy in the acute phase of myocardial infarction. N Engl J Med. 1976;295:1. 32. Holman BL, Jones Ag, Lister-​James J, et al. A new Tc-​99m-​labeled myocardial imaging agent, hexakis(t-​butylisonitriile)-​technetium(I) [Tc-​ 99m TBI]: Initial experience in the human. J Nucl Med. 1984;25:1350. 33. Wackers FJTh, Berman DS, Maddahi J, et al. Technetium-​99m hexakis 2-​methoxyisobutyl isonitrile: Human biodistribution, dosimetry, safety, and preliminary comparison. J Nucl Med. 1989;30:301.

N uclear C ardiology : H istory & M ilestones

34. Seldin DW, Johnson LL, Blood D, et al. Myocardial perfusion imaging with technetium-​99m SQ30217: Comparison with thallium-​ 201 and coronary anatomy. J Nucl Med. 1989;30:312. 35. Zaret BL, Rigo P, Wackers FJ, et al. Myocardial perfusion imaging with 99m-​Tc tetrofosmin: Comparison to 201-​Tl imaging and coronary angiography in a phase III multicenter trial. Circulation. 1995;91:313. 36. Murthy VL, Naya M, Foster CR, et al. Improved cardiac risk assessment with noninvasive measures of coronary flow reserve. Circulation. 2011;124:22. 37. Gibson RS, Watson DD, Craddock GB, et al. Prediction of cardiac events after uncomplicated myocardial infarction: A prospective study comparing predischarge exercise thallium-​201 scintigraphy in coronary angiography. Circulation. 1983;68:321. 38. Brown KA. Prognostic value of myocardial perfusion imaging: State-​ of-​the-​art and new developments. J Nucl Cardiol. 1996;3:516. 39. Hachamovitch R, Berman DS, Kiat H, et al. Exercise myocardial perfusion SPECT in patients without known coronary artery disease: Incremental prognostic value and use in risk stratification. Circulation. 1996;93:905. 40. Berman DS, Hachamovitch RH, Kiat H, et al. Incremental value of prognostic testing in patients with known or suspected ischemic heart disease: A basis for optimal utilization of single-​photon emission computed tomography. J Am Coll Cardiol. 1993;6:665. 41. Iskandrian AS, Chae SC, Heo J, et al. Independent and incremental prognostic value of exercise single-​photon emission computed tomographic (SPECT) thallium imaging in coronary artery disease. J Am Coll Cardiol. 1993;22:665. 42. Iskander S, Iskandrian AE. Risk assessment using single-​photon emission computed tomographic technetium-​99m sestamibi imaging. J Am Coll Cardiol. 1998;32:57. 43. Carr EA Jr, Beierwaltes WH, Patno ME, et al. The detection of experimental myocardial infarcts by photoscanning. Am Heart J. 1962;64:650. 44. Holman BL, Lesch M, Zweiman FG, et al. Detection and sizing of acute myocardial infarcts with 99mTc(Sn) tetracycline. N Engl J Med. 1974;291:159. 45. Parkey RW, Bonte FJ, Meyer SL, et al. A new method for radionuclide imaging with acute myocardial infarction in humans. Circulation. 1974;50:540. 46. Wackers FJTh, Lie KI, Buseman-​Sokole E, et al. Prevalence of right ventricular involvement in inferior wall infarction assessed with thallium-​201 and technetium-​99m pyrophosphate. Am J Cardiol. 1978;42:358. 47. Khaw BA, Beller GA, Haber E, et al. Localization of cardiac myosin-​specific antibody in myocardial infarction. J Clin Invest. 1976;58:439. 48. Carrio I, Berna L, Ballester M, et al. Indium-​111 antimyosin scintigraphy to assess myocardial damage in patients with suspected myocarditis and cardiac rejection. J Nucl Med. 1988;29:1893. 49. Blankenberg FG, Katsikis PD, Tait JF, et al. In vivo detection and imaging of phosphatidylserine expression during programmed cell death. Proc Natl Acad Sci USA. 1998;95:6349. 50. Hofstra L, Reutellingsperger C, Kietselaer B, et al. Noninvasive detection of cell death in myocardial disorders. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 3rd ed. Elsevier-​Mosby; 2005:649–​657. 51. Tillisch J, Brunken R, Marshall R, et al. Reversibility of cardiac wall-​ motion abnormalities predicted by positron tomography. N Engl J Med. 1986;314:884. 52. Kiat HK, Berman DS, Maddahi J, et al. Late reversibility of tomographic myocardial thallium-​201 defects: An accurate marker of myocardial viability. J Am Coll Cardiol. 1988;12:1456. 53. Dilsizian V, Rocco TP, Freedman NMT, et al. Enhanced detection of ischemic but viable myocardium by the reinjection of thallium after stress-​redistribution imaging. N Engl J Med. 1990;323:141.

 

54. Udelson JE, Coleman PS, Metherall J, et al. Predicting recovery of severe regional ventricular dysfunction: Comparison of resting scintigraphy with 201-​Tl and 99m-​Tc-​sestamibi. Circulation. 1994;89:2552. 55. Blankstein R, Osborne M, Naya M, et al. Cardiac positron emission tomography enhances prognostic assessments of patients with suspected cardiac sarcoidosis. J Am Coll Cardiol. 2014;63:329. 56. Singh V, Falk R, DiCarli MF, et al. State-​of-​the art radionuclide imaging in cardiac transthyretin amyloidosis. J Nucl Cardiol. 2019;26:158. 57. King MA, Tsui BMW, Pretorius PH. Attenuation/​scatter/​resolution correction: Physics aspects. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 3rd ed. Elsevier-​Mosby; 2005:89–​101. 58. Case JA. Attenuation correction and scatter correction of myocardial perfusion SPECT images. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 4th ed. Elsevier-​Mosby; 2010:111–​120. 59. Abbott BG, Case JA, Dorbala S, et al. Contemporary cardiac SPECT imaging: Innovations and best practices: An information statement from the American Society of Nuclear Cardiology. Circ Cardiovasc Imaging. 2018;11:e000020. https://​www.ahaj​ourn​als. org/​doi/​10.1161/​HCI.00000​0000​0000​020 60. Faber TL, Chen JI, Garcia EV. SPECT processing, quantification, and display. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 4th ed. Elsevier-​ Mosby; 2010:53–​71. 61. Slomka P, Patton JA, Berman DS, Germano G. Digital/​fast SPECT: Systems and software. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 4th ed. Elsevier-​Mosby; 2010:132–​148. 62. Liu YH, Sinusas AJ, DeMan P, et al. Quantification of SPECT myocardial perfusion images: Methodology and validation of the Yale-​ CQ method. J Nucl Cardiol. 1999;6:190.

12

63. Bacharach SL. The new generation positron emission tomography/​ computed tomography scanners: Implications for cardiac imaging. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 3rd ed. Elsevier-​Mosby; 2005:141–​152. 64. Schelbert HR, Glover DK. State-​of-​the-​art instrumentation for positron emission tomography and single-​photon emission computed tomography imaging in small animals. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 3rd ed. Elsevier-​Mosby; 2005:153–​171. 65. Tamaki N, Morita K, Kuge Y. Fatty acid imaging. In: Zaret BL, Beller GA, eds. Nuclear Cardiology: State of the Art and Future Directions. 3rd ed. Elsevier-​Mosby; 2005:559–​575. 6 6. Udelson V, Bateman TM, Bergmann SR, et al. Metabolic imaging with β-​methyl-​p -​[123I]-​iodophenyl-​pentadecanoic acid identifies ischemic memory after demand ischemia. Circulation. 2005;112:2169. 67. Zaret BL. Call to molecular arms. J Nucl Cardiol. 1997;4:347. 68. Zaret BL. Second annual Mario S. Verani, M.D. memorial lecture: Nuclear cardiology, the next ten years. J Nucl Cardiol. 2004;11:393–​407. 69. Meoli DF, Sadeghi MM, Krassilnikova S, et al. Noninvasive imaging of myocardial angiogenesis following experimental myocardial infarction. J Clin Invest. 2004;113:1684. 70. Su H, Spinale FG, Dobrucki LW, et al. Noninvasive targeted imaging of matrix metalloproteinase activation in a murine model of postinfarction remodeling. Circulation. 2005;112:3157. 71. Wu JC, Gambhir SS. Molecular imaging of gene products. In: Zaret BL, Beller GA, eds. Clinical Nuclear Cardiology: State of the Art and Future Directions. 3rd ed. Elsevier-​Mosby; 2005:673–​690. 72. Narula J, Bianchi C, Petrov A, et al. Noninvasive localization of experimental atherosclerotic lesions with mouse/​human chimeric Z2D3 antibody specific for the proliferation smooth muscle cells of human atheroma. Circulation. 1995;92:474. 73. Wackers FJTh, Leppo JA. The origins and early years of the American Society of Nuclear Cardiology. J Nucl Cardiol. 2013;20:6.

S E C T I O N I . H istorical , T echnical

 

2. RADIATION PHYSICS AND RADIATION SAFETY Paul H. Murphy and James R. Galt

K EY P OIN TS 1. Atomic processes involve the atom as a whole. Nuclear processes take place within the nucleus. X-​rays are emitted from the atomic or electron shells. Gamma rays are emitted from the nucleus. 2. Radioactive decay is the process through which unstable nuclei release excess energy in order to reach a more stable state. 3. Modes of radioactive decay include alpha emission; beta-​minus particle emission; beta-​plus emission; electron capture; gamma-​ray emission, or isomeric transition; and internal conversion. Radioactive decay is an exponential process. The term half-​life describes the time required for half of the radioactive nuclei to decay. 4. Radioactive decay is often followed by the emission of characteristic x-​rays and Auger electrons. Radionuclides for imaging are produced by nuclear reactors, particle accelerators or cyclotrons, and generators. 5. Generators are devices designed to separate a short-​lived daughter radionuclide from a parent radionuclide. 99Mo–​99mTc is the most common generator in use. 6. Charged particles transfer energy to matter through excitation, ionization, or Bremsstrahlung. X-​rays and gamma rays transfer energy to matter through several processes, the most important being absorption, Compton scattering, and

pair production. Most of the interactions in the human body by the x-​rays and gamma rays used in nuclear cardiology are due to Compton scattering. 7. Attenuation is the loss of photons through interaction of matter by all processes. Attenuation is an exponential process. The term half-​value layer describes the thickness of a material required to attenuate half of the photons traveling through a medium. 8. Dosimetry is the measurement or calculation of radiation-​absorbed dose. Radiation exposure is a measure of the amount of ionization produced by x-​rays or gamma rays in air. Radiation-​absorbed dose is the amount of energy absorbed per unit mass by any material. 9. Stochastic radiation effects are those for which the probability of occurrence increases with the radiation dose. Examples of stochastic effects are genetic abnormalities and radiation-​induced cancers. Deterministic radiation effects are those that occur only above a dose threshold. Examples of this type of effect are skin injury and radiation-​ induced cataracts. 10. The principle of ALARA is that radiation dose should be kept “as low as reasonably achievable.” Radiation workers must be constantly aware of the mechanisms to minimize their radiation exposure by optimizing the influences of time, distance, and shielding.

 

A BBREVIATION S A ALARA Bq Ci CT EC eV ICRP IT keV LET MBq mCi MeV MIRD mSv N PET SI SPECT Sv Z

mass number as low as reasonably achievable becquerel curie computed tomography electron capture electron volt International Commission on Radiological Protection isomeric transition kilo-​electron volt (1,000 eV) linear energy transfer megabecquerel (106 Bq) millicurie (10−3 Ci) mega-​electron volt (1,000,000 eV) Medical Internal Radiation Dose millisievert (10−3 Sievert) neutron number positron emission tomography International System of Units single-​photon emission computed tomography sievert atomic number

INTRODUC TIO N One of the fundamental quests of nuclear cardiology is the search for elements with appropriate chemical properties for use in radiopharmaceuticals (radioactive isotopes that produce photons well suited for imaging) and that deliver a small radiation dose to the patient. This requires that the emission of any radiation that does not contribute to the image be kept to a minimum and that the isotope remains radioactive only for a short period of time. Understanding the emission of radiation from atoms requires an understanding of atomic and nuclear structure and forces. S TR UCTUR E O F THE ATO M The simplest description of the atom is that purposed by Bohr (Figure 2.1). In this model, electrons orbit a nucleus made up of tightly bound protons and neutrons. The electrons are held in place by the electrostatic forces between the negative charge of the electrons and the positive 14

K

L

M

Figure 2.1  Schematic diagram of an atom illustrating the nucleus and

surrounding electron energy shells.

charges of the protons in the nucleus. In a neutral atom the number of electrons will equal the number of protons. The term atomic is used when speaking of the atom as a whole, while nuclear is used when describing the nucleus. Radiations emitted by atomic processes include photons called x-​rays, and electrons. Radiation emitted by the nucleus includes photons called gamma rays; electrons called beta-​minus particles; and the antimatter counterpart of electrons called positrons or beta-​plus particles. Whenever beta particles are emitted, neutrinos and their antimatter counterpart are also emitted. Together with electrons, protons, and neutrons these particles are termed fundamental particles (Table 2.1). Both atomic and nuclear processes play a role in nuclear imaging. AT OMIC S T R U C T U R E While it is convenient to picture the atom as a small solar system where the electrons orbit the nucleus like planets orbiting the sun, in truth the electrons are not confined TABLE 2.1  PROPERTIES OF SOME FUNDAMENTAL PARTICLES Particle

Symbol

Mass (kg)

m0c2 (MeV)

Charge

Electron

e−, β−

9.11 × 10−31

0.511

−1

Positron

e+​, β+​

9.11 × 10

0.511

+​1

Proton

p

1.672 × 10−27

938.3

+​1

Neutron

n

1.675 × 10

939.6

0

Neutrino

u

Nearly 0

Nearly 0

0

Antineutrino

ú

Nearly 0

Nearly 0

0

Photon

γ

0

0

0

−31

−27

SECTION I. HISTORICAL, TECHNICAL, & PHYSIOLOGIC CONSIDERATIONS

 

TABLE 2.2   E L E C T RO N B IN D IN G E N E RG IE S (K E V) Atomic No.

Element

K Shell

L Shell s Subshell

L Shell p Subshell

6

Carbon

0.3

>0

>0

8

Oxygen

0.5

>0

>0

53

Iodine

33.2

5.2

4.9

O

M

4.6

74

Tungsten

69.5

12.1

11.5

10.2

82

Lead

88.0

15.9

15.2

13.0

92

Uranium

115.6

21.8

20.9

17.2

to elliptical orbits. Instead, the orbit corresponds to the electron’s most likely position, which is determined by the electron’s binding energy (the energy required to remove the electron from orbit). The electron travels all about the nucleus and even passes through at times; for this reason the orbits are described as electron shells and sub-​shells. The orbits can be characterized as discrete energy states, each described by a unique set of quantum numbers. The Pauli exclusion principle states that in a given atom, no two electrons can have the same values for the set of quantum numbers and therefore exist in the same energy state. The most important of these quantum numbers defines the electron shell and is designated by the nomenclature K, L, M, N, . . . or n =​1, 2, 3, . . . where K or n =​1 is the shell closest to the nucleus and has the highest binding energy. The maximum number of electrons in a shell is 2n2 and the outermost shell always has eight or fewer electrons. Electron binding energies for several elements are listed in Table 2.2.1 The energy states of electrons in atoms are specific and discrete. The atom is most stable when the electrons reside in the lowest energy states. This observation and the Pauli exclusion principle allow a description of the electron state of an atom and thus the structure of the periodic table of the elements. Transitions between energy states in an atom are discrete, corresponding to the difference between the two states. These transitions result in the absorption and emission spectra observed in the visible region of the electromagnetic spectrum for low-​energy transitions, as in low-​ atomic-​number (Z) materials, or outer-​shell transitions in high-​Z elements. Inner-​shell transitions produce the characteristic x-​rays observed in higher-​Z elements (Figure 2.2). In general the electrons reside in the lowest energy states, so that as a whole, the atom is in its lowest and therefore most stable energy state. When electrons are raised to higher allowable energy states, they spontaneously return to a lower energy state with the emission of energy corresponding to the difference between the higher and lower R adiation P hysics A N D R A D I A T I O N S A F E T Y

N

L Shell d Subshell

L

K

K

K

K

L

L

M

M

L

K

Figure 2.2  Characteristic x-​rays are produced by electron transitions in high-​

atomic-​number elements. For example, a Kα x-​ray results from an electron transition from the L shell to the K shell.

states. Similarly, electrons can be raised to higher energy states by the addition of energy equal in magnitude to that corresponding to the difference between states. When sufficient energy is transferred to an electron to remove it from the atom, a process called ionization, the vacancy created in the electron structure will eventually be filled by another electron, and the resulting energy difference between the initial and final energies of the electron can be emitted as a photon. For a given element, and therefore a specified atomic number, the energy states are characteristics of that element. Therefore, the absorption energy and emission energy corresponding to transitions in electron states are characteristic of that element. Characteristic x-​ray emission is the result of the filling of inner-​shell vacancies in high-​atomic-​numbered elements. For example, the Kα1 characteristic x-​ray of lead is 72.1 kilo-​electron volts (keV; calculated from the difference between the binding energy of lead’s K shell and L shell, s subshell). This process is also important in some modes of radioactive decay. Characteristic x-​rays are produced by electron transi­ tions in high-​atomic-​number elements. For example, a Kα x-​ray results from an electron transition from the L shell to the K shell. NU C LE AR S T R U C T U R E In the Bohr model of the atom, the nucleus consists of nucleons, both protons and neutrons, held together by strong nuclear forces that act only over very small distances—​that is, the dimensions of the nucleus. The dimension of the nucleus is about 10–​23 cm, and that of the

 

TA B LE 2.3   N U C L I D E N O TAT IO N S Name

Definition

Examples

Isotopes

Same Z, different N

15

O, 16O, 17O, 18O

Isotones

Same N, different Z

12

B, 13C, 14N, 15O

Isobars

Same A, different Z

59

Fe, 59Co, 59Ni, 59Cu

Isomers

Same Z, same N, different energy level

81m 99

Kr, 81Kr; 87mSr, 87Sr; 99mTc, Tc; 113mIn, 113In

atom is about 10–​8 cm. A particular nuclear configuration is called a nuclide and is described by the number of protons, thus the element, and the number of nucleons (neutrons +​ protons), thus the mass number. The conventional designation is the chemical symbol, which implies the atomic number (Z), and the mass number (A) as superscript. The neutron number (N) is the difference between the mass number and the atomic number: N =​ A minus Z. Isotopes are nuclides that have the same number of protons and thus are the same element, but have different numbers of neutrons and therefore different mass numbers. Isotones are nuclides with the same number of neutrons. Isobars are nuclides with the same mass number but different numbers of protons. We will see that many of the nuclear transformation modes of interest in gamma-​ray imaging are isobaric transitions. Isomers are nuclides with the same number of protons and neutrons but with different nuclear energy states. To designate an excited energy state of a nucleus that has a measurable lifetime, or a metastable state, a lowercase m is appended to the mass number, for example 99mTc. An isomeric transition is one type of gamma-​ray emission (Table 2.3).

Several models to explain nuclear forces have been proposed, often relying on a sharing of fundamental particles, such as mesons, resulting in strong attractive forces between pairs of nucleons. This is analogous to sharing electrons between atoms to form molecules. Pairing of nucleons, implying stability, is observed in the 249 known stable nuclear configurations.2 Of these configurations, only four have an odd number of protons and an odd number of neutrons. These are 2H, 6Li, 10B, and 14N, the four smallest odd-​Z elements. All others have even numbers of protons and neutrons, even numbers of neutrons, or even numbers of protons. In addition to this pairing observation for nucleus stability, another descriptive characteristic is the relationship between the number of neutrons and protons that yield stable configurations. For the lower-​atomic-​number stable nuclei, the proton-​to-​neutron ratio is approximately one to one. For the more massive, high-​atomic-​number stable nuclei, this ratio approaches 1.5 to 1. A plot of this relationship, shown in Figure 2.3, is referred to as the line of stability. The 249 data points define a narrow range for the neutron-​to-​proton ratio over the range of elements observed in nature. Any other nuclear configuration will be unstable, meaning it will undergo transformation by the process of radioactive decay to eventually arrive at a stable nuclear configuration. If a nucleus has a higher neutron-​to-​proton ratio than neighboring stable nuclei, it will undergo a nuclear transformation so that the neutron-​ to-​proton ratio will decrease. This will generally be in the form of beta (β–​) decay. Conversely, if the unstable nucleus has a neutron-​to-​proton ratio lower than its neighboring stable nuclei, then the mode of radioactive decay will result in an increase in the neutron-​to-​proton distribution, which

140 120

Neutron Number

100 Line of stability

Neutron excess

80 60 Line of identity 40 20 0

0

10

20

30

40

50

60

70

80

90

Proton Number Figure 2.3  The relationship between the number of neutrons and protons for the stable nuclear configurations.

16

SECTION I. HISTORICAL, TECHNICAL, & PHYSIOLOGIC CONSIDERATIONS

 

can occur by means of either positron (β+​) emission or electron capture (EC). Thus, it is often possible to predict the mechanisms of radioactive decay for a given unstable nucleus by comparing its neutron-​to-​proton distribution to that of the stable isotopes. There can be more than one stable isotope of an element. Elements with “magic numbers” (2, 8, 20, 50, 82, 126) of protons or neutrons tend to have multiple stable configurations. For example, calcium, with Z =​ 20, has five stable isotopes, and tin, with Z =​ 50, has 10 stable isotopes. RA DIOAC TIVI TY MODES OF RADIOACTIVE DECAY

If the nucleus is unstable, it is radioactive. Unstable nuclei rearrange through one of several mechanisms to arrive at a stable configuration—​that is, lowest energy state. The rearrangement processes are referred to as the modes of radioactive decay. These include alpha decay; β–​emission; β+​ emission; electron capture (EC); gamma-​ray emission, or isomeric transition (IT); and internal conversion (IC). During these processes there could also be emission of characteristic x-​rays from the electron orbits surrounding the nucleus and emission of discrete energy orbital electrons, either IC electrons or Auger electrons. By all of these mechanisms, energy is released, and the nucleus and entire atom end up in a lower total energy state. An alpha particle is the nucleus of an 4He atom. It consists of two neutrons and two protons. Alpha decay usually occurs only for high-​atomic-​number nuclei. They are emitted in one or more discrete energies, and the resulting daughter nucleus has an atomic number that is two less than the parent, and a mass number four less. A

The following modes of radioactive decay are more commonly encountered in radionuclides used for diagnostic imaging. Beta decay, the emission of a high-​energy electron and an antineutrino from a nucleus, results in the transformation of the parent element to a different element having an atomic number one larger than that of the parent (Figure 2.4). The mass number remains unchanged. A

X Z → A YZ+1 + β −+ ú + Q

The transformation is equivalent to the conversion, within the nucleus, of a neutron to a proton plus the electron and an antineutrino (ú), with the emission from the nucleus of the electron and the antineutrino. The effect on the neutron-​to-​proton ratio is the loss of one neutron and the gain of one proton, resulting in a decrease in the ratio from parent to daughter. Thus one would predict that unstable nuclei with excess neutrons would decay by beta emission. The neutrino and antineutrino are chargeless, nearly massless particles traveling at a velocity approaching the speed of light (see Table 2.1). Their existence was predicted many years before experimental verification to explain the continuum of beta-​ particle energies that was observed from beta-​emitting radionuclides. The sum of the energy of the beta particle and the antineutrino is constant for a given beta transition and is characteristic of the nuclear transformation. This energy is shared by the beta particle and the antineutrino, so the beta particle can have an energy ranging from zero up to that maximum. A positron is a positive electron, the antiparticle to an electron. Positron decay is equivalent to the transformation n

p

´

X Z → A-4 YZ-2 + α + Q

Q, the disintegration energy, includes the alpha particle energy, any recoil energy of the nucleus, and any gamma-​ray energy. Because an alpha particle is such a massive, doubly charged, ionizing particle, its range in solid material is small, typically microns. This high ionization density results in large amounts of energy deposited in a small volume around the atom. The high radiation dose from alpha emitters precludes their use in diagnostic radiopharmaceuticals, although there is increasing interest in their use in radiation therapy. R adiation P hysics A N D R A D I A T I O N S A F E T Y

´

Figure 2.4  In beta decay, the beta particle and an antineutrino are emitted

from the nucleus. The daughter nucleus has an atomic number one greater than the parent nucleus. The mass number is unchanged.

 

p

e

n

Figure 2.5  In positron decay, the positron and a neutrino are emitted from the nucleus. The daughter nucleus has an atomic number one less than the parent nucleus. The mass number is unchanged.

within the nucleus of a proton to a neutron plus a positron and a neutrino (u).The positron and the neutrino are ejected from the nucleus (Figure 2.5). A

X Z → A YZ −1 + β+ + u +Q

The result of this transformation is an increase in the neutron-​to-​proton ratio from the parent to the daughter. Thus, one would predict that unstable nuclei with neutron deficits might decay by positron emission. Being an antiparticle to an electron, the positron, after losing most of its kinetic energy, will encounter an electron, combine, and annihilate. To satisfy the principle of conservation of energy, on annihilation the two electrons’ masses are converted into photons with total energy of 1.022 mega-​electron volts (MeV), 0.511 MeV for each particle. From E =​mc2, the energy equivalence of an electron mass of 9.11 × 10–​31 kg is 0.511 MeV (see Table 2.1). These two 0.511 MeV protons are emitted at approximately 180 degrees to each other to satisfy conservation of linear momentum—​that is, the net linear momentum of the two particles before annihilation equals the net linear momentum of the two photons after annihilation. The simultaneous emission and fixed spatial orientation and energy of these two photons are the basis of positron emission tomography (PET). Electron capture is another mechanism whereby the nucleus can undergo a transformation that results in a higher neutron-​to-​proton ratio. An orbital electron, typically a K-​shell electron, combines with a proton in the nucleus to produce a neutron and a neutrino. The neutrino is ejected from the nucleus (Figure 2.6). The resulting daughter nucleus has an atomic number one less than that of the parent nucleus. 18

p

n

Figure 2.6  In electron capture, an orbital electron combines with a nuclear proton to produce a neutron and a neutrino. The neutrino is emitted from the nucleus. The daughter nucleus has an atomic number one less than the parent nucleus. The mass number is unchanged. The daughter atom has an electron vacancy in one of the inner shells.

A

X Z + e − → A YZ-1 + u + Q

Because a neutrino is virtually undetectable, if there are no other energy transitions, the electron capture would be undetectable. However, the capture of the electron results in a vacancy, typically in the K shell of the atom, which is now the daughter element, Y, and therefore there is the potential for the emission of a characteristic x-​ray. Characteristic x-​ray emission following orbital electron capture can be a major photon contributor from some medically useful radionuclides. 201Tl is an example of a radionuclide in which the most abundant photon emissions are the characteristic x-​rays of the daughter 201Hg following the capture of an orbital electron by the 201Tl nucleus. Following any of the modes of nuclear transformation just described, the nucleus may still have excess energy over that of the stable configuration. Under these circumstances, a photon—​a gamma ray—​may be emitted, carrying away some or all of this excess energy. These gamma-​ray emissions are either instantaneous at the time of the nuclear transformation or delayed. If delayed such that there is a measurable lifetime to the excited energy state, the emission is called an isomeric transition. These excited or metastable energy states are designated with an m following the mass number, as in 99mTc (see Table 2.3). An alternative to the emission of the gamma ray from the nucleus is a transfer of the gamma-​ray energy directly to an orbital electron of that atom, with the ejection of the electron from the atom. The gamma-​ray energy must exceed the binding energy of the electron for this to occur. The most probable electron is one from the shell that has a binding energy closest to but less than the gamma-​ray energy. This

SECTION I. HISTORICAL, TECHNICAL, & PHYSIOLOGIC CONSIDERATIONS

 

process (IC) results in a discrete energy electron and a vacancy in an electron shell of the atom. Subsequent electron filling of the vacant shell can result in either a characteristic x-​ray or an Auger electron. Auger electron emission is an alternative to characteristic x-​ray emission, and the process is analogous to IC electron emission instead of the gamma ray. Auger electrons originate from a lower energy state than that of the original electron shell vacancy, with the emission producing another electron shell vacancy. This process can occur several times in a single atom, resulting in the emission of a number of ionizing electrons. This cascading effect of Auger electrons can produce relatively high energy deposition within very small volumes and is of some interest in the development of therapeutic radiopharmaceuticals. The probability that a gamma ray will be internally converted is designated by the IC coefficient, α. It is defined as the number of IC electrons emitted divided by the number of gamma rays emitted. It is typically designated for each of the electronic shells, and therefore the individual shell IC coefficients add to give the total conversion coefficient. α = (#ICe , s)/ (# gammas) α = α K + α1 + α m + . . . The probability that a characteristic x-​ray will be emitted when a vacancy occurs in an electronic shell is the fluorescent yield. It is a probability that ranges from 0 to 1.0. The Auger electron yield is 1 minus the fluorescent yield. These parameters are important in describing and developing diagnostic and therapeutic radiopharmaceuticals because they have a direct impact on patient radiation absorbed dose. An energy level diagram, also referred to as a decay scheme, can illustrate the possible mechanisms by which a radionuclide may undergo transformation. In these schematic presentations, nuclear energy levels are represented as horizontal lines and energy transitions by arrows originating at one energy level and terminating at another, lower level. The horizontal axis represents the atomic number, so a transformation resulting in an increase in the atomic number from parent to daughter nuclide, such as β–​ decay, is diagrammed by an arrow pointing downward to the right. A decrease in atomic number, such as β+​ or EC, is diagrammed as an arrow pointing downward to the left. A vertical arrow represents no change in atomic number, such as gamma emission. The parent radionuclide with half-​life is represented by the top horizontal line and the daughter by the bottom line.

R adiation P hysics A N D R A D I A T I O N S A F E T Y

P32

14 days

1.7 MeV

100%

S32 Figure 2.7  Decay scheme for

32

P.

In the simplest decay scheme, only one energy transition is allowed, as illustrated by the β–​ emission from 32 P (Figure 2.7). More often there are multiple possible transitions of defined frequency, subsequently followed by gamma emission (Figures 2.8–​2.10).3 The decay schemes illustrate the allowed transitions but generally do not indicate information on any IC of the gamma emissions or emission of x-​rays or Auger electrons. A table of all transitions and emissions usually accompanies the decay scheme to provide additional information on IC electrons, Auger electrons, and characteristic x-​rays. MAT H OF R ADIOAC T IV E DE C AY Radioactive decay is a spontaneous, random process, meaning that the probability that a nucleus will undergo decay over a specified time period can be predicted, or the fraction of a number of unstable nuclei that will undergo decay per unit time can be defined, but the exact time of any individual transformation cannot. The number of nuclei undergoing transformation per unit time, dN/​dt, is directly proportional to the total number of nuclei, N. The constant relationship between the disintegration rate and the number of atoms is expressed by the decay constant, λ, which is characteristic of the radionuclide. F 18

110 mins.

EC 3% EC

97%

0.65 MeV O18 Figure 2.8  Decay scheme for

18

F.

 

TI 201

differential form of the decay equation. It can be expressed in the integral form N(t) = No e − λt , and because activity, A, equals λN, it can also be expressed as

73.1 hrs EC 1

EC 1 29%

EC 2

EC 2 12%

167 keV

EC 3 59%

135 keV 1

2

EC 3

• N(t) =​the number of atoms at time =​t; • N0 =​the number of atoms at time =​0;

Hg 201 Figure 2.9  Decay scheme of 201Tl. Not discernible from the scheme is an abundance of 201Hg x-​rays from vacancies created by the electron capture and internal conversion of the gamma rays.

dN = −λN dt The decay constant is the probability per unit time that a given nucleus will undergo decay, or, equivalently, the fraction of the nuclei present that will undergo decay per unit time. The number undergoing decay per unit time, or the number of transformations per second, is defined as the activity. The International System of Units (SI)4 designates the unit for activity as the becquerel (Bq). One Bq is one disintegration per second. The traditional unit is the curie (Ci), which is equal to 3.7 × 1010 disintegrations per second (the activity of 1 gram of radium-​226, an isotope studied by Marie and Pierre Curie). The becquerel is too small and the curie too large to be convenient for use in nuclear cardiology. Most radiopharmaceutical doses are given in megabecquerels (MBq, 106 becquerels) or millicuries (mCi, 10−3 curies), where 1 mCi =​37 MBq. While the use of mCi and Ci is discouraged in scientific publications, the traditional units are widely used throughout the United States of America. The relationship between the activity and the decay constant and the number of atoms is referred to as the

82%

2

0.3%

3

1.1%

4

16.4%

921 keV 3 2

Tc 99m Tc 99 Figure 2.10  The decay of

the 99mTc generator.

20

6 hrs

509 181 143 140

keV keV keV keV

2.2 E 5 yr Mo results in an isomeric state of 99Tc, enabling

99

• A0 =​the activity at time =​0. The exponential relationship indicates that the activity will change by the same fraction for equal time intervals. It is convenient to express the fractional change of one-​half, and therefore the associated time interval is referred to as the half-​life, or T1/​2. Using this in the foregoing equation A=

A0 when t = T1/2 2

T1/2 =

ln(2) λ

(ln(2) is the Naperian or natural logarithm of 2). Written in terms of half-​life, the decay equation becomes A(t) = A 0 e − ln( 2 )t/T1/2 The exponential nature of radioactive decay and the concept of half-​life are illustrated in Figure 2.11. Another useful measure of the change in activity of a radioactive material is the mean life, or average life, Taver. It is equal to the reciprocal of the decay constant:

65.9 hrs 4

1

• A(t) =​the activity at time =​t; and

Taver = 1/λ

Mo 99 1

A(t) = A o e − λt

When a radiopharmaceutical is administered to a patient, the decrease in activity with time is a combination of radioactive decay and biologic elimination. If the biologic removal is exponential—​that is, a constant fraction per unit time—​then the total removal fraction per unit time is the sum of the individual rate constants. λT = λp + λb

SECTION I. HISTORICAL, TECHNICAL, & PHYSIOLOGIC CONSIDERATIONS

 

TA B LE 2 .4   CH ARACTE RIS TICS O F CO MMO N RAD IO N U CL ID E S U S E D IN N U CL E AR IMAG IN G

100.0 87.5

GAMMA AND X-​RAY EMISSION IMAGING

Activity (%)

75.0

Radionuclide

62.5

123

50.0

Production

Decay

Emission (keV)

Half-​Life

I

Cyclotron

EC

γ 159

13.21 hrs

Tc

Generator

IT

γ 140

6.02 hrs

Tl

Cyclotron

EC

x 68–​80 keV, γ 167 keV

73 hrs

Production

Decay

Emission (keV)

Half-​Life

99m

37.5

201

25.0

POSITRON EMISSION IMAGING

12.5 0.0 0.0

2T 1/2

T 1/2 1.0

2.0

Radionuclide

3T 1/2 3.0

4.0

Time (Half-Lives, T 1/2 )

T0

T1/2

2T1/2

3T1/2

11

C

Cyclotron

β+​

385

20.3 min

18

F

Cyclotron

β+​

248

110 min

15

O

Cyclotron

β+​

735

122 sec

13

N

Cyclotron

β+​

491

9.96 min

82

Rb

Generator

β+​

1,523

1.3 min

SEALED SOURCES (QUALITY CONTROL AND TRANSMISSION IMAGING) Figure 2.11  Radioactivity decays exponentially. The curve represents the

percentage of radioactive nuclei that remain as a function of time. A half-​ life is the time required for half of the radioactive nuclei to decay.

Radionuclide 137

57

where λT is the total removal rate, λp is the physical removal rate (the decay constant), and λb is the biologic removal rate. The effective half-​life (Teff) reflects both mechanisms of removal and is obtained from the relationship between the half-​life and decay constant. Teff =

Tp Tb Tp + Tb

where Tp is the physical half-​life and Tb is the biologic half-​life. Half-​lives and photon emission energies of the common radionuclides encountered in a nuclear cardiology laboratory are shown in Table 2.4.5–​7 Examples of the application of the decay equations are shown in Examples 2.1 and 2.2. The radioactive decay curves of four radionuclides used in nuclear cardiology are shown in Figure 2.12. P RODUCTION O F RAD I O N UCLI D ES Earth and its atmosphere contain many naturally occurring radioactive elements. In addition to several radioactive decay series originating from parent radionuclides that have half-​lives of billions of years, there is constant production R adiation P hysics A N D R A D I A T I O N S A F E T Y

Co

153

68

Cs

Gd

Ge, 68Ga

Production

Decay

Emission (keV)

Half-​Life

Reactor

β−

γ 662

30 years

Cyclotron

EC

γ 122

272 days

Reactor

EC

γ 97, 103

240 days

Accelerator

EC, β+​

γ 511 × 2

271 days

EC, electron capture; IT, isomeric transition. Decay mode, emission, and half-​life data from MIRD: Radionuclide Data and Decay Schemes.7

of radioactive materials in the atmosphere from the interaction of cosmic rays with the elements of the atmosphere. In particular these interactions produce large quantities of 14C and 3H. Another notable long-​life, naturally occurring radionuclide is 40K. This potassium radioisotope is incorporated in living organisms in proportion to the total potassium in the organism. In humans it is the major contributor to radiation doses from naturally occurring, internally deposited radioactive materials. Most radionuclides used in medicine are not naturally occurring but are created—​produced by intentional transformations of a stable nuclide to an unstable configuration, usually employing nuclear reactors or charged particle accelerators. NU C LE AR R E AC T OR A nuclear reactor is a device in which a controlled chain reaction of a fissionable fuel material, such as 235U, is initiated

 

100.0

EXAMPLES OF RADIOACTIVE DECAY CALCULATIONS

EXAMPLE 2.1 

87.5

calibrated for 10 a.m. What was the concentration at 8 a.m.? At 3 p.m. that afternoon?

At 8 a.m.

Activity (%)

A 200-​mCi vial of Tc99m in 5 mL was received at 8 a.m.,

62.5 50.0 37.5 25.0

2 hrs/​6 hrs =​0.333 T1/​2

12.5

(0.5)0.333 =​0.794

0.0 0

(40 mCi/​mL)/​0.794 =​50.4 mCi/​mL

At 3 p.m.

12

18

24

Figure 2.12  Radioactive decays curves for four common radionuclides. After one day essentially all of the activity from an 18F source will be gone while significant amounts of 123I or 201Tl will remain. The black arrow indicated where the I-​123 decay curve crosses the 50% level (one half-​life)

(0.5)0.8333 =​0.561 (40 mCi/​mL)(0.561) =​22.4 mCi/​mL

and maintained. The fission of an atom of 235U results when a neutron is absorbed resulting in the breakup of the nucleus into two fission products and high-​energy neutrons. U + n →236 U → FP1 + FP2 + 3 n + ‡s

Where n represents high-​energy neutrons, and FP1 and FP2 are the two fission products and γs are multiple gamma rays produced after the reaction. Maintaining a chain reaction with 235U requires slowing down these neutrons and ensuring that at least one initiates another fission of a 235U nucleus. The rate of fission determines the rate of energy released and thus the power level of the reactor. The power can be adjusted by competing for the fission

EXAMPLE 2.2 

6

Time (Hours)

5 hrs/​6 hrs =​0.8333 T1/​2

235

Tc-99m F-18 I-123 TI-201

75.0

RADIOACTIVE DECAY CALCULATION

If a 100-​mCi source of Tc99m is stored for complete decay of the Tc99m, what is the resulting Tc99 activity? Must the Tc99

neutrons with a material that absorbs neutrons but does not undergo fission. This is the function of the control rods in the reactor (Figure 2.13). Control rods commonly contain cadmium, which has a high probability of interaction, or high cross-​section, for thermal neutrons. The fission products are usually radioactive, and at the time of the fission high-​energy gamma rays are commonly emitted. Thus the environment around the reactor core has very high radiation levels and requires massive protective shielding. The majority of the energy released in fission results in heating the coolant, which is typically water or heavy water. In a reactor designed to produce electricity from this heat, the reactor vessel is usually sealed and pressurized to produce the steam to drive turbines. In experimental reactors the vessel is often open and contains a large volume of water as the coolant and the neutron moderator, and as a radiation shield. There are also other reactor fuels besides uranium enriched in U235 that rely on high-​ energy neutrons for fission. Control Rods Shielding

be treated as radioactive waste? A =​λN

Uranium-235

For Tc99m, A =​3.7 × 109 dps N =​(3.7 × 109 dps)/​λ99m For Tc99, A =​λ99N A =​(λ99/​λ99m)(3.7 × 109 dps)

Neutron Moderator

Since (λ99/​λ99m) =​T99m/​T99 A =​(6 hr)(3.7 × 109 dps)/​{(2.1 × 105 years)(365 days/​year) (24 hr/​day)}

Coolant Circulation

Port for Neutron Bombardment of Stable Target

A =​12.1 dps =​0.33 nanoCi This level of activity would not be distinguishable from background and could be treated as nonradioactive waste.

22

Figure 2.13  Nuclear reactor for the production of radionuclides.

SECTION I. HISTORICAL, TECHNICAL, & PHYSIOLOGIC CONSIDERATIONS

 

In a reactor, a radionuclide with a higher-​than-​stable neutron-​to-​proton ratio can be produced either by neutron bombardment of a stable target nucleus to add a neutron or by splitting a large nucleus into two smaller, unstable nuclei. The resultant radionuclides, with neutron excesses, are most likely to decay by beta emission. An example of a neutron capture reaction is the production of 99Mo by the neutron irradiation of 98Mo with gamma-​ray emission of at the time of the capture of the neutron. This gamma ray is referred to as a prompt gamma and is not from the subsequent radioactive decay of the 99Mo.

TA B LE 2 .5   RE ACTO R- ​P RO D U CE D RAD IO N U CL ID ES Radionuclide P

14.3 days

32

S (n,p) 32P

60

Co

5.2 years

59

Co (n,γ) 60Co

99

Mo

66 hrs

235 98

U (n, fission) 99Mo Mo (n,γ) 99Mo Xe, 125Xe →

125

I

60 days

124

Xe (n,γ)

131

I

8.1 days

130

Te (n,γ) 131Te, 131Te → 131I U (n, fission) 131I

235

Cs

30.0 years

235

125

125

I

U (n, fission) 137Cs

Mo + n → 99 Mo + γ

Nuclear reactions are often abbreviated with the target material to the left, the product to the right, and the incident particle and output particle in parentheses. 98

Reaction

32

137

98

Half-​Life

Mo +(n, γ )Mo 99

Another mechanism to produce 99Mo is fission of 235U. The fission products resulting from the 235U breaking into two smaller nuclides are not uniformly distributed over the atom mass scale and instead have a bipolar distribution resulting in relatively high yields for mass numbers around 100 and 130. Thus 99Mo can be produced with fairly high yield from the fission of 235U. 99Mo produced as a fission product has a much higher specific activity, or activity/​g , than that produced by neutron irradiation of stable 98Mo. The higher specific activity produces higher 99m Tc concentrations when used in 99Mo–​99mTc generators. Concern over nuclear proliferation, however, has prompted efforts to shift 99Mo production away from traditional reactors that use highly enriched uranium (>20% 235U) to other methods. This effort is aimed at reducing the availability of highly enriched uranium that might be misused for non-​peaceful purposes. One method now in use is extraction from reactors designed to work with low enriched uranium (0.35. In support of Badhwar et al.,81 LV synchrony did improve after 3 months of CRT, and rest and exercise LVEF also improved. RVEF improved from a mean of 0.30 to 0.37 at rest and from 0.28 to 0.37 during exercise in the patients with reduced RV function at baseline but not in those with normal RVEF at baseline. Clinical outcome data were not available except for NT-​proBNP levels, which did significantly drop after CRT in both groups. Interestingly, RV and LV dyssynchrony worsened during exercise regardless of resting function. The study did not clearly demonstrate the value of adding exercise to the assessment of the response to CRT. Diastolic dyssynchrony has also been examined in an echo TDI study of 116 patients with CHF and severely reduced LVEF (mean 0.26 ± 0.08). Diastolic dyssynchrony was found more often than systolic dyssynchrony and was less likely to improve with CRT even when there was good systolic resynchronization,82 which could contribute to clinical nonresponders.

S E C T I O N I . H istorical , T echnical

 

ERNA has been used to assess the impact of different pacing sites on dyssynchrony and LV function. Singh et al. studied the changes in SDθ and LVEF between standard apical RV pacing and RV outflow-​tract pacing in patients who required a permanent pacemaker. Their data did show a smaller drop in LVEF using RV outflow-​tract pacing compared to RV apical pacing; it reached significance, although the differences were extremely small and not likely clinically relevant.110 There has been increasing interest in the prognosis of patients with ventricular dyssynchrony unrelated to CRT therapy.111–​115 That literature is entirely based on gated SPECT MPI phase analysis and will not be reviewed here. S U R V E I L L A N C E O F PAT I E N T S U N D E R G O I N G CHEMOTHERAPY

Early approaches to surveillance of patients treated with cardiotoxic chemotherapy were primarily related to the use of anthracyclines. The array of potentially toxic chemotherapeutic agents has greatly expanded to now include HER2 inhibitors, tyrosine kinase inhibitors, alkylating agents, antimetabolites, proteasome inhibitors, and immune checkpoint inhibitors as well as radiation therapy.116 Initial reports of surveillance involved the measurement of LVEF by RNA. The first such report, by Alexander et al., applied serial FPRNA to 55 patients receiving doxorubicin.117 In that study, all five patients who developed CHF had an LVEF of less than 30% at the time of the diagnosis of CHF. The incidence of toxicity varied with the cumulative dose of doxorubicin: No cardiotoxicity was detected in patients receiving less than 350 mg/​m2, whereas the patients who developed CHF had received at least 490 mg/​m2. Importantly, patients who developed CHF had radionuclide evidence of moderate toxicity (decline in LVEF to £45%) prior to reaching their lowest LVEF and the appearance of CHF. In contrast, those who developed moderate toxicity in whom doxorubicin was discontinued showed no CHF and no further decline in LVEF. That was a landmark study suggesting that the doxorubicin-​induced cardiomyopathy progressed gradually and that if identified early enough, chemotherapy could be withheld and any further deterioration in LV function avoided. That study was followed by one focused on patients with abnormal baseline LVEF,118 and then in 1987, the same group’s cumulative 7-​year experience was published.119 In 2003, the group once again updated their experience.120 They were able to demonstrate the success of the approach in preventing the appearance of CHF in patients treated with doxorubicin. They emphasized the increased risk of doxorubicin R adionuclide A ngiography

toxicity in patients with diabetes, concomitant use of other chemotherapeutic agents, prior or concurrent mediastinal irradiation, a lower baseline LVEF, and a higher cumulative dose of doxorubicin. Patients were considered at risk for CHF if either the baseline LVEF was at least 50% and dropped 10% or more to less than 50% during therapy or if the baseline LVEF was less than 50% and then dropped by 5% or had a final LVEF of less than 30%. Initial ERNA follow-​up was performed after a cumulative dose of 240 to 300 mg/​m2. The occurrence of CHF was 12% in the at-​risk patients and 1% in those not considered to be at risk. The 1% included two patients who developed CHF at an unexpectedly low cumulative dose of doxorubicin. Subsequent confirmation by others ultimately led to an algorithm and guideline that remained in use for decades. However, it was demonstrated early on that histologic changes of doxorubicin cardiotoxicity were present on myocardial biopsy before the appearance of changes in LVEF, suggesting poor sensitivity of resting LVEF for detection of subclinical cardiotoxicity. Druck et al. suggested that the addition of exercise RNA LVEF detected 6/​31 cases of biopsy-​proven anthracycline cardiotoxicity that were not identified on resting RNA alone. They also showed a linear correlation between the biopsy grade of toxicity and LVEF.121 The increase in sensitivity by adding exercise RNA was confirmed by Alcan et al.122 However, McKillop et al. showed that the addition of exercise LVEF increased the sensitivity of detection of moderate-​ or high-​risk patients from 53% to 89% but lowered the specificity to 41% in a study that confirmed the diagnosis of cardiotoxicity by endomyocardial biopsy.123 Other markers of LV dysfunction have been reported to appear prior to changes in resting LVEF, including LV diastolic dysfunction,124,125 LV global longitudinal strain (GLS),126,127 and troponin I levels.128,129 When diastolic function and systolic function were both evaluated by ERNA in patients receiving trastuzumab therapy, Reuvekamp et al. could not demonstrate that the diastolic dysfunction that occurred in half the patients occurred sufficiently before the change in LVEF to be clinically helpful.125 In all studies looking at alternative measurements of LV dysfunction and biomarkers to detect early cardiotoxicity, the 10% drop in LVEF and/​or CHF were still used as the clinical criteria for the diagnosis of cardiotoxicity. Cardinale et al. showed that LVEF, in that case using 2D echo biplane measurements, was still a viable marker for surveillance of an at-​risk population receiving anthracycline-​containing chemotherapy, but they showed that changes in troponin I predicted subsequent declines in LVEF.129 Criteria for cardiotoxicity remained similar to those recommended by Schwartz et al. using FPRNA in 1987.121 In the current era, however,

 

recommendations have evolved to include multimodality imaging and biomarkers, and a normal LVEF has been defined as 55% rather than 50%. 3D echo LVEF has been recommended as the first-​line method for surveillance, with ERNA or MRI to be used when 3D echo is not available or echo results are technically suboptimal. 2D biplane echo LVEF is considered the least reliable of the methods. For a more thorough evaluation, it has been recommended to add measurements of diastolic function, echo GLS, and valve assessment at baseline before initiating potentially cardiotoxic therapy. For patients with a mildly reduced baseline LVEF of 45% to 54%, pretreatment with a beta blocker and an angiotensin-​converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) should be considered as well as the addition of a cardiac MRI. For those with normal or mildly reduced baseline LVEF, clinical cardiotoxicity is still defined as a drop in LVEF of at least 10% from baseline. For a thorough review of contemporary approaches to chemotherapy-​related cardiac dysfunction, the reader is referred to the excellent review by Soufer et al.116 At present, there is a wide array of imaging techniques being applied to the study of the problem, ranging from imaging reactive oxygen species,130 a putative cause of cardiac dysfunction from chemotherapy, to imaging apoptosis, a marker of cell death.131 At some point, the guidelines for detection and management of chemotherapy-​related cardiac dysfunction will likely be amplified or restructured, but for now, radionuclide, echo, and MRI measurements of systolic and diastolic LV function remain the backbone of a surveillance program. The major limitation of ERNA for surveillance is the radiation burden. In anthracycline therapy, toxicity is, in general, related to cumulative dosing, so surveillance studies can be tied to the dose and thereby minimized. But with trastuzumab therapy, where toxicity is not related to cumulative dose, surveillance must be performed at scheduled intervals before, during, and after chemotherapy. Laboratories should, therefore, consider the application of CZT detector systems that would allow radionuclide dose reductions of 50% or more. RV SYSTOLIC FUNCTION

CAD Quantitation of RV systolic function has been and continues to be a challenge, and FPRNA, gated FPRNA, and SPECT ERNA remain viable techniques for application to patients with most forms of heart disease. Standard echocardiography is of value for the qualitative assessment of RV size and function but not for quantitation. RV strain imaging 120

with echo speckle-​tracking is a more reliable quantitative assessment, but no head-​to-​head comparison between RNA RVEF and echo RV strain is yet available. The radionuclide evaluation of RVEF began to appear in the literature over 40 years ago in patients with acute inferior wall and associated RV infarction. Tobinick et al. performed technetium-​99m pyrophosphate (PYP) planar imaging to detect RV infarction in patients presenting with an acute MI. FPRNA was used to calculate RVEF and was acquired during the PYP injection. In the patients with inferior MI and no RV uptake of PYP, RVEF was 0.51 ± 0.10 compared to 0.39 ± 0.05 in those with PYP evidence of RV infarction.132 The course of RV dysfunction accompanying acute inferior wall infarction was described by Dell’Italia et al. using ERNA in 33 patients at 6 to 12 weeks after MI.133 Of the 12 patients whose initial ERNA showed evidence of RV infarction, RVEF improved from 0.27 ± 0.07 to 0.36 ± 0.09 (p < .01) without any revascularization. RVEF was systematically underestimated due to the ERNA method used but, nonetheless, demonstrated the spontaneous improvement characteristic of many patients with acute and sometimes severe RV dysfunction accompanying acute inferior MI even in the absence of pharmacologic or interventional revascularization. In chronic CAD, De Groote et al. studied the prognostic value of RVEF measured with planar ERNA in a cohort of patients with moderate heart failure, which included ischemic and nonischemic etiologies. In multivariate analysis, RVEF proved to be a significant independent predictor of total mortality and CV mortality along with NYHA class and percentage peak predicted exercise VO2 max.134

Pulmonary Hypertension FPRNA and ERNA have been in use for decades to assess RV systolic function in patients with PH. Survival in patients with PH is related to measures of RV performance. The 2015 European Society of Cardiology guideline suggested that prognosis in PH is best assessed by determining functional class, at least one measurement of exercise capacity (either the 6-​minute walk test or cardiopulmonary exercise testing), and right ventricular function.135 Recent guidelines, including the 2015 European guideline, recommend the use of 2D echo or MRI for routine follow-​up of PH patients, which, in part, is driven by the frequency with which the measurements are recommended and the concern for the cumulative radiation burden if RNA were used routinely. As of 2014, however, the French pulmonary hypertension registry included many patients followed with

S E C T I O N I . H istorical , T echnical

 

conventional planar ERNA, and a subgroup analysis of those patients dichotomized the group into those with an RVEF 50–​60% luminal narrowing) enlarged the eligible pool of patients for MPI testing (see of major epicardial coronary arteries or branches leads to Chapter 12, Pharmacological Stress Testing). More recent uneven distribution of the flow and to a regional decrease developments have been driven by another technological of tracer uptake. With knowledge of normal coronary CZT ECG EF FBP FOV IR LV MPI PET PMT QC SPECT

cadmium-​zinc-​telluride electrocardiogram ejection fraction filtered backprojection field of view iterative reconstruction left ventricular myocardial perfusion imaging positron emission tomography photomultiplier tube quality control single-​photon emission computed tomography summed rest score summed stress score technetium-​99m transient ischemic dilation thallium-​201 total perfusion deficit

TAB LE 6 . 1   P H YS ICA L P RO P E RT IE S O F TH E TH RE E CL IN ICAL LY AVAIL AB L E S PE CT RAD IO IS O TO PE S Half-​Life (T½)

Photon Energy

First-​Pass Uptake

Effective Dose

Tl-​201

73.1 hours

Principal emission of 68 to 80 keV

85%

4.4 mSv/​mCi

Tc-​99m sestamibi

6 hours

140 keV

≈60%

0.3 mSv/​mCi

Tc-​99m tetrofosmin

6 hours

140 keV

≈50%

0.3 mSv/​mCi

G ated S P E C T M P I

 

40

Ultra-Fast Protocol

35

Half-Time Protocol

insulin while they are NPO. The study procedure, including imaging and stress, proper attire for exercise stress, and estimation of the length of the study, should be explained in advance to set expectations for the testing day.

Conventional SPECT

Dose (mCi)

30 25 Half-Time Half-Dose Protocol

20

Half-Dose Protocol

P R E T E S T P R E PA R AT I O N

15 Fast/LowDose Protocols

10 5

Ultra-Low Dose Protocol

0 0

5 10 Imaging Time (Min)

15

Figure 6.1  Patient-​centered imaging options using iterative reconstruction

(half-​time—​half-​dose software) and high-​efficiency SPECT cameras  Adapted from Slomka et al. (10)

anatomy, inferences can be made about the location of epicardial stenoses. Absolute coronary flow currently cannot be routinely calculated from SPECT MPI as opposed to PET imaging, in spite of efforts to do so (see Chapter 10, Measurement of Myocardial Blood Flow by SPECT).9 Modern patient-​centered imaging protocols utilizing iterative reconstruction algorithms for conventional SPECT cameras and high-​efficiency SPECT cameras allow for either lower tracer dose or shorter imaging time or a combination of both (Figure 6.1).10,11 No guideline-​mandated protocols were adopted prior to the release of this radiation dose-​reducing technology, but they were eventually incorporated into current guidelines.12 The rigidity of fixed-​dose protocols can be replaced by more flexibility of dosing and image acquisition time tailored to individual patients. Im aging P ro t ocols PAT I E N T P R E PA R AT I O N

The general principles of patient preparation are the same for all stress SPECT MPI studies regardless of protocol. Patients should be NPO overnight prior to testing with the exception of medications, which can be taken with sips of liquid. For those having afternoon studies, a liquid diet for breakfast can be considered to avoid dehydration. Caffeine should be avoided for at least 12 hours prior to testing to prevent competitive antagonism when vasodilator stressors are used or to allow for backup vasodilator stress if exercise stress is inadequate. Diabetic patients should receive special instructions on taking oral hypoglycemic medications and 128

Immediately prior to testing patient identification, appropriate use criteria consultation,13,14 explanation of the test procedure with associated risks (including the use of radioactive tracers) and benefits, and assessment of possible contraindications to testing as described in ASNC guidelines are mandatory.12 The indication for the planned testing should be reviewed and the best protocol for the individual patient selected based on clinical information, body habitus, and the patient’s ability to exercise and ability to cooperate (see also Chapter 11, Treadmill Exercise Testing and Chapter 12, Pharmacologic Stress Testing).1 An abbreviated history and physical exam, along with informed consent, is required for stress testing with SPECT imaging. Radiotracer doses should be planned and need to follow ALARA principles—​use the lowest tracer dose that will obtain high-​quality, diagnostic imaging based on patient characteristics and laboratory equipment. The ASNC goal of less than 9 mSv radiation for a complete SPECT MPI study unfortunately remains only a desirable goal, not a consistent reality.15 T L - ​2 0 1 P R O T O C O L S

Tl-​201 is a cyclotron-​produced element with a physical half-​life of 73.1 hours. Tl-​201 is a low-​energy emitter with a primary Tl-​201 photopeak of 68 to 80 keV. There is no on-​site preparation or QC procedure prior to intravenous injection, only dose calibration. First-​pass myocardial extraction of Tl-​201 at normal coronary flow in vivo models is approximately 87%. Linearity of myocardial uptake is preserved up to high flow rates (up to 2.5 cc/​min/​g ).12 Underestimation of flow may result, particularly with the use of pharmacologic stressors (Figure 6.2). Of the injected Tl-​201 dose at peak stress only 3% to 5% of the dose is taken up by the myocardium. The highest noncardiac uptake of Tl-​201 is by the kidneys (target organ).

Standard Stress-​Redistribution Protocol After intravenous injection of Tl-​201 at peak stress, differential washout (redistribution) from myocardial segments with uneven initial tracer uptake allows for distinction between “fixed” and “reversible” perfusion defects. Washout

S E C T I O N i . H istorical , T echnical

 

15O-water

5

18F-flurpiridaz

Tracer uptake (×normal)

4 99mTc-teboroxime

3

201T1 13N-ammonia 82Rb

2

99mTc-sestamibi

1

99mTc-tetrofosmin

0 0

1

2

3

4

5

Coronary blood flow (mL/min/g) Rest Exercise Pharmacologic vasodilation Figure 6.2  Relationship of radiotracer uptake and myocardial blood flow. Commonly used SPECT tracers “tail off” and lose their linearity with blood flow at

higher flow rates, which may result in underestimation of coronary flow, particularly with the use of pharmacologic stressors  Figure from Schindler, 2015. (74)

is higher from segments with higher initial uptake and slower from the segments with lower initial uptake due to the concentration gradient between the myocardium and the arterial blood. Tl-​201 redistribution occurs in 3 to 5 hours after injection. Redistribution or “fill in” of post-​ stress defects implies the presence of ischemia not scar (i.e., viable myocardium). The persistence of stress perfusion defects is more consistent with the presence of scar tissue (fibrotic tissue rather than viable myocytes). Using the guideline-​recommended 2.5 to 3.5 mCi for a conventional Anger camera, the estimated radiation dose to the patient is 10.9 to 15.3 mSv.12 Using more efficient solid-​ state detectors (CZT cameras), a Tl-​201 dose of 1.3 to 1.8 mCi was shown to be adequate for high-​quality imaging.12 Radiation dose to the patient is thereby decreased to 5.7 to 7.9 mSv (Table 6.2). In cases where standard stress-​redistribution imaging shows a fixed or minimally reversible perfusion abnormality, myocardial viability can be assessed with additional rest images at 18 to 24 hours or following reinjection of an additional 1-​ to 2 mCi dose of Tl-​201. Tl-​201 in this manner can be used for detection of myocardial “viability” G ated S P E C T M P I

(see Chapter 19, Myocardial Viability Assessment by Nuclear Techniques). An alternative method of viability assessment is the injection of 2.5 to 3.5 mCi of Tl-​201 at rest followed in 3 to 4 hours or 18 to 24 hours by imaging (Figure 6.3). The time of Tl-​201 injection during exercise and pharmacologic stress is identical to that of Tc-​99m and occurs with 1 minute of exercise stress remaining and at peak hyperemia during pharmacologic stress. Post-​stress imaging is started shortly (minutes) after completion of the stress portion of the test (see Figure 6.3). The timely review of processed post-​stress images is critical for correction of possible technical deficiencies (patient motion, low count density, extracardiac activity) given the rapid onset of redistribution after stress. Redistribution/​rest imaging is scheduled 2.5 to 4 hours after completion of stress imaging. Considering the high proportion of normal SPECT studies,16 Tl-​201 is an ideal tracer for “stress-​only” imaging. If both the stress ECG results and imaging results are normal, delayed (redistribution) imaging may be cancelled, resulting in shortened test length by many hours if not a reduction in patient radiation exposure (Box 6.1).17

 

TA B LE 6.2   R E C OM M E N D ED RA D IO T RACER D O S E S FO R CO MMO N TC- 9 ​ 9 M AN D TL - ​2 0 1 S PE CT PRO TO CO L S U S IN G CONV E NT I O N A L SPECT A N D H IG H - E​ F F ICIE N CY S P ECT CAME RAS First Injection

Second Injection

Total Dose (mSv)

Phase

Activity (mCi)

Activity (MBq)

Phase

Activity (mCi)

Activity (MBq)

1-​day rest–​stress

Rest

8–​12

296–​444

Stress

24–​36

888–​1,332

8.4–​12.6

1-​day stress–​rest

Stress

8–​12

296–​444

Rest

24–​36

888–​1,332

9.0–​13.5

2-​day large patient

Stress

18–​30

666–​1,110

Rest (if needed)

18–​30

666–​1,110

9.8–​16.3

1-​day rest–​stress

Rest

4–​6

148–​222

Stress

12–​18

444–​666

4.2–​6.3

1-​day stress–​rest

Stress

4–​6

148–​222

Rest

12–​18

444–​666

4.5–​6.7

2-​day large patient

Stress

9–​15

333–​555

Rest (if needed)

9–​15

333–​555

4.9–​8.1

Stress

2.5–​3.5

92.5–​129.5

n/​a

n/​a

n/​a

10.9–​15.3

Stress

1.3–​1.8

48.1–​66.6

n/​a

n/​a

n/​a

5.7–​7.9

Tc-​99m Protocols Conventional SPECT

High-​Efficiency SPECT

Tl-​201 Protocols Conventional SPECT Stress-​redistribution rest High-​Efficiency SPECT Stress-​redistribution rest Adapted from Henzlova et al.12

T C - ​9 9 M T R A C E R P R O T O C O L S

Tc-​99m agents are currently used for most SPECT studies in the United States. Of the two available Tc-​99m myocardial perfusion agents, Tc-​99m sestamibi (Cardiolite) was introduced for clinical use in 1990. Tc-​99m tetrofosmin (Myoview) was introduced several years later, in 1996. Tc-​99m has a physical half-​life of 6 hours with photon energy of 140 keV. The first-​pass extraction of Tc-​99m tracers is only 50% to 60%. Linearity between myocardial blood flow and myocardial extraction is less preserved at higher flows when compared to Tl-​201 or to available PET agents (fubidum-​82 and N-​13 ammonia) (see Figure 6.2). Tc-​99m tetrofosmin flow-​uptake linearity is less favorable at high coronary flows (using pharmacologic stress) than Tc-​99m sestamibi. After initial myocardial uptake by passive diffusion, the agent is retained in the mitochondria. Since both Tc-​99m agents show very slow myocardial clearance, there is no clinically significant “redistribution” of Tc-​99m tracers. Therefore, a separate intravenous dose is needed for the stress and rest imaging. Tc-​99m tracers are excreted by the hepatobiliary system into the gastrointestinal tract, and the target organ of Tc-​99m sestamibi is the upper large intestine, while it is the gallbladder wall for Tc-​99m tetrofosmin. Clearance from the liver is faster with Tc-​99m tetrofosmin compared to Tc-​99m sestamibi, resulting in a shorter time 130

to imaging after tracer injection for tetrofosmin.18 Imaging should be started 30 to 45 minutes after the rest injection, 15 to 30 minutes after exercise, and 45 to 60 minutes after pharmacologic stress.19 For each patient there is an optimal imaging time when the counts in the liver have cleared but activity has not concentrated in bowel close to the heart. The lack of redistribution of Tc-​99m agents (tracer clearance is dictated only by physical decay) allows for flexibility in the type of imaging protocols: 1-​day, 2-​day, stress-​ first, rest–​stress, or stress–​rest sequence. Repeat imaging in cases of patient motion or other technical difficulties is also possible and should be implemented according to the clinical scenario and laboratory flexibility (see Table 6.1).

Rest–​Stress Protocols 1 Day Protocols Given the 6-​hour physical half-​life of Tc-​99m, a 24-​hour interval would be needed for complete resolution of background activity. However, in clinical practice the most commonly performed Tc-​99m protocol is a 1-​day, split-​dose study with a 1:3 ratio of low to high dose (Figure 6.4). This protocol is widely used due to the lack of delay between the low-​dose rest and high-​dose stress, which allows for efficient patient and laboratory workflow and convenience. The current ASNC guidelines suggest a low dose of 8 to 12 mCi and a high dose of 24 to 36 mCi using a conventional

S E C T I O N i . H istorical , T echnical

 

(A) Day 1

Day 2

Inject TI-201 Stress

Stress

15 min.

Stress Imaging

Review

2.5–4 hour Delay

Rest Imaging

Review

Time

24 hour Redistribution Imaging

Review

Optional, Depending on Physician’s Interpretation of the Images

(B) Day 1

Day 2

Inject TI-201 Stress

Stress

15 min.

Reinject TI-201

Stress Imaging

Review

2.5–4 hour Delay

Rest Imaging

Review

Time

15 min.

Reinjection Imaging

24 hour Imaging

Review

Optional, Depending on Physician’s Interpretation of the Images

(C) Day 1 Inject Tc-99m Stress

Inject TI-201 Rest

15 min.

Day 2

Rest Imaging

Stress

15–45 min. Delay

Reinject TI-201

Stress Imaging

Time

Review

24 hour TI-201 Redistribution Imaging

Review

Optional, Depending on Physician’s Interpretation of the Images

Figure 6.3  Traditional stress-​redistribution Tl-​201 imaging protocol (A), and with reinjection of additional activity for improved viability assessment (B).

Resting Tl-​201 imaging for viability assessment with optional reinjection illustrated  Reproduced with permission from Henzlova MJ, Duvall WL, Einstein AJ, Travin MI, Verberne HJ. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers. J Nucl Cardiol 2016;23:60639.

Anger camera, which results in a radiation exposure to the patient of 11.3 mSv.12 Using high-​efficiency cameras, which allow for shorter imaging times, lower tracer doses, or a combination of both, the suggested rest doses are 4 to 6 G ated S P E C T M P I

mCi and stress doses are 12 to 16 mCi, with resulting radiation exposure to the patient decreased to 4.5 to 6.7 mSv.12 The time of Tc-​99m injection during exercise and pharmacologic stress is identical to that of Tl-​201 and occurs with

 

BOX 6.1 

PROS AND CONS OF TL-​2 01 IMAGING

Advantages of Tl-​201 SPECT Imaging Extensive evidence-​based data accumulated over several decades of use Acceptable flow-​uptake linearity and high first-​pass uptake of the tracer Absence of liver uptake, thus no interference with evaluation of inferior wall perfusion Possible “stress-​only” protocol Acquisition and review of anterior planar images allows for quantification of lung:heart count ratio. Elevated Tl-​201 lung activity early after exercise is indicative of increased LVEDP and of LV dysfunction.71 Abnormal values (lung:heart ratio >0.55) should be reported. Preferred SPECT tracer for evaluation of myocardial viability

Disadvantages of Tl-​201 SPECT Imaging More prominent soft tissue attenuation due to lower photon energy (68–​80 keV compared to 140 keV for Tc-​99m) is of importance with the currently high prevalence of obesity. The long half-​life of Tl-​201 (73.1 hours) also limits the ability to increase the injected dose to offset this problem. Gated images may be relatively count-​poor, and at times longer imaging time is required for reliable evaluation of LV systolic function. Also, early post-​exercise imaging (only minutes after peak stress) does not allow for assessment of true resting LV systolic function. In patients with extensive ischemia, LV function early post-​exercise may differ significantly from LV function at rest.72 Radiation dose of Tl-​201 SPECT is higher compared to Tc-​99m tracers. The use of Tl-​201 for SPECT MPI in younger patients without known limited life span should be discouraged unless high-​efficiency cameras allowing for low tracer doses are available. There is no on-​site preparation of Tl-​201; therefore, only an estimated number of doses can be purchased.

1 minute of exercise stress remaining and at peak hyperemia during pharmacologic stress.

Two-​Day Protocols While they may be technically superior, the routine use of 2-​day tests is not practical as they are inefficient, requiring two patient encounters, and result in higher radiation exposure. Two-​day protocols allow for the administration of two higher-​dose injections by taking advantage of the 6-​ hour half-​life of Tc-​99m, in which complete resolution of background activity is possible after 24 hours (see Figure 6.4). The stress study should be performed first as rest imaging will be unnecessary if the stress images are normal (see “Stress-​First Protocols” below). Two-​day protocols are recommended when PET MPI is not available for obese patients (>250 lbs or BMI > 35 kg/​m2) or in patients where significant breast attenuation is anticipated as the higher injected activity is often needed for diagnostic-​quality perfusion images.12 Gated acquisition should be performed on both rest and stress images given the higher dose of injected activity. The current ASNC guidelines suggest a dose of 8 to 12 mCi for non-​obese patients and 18 to 30 mCi for larger patients using a conventional Anger camera, which results 132

in a radiation exposure to the patient of 4.3 to 16.3 mSv. Using high-​efficiency cameras, the suggested doses are 4 to 6 mCi for non-​obese patients and 9 to 15 mCi for obese patients, with resulting radiation exposure to the patient decreased to 2.2 to 8.1 mSv (see Table 6.2).12

Dual-​Isotope (Tl-​201 and Tc-​99m) Protocols Dual-​isotope protocols (rest Tl-​201 and stress Tc-​99m) were popular in the early 1990s, mostly in the western United States. The protocol aims to take advantage of the properties of both tracers—​Tl-​201’s ability to find more viable myocardium with resting images, and Tc-​99m’s ability to provide higher-​quality stress and stress-​gated images due to higher-​ energy photons. In this protocol a rest injection of Tl-​201 (3.0–​3.5 mCi) is immediately followed by rest imaging and then by stress and stress imaging. A stress dose of a Tc-​99m agent is followed 15 to 45 minutes later by stress imaging (see Figure 6.4). The advantage of the protocol is shortening of the test (no waiting time after rest tracer injection), absence of gastrointestinal uptake of Tl-​201, and absence of background Tc-​99m from rest imaging. However, the disadvantages of this approach exceed its advantages: Rest Tl-​201 counts may be too low for valid image quality, especially for gated images;

S E C T I O N i . H istorical , T echnical

 

(A) Inject Tc-99m Rest

Inject Tc-99m Stress

30–60 minutes

Rest Imaging

15–45 minutes

Stress

Stress Imaging

Review

Time

(B) Inject Tc-99m Stress

Stress

Day 1

Day 2

Inject Tc-99m Rest

15–45 minutes Stress Imaging

Review

30–60 minutes

Time

Review

Optional, Depending on Physician’s Interpretation of Stress Images

(C)

Day 1

Inject TI-201 Rest

15 min.

Day 2

Inject Tc-99m Stress

Rest Imaging

Stress

15–45 min. Delay

Stress Imaging

Review

24 hour TI-201 Redistribution Imaging

Time

(D)

Rest Imaging

Optional, Depending on Physician’s Interpretation of the Images

Inject Tc-99m Stress

Stress

Review

15–45 minutes

Inject Tc-99m Rest

Stress Imaging

Time

Review

30–60 minutes

Rest Imaging

Review

Optional, Depending on Physician’s Interpretation of Stress Images

Figure 6.4  Traditional 1-​day rest–​stress (A) and 2-​day (B) stress–​rest Tc-​99m SPECT MPI protocols. Dual-​isotope (Tl-​201 rest and Tc-​99m stress) protocol

(C), and 1-​day stress-​first protocol (D)  Reproduced with permission from: Henzlova MJ, Duvall WL, Einstein AJ, Travin MI, Verberne HJ. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers. J Nucl Cardiol 2016;23:60639.

G ated S P E C T M P I

 

comparing images obtained with two different tracers is problematic; and the radiation exposure to the patients is excessively high. Using the recommended tracer doses, the estimated radiation exposure to the patient exceeds 20 mSv, and as a result the routine use of dual-​isotope protocols is not recommended by ASNC guidelines.12

Stress-​First Protocols Stress-​first approaches to MPI provide diagnostically and prognostically accurate perfusion data equivalent to a full rest–​stress study while saving time in the imaging laboratory and reducing the radiation exposure to patients and laboratory staff. MPI interpretation is traditionally conceptualized in two parts. First, an image of radiotracer distribution under stress conditions is reviewed for any areas of decreased activity. The reader then compares these areas to a resting scan to determine whether the defect is reversible (ischemia) or fixed (infarction). When stress MPI is normal, however, the rest image becomes superfluous, which is the underpinning logic for stress-​first protocols. In current clinical practice, the majority of appropriately indicated diagnostic stress MPI studies are found to be normal, especially in patients with no prior history of CAD.16,20 Stress-​first protocols represent an attractive option for a cost-​effective strategy for the initial evaluation of patients who are currently at low risk for abnormal findings during stress MPI studies (see Figure 6.4). The prognosis of a normal stress-​only SPECT MPI study is comparable to a normal rest–​stress study, with multiple studies demonstrating annualized cardiac event rates of less than 1% following a normal stress-​only MPI.21 Low all-​cause mortality and cardiac event rates following a normal stress-​only MPI suggest that rest imaging can be omitted without any reduction in the prognostic value of the test. In general, patients with low to intermediate pretest probability for CAD (based on age, gender, risk factors, symptoms, and rest ECG) are suitable candidates for a stress-​ first or stress-​only MPI protocol. Another suitable group is patients with a high BMI (>35 kg/​m2 or weight >250 lbs); also, patients with recent ( basal) lead to a heterogeneous pattern in the polar map.67 Description of segmental wall motion follows the standard 17-​segment model and classifies wall motion as normal, mildly, moderately, or severely 148

hypokinetic; akinetic; or dyskinetic. Interpretation of wall motion should be used in context with perfusion imaging and hence may be helpful in discrimination of artifact versus true perfusion defects.

S E C T I O N i . H istorical , T echnical

 

Study interpretation should also assess for the presence of TID, which can be visually interpreted and/​or quantified. TID, where the post-​stress LV cavity appears larger than the rest cavity, represents either endocardial ischemia at peak stress (i.e., absence of endocardial counts as opposed to restored endocardial perfusion at rest) or stress-​induced LV stunning with true post-​stress LV dilation. Quantitatively the stress:rest cavity size ratio is more than 1, and the ratio is calculated from ungated LV volumes post-​stress and at rest. The presence of TID in the setting of reversible stress-​induced ischemia is suggestive of significant (extensive) CAD, while the significance of TID in the setting of normal perfusion is less clear.68,69 TID has been shown to portend a poor prognosis, with the annual mortality rate when TID is accompanied by ischemia described as 6%.68 Besides TID, a number of other findings unrelated to perfusion have been correlated with the presence of CAD, including increased pulmonary uptake, increased right ventricular tracer uptake, and decreased post-​stress ejection fraction.70 Finally, the SPECT MPI report summarizes the demographic, clinical, and technical information, as well as the stress and imaging results, in clear and concise language necessary for optimal clinical decision-​making by report recipients (see Chapter 36, Nuclear Cardiology Report Generation).51 The report should have a defined structure containing standardized data elements to ensure the efficient and thorough communication of results. Comparison with previous studies, if available, is valuable and should be part of the report. ASNC supports the mandatory use of structured reporting as a mechanism to improve the communication and reporting of nuclear cardiology reports.51

R EF ERENCES 1. Depuey EG, Mahmarian JJ, Miller TD, et al. Patient-​centered imaging. J Nucl Cardiol. 2012;19:185–​215. 2. Einstein AJ, Moser KW, Thompson RC, et al. Radiation dose to patients fro m cardiac diagnostic imaging. Circulation. 2007;116: 1290–​130 5. 3. Fazel R, Krumholz HM, Wang Y, et al. Exposure to low-​dose ionizing radiation from medical imaging procedures. N Engl J Med. 2009;361:849–​857. 4. Einstein AJ, Berman DS, Min JK, et al. Patient-​centered imaging: Shared decision making for cardiac imaging procedures with exposure to ionizing radiation. J Am Coll Cardiol. 2014;63:1480–​1489. 5. Pagnanelli RA, Basso DA. Myocardial perfusion imaging with 201Tl. J Nucl Med Tech. 2010;38:1–​3. 6. Iskandrian AS, Heo J, Askenase A, et al. Thallium imaging with single photon emission computed tomography. Am Heart J. 1987;114: 852–​865. 7. Maddahi J, Kiat H, Van Train KF, et al. Myocardial perfusion imaging with technetium-​99m sestamibi SPECT in the evaluation of coronary artery disease. Am J Cardiol. 1990;66:55E–​62E. G ated S P E C T M P I

8. Udelson JE. Choosing a thallium-​201 or technetium 99m sestamibi imaging protocol. J Nucl Cardiol. 1994;1:S99–​S108. 9. Slomka P, Berman DS, Germano G. Myocardial blood flow from SPECT. J Nucl Cardiol. 2017;24:278–​281. 10. Slomka PJ, Dey D, Duvall WL, et al. Advances in nuclear cardiac instrumentation with a view towards reduced radiation exposure. Curr Cardiol Rep. 2012;14:208–​216. 11. Travin MI. Cardiac cameras. Semin Nucl Med. 2011;41:182–​201. 12. Henzlova MJ, Duvall WL, Einstein AJ, et al. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers. J Nucl Cardiol. 2016;23:606–​639. 13. Hendel RC, Berman DS, Di Carli MF, et al. ACCF/​ASNC/​ACR/​ AHA/​ASE/​SCCT/​SCMR/​SNM 2009 appropriate use criteria for cardiac radionuclide imaging. J Am Coll Cardiol. 2009;53:2201–​2229. 14. Wolk MJ, Bailey SR, Doherty JU, et al. ACCF/​AHA/​ASE/​ASNC/​ HFSA/​HRS/​SCAI/​SCCT/​SCMR/​STS 2013 multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease. J Am Coll Cardiol. 2014;63:380–​406. 15. Cerqueira MD, Allman KC, Ficaro EP, et al. Recommendations for reducing radiation exposure in myocardial perfusion imaging. J Nucl Cardiol. 2010;17:709–​718. 16. Rozanski A, Gransar H, Hayes SW, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991 to 2009. J Am Coll Cardiol. 2013;61:1054–​65. 17. Duvall WL, Hiensch RJ, Levine EJ, et al. The prognosis of a normal Tl-​201 stress-​only SPECT MPI study. J Nucl Cardiol. 2012;19:914–​921. 18. Duvall WL, Case J, Lundbye J, Cerqueira M. Efficiency of tetrofosmin versus sestamibi achieved through shorter injection-​to-​ imaging times: A systematic review of the literature. J Nucl Cardiol. 2021;28(4):1381–​1394. 19. Dorbala S, Ananthasubramaniam K, Armstrong IS, et al. Single photon emission computed tomography (SPECT) myocardial perfusion imaging guidelines: Instrumentation, acquisition, processing, and interpretation. J Nucl Cardiol. 2018;25:1784–​1846. 20. Duvall WL, Rai M, Ahlberg AW, et al. A multi-​center assessment of the temporal trends in myocardial perfusion imaging. J Nucl Cardiol. 2015;22:539–​551. 21. Gowd BM, Heller GV, Parker MW. Stress-​only SPECT myocardial perfusion imaging: A review. J Nucl Cardiol. 2014;21:1200–​1212. 22. Mathur S, Heller GV, Bateman TM, et al. Clinical value of stress-​ only Tc-​99m SPECT imaging: Importance of attenuation correction. J Nucl Cardiol. 2013;20:27–​37. 23. Tragardh E, Valind S, Edenbrandt L. Adding attenuation corrected images in myocardial perfusion imaging reduces the need for a rest study. BMC Med Imaging. 2013;13:14. 24. Case JA, Bateman TM. Taking the perfect nuclear image: Quality control, acquisition, and processing techniques for cardiac SPECT, PET, and hybrid imaging. J Nucl Cardiol. 2013;20:891–​907. 25. Hutton BF. The origins of SPECT and SPECT/​CT. Eur J Nucl Med Mol Imaging. 2014;41(Suppl 1):S3–​S16. 26. Alenazy AB, Wells RG, Ruddy TD. New solid state cadmium-​zinc-​ telluride technology for cardiac single photon emission computed tomographic myocardial perfusion imaging. Expert Review Med Devices. 2017;14:213–​222. 27. Acampa W, Buechel RR, Gimelli A. Low dose in nuclear cardiology: State of the art in the era of new cadmium-​zinc-​telluride cameras. Eur Heart J Cardiovasc Imaging. 2016;17:591–​595. 28. Sharir T, Slomka PJ, Berman DS. Solid-​state SPECT technology: Fast and furious. J Nucl Cardiol. 2010;17:890–​896. 29. Garcia EV, Faber TL, Esteves FP. Cardiac dedicated ultrafast SPECT cameras: New designs and clinical implications. J Nucl Med. 2011;52:210–​217. 30. Huang JY, Huang CK, Yen RF, et al. Diagnostic performance of attenuation-​corrected myocardial perfusion imaging for coronary artery disease: A systematic review and meta-​analysis. J Nucl Med. 2016;57:1893–​1898.

 

31. Perisinakis K, Theocharopoulos N, Karkavitsas N, Damilakis J. Patient effective radiation dose and associated risk from transmission scans using 153Gd line sources in cardiac SPECT studies. Health Physics. 2002;83:66–​74. 32. Patchett ND, Pawar S, Miller EJ. Visual identification of coronary calcifications on attenuation correction CT improves diagnostic accuracy of SPECT/​CT myocardial perfusion imaging. J Nucl Cardiol. 2017;24:711–​720. 33. Husmann L, Tatsugami F, Aepli U, et al. Prevalence of noncardiac findings on low dose 64-​slice computed tomography used for attenuation correction in myocardial perfusion imaging with SPECT. Int J Cardiovasc Imaging. 2009;25:859–​865. 34. Brix G, Nekolla EA, Borowski M, Nosske D. Radiation risk and protection of patients in clinical SPECT/​CT. Eur J Nucl Med Mol Imaging. 2014;41(Suppl 1):S125–​S136. 35. Baghdasarian SB, Noble GL, Ahlberg AW, et al. Risk stratification with attenuation corrected stress Tc-​99m sestamibi SPECT myocardial perfusion imaging in the absence of ECG-​gating due to arrhythmias. J Nucl Cardiol. 2009;16:533–​539. 36. Pazhenkottil AP, Ghadri JR, Nkoulou RN, et al. Improved outcome prediction by SPECT myocardial perfusion imaging after CT attenuation correction. J Nucl Med. 2011;52:196–​200. 37. Ou X, Jiang L, Huang R, et al. Computed tomography attenuation correction improves the risk stratification accuracy of myocardial perfusion imaging. Nucl Med Commun. 2013;34:495–​500. 38. Ardestani A, Ahlberg AW, Katten DM, et al. Risk stratification using line source attenuation correction with rest/​stress Tc-​99m sestamibi SPECT myocardial perfusion imaging. J Nucl Cardiol. 2014;21:118–​126. 39. DePuey EG 3rd. Advances in cardiac processing software. Semin Nucl Med. 2014;44:252–​273. 40. Bruyant PP. Analytic and iterative reconstruction algorithms in SPECT. J Nucl Med. 2002;43:1343–​1358. 41. Lyra M, Ploussi A. Filtering in SPECT image reconstruction. Int J Biomed Imaging. 2011;2011:693795. 42. Brambilla M, Lecchi M, Matheoud R, et al. Comparative analysis of iterative reconstruction algorithms with resolution recovery and new solid-​state cameras dedicated to myocardial perfusion imaging. Phys Med. 2017;41:109–​116. 43. Piccinelli M, Garcia EV. Advances in software for faster procedure and lower radiotracer dose myocardial perfusion imaging. Progress Cardiovasc Dis. 2015;57:579–​587. 44. Zoccarato O, Scabbio C, De Ponti E, et al. Comparative analysis of iterative reconstruction algorithms with resolution recovery for cardiac SPECT studies: A multi-​center phantom study. J Nucl Cardiol. 2014;21:135–​148. 45. DePuey EG, Gadiraju R, Clark J, et al. Ordered subset expectation maximization and wide beam reconstruction “half-​time” gated myocardial perfusion SPECT functional imaging: A comparison to “full-​ time” filtered backprojection. J Nucl Cardiol. 2008;15:547–​563. 46. Bateman TM, Heller GV, McGhie AI, et al. Multicenter investigation comparing a highly efficient half-​time stress-​only attenuation correction approach against standard rest-​stress Tc-​99m SPECT imaging. J Nucl Cardiol. 2009;16:726–​735. 47. DePuey EG, Ata P, Wray R, Friedman M. Very low-​activity stress/​ high-​activity rest, single-​day myocardial perfusion SPECT with a conventional sodium iodide camera and wide beam reconstruction processing. J Nucl Cardiol. 2012;19:931–​944. 48. Lyra M, Ploussi A, Rouchota M, Synefia S. Filters in 2D and 3D cardiac SPECT image processing. Cardiol Res Practice. 2014;2014: 963264. 49. Ibrahim DY, DiFilippo FP, Steed JE, Cerqueira MD. Optimal SPECT processing and display: Making bad studies look good to get the right answer. J Nucl Cardiol. 2006;13:855–​866. 50. Cerqueira MD, Weissman NJ, Dilsizian V, et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of

150

the heart: A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. J Nucl Cardiol. 2002;9:240–​245. 51. Tilkemeier PL, Bourque J, Doukky R, et al. ASNC imaging guidelines for nuclear cardiology procedures: Standardized reporting of nuclear cardiology procedures. J Nucl Cardiol. 2017;24:2064–​2128. 52. Caldwell JH, Williams DL, Harp GD, et al. Quantitation of size of relative myocardial perfusion defect by single-​photon emission computed tomography. Circulation. 1984;70:1048–​1056. 53. Garcia EV, Van Train K, Maddahi J, et al. Quantification of rotational thallium-​201 myocardial tomography. J Nucl Med. 1985;26: 17–​26. 54. Driessen RS, Raijmakers PG, Danad I, et al. Automated SPECT analysis compared with expert visual scoring for the detection of FFR-​defined coronary artery disease. Eur J Nucl Med Mol Imaging. 2018;45:1091–​1100. 55. Leslie WD, Tully SA, Yogendran MS, et al. Prognostic value of automated quantification of 99mTc-​sestamibi myocardial perfusion imaging. J Nucl Med. 2005;46:204–​211. 56. Betancur J, Commandeur F, Motlagh M, et al. Deep learning for prediction of obstructive disease from fast myocardial perfusion SPECT: A multicenter study. JACC Cardiovasc Imaging. 2018;11:1654–​1663. 57. Betancur J, Otaki Y, Motwani M, et al. Prognostic value of combined clinical and myocardial perfusion imaging data using machine learning. JACC Cardiovasc Imaging. 2018;11:1000–​1009. 58. Smith WH, Kastner RJ, Calnon DA, et al. Quantitative gated single photon emission computed tomography imaging: A counts-​based method for display and measurement of regional and global ventricular systolic function. J Nucl Cardiol. 1997;4:451–​463. 59. Nakajima K, Taki J, Higuchi T, et al. Gated SPECT quantification of small hearts: Mathematical simulation and clinical application. Eur J Nucl Med. 2000;27:1372–​1379. 60. Ford PV, Chatziioannou SN, Moore WH, Dhekne RD. Overestimation of the LVEF by quantitative gated SPECT in simulated left ventricles. J Nucl Med. 2001;42:454–​459. 61. Kondo C, Watanabe E, Momose M, et al. In vivo validation of gated myocardial SPECT imaging for quantification of small hearts: Comparison with cardiac MRI. EJNMMI Res. 2016;6:9. 62. Hambye AS, Vervaet A, Dobbeleir A. Variability of left ventricular ejection fraction and volumes with quantitative gated SPECT: Influence of algorithm, pixel size and reconstruction parameters in small and normal-​sized hearts. Eur J Nucl Med Mol Imaging. 2004;31:1606–​1613. 63. Kakhki VR, Zakavi SR, Sadeghi R. Comparison of two software in gated myocardial perfusion single photon emission tomography, for the measurement of left ventricular volumes and ejection fraction, in patients with and without perfusion defects. Hell J Nucl Med. 2007;10:19–​23. 64. Schaefer WM, Lipke CS, Standke D, et al. Quantification of left ventricular volumes and ejection fraction from gated 99mTc-​ MIBI SPECT: MRI validation and comparison of the Emory Cardiac Tool Box with QGS and 4D-​MSPECT. J Nucl Med. 2005;46:1256–​1263. 65. Abidov A, Germano G, Hachamovitch R, et al. Gated SPECT in assessment of regional and global left ventricular function: An update. J Nucl Cardiol. 2013;20:1118–​1146. 66. Slomka PJ, Berman DS, Xu Y, et al. Fully automated wall motion and thickening scoring system for myocardial perfusion SPECT: Method development and validation in large population. J Nucl Cardiol. 2012;19:291–​302. 67. Adachi I, Morita K, Imran MB, et al. Heterogeneity of myocardial wall motion and thickening in the left ventricle evaluated with quantitative gated SPECT. J Nucl Cardiol. 2000;7:296–​300. 68. Alama M, Labos C, Emery H, et al. Diagnostic and prognostic significance of transient ischemic dilation (TID) in myocardial

S E C T I O N i . H istorical , T echnical

 

perfusion imaging: A systematic review and meta-​analysis. J Nucl Cardiol. 2018;25:724–​737. 69. Bajaj NS, Singh S, Farag A, et al. The prognostic value of non-​ perfusion variables obtained during vasodilator stress myocardial perfusion imaging. J Nucl Cardiol. 2016;23:390–​413. 70. Higgins JP, Higgins JA, Williams G. Stress-​induced abnormalities in myocardial perfusion imaging that are not related to perfusion but are of diagnostic and prognostic importance. Eur J Nucl Med Mol Imaging. 2007;34:584–​595. 71. Kushner FG, Okada RD, Kirshenbaum HD, et al. Lung thallium-​ 201 uptake after stress testing in patients with coronary artery disease. Circulation. 1981;63:341–​347. 72. Beller GA. Radionuclide exercise testing for coronary artery disease. Cardiol Clin. 1984;2:367–​378. 73. Esteves F, Galt J. SPECT attenuation correction. In: Iskandrian AE, Garcia EV, eds. Nuclear Cardiac Imaging: Principles and Applications. 5th ed. Oxford University Press, 2016:178–​195.

G ated S P E C T M P I

74. Schindler TH. Positron-​emitting myocardial blood flow tracers and clinical potential. Progress Cardiovasc Dis. 2015;57:588–​606. 75. Paul AK, Nabi HA. Gated myocardial perfusion SPECT: Basic principles, technical aspects, and clinical applications. J Nucl Med Tech. 2004;32:179–​189. 76. Cal-​Gonzalex J, Rausch I, Shiyam Sundar LK, et al. Hybrid imaging: Instrumentation and data processing. Front Phys. 2018. https://​doi.org/​10.3389/​fphy.2018.00047. 77. Gillam JE, Rafecas M. Monte-​Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography. Nucl Instruments Methods Phys Res A. 2016;809:76–​88. 78. Germano G. Technical aspects of myocardial SPECT imaging. J Nucl Med. 2001;42:1499–​1507. 79. Yao B, Zhu R, Yang H. Characterizing the location and extent of myocardial infarctions with inverse ECG modeling and spatiotemporal regularization. IEEE J Biomed Health Informatics. 2018;22:1445–​1455.

 

7. ARTIFACTS William A. Van Decker

K EY P OINTS 1. Imaging artifacts occur in all forms of medical imaging; quality clinical image interpreters manage these successfully. 2. Artifacts can be minimized by meticulous adherence to professional imaging guidelines. 3. SPECT MPI artifacts can be broadly characterized as acquisition, reconstruction, display normalization, anatomic/​physiologic, hybrid imaging intrinsic, and byproducts of newer imaging systems. 4. The most common artifact is soft tissue attenuation, which can be managed by pattern recognition but is scientifically mitigated by advancing physics attenuation correction systems. 5. Reconstructions in tomography should be quality control assessed and re-​reconstructed as necessary. 6. Image filtering selections are lab specific but may need to be adjusted for any given patient habitus. 7. Display normalization artifacts are a vexing rare occurrence; clear understanding of the normalization process is needed to assess them. 8. Left bundle branch block is an interesting cause of physiologic artifacts but less challenging in the era of vasodilator pharmacologic stress testing and pattern recognition. 9. Hybrid imaging done sequentially with CT attenuation mapping also needs systematic quality assurance. 10. Newer imaging systems improve some imaging characteristics but may also come with their own new imaging variations to understand.

AB B R E V IAT IONS AC attenuation correction CT computed tomography CZT cadmium-​zinc-​telluride (crystal) DICOM Digital Imaging and Communications in Medicine HLA horizontal long axis LAO left anterior oblique LPO left posterior oblique LV left ventricle LVEF left ventricle ejection fraction MPI myocardial perfusion imaging PET positron emission tomography RAO right anterior oblique RV right ventricle SA short axis SPECT single-​photon emission computed tomography VLA vertical long axis

INT RODU C T ION The SPECT and PET perfusion pattern in normal subjects is anticipated to reveal a homogenous tracer uptake distribution pattern at rest and stress (though in actuality some variations exist due to papillary muscles and variations in regional wall stress and wall thickness, such as apical thinning). However, there are times when image inhomogeneities that are observed are unrelated to true physiologic changes; these are referred to here as image artifacts.1,2 This chapter will address the types, causes, recognition, and correction of the common artifacts.

 

S TEP S OF I MAG E CREATI O N AN D TI M E S OF P OTENTIA L ARTI FACT I N TRO D UCTI O N

The acquisition, reconstruction, and display in image generation can be also complicated by cardiac gating diffi­ culties, incidental cardiac anatomy/​physiologic artifacts, The photons emitted from the decaying radiopharmaceu- hybrid imaging artifacts with CT, and emerging recognized tical within heart muscle are imaged on the imaging table artifacts specific to newer imaging systems. In a perfect world, decreased relative signal intenover time in minutes by appropriate quality control detector sity in a myocardial segment would represent a relative equipment. The (most frequently) moving equipment (when using the Anger gamma camera) assumes the patient hypoperfusion defect (mild, moderate, severe in intensity) remains steady. Its multiple planar acquisition stops allow and its extent would be well characterized by the number mathematical reconstruction and placement of the isotope of myocardial segments involved. However, in a pragmatic count photon intensity signal (proportional to uptake of world, it would take little imagination to recognize that the flow tracer imaged at the cardiac surface) into thin-​slice to- complexities of the imaging technique may introduce artimographic cardiac images by either filtered backprojection ficial defects at each step (or several additive steps) of the image generation. Moreover, since comparison stress and or iterative reconstruction. However, the emitted signal travels from the heart to the rest imaging entail two separate, independent image generexternal detector through varying amounts of body soft tissue ations, it is possible to introduce an artificial defect on stress at each angle of acquisition, and that travel degrades the signal but not on rest, or on rest but not on stress, or a systematic by photon–​tissue matter interaction known as Compton artificial defect that appears on both stress and rest, or a sysscatter. To the degree that the amount of Compton scatter tematic artificial defect that appears in different severities or varies from stop-​to-​stop angle or across different levels/​ different positions or different extents on stress versus rest portions of the heart at any one stop angle, radiographic imaging. These artificial defects (artifacts) may alter internonuniformities may be introduced that do not reflect the pretation of patients with or without coronary artery ditrue cardiac region relative uptakes. The proportional re- sease. Meticulous, standardized acquisition protocols help 3–​6 corded signal from the planar spin acquisition requires op- decrease variability. Realization of the challenges of the imaging process is erator interaction to identify the heart for reconstruction, fortunately no reason for clinical despair. The challenges create tomographic axes of reconstruction (similar for comparison of stress and rest images), and apply prefiltering for of imaging artifacts in nuclear cardiology are certainly no signal to noise and ramp filtering in reconstruction due to the less nor more than in the other imaging modalities such as lower counts inherent in tomographic imaging, which may CT scanning, magnetic resonance scanning, ultrasound introduce variances. The resulting tomogram images are then scanning, or cardiac catheterization fluoroscopy and cine visually displayed by scaling both the stress tomographic se- fluoroscopy. Yet all these imaging modalities also remain ries and the rest tomographic series, each to its own hottest incredibly clinically important in clinical care because of count pixel element within the series (intrinsic differences the individual strengths they bring to patient diagnosis and in delivered tracer dose for stress vs. rest same-​day imaging prognosis. Nuclear cardiology has scientifically studied and cata­ would mean there is an absolute difference in counts/​pixel of logued the spectrum of potential common imaging artifacts. the maximal count pixel in each of the two series, made neuThis leads to understanding of causation and descriptions of tral by scaling each series to its own maximal pixel). In this manner, relative signal in different myocardial pattern recognition of the “characteristic footprint” of each vascular distributions can be compared within a series (rest artifact on images. Armed with these data, some artifacts or stress) and then assessed to see if there is a change in rel- can be avoided by meticulous study quality control (equipative signal pattern displayed through an assigned radio- ment maintenance, efforts to decrease patient motion graphic look-​up scale of mathematically acquired counts/​ under the scanner, etc.). Some may be approached by syspixel between the same myocardial vascular distributions tematic physics adjustments (soft tissue AC, motion coron the comparison series (stress or rest). In other words, is rection software, etc.). Some may be approached by repeat the relation of signal intensity comparison between myocar- acquisitions (too much patient motion, initial significant dial wall A and myocardial wall B on the stress tomogram gut activity adjacent to the heart reconstruction/​display series equal? If not, does the relationship of myocardial wall needing time to clear), some by repeat image reconstruction A′ signal intensity versus myocardial wall B′ signal intensity (changing axes of reconstruction), and some by simple pattern recognition and “read around.” Options of approaches change on resting images compared to stress images?

A rtifacts

 

are specific to each artifact type once it has been appropriately recognized, and many common artifacts will have a variety of different approaches or additive approaches to consider. For the purposes of organized discussion of the artifacts, using SPECT MPI as a baseline, we will categorize them as follows:

of its “signature footprint” on the image; the causation; variable nuances as to how it may present; and common strategies to either avoid creating, mitigate the effect, correct the artifact, or default “read around” the pattern recognition. AC QU IS IT ION AR T IFAC T S

1. Artifacts introduced at acquisition 2. Image reconstruction artifacts 3. Image display normalization artifacts 4. Artifacts caused by incidental cardiac anatomy/​ physiology

Potential artifacts introduced at acquisition include two subcategories: defective equipment failure (field crystal nonuniformity, center of rotation artifact) and patient-​ related acquisition artifacts (Box 7.2). The patient-​related

5. Hybrid imaging artifacts 6. Emerging recognized artifacts on newer imaging systems.

BOX 7.2 

ARTIFACTS AND POTENTIAL SOLUTIONS

1. Acquisition artifacts A. Nuclear medicine hardware

Artifacts will be subcategorized in each topic (Box 7.1). Under each imaging artifact discussion will be a description

Potential solution: Meticulous equipment quality control B. Motion artifacts Potential solutions: Preventive measures; motion

BOX 7.1 

CONSTRUCT OF PERFUSION IMAGING ARTIFACTS

1. Acquisition artifacts A. Nuclear medicine hardware B. Patient motion C. Soft tissue attenuation 2. Reconstruction artifacts

recognition C. Soft tissue attenuation Potential solutions: Positioning; AC algorithms; pattern recognition 2. Reconstruction artifacts A. Improper constraint

A. Improper constraint

Potential solution: Reprocess

B. Improper axis of reconstruction

B. Improper axis of reconstruction

C. Filter and tomographic artifacts

Potential solution: Match stress to rest and

3. Normalization and display artifacts

reprocess

A. Liver and splanchnic activity

C. Filter and tomographic artifacts

B. Hypertrophy patterns

Potential solutions: Trial filter change; pattern

C. Low-​count studies 4. Physiologic artifacts

recognition 3. Normalization and display artifacts

A. Left bundle branch block

A. Liver and splanchnic activity

B. Metabolic variances

Potential solutions: Reacquisition; reprocess;

C. Apical thinning D. Gating artifact 5. Hybrid imaging

understand display look-​up scales; manually normalize B. Hypertrophic patterns

A. Misregistration artifact

Potential solution: Pattern recognition

B. CT hardware

C. Low-​count studies

6. Newer imaging systems A. Positional shifting of traditional artifacts B. Truncation C. Low-​count studies

154

correction algorithms; reacquisition; pattern

Potential solutions: Reacquisition; consider different tracer; attenuation algorithm 4. Physiologic artifacts A. Left bundle branch block

S E C T I O N i . H istorical , T echnical

 

Potential solutions: Vasodilator pharmacologic

patterns on images if they slip through correction at the quality control level.

stress; pattern recognition B. Metabolic variances Potential solutions: Strict dietary preparation adherence; pattern recognition C. Apical thinning Potential solution: Pattern recognition D. Gating artifact Potential solutions: Assess EKG adequacy; suppress arrhythmias; pattern recognition 5. Hybrid imaging A. Misregistration artifact Potential solution: Re-​register CT fusion to nuclear medicine images B. CT hardware Potential solution: Meticulous CT equipment quality control 6. Newer imaging systems A. Positional shifting of traditional artifacts B. Truncation C. Low-​count studies Potential solutions: Understand intricacies of newer

Crystal Field NonUniformity The crystal needs to respond uniformly to photon strikes across its entire surface. Problems such as a nonfunctioning photomultiplier tube (a cold spot), a cracked crystal, a hydrated edge packing crystal, and unequal electronic photo peaking at the required KeV will all cause a local signal registration problem. For the most part these should be picked up on the daily 3-​million-​count extrinsic flood performed on each detector using a uniform flood source or on the electronic uniformity 30-​million-​count flood done monthly and dealt with by the equipment vendor as necessary. Should they escape detection, the spot defects on a static flood will create a circular arc of hot and cold alternating “ring artifacts” by the very nature of multiple planar moving acquisitions of SPECT tomographic imaging. Should the defect orbit over the myocardial field, it will create multiple slit alternating hot and cold artifacts on the SA tomogram (Figure 7.1). These problems should not be worked around but definitively corrected on the equipment.

systems; pattern recognition

Center of Rotation Artifact acquisition artifacts can be further subdivided into patient motion artifact; acquisition of a significant amount of noncardiac tracer activity closely adjacent to the heart, creating downstream artifacts in image reconstruction and image display (see “Image Reconstruction Artifacts” below); and soft tissue attenuation artifact due to large body habitus, obesity, breast attenuation, diaphragmatic attenuation, fat folds, and left arm (when on the side rather than above the head). Recognition of these artifacts entails close inspection of the raw planar acquisition rotating spin, inspection of daily and monthly camera quality control data, and recognition of classic “footprints” on the end tomograms. There are specific responses that can be considered for each to improve the confidence of image interpretation.

D E F E C T I V E E Q U I P M E N T FA I L U R E D U R I N G ACQUISITION

Meticulous review of camera quality control data make this subset avoidable and correctable before imaging any patient. These equipment abnormalities will create telltale

A rtifacts

SPECT image reconstruction depends on the acquired count data to be matched centrally in its rotation to the volumetric computer matrix. Whether the center of rotation is appropriately matched can be checked by the vendor using an intrinsic point source and a test acquisition during routine camera maintenance. Fortunately, modern cameras fall into misalignment on center of rotation less frequently than their early prototypes. The equipment failure generates a blurring of the image but most characteristically creates a misregistration of a portion of the myocardial signal pattern and a “disjointed” or “skewed” image, classically represented by a pull-​down and shift of the lateral wall on the horizontal SA, resulting in a severe small defect near the lateral apex, and an inability to redraw a connecting smooth straight myocardial contour. If caused by the equipment, the artifact will be reproducible on every acquisition until it is corrected. However, these exact same “footprint findings” can be seen in patient motion artifact. In the current era, such findings are much more likely related to patient motion. Characteristically, motion artifact will be detected as occurring in only patients who moved (could be seen by inspecting the planar raw spin) while it is absent in other patients imaged that day. Center of rotation artifacts should

 

Flood Field Non-Uniformities

Reconstructed SPECT Ring Artifacts

Myocardial SPECT Acquisition

SA Tomogram with Artifacts

Figure 7.1  Flood field nonuniformity resulting in ring artifacts and artifactual myocardial perfusion defects. SA = short axis.

be corrected by the equipment maintenance vendor and not consistently read around.

PAT I E N T- R ​ E L AT E D AC Q U I S I T I O N A R T I FAC T S

Patient Motion Artifact The recommended traditional SPECT technetium perfusion radiopharmaceutical agent imaging involves 64 orbital planar acquisitions that are reconstructed with an assumed aligned stationary patient throughout acquisition. Depending on imaging equipment, this acquisition may take 10 to 20 minutes. Given human nature, it is not a given that the patient will remain essentially steady on the imaging table with a stable consistent breathing pattern throughout. The patient may move up and down on the table (y-​axis), side to side (x-​axis), vertically off the table (z-​axis, as when the patient lifts off the table due to shoulder discomfort), rotational twist, or a combination of the above. Additionally, the patient may move only a small amount (1 pixel from camera stop to stop) or a significant amount (>1 pixel from camera stop to stop), at the start or toward the end, once or several times during one acquisition, or once or multiple times at different intervals on the rest and stress acquisitions.7–​10 Patient motion in the x and y planes is clearly visible by inspecting the raw planar acquisition spin. Z-​a xis

156

motion is harder to see on the raw spin. Most systems generate a pictorial quality check “sinogram” where a break in the smooth sinogram represents motion at that stage (Figure 7.2).11 The characteristic footprint of patient motion on tomograms includes image blurring; disjointed cardiac silhouettes; count streaking outside the cardiac silhouette (sometimes called the “comet tail” or “hurricane sign”); walls sliding over each other, especially in the HLA plane; and diametrically opposed perfusion defects in the SA. Motion could also affect LVEF measurement. There are several ways to approach patient motion. One is preventive. The patient should be instructed on the importance of staying still for the study. The technologist should watch the patient’s acquisition and reassure them. Appropriate cushions, supports, and leg flexions and gentle upright arm positioning to ensure patient comfort during acquisition should be accomplished. The patient should be told not to talk because repetitive diaphragmatic movements could also result in motion artifact. The second approach is mitigation. All systems contain motion-​ correction software. This software allows the technologist to realign each planar stop acquisition to the same apex touch line throughout the spin after the fact (usually by up or down 1 pixel). Mild motion can therefore be computer-​ reregistered, and the new motion-​corrected dataset can then be used in the reconstruction algorithm rather than

S E C T I O N i . H istorical , T echnical

 

Figure 7.2  Image of quality assurance generated sinogram to assess for patient motion. One or more linear breaks in smooth sinogram are associated

with patient motion artifact at different portions of the spin acquisition.

the initial raw spin. The third approach, which is the only one feasible with severe motion and is only available with the technetium perfusion agents (since the “frozen in time” perfusion image is stable for several hours), is to entirely repeat the acquisition, taking extra precautions and working with the patient to avoid motion.12–​14 Shorter acquisition times, as when imaging with CZT gamma cameras, help decrease motion artifacts; however, review of raw acquisition spin is not helpful for detecting motion on these cameras, and the reader has to be familiar with the characteristic footprint discussed above to suspect motion. Shorter acquisitions could be done with Anger cameras, especially when a high dose of radiopharmaceutical is used.

Acquisition of significant amount of noncardiac tracer activity closely adjacent to the heart A significant amount of radiotracer may accumulate in adjacent organs such as the liver, gallbladder, stomach, transverse colon, or splenic flexure of the descending colon. The splenic colon flexure may be significantly problematic if the left hemidiaphragm is high. Such overlapping activity will create significant challenges in both image reconstruction and in image normalization display, as will be described below. It is very helpful if such activity can be excluded prior to reconstruction and display. If one cannot exclude the extraneous field activity in tight chosen pixel constraints for cardiac tomographic reconstruction, one needs to consider repeating a technetium-​based acquisition

A rtifacts

with the lapse of 1 to 2 hours and after a full meal in hopes that the activity has transited more distally and out of the reconstruction field; alternatively, one could consider using a different radiotracer that may not come with as much abdominal activity, such as thallium.15,16 Imaging effects of this overlapping noncardiac activity will be described in the subsections on image reconstruction and display.

Soft Tissue Attenuation Artifact The most pervasive nuclear cardiology perfusion imaging artifact that muddles image interpretation is soft tissue attenuation. Increasing amounts of soft tissue positioned between the heart and the photon emission capture by the detector increases the amount of Compton scatter that occurs and decreases the amount of appropriate photon counts for image generation at the detector head. The result is usually predictable by viewing the rotating raw planar spin. The image appears “grainy” due to poor signal-​to-​ noise (target-​to-​background) ratio. The attenuation may be evenly spread across the cardiac image, leading to a problem of poor count statistics, or attenuation may be focal and/​ or more prominent across portions of the cardiac silhouette based on varying distributions of different soft tissue densities. Moreover, and more perplexing for image interpretation, is that attenuation patterns may differ from stress acquisition to rest acquisition. There may be a variety of approaches to attenuation artifact, some specific to the type and position of attenuation.

 

Generalized Large Body Habitus Truncal Obesity This is a morphology that usually leads to a uniform decrease in imaging counts. Poor count statistics make it difficult to assess whether apparent variations in counts represent statistical noise or true hypoperfusion. Resulting tomograms appear patchy and grainy. Three approaches to the obese patient may be considered. One is to deliver a weight-​based tracer dose and use an increased dose for obese patients. This increased delivered dose will create increased signal of emission count photons and improved image quality at the cost of increased radiation exposure (however, nondiagnostic images at a lower delivered dose of tracer would create no benefit from the delivered radiation exposure). The second approach would be to consider a PET perfusion agent such as 82-​rubidium, whose more energetic 511 KeV photon with greater penetrating energy would produce increased count statistics in the image generator. A third approach would be to consider SPECT AC imaging to improve SPECT count statistics using CT or, less commonly now, line source AC (remembering that while SPECT acquisition can be with or without AC, PET is always accomplished with AC). Attenuation from large body habitus can also be more focal in the inferior/​ posterior wall since this wall is farther from the detector than the anterior wall and photon emission from this region traverses more tissue. Newer software reconstruction programs including iterative reconstruction with depth-​ dependent reconstruction help mitigate the accentuation of distance in these patients on image generation.18–​23

wall, but positioning is extremely variable and thus the need to review the raw cine spin images. Also, breast attenuation defects are usually (but not always) more pronounced proximally and spare the apex, unlike true left anterior descending artery coronary arter disease/​ischemia, which is usually worse at the apex). It is rare for the inferior wall to be involved, but there may be a very unusual exception to the rule (more likely to occur in upright imaging). The technologist should do everything possible to acquire stress and rest images in a similar manner. The patient’s bra should be off for both acquisitions, and the positioning of the patient on the SPECT table should be as similar as possible in the two acquisitions; some labs make a notation of bra sizing.24 Assessment of the gated SPECT images is frequently helpful with fixed defects because normal wall thickening and motion in the same fixed region (as in any focal attenuation) is more consistent with artifact rather than hypoperfusion.25,26 Beyond mitigation attempts in the acquisition and pattern recognition matching raw spin findings, the most successful intervention is likely the use of an AC set of images (using either a nuclear rod transmission source with gadolinium or one of the x-​ray attenuation map techniques). While it is helpful to assess the AC images to the noncorrected corresponding series, it is also important to assess AC stress versus AC rest tomographic series (Figure 7.3). Some laboratories also use breast position imaging (by taping the breast) as attenuation mitigation.27

Diaphragmatic Attenuation Artifact This is a euphemistic term used to imply artifactual decreased Breast Attenuation Artifact counts in the inferior wall from the left hemidiaphragm most Localized soft tissue attenuation adds increasing complexity commonly seen in men. However, it is more pragmatic to consince an artificial local decrease in counts may mimic defects sider the term a transition into a discussion of various causes of myocardial scar if fixed and myocardial ischemia if the of inferior attenuation sparing the anterior wall. Causes may attenuator shifts position between the stress and rest acqui- include protuberant abdomen, a gastric air bubble (visualized sition. Careful examination of the planar raw cine spin on fe- on raw spin), or disproportionate obesity. Notations on pamale patients is critical since breast tissue is a very common tient height and weight may be helpful to interpretation in adcause of attenuation. While it is hoped that the left breast will dition to the ever-​important assessment of the raw planar spin. be a uniform attenuator of cardiac counts in an RAO to LPO “Inferior attenuation” can also be seen in significantly acquisition, the size, positioning, and density of the breast dilated LVs where the inferior wall moves more posterior frequently create focal areas of attenuation. The approxi- from the detector while anterior wall positioning is stable. mate distribution and severity can frequently be assessed by This is essentially another problem that depth resolution retracking the breast “shadow” on the raw cine planar spin (and covery software may help with, in addition to other methods it is important to compare the spin of stress to spin of rest of dealing with inferior attenuation. Dilated RVs that sit to seek differences of positioning of the soft tissue that will anterior and slightly inferior to the left ventricle can cause cause differences in stress vs. rest displays) before evaluating cardiac rotation shift in the chest and, along with the RV the SPECT images. The tomographic abnormalities usually dilatation overlay, produce an inferior attenuation pattern produce mild-​ to moderate-​severity defects (not moderate-​ in patients with chronic obstructive pulmonary disease. severe). The artifacts frequently are in the mid anterior and In the prior era of more thallium SPECT MPI, inferior anterolateral wall and sometimes extend to the septal/​apical counts were documented to be artifactually decreased from 158

S E C T I O N i . H istorical , T echnical

 

Panel A

Panel B

Figure 7.3  (A) Classic mild anterior breast attenuation artifact. (B) Correction of the image by use of an AC map.

a phenomenon known as “diaphragmatic creep” caused by heavy and deep breathing diaphragm motion during early image acquisition right after treadmill exercise that is not present during rest imaging (or when technetium is used, since there is a more significant delay between exercise and imaging with technetium). While thallium does need to be imaged early before redistribution starts to occur, waiting 10 to 15 minutes after stress to start acquisition in order to decrease the effect of diaphragmatic creep is prudent. In addition to pattern recognition assessments by viewing the raw spin, the main approach to inferior attenuation is to perform image acquisition in the prone

position and compare the images to those obtained in the usual supine position. Prone positioning will move the left hemidiaphragm and bowel contents farther from the heart and shift abdominal soft tissue, and therefore will frequently improve images compared to supine position imaging if the finding is artifactual. It is important to note that changing positions (prone vs. supine) should have no effect on true defects. The causes of inferior attenuation are much more frequently “fixed” in nature from stress to rest (than shifting anterior breast attenuation), and gated SPECT inspection of these walls can be particularly helpful if normal wall motion and thickening is present. Finally, AC systems

Panel A

Panel B

Figure 7.4  (A) Classic inferior attenuation artifact. (B) Correction of the image by use of an AC map.

A rtifacts

 

are equally effective in correcting inferior attenuation as anterior attenuation and serve a valuable function in these patients when available (Figure 7.4).28–​32 Lateral Body Wall Soft Tissue Attenuation Some patients by body habitus will have thick lateral axillary skin folds, and these will cause focal lateral wall attenuation with the left arm over the head during acquisition. Others will be unable to lift their left arm over head for acquisition, and left-​arm-​down acquisition will lead to lateral wall attenuation. Both shadows can be visualized on the raw planar spin, and thus close inspection of the raw images will help anticipate these artifacts. Fortunately, both forms of lateral artifacts tend to be fixed, and therefore information from gated SPECT wall motion/​thickening and AC images is very useful. It is impressive how well AC systems handle left-​arm-​down artifacts.33 IM AGE R ECO N STRUCTI O N ARTI FACTS The reconstruction process from the raw planar spin acquisition to SPECT tomograms involves technologist definition of reconstruction constraints of apex and base, application of a prefilter to images due to the inherent low signal count statistics of SPECT, application of a ramp filter during filtered backprojection/​iterative reconstruction transaxial tomogram creation, and technologist definition of an axis of reconstruction for each of VLA, HLA, and SA tomograms (which need to be similar for both stress and rest) (see Box 7.2). Artifacts may also be introduced into the AC images during their reconstruction. Moreover, the creation of quantitative parametric maps utilized in image interpretation involve technologist generation and must also be quality controlled.

F I LT E R I N G A R T I FAC T S

A prefilter is utilized just prior to reconstruction and is usually a mathematical convolution formulation in the Butterworth or Henning family. Filter specifics are beyond this chapter, but suffice to say that too little prefiltering leaves grainier images and, while closer to true image data, creates the possibility of interpreting smaller statistical count variations as true defects. Heavier filtering creates smoother imaging but creates the possibility of over-​ smoothing pixels and downplaying smaller mild defects. While some would argue this could be approached by varying filters to patient count statistics (mostly due to patient size), most labs stick to one prefilter in a midrange, recognizing some mild limitations. A ramp filter is applied during a filtered backprojection reconstruction algorithm. As important historically as ramp filtering has been to tomographic reconstruction, it is recognized that it creates the possibility of two diametrically opposed artifacts when there is extracardiac activity close to the heart—​ usually the inferior wall. On the one hand, reconstruction may include Compton scatter photons from a very close extracardiac structure over the cardiac silhouette “filling in” a mild defect. On the other hand, if the close extracardiac activity is densely hot and oversaturates the formula, a “star artifact” may place in nil values, creating a defect. It has been argued that this problem is less pronounced with iterative reconstruction.35 Remember that extracardiac activity in the field needs to be noted and mitigated if possible before the reconstruction and display steps. Viewing both filtered backprojection and iterative reconstruction datasets, when available, is sometimes reassuring, since they represent slightly different representations of the same raw data (Figure 7.5).36 INAPPROPRIATE AXES OF RECONSTRUCTION

M YO C A R D I A L C O N S T R A I N T A R T I FAC T S

The technologist starts with the longest image of the planar LV, usually midway through the spin in LAO position, and defines the base and the apex of the LV by linear reconstruction lines across the image. This region of interest defines the SPECT transaxial reconstruction. If the region is too broad, it may include too much extracardiac activity, leading to normalization problems later. If the region is too tight, it may exclude the inferior apex, creating a sharp cut-​off apical defect. The constraint image is saved in the reconstruction quality control save screen and can be viewed for anomalies during interpretation. If concerns are raised, the constraints should be redefined and the image reprocessed.34 160

The technologist draws an axis of reconstruction on the transaxial generated tomogram down the middle of the ventricle from base through apex to generate VLA slices (this is sometimes more difficult in patients with true severe apical defects). The technologist then draws an axis of reconstruction line down the middle of the ventricle in the subsequent generated VLA from base to apex to generate an HLA. They also draw a perpendicular axis to the HLA transection line on the VLA at the apex, which will generate SA cuts from apex to base. The main concern is use of too steep or too shallow an axis on any of the cuts, which can lead to shorter, fatter ventricles rather than longer, narrower ventricles, changing perception of cavity size and changing

S E C T I O N i . H istorical , T echnical

 

Panel A

Panel B

Figure 7.5  Panels A and B show the exact same SPECT series prefiltered by two different Butterworth filter convolutions. “Smoother filters” decrease mild

adjacent mathematical count statistic variations but move farther away from raw data.

the position of the LV apex away from the 3 to 4 o’clock position on the VLA and the 12 o’clock position on the HLA, which is bound to change the perception of counts in the basal wall, especially the inferior wall. Even more concerning is when different axes are chosen for stress and rest images, leading to “comparing apples to oranges.” For this reason, it is likely prudent for the technologist to do both stress and rest reconstructions at the same time rather than different times of the day. The reconstruction axes chosen are saved in the reconstruction quality assurance save screen

and can be viewed, and either stress images, rest images, or both should be re-​reconstructed as necessary at interpretation (Figure 7.6).37 AC A R T I FAC T S

While the use of AC systems adds benefit for the interpretation of images, as discussed above, there are potential risks in any mathematical modeling. While beyond the scope of this chapter, there exists the possibility in large patients of

Panel A

Panel B

Figure 7.6  Panels A and B show the exact same SPECT series reconstructed through different axes of reconstruction. Note difference in cavity shape and

perceived cavity sizing. Rest and stress tomograms should always use the same axes of reconstruction.

A rtifacts

 

truncation artifacts of the transmission scan, leading to uniformity difficulties, and residual attenuation defects due to inadequate transmission source count density making it through the patient, which ultimately lead to an inadequately robust AC map and worsening of the normal variant “apical thinning slit” due to partial volume effect.38 Further, correcting the activity of adjacent subdiaphragmatic counts can cause increase Compton scatter spill into mild inferior wall defects. Some correction systems have quality parameters for some of these data. In either case, it is always useful to evaluate BOTH noncorrected and corrected images together for SPECT. PET is always attenuation-​corrected and is only viewed attenuation-​corrected. Q U A N T I TAT I V E PA R A M E T R I C M A P R E C O N S T R U C T I O N A R T I FAC T

Quantitative DICOM parametric maps (“bull’s-​eye polar plots”) have added value in the interpretation of images. A key portion of the parametric map generation is the correct positioning of the limits at the LV apex and base. Improper limits could produce apical or basal defects (or both) that may appear fixed or reversible, depending on the variations of the position of these limits in the stress and rest images. Conversely, too tight constraints (such as excluding the apex or base) may reduce the size of true defects or eliminate them altogether. These problems could be readily identified (because the polar maps do not agree with visual interpretation) and could be readily corrected at the time of image review. IM AGING NORMALI ZATI O N D I SPLAY A R TIFACTS Reconstructed tomograms when stress and rest images are obtained are presented in six series (stress VLA, HLA, SA, and rest VLA, HLA, SA)—​12 series if one adds the AC datasets as well; each series has eight to 12 slice frames. Each series is scaled or “normalized” to the hottest counts/​pixel within the series; this is set to 100%, and then the rest of the series are scaled proportionally in a grayscale or a color scale of the imager’s choice. Images are usually displayed by linear map proportionalities, but some have also utilized additional log or exponential scale representations, which requires extra caution in interpretation. Display artifacts, an underappreciated category, can be intrinsic cardiac normalization artifacts, extrinsic cardiac normalization artifacts, or artifacts as the result of computer look-​up scale choices of representation (see Box 7.2). 162

I N T R I N S I C C A R D I AC N O R M A L I Z AT I O N A R T I FAC T S

Complexities in scaling or normalizing the heart appropriately to itself within each series can be caused by using frame normalization rather than series normalization, attempting to normalize a very-​low-​count study (such as due to obesity, small dose, or partial dose infiltration), or myocardial wall thickness variations scaled differently in the VLA, HLA, and SA projections. Scaling each frame to itself may artificially remove clear defects otherwise seen using normalization in series, though it may make a defect appear more severe. In the current era, all normalization should be by series. Low count statistic studies are difficult to normalize because the standard deviations of counts within each pixel are wide creating “patchy defects.” If due to dose infiltration, the study should be repeated. If due to obesity, poorly compensated by AC, then other options described for this problem earlier should be considered. Variations in LV wall muscle thickness can also cause intrinsic normalization artifacts.39 Areas of significant, more regional muscle mass will have higher counts than areas with less muscle mass. The most common scenarios are asymmetric septal hypertrophy, some patients with left ventricular hypertrophy and prominent papillary muscles, and those with end-​stage renal disease on dialysis. In these circumstances the lateral wall appears to harbor a perfusion defect that appears fixed, while in actuality, myocardial perfusion is normal. E X T R I N S I C C A R D I AC N O R M A L I Z AT I O N A R T I FAC T S

A common artifact is due to extracardiac activity due to liver or bowel activity (or occasionally gastric or esophageal activity in patients with duodenogastric or gastric-​esophageal reflux) adjacent or even overlapping the inferior LV wall. Both structures receive tracer uptake during the first pass (just like the heart and brain), but also the technetium-​ labeled tracers are eliminated through the hepatobiliary system. In most patients, the liver is separated from the heart and the small bowel is even lower. The problem often arises when the left diaphragm is high and hence the liver is closer to the heart, or the large bowel (which is the reservoir of the tracer that had reached the small bowel) is higher than usual and is just under the diaphragm. This causes the heart activity to be normalized to a hottest extracardiac activity rather than the hottest pixel within the heart itself. In the worst-​case scenario the entire heart looks abnormal, but more often the adjacent segment (usually the inferior wall) is downscaled and appears abnormal. Ironically, using quantitative automated analysis software, the “hot” extracardiac activity is backprojected and the inferior wall appears “hot”

S E C T I O N i . H istorical , T echnical

 

Panel A

Panel B

Figure 7.7  (A) SPECT series, which the computer normalizes to the highest count per pixel in extracardiac activity and not to the highest count pixel within

myocardium. (B) An attempt to manually normalize the same series to the highest count myocardial pixel in a common color look-​up scale.

while the rest of the LV appears downscaled (abnormal). To carry the problem one step further, the software used to asses LV function traces the extracardiac activity rather than the heart and comes up with a very unusual result for LVEF! Fatty meals, water drinks, and repeat imaging after 1 to 2 hours to allow elimination of the extracardiac activity may help in some but not all patients. More recent data suggest that withdrawal of proton-​pump inhibitors for a week may reduce gastric activity. Exclusion of the extracardiac activity in the reconstruction constraints during reprocessing has also been advocated. Once in the display series, there are two options. First, some software allows portions of each frame image to be “extracted,” leaving a dark black jagged segment of the postage stamp frame (dark because background counts have been removed as well as signal counts). This is occasionally helpful if there is some reasonable separation between cardiac silhouette and extracardiac activity to avoid extracting myocardial signal counts from the image. The second option is to “manually normalize the heart to its own hottest pixel.” This process creates an “oversaturation scaling appearance” of the extracardiac activity. However, human manipulation, unlike computer manipulation, is not consistent, even in experienced hands. When all else fails, consideration should be given to repeat imaging using thallium-​201 (Figure 7.7).40 DISPLAY MAP PERCEPTIONS OF LOOK-U ​ P SCALE

Tomographic images can be displayed in gray scale as linear representations, logarithmic or exponential representations. A rtifacts

Best practice should be linear representations to be as close to raw reconstruction data as possible. Exponential representations will subtract more background but also some signal and will create more perception of a defect. Log representations tend to “cover defects” by blossoming count signal of both target and background. Tomograms can also be displayed in a variety of “color look-​up scale maps” of different hues of same color or multicolor maps. While multicolor scales can display apparently dramatic visual appearances in count differences, one needs to remember that if a color assignment changes at 70% maximum pixel uptake on the look-​up scale, a pixel at 67% maximum pixel uptake and a pixel at 72% maximum pixel uptake will look visually very different although they are close in counts. When using a color scale in interpretation, best practices would argue for reviewing both the grayscale images and the color-​scale images (both are the exact same image, just represented differently), and one should be comfortable with understanding the spectrum of count assignments along the color maps. AR T IFAC T S DU E T O C ONDU C T ION OR R H YT H M DIS OR DE R S Some perfusion defects can be caused by disorders in myocardial blood flow not related to epicardial coronary stenosis (see Box 7.2). One example is left bundle branch block, where reversible perfusion defects that mimic those due to stenosis of the left anterior descending artery may occur.

 

Figure 7.8  Classic physiologic left bundle branch block artifact, most prominent in septum, needing pattern recognition in the appropriate patient.

These defects are more common at higher heart rates such as with treadmill exercise or dobutamine stress, which explains why guidelines recommend vasodilator stress (without concomitant exercise) as the stress modality of choice in such patients. The same may be observed in patients with ventricular pacemakers. It may actually be a misnomer to call such defects “artifacts,” as they be related to abnormalities in myocardial blood flow—​although others have suggested alternative explanations (Figure 7.8).41–​45 Perfusion imaging interpretation itself is not significantly affected by rhythm challenges in gating the cardiac cycle for the wall motion analysis and ejection fraction measurement when using gated SPECT MPI. This is because the perfusion images are simply the static addition of all the temporal frames of a gated SPECT acquisition. The heartbeat produced for gated SPECT is an “artificial heartbeat” formed by an average of 10 heartbeats pre-​acquisition and divided into eight or 16 temporal bins across the idealized heart rate to assess cardiac motion. Frequent premature atrial contractions, frequent premature ventricular contractions, and atrial fibrillation with widely varying cardiac cycles or ventricular bigeminy will create marked variations in the number of temporal bins filled with counts during each heartbeat during acquisition, resulting in “count mixing” less counts in the late frames from short cardiac cycles compared to the early frames. Visually, this is seen as a “blinking” or “fading” of count thickening intensity during the cardiac motion cine from the darkening

164

effect of some lower-​count frames. It is easily identified by examining the time–​activity curve across the cardiac cycle, which will show the late frames not recovering to similar levels of the end-​diastolic frame counts. Such findings on pattern recognition should be noted and in some cases may lower the accuracy of ejection fraction measurement. The only potential way to improve gating on a highly arrhythmic patient is to acquire “list mode” rather than “frame mode,” but this is computer processing intense and little used.46,47 Artifacts could also be seen in nonperfusion imaging. F-​18 deoxyglucose PET imaging, used in myocardial viability assessments and in inflammatory cardiomyopathy investigations (such as sarcoid), must be acquired in a highly controlled metabolic state for appropriate interpretation, mandating scrupulous dietary restrictions for 24 hours prior to tracer injection. These requirements are well outlined in guideline manuscripts and elsewhere in this book.48–​50 AR T IFAC T S OF H YB R ID IMAGING Acquisition of MPI imaging by PET/​CT and SPECT/​ CT equipment is more common in the recent era (see Box 7.2). The CT component of these examinations involves low-​radiation “nondiagnostic” CT scans compared to full (radiation) CT scans, but this is useful for AC. The CT attenuation map is robust with some advantages, but unlike

S E C T I O N i . H istorical , T echnical

 

Panel A

Panel B

Figure 7.9  (A) Significant apparent perfusion defect caused by misregistration of sequential AC CT on prior acquired SPECT images. (B) Marked

improvement in perfusion images when SPECT and CT are appropriately fused and co-​registered.

AC on dedicated SPECT or PET scanners using external sources or rods, the CT attenuation map is acquired sequential to the nuclear scan by moving the table up into the CT ring from between the proximal attached nuclear detectors. The transmission attenuation map in dedicated PET or dedicated SPECT is acquired simultaneous with simultaneous positioning with the emission perfusion image. In PET/​CT or SPECT/​CT, the sequential images must be co-​registered and fused. If the overlay co-​registration is not fitted correctly, marked apparent perfusion defects may be created. Good quality control mandates routine evaluation of the adequate registration of the nuclear tomograms and the CT attenuation map on a save screen (Figure 7.9).51–​57 P ROM IS ES AN D CHALLEN G ES O F N EW E R C A M ER A TECHN O LO G Y The last decade has been notable for diverse innovations in nuclear cardiology hardware and reconstruction software beyond the several early decades of SPECT foundations starting with the 1980s experience with supine rotational Anger cameras, parallel-​hole collimation, filtered backprojection reconstructions, and in the 1990s early AC with transmission source gadolinium rods (see Box 7.2). A rtifacts

Some of these innovations changed the positioning of patient imaging from supine to reclining chairs or upright imaging for patient ease and lowering bowel position. These offer some advantages but in some ways may shift attenuation artifacts slightly to new positions to be recognized. Some of the innovations involve solid-​state detectors and new CZT crystals, which improve image quality counts and some spatial resolution but will still encounter count variabilities from soft tissue attenuation to be recognized. Some systems acquire now with neither detector rotation nor patient rotation, which decreases opportunities for motion but makes recognizing motion more difficult when it does occur without a rotational raw planar nor sinogram to review (some stationary systems generate a “planogram” for assessment of patient fidgets). Some systems use more focused collimation methods or pinhole collimations to decrease accepted scatter, but careful centering of the heart in the field of view is important to avoid truncation artifacts. Some offer more iterative reconstructions or wide-​ beam reconstructions to work to allow lower administered doses or shorter acquisitions, but care must be taken when working with lower count statistic imaging as well.58–​65 The diverse engineering improvements active in the field reflect the vibrance in the profession. The continuous improvements in perfusion imaging over the past four

 

decades come from working with multidisciplinary science stakeholders in the field to find hardware and software solutions to mitigate/​correct artifacts systematically, to standardize quality acquisitions, and to recognize standard artifacts.66–​68 C ONCL US IONS Perfusion imaging by SPECT or PET plays a vital seamless role in cardiac patient management. As with all medical imaging, there are some challenges in the image creation process, which may add artifacts to the image interpretation mix. Building on the long history of SPECT and PET experience and continuing technologic advancements, potential artifacts have been well characterized, allowing for pattern recognition, understanding of causations, and systematic attempts for avoidance/​mitigation/​fixes. As technology marches forward, some of these challenges will be appropriately addressed, but science tradeoffs and the realities of radiographic signal-​to-​noise relationships will remain to some degree. Continuing research and cataloguing of image artifacts, including thoughtful image interpretation and approaches to defect assessment in perfusion imaging, will continue to move the field forward. ACK NOW L EDG MEN TS Special thanks to Mathew Mathai, CNMT, Michael Gall, CNMT, and Syed Muhammad Zaidi, MD, for assistance on the image files. REFER ENC ES 1. DePuey EG, Garcia EV. Optimal specificity of thallium 201SPECT through recognition of imaging artifacts. J Nucl Med. 1989;30:441–​449. 2. Burrell S, MacDonald A. Artifacts and pitfalls in myocardial perfusion imaging. J Nucl Med Technol. 2006;34:193–​211. 3. Abbott B, Case J, Dorbala S, et al. Contemporary cardiac SPECT imaging: Innovations and best practices: An information statement from the American Society of Nuclear Cardiology. Circ Cardiovasc Imaging. 2018;11:e 000020. 4. Dorbala S, Ananthasubramariam K, Armstrong I, et al. Single photon emission computed tomography (SPECT) myocardial perfusion imaging guidelines: Instrumentation, acquisition, processing, and interpretation. J Nucl Cardiol. 2018. https://​doi.org/​10.1007/​s12​ 350-​018-​1283-​y. 5. Dilsizian V, Bacharach S, Beanlands R, et al. ASNC imaging guidelines/​SNMMI procedure standard for positron emission tomography (PET) nuclear cardiology procedures. J Nucl Cardiol. 2018;25:1784–​1846. doi:10.1007/​s12350-​016-​0522-​3.

166

6. Dorbala S, Di Carli M, Delbeke D, et al. SNMMI/​ASNC/​SCCT guideline for cardiac SPECT/​CT and PET/​CT 1.0. J Nucl Med. 2013;54(8):1485–​1507. 7. Friedman J, Berman DS, Van Train, K, et al. Patient motion in thallium 201 myocardial SPECT imaging: An easily identified frequent source of artificial defect. Clin Nucl Med. 1988;13:321–​324. 8. Cooper JA, Neumann PH, McCandless BK. Effect of patient motion on tomographic myocardial perfusion imaging. J Nucl Med. 1992;13:1566–​1571. 9. Botvinick EH, Yu YZ, O’Connell WJ, et al. A quantitative assessment of patient motion and its effect of myocardial SPECT images. J Nucl Med. 1993;34:303–​310. 10. Prigent FM, Hyun M, Berman DS, et al. Effect of motion on thallium 201 SPECT studies: A simulation and clinical study. J Nucl Med. 1993;34:1845–​1850. 11. Eisner RL, Churchwell A, Noever T, et al. Quantitative analysis of tomographic thallium 201 myocardial bull’s-​eye display: Critical role of correcting for patient motion. J Nucl Med. 1988;29:91–​98. 12. Geckle WJ, Frank TL, Links JM, et al. Correction for patient and organ movement in SPECT: Application to exercise thallium 201cardiac imaging. J Nucl Med. 1986;27:899. 13. Cooper JA, Newman PH, McCandless BK. Detection of patient motion during tomographic myocardial perfusion imaging. J Nucl Med. 1993;34:1341–​1348. 14. Germano G, Chua T, Kavanagh PB, et al. Detection and correction of patient motion in dynamic and static SPECT using a multidetector camera. J Nucl Med. 1993;34:1349–​1355. 15. Pittman A, Kalff V, Van Every B, et al. Contributions of subdiaphragmatic activity, attenuation, and diaphragmatic motion to inferior wall artifact in attenuation-​corrected Tc-​99m myocardial perfusion SPECT. J Nucl Cardiol. 2005;12:401–​409. 16. Germano G, Chua T, Kiat H, et al. A quantitative phantom analysis of artifacts due to hepatic activity in technetium-​99m myocardial perfusion SPECT studies. J Nucl Med. 1994;35:356–​359. 17. Oddstig J, Martnsson E, Jogi J, et al. Differences in attenuation pattern in myocardial SPECT between CZT and conventional gamma cameras. J Nucl Cardiol. 2018;26(6):1984–​1991. 18. Lui C, Cheng J, Huang Y, et al. A performance comparison of novel cadmium-​zinc-​telluride camera and conventional SPECT/​CT using anthromorphic torso phantom and water bags to simulate soft tissue and breast attenuation. Ann Nucl Med. 2015;29:342–​350. 19. Pourmoghaddas A, Vanderwerf K, Ruddy T, et al. Scatter correction improves concordance in SPECT MPI with a dedicated cardiac SPECT solid state camera. J Nucl Cardiol. 2015;22(2):334–​343. 20. Okuda K, Nakajima K, Shibutani T, et al. Impact of iterative reconstruction with resolution recovery in myocardial perfusion SPECT: Phantom and clinical studies. Scientific Reports (Nature Research). 2019;9:19618. 21. James O, Pagnanelli R, Neto S. Resolution recovery and noise regularization in nuclear cardiology. J Nucl Cardiol. 2017;24:138–​141. 22. Liang Z, Turkington T, Gilland D, et al. Simultaneous compensation for attenuation, scatter, and detector response for SPECT reconstruction in three dimensions. Phys Med Biol. 1992;37:587–​603. 23. Zoccarato O, Scabbio C, De Ponti E, et al. Comparative analysis of iterative reconstruction algorithms with resolution recovery for cardiac SPECT studies: A multicenter phantom study. J Nucl Cardiol. 2014;21:135–​148. 24. Manglos SH, Thomas FD, Gagne GM, et al. Phantom study of breast tissue attenuation in myocardial imaging. J Nucl Med. 1993;34:992–​996. 25. DePuey E, Rozanski A. Using gated technetium 99m sestamibi SPECT to characterize fixed myocardial defects as infarct or artifact. J Nucl Med. 1995;36:952–​955. 26. Smanio P, Watson D, Segalla D, et al. Value of gating technetium 99m sestamibi single photon emission computed tomography imaging. J Am Coll Cardiol. 1997;29:69–​78. 27. Farag A, Heo J. Simple method to correct for breast attenuation artifact. J Nucl Cardiol. 2015;6(3):583–​585.

S E C T I O N i . H istorical , T echnical

 

28. Machac J, George T. Effect of 360SPECT prone imaging on thallium 201 myocardial perfusion studies. J Nucl Med. 1979;220:183–​188. 29. Araujo W, DePuey E, Kamran M, et al. Artifactual reverse redistribution in myocardial perfusion SPECT with Tc-​99m sestamibi. J Nucl Cardiol. 2000;7:633–​638. 30. Kiat H, Van Train KF, Friedman JD, et al. Quantitative stress redistribution thallium 201 SPECT using prone imaging: methodologic development and validation. J Nucl Med. 1992;33:1509–​1515. 31. Johnson LL, Tauxe E, Smith K. Comparison of supine and upright SPECT myocardial perfusion imaging (abstract). J Am Coll Cardiol. 1995;25:363A. 32. Friedman J, Van Train K, Maddahi J, et al. “Upward creep” of the heart: A frequent source of false positive reversible defects during thallium-​201 stress-​redistribution SPECT. J Nucl Med. 1989;30:1718–​1722. 33. Toma DM, White MP, Mann A, et al. Influence of arm positioning on rest/​stress technetium 99m labeled sestamibi tomographic myocardial perfusion imaging. J Nucl Cardiol. 1999;6:163–​168. 34. Hansen C. Digital image processing for clinicians, Part I: Basics of image formation. J Nucl Cardiol. 2002;9:343–​349. 35. DePuey E. Ramp filter artifact associated with filtered backprojection, resolved with iterative reconstruction. J Nucl Cardiol. 2019;26:1383–​1391. 36. Hansen C. Digital image processing for clinicians, Part II: Filtering. J Nucl Cardiol. 2002;9:429–​437. 37. Hansen C. Digital image processing for clinicians, Part III: SPECT reconstruction. J Nucl Cardiol. 2002;9:542–​549. 38. Steffen D, Giannopoulos AA, Grossman M, et al. “Apical thinning”: Relations between myocardial wall thickness and apical left ventricular tracer uptake as assessed with positron emission tomography myocardial perfusion imaging. J Nucl Cardiol. 2020;27(2):452–​460. 39. Galt J, Garcia E, Robbins W. Effects of myocardial wall thickness on SPECT quantification. IEEE Trans Medical Imaging. 1990;9:144–​150. 40. Hansen C. The role of the translation table in cardiac image display. J Nucl Cardiol. 2006;13:571–​575. 41. DePuey E, Krawczynska E, Robbins W. Thallium 201 SPECT in coronary artery disease patients with left bundle branch block. J Nucl Med. 1988;29:1479–​1485. 42. Burns R, Galligan L, Wright, L, et al. Improved specificity of myocardial thallium 201 single photon emission computed tomography in patients with left bundle branch block by dipyridamole. Am J Cardiol. 1991;68:504–​508. 43. Larcos G, Brown M, Gibbons R. Role of dipyridamole thallium 201 imaging in left bundle branch block. Am J Cardiol. 1991;68:1097–​1098. 44. Meredith D, Cremer P, Harb S, et al. Initial experience with regadenoson stress positron emission tomography in patients with left bundle branch block: Low prevalence of septal defects and high accuracy for obstructive coronary artery disease. J Nucl Cardiol. 2021;28(2):536–​542. https://​doi.org/​10.1007/​s12​ 350-​019-​01681-​4. 45. Gupta K, Bajaj N, Hage F, et al. Myocardial perfusion artifacts in left bundle branch block: A diagnostic challenge. J Nucl Cardiol. 2021;28(2):543–​545. 46. DePuey E. Artifacts clarified by and caused by gated myocardial perfusion SPECT. In: Germano G, Berman D, eds. Clinical Gated Cardiac SPECT. Futura Publishing. 1999. 47. Nichols K, Yao S, Kamran S, et al. Clinical impact of arrhythmias on gated SPECT cardiac myocardial perfusion and function assessment. J Nucl Cardiol. 2001;8:19–​30. 48. Gropler R, Siegel B, Lee K, et al. Nonuniformity in myocardial accumulation of fluorine-​18-​flurodeoxyglucose in normal fasted humans. J Nucl Med. 1990;31:1749–​1756. 49. Choi Y, Brunken R, Hawkins R, et al. Factors affecting myocardial 2-​[F-​18] fluoro-​2-​deoxy-​d-​glucose uptake in positron emission tomography studies of normal humans. Eur J Nucl Med Mol Imaging. 1993;20:308–​318.

A rtifacts

50. Barlett M, Bacharach S, Voipio-​Pulkki L, et al. Artifactual inhomogeneities in myocardial PET and SPECT scans in normal subjects. J Nucl Med. 1995;36:188–​195. 51. Dvorak R, Brown R, Corbett J. Interpretation of SPECT/​CT myocardial perfusion images: Common artifacts and quality control techniques. Radiographics. 2011;31(7):2041–​2057. doi.org//​ 10.1148/​rg.317115090. 52. Loghin C, Sdringola S, Gould L. Common artifacts in PET myocardial perfusion images due to attenuation–​emission misregistration: Clinical significance, causes, and solutions. J Nucl Med. 2004;45:1029–​1039. 53. Gould L, Pan T, Loghin C, et al. Frequent diagnostic errors in cardiac PET/​CT due to misregistration of CT attenuation and emission PET images: A definitive analysis of causes, consequences, and corrections. J Nucl Med. 2007;48:1112–​1121. 54. Camoni L, Santos A, Attard M, et al. Best practice for the nuclear medicine technologist in CT based attenuation correction and calcium score for nuclear cardiology. Eur J Hybrid Imaging. 2020;4:11. 55. Tantawy H, Abdelhafez Y, Helal N, et al. Effect of correction methods on image resolution of myocardial perfusion imaging using single photon emission computed tomography combined with computed tomography hybrid systems. J Phys Commun. 2020;4:015011. 56. Malkerneker D, Brenner R, Martin W, et al. CT based attenuation correction versus prone imaging to decrease equivocal interpretation of rest/​stress Tc-​99m tetrofosmin SPECT MPI. J Nucl Cardiol. 2007;14:314–​323. 57. Cohen M. Combined supine and prone imaging acquisition cardiac SPECT: A turn for the better. J Nucl Cardiol. 2016;23:1477–​1479. 58. Wosnitzer B, Friedman M, DePuey G. Truncation in myocardial perfusion SPECT. Intl J Nucl Energy Science Engineering. 2012;2:116–​121. 59. Hyafil F, Chequer R, Sorbets E, et al. Head-​to-​head comparison of the diagnostic performance of rubidium-​PET and SPECT with CZT camera for the detection of myocardial ischemia in a population of women and overweight individuals. J Nucl Cardiol. 2020;27(3):755–​768. 60. Esteves F, Raggi P, Folfs R, et al. Novel solid state detector dedicated cardiac camera for fast myocardial perfusion imaging: Multicenter comparison with standard dual detector cameras. J Nucl Cardiol. 2009;16:927–​934. 61. Ben-​Haim S, Almukhailed O, Neill J, et al. Clinical value of supine and upright myocardial perfusion imaging in obese patients using the D SPECT camera. J Nucl Cardiol. 2014;21:478–​485. 62. Gremiller E, Agostini D. How to use cardiac IQ-​SPECT routinely? An overview of tips and tricks from practical experience to the literature. Eur J Nucl Med Mol Imaging. 2016;43:707–​710. 63. Timmins R, Ruddy T, Wells, G. Patient position alters attenuation effects in multi-​pinhole cardiac SPECT. Med Phys. 2015;42:1233–​1240. 64. Allie R, Hutton B, Prvulovich B, et al. Pitfalls and artifacts using the D SPECT dedicated cardiac camera. J Nucl Cardiol. 2016;23:301–​310. 65. Hindorf C, Oddstig J, Hedeer F, et al. Importance of correct patient positioning in myocardial perfusion SPECT when using a CZT camera. J Nucl Cardiol. 2014;21:695–​702. 66. Betancur J, Hu L, Commandeur F, et al. Deep learning analysis of upright-​supine high efficiency SPECT myocardial perfusion imaging for prediction of obstructive coronary artery disease: A multicenter study. J Nucl Med. 2019;60(5):664–​670. 67. Case J, Bateman T. Taking the perfect nuclear image: Quality control, acquisition, and processing techniques for cardiac SPECT, PET, and hybrid imaging. J Nucl Cardiol. 2013;9:891–​907. 68. Abreu C, Frade AG. Artefacts and pitfalls in myocardial imaging (SPECT, SPECT/​CT, and PET/​CT). In Myocardial Perfusion Imaging. European Association of Nuclear Medicine (EANM). 2014;109–​123. 69. Piekarski E, Manrique A, Rouzet F, Le Guludec D. Current status of MPI with new SPECT/​CT cameras. Semin Nucl Med. 2020;50(3):219–​226.

 

 

II. DIAGNOSIS AND RISK ASSESSMENT

 

 

8. REGULATION OF MYOCARDIAL BLOOD FLOW Henry Gewirtz

K EY P OIN TS 1. MBF is adjusted to meet myocardial oxygen demand. 2. Myocardial oxygen demand is indicated by coronary venous oxygen saturation. 3. If, for instance, coronary venous oxygen saturation declines with increased metabolic activity, RBC release of oxygen increases to meet demand. 4. RBC release of ATP initiates an ascending vasodilation via pre-​arteriolar vascular smooth muscle relaxation (NO dependent). ADP and AMP resulting from ATP breakdown also participate in vascular relaxation. 5. There are three main time-​varying resistances to flow in the coronary circulation: conduit vessels (viscous)—​very small under normal conditions; compressive—​related to systolic compression of intra-​myocardial coronary vessels; and microvasculature—​vast majority of resistance to flow, under metabolic regulation. 6. Pressure drop across a coronary artery stenosis generally conforms to a quadratic model, which means pressure loss across it increases geometrically as flow increases: dP = AQ +BQ 2

where dP =​pressure drop, A ~ Poiseuille resistance, and B ~ stenosis geometry. 7. Awareness of this equation is essential for understanding of fractional FFR since distal pressure (Pd; mean pressure distal to stenosis under conditions of maximal coronary dilation)

will depend on flow across the stenosis and the many factors influencing flow, including Pa (aortic mean pressure). 8. A new index of coronary stenosis severity (iFR, instantaneous wave-​free ratio) recently has been found to be non-​inferior to FFR for assessment of stenosis severity and revascularization decision-​making. It does not require a coronary vasodilator drug. 9. Closely related to iFR is full cycle Pd/​Pa (mean stenosis pressure gradient), which also has been found a useful predictor of stenosis severity and outcomes of revascularization therapy. 10. PET indices of stenosis severity include MFR, stress MBF, and RFR. Each has been found to have prognostic information, depending on the patient population, study end points, sample size, and specifics of data analysis.

AB B R E V IAT IONS BSR CAD CAS CBF CCTA

basal stenosis resistance coronary artery disease coronary artery stenosis coronary blood flow coronary computed tomography angiography CFR coronary flow reserve CFVR coronary flow velocity reserve CMR cardiac magnetic resonance DSE dobutamine stress echo FFR fractional flow reserve FFR-​CT fractional flow reserve by computed tomography

 

FFR-​PET HSR iFR IMR LAD LV MACE MBF MFR MPI PET RBC RFR

fractional flow reserve by PET hyperemic stenosis resistance instantaneous wave-​free ratio index of microvascular resistance left anterior descending artery left ventricle major adverse cardiac events myocardial blood flow myocardial flow reserve myocardial perfusion imaging positron emission tomography red blood cell relative flow reserve

MBF METABOLIC REGULATION O2 Supply MBF

O2 Extraction

O2 Demand Heart Rate Pre-Load Afterload Contractility

Figure 8.1  The relationship between myocardial oxygen supply and demand.

Myocardial oxygen supply is heavily dependent upon MBF. Myocardial oxygen demand is determined by heart rate, preload, afterload, and contractility. To maintain balance, MBF typically is adjusted to meet the prevailing level of myocardial oxygen demand.

A UTHOR ’ S NO TE Much of the information provided in this chapter has been adapted and updated as needed from a previously published editorial by the author and used with the editor’s permission.1

BA S IC P HY SI O LO G Y O F THE N O RMAL C ORONA RY CI RCULATI O N METABOLIC THEORY OF FLOW REGULATION

The paradigm of myocardial oxygen supply and demand2–​8 was initially proposed in the mid-​1900s when Gregg et al.3 and Sarnoff et al.5 first published on the subject. In brief, the heart relies upon MBF to deliver oxygen to meet its needs for aerobic synthesis of ATP. Since myocardial oxygen extraction is near maximal under basal conditions, the principal mechanism for increasing oxygen delivery is primarily via increasing MBF.2 The major determinants of myocardial oxygen demand (MVO2) are well known2,9 and include (1) heart rate; (2) LV afterload, the product of LV wall tension and heart rate; (3) LV preload (approximated by left atrial mean pressure and hence a contributor to afterload); and (4) LV contractile state, which is often defined by end-​systolic elastance, the slope of a series of LV end-​systolic pressure/​end-​systolic volume data points (Figure 8.1). Under aerobic conditions, oxidation of glucose and fatty acids ultimately makes molecular oxygen available to the mitochondria for generation of ATP. Though both glucose and fatty acids are used, the mix varies depending

172

on activity level and overall metabolic milieu.8 Under basal conditions the preferred substrate is fatty acid. Each molecule metabolized under aerobic conditions results in the production of 37 ATP versus one from glucose, even though oxygen consumption in generation of ATP is more efficient with glucose (~16% less/​ATP). ATP catalyzes actin–​myosin interaction (sliding filaments) and thereby myocardial contraction. Calcium is stored in the sarcoplasmic reticulum and is required for contraction. It is sequestered back in the sarcoplasmic reticulum, an active process that is essential to myocardial relaxation with each beat. The process by which the myocardium and coronary vasculature “talk” to one another also is complex but must result in matching of oxygen supply to demand (Figure 8.2).2,4,6,8 The regulated variable, currently, is thought to be hemoglobin O2 saturation in coronary venous capillaries, which reflects tissue metabolic activity.2,10–​15 RBCs transport ATP as well as oxygen. An increase in metabolism, for instance, will result in a decline in coronary capillary venous O2 saturation, which in turn causes ATP release from RBCs transiting the myocardial capillary network. The ATP acting by P2Y1 endothelial receptors initiates an ascending vasodilation extending to pre-​capillary arterioles whose vascular smooth muscle relaxes (NO dependent), thereby increasing MBF. ADP and AMP from breakdown of ATP also participate, ADP via P2Y1 and AMP by P1 endothelial receptors.14 ADP also is an agonist of RBC P2Y13 receptors, which inhibit further ATP release from RBCs.14 Under aerobic conditions adenosine does not appear to play a role.16,17 Adjustment of MBF to the prevailing level of oxygen demand means that flow will remain nearly constant over

 

MBF METABOLIC REGULATION Coronary Venous O2 Sat

O2 DELIVERY

RBC’s RELEASE O2 AND ATP

MBF

ATP -> VASODILATION (P2Y1 -> NO + SHEAR) ADP -> DIL (P2Y1) AMP -> DIL (P1)

Figure 8.2  Mechanisms involved in the augmentation of MBF in response

to an increase in myocardial oxygen demand (flame). Coronary venous oxygen saturation declines and RBCs release both ATP and oxygen. ATP in turn initiates an ascending vasodilation via endothelial P2Y1 receptor agonism and subsequent nitric oxide release with relaxation of arteriolar pre-​capillary smooth muscle and thus an increase in MBF. ATP also is metabolized to ADP and AMP, both of which participate in vascular relaxation. In addition, ADP stimulates RBC receptors, which inhibit further ATP release once MBF has increased sufficiently to meet myocardial oxygen demand and a new steady state has been attained.

coronary stenosis, which for instance reduces mean perfusion pressure by as much as 40% or more (e.g., from ~100 to ~60 mmHg; see Figure 8.3) before rest MBF begins to decline.19 A great deal follows from this fact, as will be discussed below.

CORONARY HEMODYNAMICS AND APPLIED PHYSIOLOGY

Clinical cardiologists have, for practical, purposes adopted a simple Ohm’s law model to describe coronary pressure/​ flow relations.1,2,8,9,12,15,19–​25 Thus, flow is analogous to current (I) as follows: (1)

I = V/R 

Coronary mean perfusion pressure is analogous to voltage (V) and resistance is R. Many more complex models have been proposed, including those that account for the distribution of MBF across the LV wall.21–​24 Nonetheless, the transmural distribution of MBF may be thought of as governed by three time-​varying resistances, each obeying a broad range of coronary perfusion pressures (~70–​ the simplified model. Thus, compressive forces of the contracting LV (R1) 140 mmHg).2,14,18 This characteristic of the coronary circulation (i.e., metabolic regulation, not strictly speaking have several effects, including the following (Figure 8.4): autoregulation; Figure 8.3) is an essential feature of the system and in large measure accounts for the fact 1. Limiting MBF to diastole with only modest epicardial (conduit vessel) flow in systole that resting MBF will remain at control level despite a

MBF METABOLIC REGULATION

CBFmax @ LV Max-dP/dt LVP (mmHg)

180 140 120

100 50 0

100 LV dP/dt (mmHg/s)

80 60 40 20 0 0

50

100

150

mmHg

CBF (ml/min)

MBF ml/min/100g

160

5000 2500 0 –2500 150 100 50 0

Figure 8.3  Metabolic regulation of MBF implies over a broad range of perfusion

pressure (~70–​140 mmHg) that MBF remains constant (blue line plateau) in the face of constant myocardial oxygen demand. A maximally dilated vascular bed in which metabolic signaling has been nulled behaves in a perfusion-​ pressure–​dependent fashion (red line). Vasodilator reserve may be thought of as the distance between MBF/​perfusion pressure plateau (blue line) and the corresponding data points above (red line) of the maximal dilation MBF/​ perfusion pressure line. mmHg =​mean coronary perfusion pressure.

M B F R egulation

Figure 8.4  Relationship between instantaneous coronary blood flow (CBF)

and left ventricular dP/​dt. Note that peak coronary inflow occurs in early diastole at the time of maximum negative dP/​dt; this is an indication that LV relaxation plays an important role in coronary filling. Similarly, LV pressure peak positive dP/​dt coincides with cessation of CBF; this observation indicates that LV contraction all but terminates CBF in systole  (Courtesy of Dirk D. J. Duncker, MD, PhD, Erasmus University, Rotterdam, NE)

 

2. Release of compressive forces at the onset of diastole actually has a suction effect, which accelerates coronary and myocardial blood flow in early diastole.25 3. The distribution of MBF is not uniform across the LV wall because compressive systolic forces are more marked in endocardial versus epicardial layers. Thus, wall tension (T) by Laplace: T = P * R/h

(2)

where T is tension, P =​LV pressure, R =​radius of modeled LV chamber, and h =​wall thickness. So, while there is some epicardial MBF in systole, where compressive force are least, the closer one measures to the endocardial surface, where compressive forces are greatest, the less systolic flow there is (see Figure 8.4). Accordingly, in compensation for relatively low systolic flow and what may be thought of a transient ischemia, endocardial resistance declines such that diastolic inflow actually exceeds that of the epicardium, where resistance now is greater. Thus, the endo/​epi MBF ratio typically exceeds 1.0 (1.1–​1.3). Note is made, however, that increased endocardial capillary density and increased MVO2 in endocardial layers resulting from systolic compression have been proposed as contributors to the relative overall excess of endo versus epi rest MBF.2,9 In addition to compressive resistance to MBF, there is fluid/​viscous resistance in epicardial, conduit-​level vessels (R2).2 This resistance under normal conditions is minimal and so plays only a modest role in MBF distribution and flow regulation. In the presence of coronary stenosis that is severe enough, however, this resistance becomes the dominant one. In the absence of stenosis in the normal coronary circulation, the most important resistance to MBF is found at the microvascular pre-​capillary, arteriolar level (R3).2,25 These vessels represent a very large fraction of the total myocardial vascular volume and so play the dominant role in regulation of MBF.25 It is microvascular tone (under metabolic control12,13) at the pre-​capillary arteriolar level (R3) that by turns controls MBF in the normal circulation (see Figures 8.2, 8.3, and 8.4). A simplified model of all three resistances to MBF, therefore, may be given as: Rt = R1 + R2 + R3 

(3)

where Rt is total resistance, R1 compressive forces, R2 epicardial viscous forces, and R3 microvascular, primarily under metabolic control and the controlling resistance of the system.

174

These basics are critical to keep in mind as one seeks to understand MBF and flow distribution in the setting of disease at any combination or all three levels of the coronary circulation.

C ORONAR Y PR E S S U R E / F​ LOW R E LAT IO N S : C AD S E T T ING By far the most common pathophysiologic clinical scenario encountered in the practice of nuclear cardiology is atherosclerotic cardiovascular disease. CAS pressure–​flow relations have been modeled since the early 1970s by Young et al.26, 27 and pioneered in cardiology by Gould et al.28–​30 It was appreciated from the outset, in the CAD setting, that several factors render formal description of pressure flow relations more complex than that of the necessarily simpler experimental models first used. Such factors include (1) diffuse disease with only mild stenosis with or without additional superimposed hemodynamically significant lesion(s); (2) collateral blood supply to an occluded or severely stenotic vessel; and (3) serial lesions of variable hemodynamic severity in a given artery.31–​34 So, for the simple case of an otherwise normal coronary vessel from top (origin) to bottom (microcirculation) and all levels in between, the pressure drop (ΔP) across an epicardial stenosis is given by26–​28: ∆P = AQ + BQ 2

(4)

where Q is flow and A and B are constants related, respectively, to Poiseuille (frictional) resistance and stenosis geometry (flow separation). It is immediately apparent that the pressure drop across the stenosis is directly related to flow through it and that the pressure loss related to stenosis geometry (BQ2) is geometrically greater than that related to Poiseuille resistance (AQ). Hence, any factor that impacts flow in the vascular bed distal to the stenosis (e.g., diffuse disease or microvascular dysfunction or both) must be reflected in the stenosis pressure gradient. Accordingly, for a given anatomic stenosis severity, even if precisely known, less flow means less pressure loss and vice versa. The relationship is geometric, not linear. These principles, which are underappreciated, are crucial to understanding all pressure-​based metrics of stenosis hemodynamic severity (see below). The maximal flow capacity of a coronary vascular bed may be characterized in a variety of ways. Invasive methods

 

employ pressure or flow (or both) measurements, while noninvasive methods focus on flow. CCTA, however, combines anatomic data and fluid dynamic modeling to estimate pressure loss, at a modeled, patient-​specific, virtual maximal blood flow, to obtain a noninvasive estimate of a pressure parameter, FFR.35 While invasive FFR is currently employed as the gold-​standard metric for assessing coronary stenosis severity and guiding revascularization, more recently iFR (see below) has been shown to be non-​ inferior for this purpose.36–​39 Further, rest, full cardiac cycle Pd/​Pa correlates closely with iFR and so empirically may be found to be as useful in guiding revascularization decision-​making.38 Strengths and limitations of these and other frequently employed parameters of coronary dilator capacity (e.g., IMR, CFR, FFR, maximal myocardial blood flow1,40–​42) are reviewed in the following section. P RES S UR E - B ​ ASED METRI CS O F CO RONAR Y S TENOS IS SEVERI TY Pressure-​based measurements of stenosis hemodynamic severity represent efforts to estimate maximal flow attainable in the coronary vessel of interest.43 Early in the history of interventional cardiology, an effort to relate the LAD trans-​stenosis pressure gradient to exercise-​induced myocardial ischemia found only a loose inverse correlation between LVEF and stress gradient, with suboptimal predictive power in a given patient.44 The ratio of mean distal coronary pressure (Pd) to proximal mean aortic pressure (Pa) likely was found to be unreliable due to the presence of the angioplasty catheter itself. More recently, of course, the advent of micro-​transducer pressure (and flow) wires makes possible the measurement of the trans-​stenotic gradient. Indeed, the ratio of Pd/​Pa measured under conditions of maximal coronary dilation is FFR (Figure 8.5).43 Moreover, it was demonstrated in the original description of the metric, under conditions of maximal coronary vasodilation (papaverine, 8 mg intracoronary, canine model), that as stenosis severity was increased, Pd and the Pd/​Pa ratio decreased.43 The decline in the pressure ratio correlated very closely (R2 ≥ 0.94) with the directly measured flow ratio in the presence of the same stenosis, relative to flow in the vessel in the absence of a stenosis (i.e., Qs/​QN =​1, in vessel free of stenosis). Hence, the designation FFR (see Figure 8.5), as has been pointed out, represents relative as opposed to absolute flow reserve, since the observed ratio implicitly is compared to a

M B F R egulation

ratio of unity in the absence of the stenosis.43,45 The FFR ratio, as discussed in the original paper, was developed as a surrogate for maximal CBF.43 The authors noted that this metric was superior to flow reserve (maximal/​rest flow) since (1) it was not subject to variation associated with resting flow and (2) it directly addresses the clinical question of interest: the extent, if any, to which the stenosis compromised the ability of the artery to supply blood to the heart under conditions of stress.43 The myocardium lives on blood flow (mL/​min/​g ) and not unit-​less ratios. The authors noted at the time, however, that PET, which was (and still is) the optimal way to quantitatively measure maximal MBF in humans, was not widely available and of course was not feasible for immediate clinical decision-​ making about percutaneous coronary intervention in the cardiac catheterization laboratory.43 Hence the advantage of a pressure-​wire–​based metric, FFR: It provided an estimate, in the presence of the stenosis, of the fraction of maximal MBF attainable in the absence of the stenosis (i.e., normal coronary circulation). C LINIC AL IMPLE ME NTAT ION OF PR E S S U R E / ​F LOW ME T R IC S Another important practice is the unfortunate, though perhaps necessary, expedient of dichotomizing pressure-​ and flow-​related metrics for purposes of both clinical decision-​making and data analysis.46 A statistically defined cut point is chosen, and so continuous variables are transformed to “normal” and “abnormal” categories. While in individual clinical decision-​making, values on or just either side of the line may be weighed accordingly with other relevant factors, in research work the data must be grouped as defined and are counted just as those very far from the line. Moreover, much attention has been drawn to the problem of metrics, once dichotomized, pointing in opposite directions. Thus, a “normal” FFR (>0.80) coupled with an abnormal CFR ( ascend vasodilation => arteriolar tone (↓) => MBF (↑) => (↑))O2 delivery => MVO2 (↑)

The “Great Mandala” turns until MVO2 returns to control, at which point O2vein (↑), the wheel slows down, and MBF and MVO2 come into new equilibrium. 3. In the presence of coronary stenosis, a pressure drop (ΔP) across the stenosis occurs as follows: ∆P = AQ + BQ 2

180

where Rt =​total resistance unchanged, R1 =​compressive resistance typically unchanged unless ischemia ensues, R2 (↑; reflects stenosis resistance); and R3 (↓; reflects compensatory small conduit and principally microvascular dilation). As R3 declines to maintain rest MBF, stress MBF begins to fall off as R3 approaches minimum, at which point rest MBF declines as well, typically at approximately 80% coronary artery diameter reduction (see Figure 8.3). 5. Clinical assessment of coronary pressure flow relations A. Invasive: Coronary stenosis including microvascular compensation (R2 +​R3) i. FFR: full cardiac cycle Pd/​Pa during maximal coronary dilation; the fraction of flow deliverable by the vasculature interrogated compared to fraction flow in a normal vessel (Pd/​Pa =​1; see Figure 8.5)—​hence FFR, which is relative flow reserve. The metric is stenosis-​specific only in presence of an entirely normal circulation distal to it (generally uncommon in the presence of atherosclerotic cardiovascular disease). ii. MFR is commonly referred to as CFR but they are strictly not the same: MFR indicates MBF while CFR indicates CBF (see Figure 8.3). Both are measures of absolute flow since stress/​rest MBF in the coronary artery (CFR) or myocardium distal to a stenosis (MFR) is measured. Like FFR, both reflect resistance (R2 +​R3) of the entire vasculature in the vessel(s) of interest. Neither is specific for stenosis resistance nor coronary microvascular disease, though given anatomic data indicating “clean” coronary vessels or “non-​obstructive” stenosis, abnormal CFR (or MFR) typically is attributed to microvascular disease. The same would apply to FFR. iii. iFr, Pd/​Pa (full cardiac cycle): Both metrics focus on stenosis severity (see Figure 8.6). However, like FFR, MFR, and CFR, all are sensitive to

 

abnormal R3, notwithstanding the assumption R3 is minimal or nearly so in compensation for a hemodynamically significant coronary stenosis. Recall that iFR requires a dedicated measuring system to assess Pd/​Pa during the wave-​free period of diastole. Full-​cycle Pd/​Pa correlates closely with iFR and has similar diagnostic performance. iv. Another invasive mid-​diastolic flow index is dP @ 50 cm/​sec (Figure 8.7).101 The instantaneous stenosis Pa-​Pd (dP) versus coronary flow velocity is plotted for mid-​diastole, the data are fit to a quadratic function (Equation 4, above), and the value of the gradient at flow velocity 50 cm/​sec is taken. An empiric cut point of 22 mmHg has been found to have excellent predictive power for hemodynamically significant stenosis versus DSE or SPECT MPI. Comparison to FFR and CFVR also was made for prediction of ischemia on DSE or SPECT MPI. Results were excellent for sensitivity, specificity, and accuracy (Table 8.1): After removing the highest quartile of flow velocities, there was only 3% difference in the recalculated data. Thus, the authors concluded that in contrast to CFVR and FFR,

STNS dP (mmHg)

70 60 50 40 30

Severe

20

Mild

10 0 20

30

40

50

Specificity

Accuracy

Stenosis dP@50

95%

95%

95%

CFVR

56%

86%

76%

FFR

77%

99%

91%

Noninvasive stress test (SPECT MPI with adenosine or DSE). Data from reference 101.

dP @ 50 cm/​sec retained predictive accuracy for hemodynamically significant stenosis without pharmacologic coronary vasodilation and appeared superior to both CFVR and FFR in the same dataset for this purpose.   Obviously, additional prospective randomized controlled trials are required to evaluate the clinical utility of the index. It is an attractive one since it appears independent of maximal hyperemia and could be obtained with a single Doppler flow velocity/​pressure wire and dedicated black-​box to display the diastolic dP flow velocity (v) data, do the fit on the fly, and display the value of dP at v =​50 cm/​sec. Values higher than 22 mmHg would be indicative of an hemodynamically significant coronary stenosis.

Classical resistances at rest and with vasodilator stress

STENOSIS dP

10

Sensitivity

v. Simultaneous pressure/​flow measurements to compute resistances40:

dP@50

0

TA B LE 8 .1   S TE N O S IS D P V E RS U S CFV R AN D FFR FO R ID E N TIFICATIO N O F IS CH E MIA

60

70

80

1) stenosis resistance =​ΔP (across stenosis)/​MBF (or CBF) if volume flow measured as MTT then stenosis resistance (R2): R2 =​ΔP (ACROSS STENOSIS)*MTT

Q (cm/s)

Figure 8.7  A hypothetical stenosis pressure gradient (dP mmHg) versus mid-​

diastolic coronary flow velocity curves (cm/​sec) for a hemodynamically mild (red) and severe (blue) stenosis. Note that at flow velocity 50 cm/​sec, the gradient across the severe stenosis is 38 mmHg versus 13 mmHg for mild. On the other hand, the mild stenosis will appear high risk (gradient ≥22 mmHg) at flow velocity 70 cm/​sec, while the severe will appear low risk (gradient 0.80), which would then suggest that relatively reduced maximal MBF reflects more diffuse small vessel/​microvascular disease. CFR if measured would be expected to be abnormal (2.0). Although heart rate and blood pressure N-​13 ammonia and, even more so, with Rb-​82. failed to respond to the pharmacologic vasodilator in some MBFs at rest depend on cardiac work, commonly depatients with detectable serum caffeine levels, hemodynamic fined by the product of heart rate and systolic blood pressure M B F M easurement by P E T

 

Figure 9.10  Stress–​rest N-​13 ammonia PET myocardial perfusion images and parametric polar maps of quantitative MBFs during stress and rest and

the MFR in a 71-​year-​old male with coronary artery disease, percutaneous coronary intervention of the anterior descending and the left circumflex coronary arteries, and complete obstruction of the right coronary artery on CT coronary angiography. The perfusion images reveal stress-​induced perfusion defects in the inferior wall and the basal portion of the anterior lateral wall. On the parametric polar maps, MBF at rest is homogeneous throughout the LV myocardium and is in the normal range. During adenosine stress, however, hyperemic flows are attenuated in the territory of the right coronary artery and the left circumflex coronary artery. MFR is abnormally reduced in the inferior wall (1.73) and attenuated in the lateral wall (2.4) when compared to the anterior wall.

as the rate–​pressure product (RPP; Figure 9.11).96,97 To account for effects of cardiac work (expressed as heart rate times systolic pressure or RPP), rest flows are frequently normalized where

estimates as high as 5.0 mL/​min/​g . An upper limit of normal for hyperemic flows has yet to be determined, although lower thresholds for pharmacologic stress flows have been suggested. Values of 1.85, 2.4, and less than 1.5 mL/​min/​g increase above rest flows have been reported in several investigations as “cut points” or thresholds for MBFNORMALIZED =​[MBFMEASURED/​RPP] × 10,000. abnormally reduced stress flows associated with flow-​ limiting coronary lesions.98 An even lower threshold value FLOWS DURING VASODILATOR STRESS was reported in another investigation, where stress flows Pharmacologically stimulated hyperemic flows (deter- of less than 0.91 mL/​min/​g were found to be associated mined in 3,484 healthy volunteers) as reported in numerous with myocardial ischemia.99 investigations averaged 2.86 ± 1.29 mL/​min/​g , with correSeveral reasons explain differences in the reported cut sponding average MFR 3.55 ± 1.36.94 Statements by pro- points. They include use of different, laboratory-​specific fessional societies list comparable values of 2.58 mL/​min/​ methodologies of PET flow measurements as well as use of g (range 1.86–​4.33) and 2.86 mL/​min/​g (range 2.5–​3.82) different end points, as for example angiographic estimates for N-​13 ammonia-​ and Rb-​82-​determined estimates of of stenosis severity, fractional flow reserves for stress-​ hyperemic flows in normal volunteers, derived as weighted induced perfusion defects, as well as clinical signs of ismean values from several investigations.7 chemia. They also relate to differences in study populations, Pharmacologic-​stimulated hyperemic flows vary con- together with differences in extent and severity of coronary siderably between normal volunteers, with some flow artery disease, as for example presence of a single discrete 202

 

Figure 9.11  MBF and cardiac work. Global MBFs at rest (basal, red dots) and during dipyridamole-​induced hyperemia (green dots) are plotted against RPP

as an index of cardiac work. MBFs at rest correlated with the RPPs but are independent of cardiac work during dipyridamole-​induced hyperemia  Data plotted from Czernin et al 97

coronary lesion, multiple lesions in series, diffuse disease, as well as microvascular dysfunction/​disease. MYOCARDIAL FLOW RESERVE

The term “flow reserve” originated at a time of intense investigations of coronary vasomotion with intracoronary flow velocity probes when responses to vasodilator agents were expressed as the ratio of hyperemic to baseline flow velocities or the flow velocity reserve. MFRs as the ratio of hyperemic over rest MBFs in normal volunteers averaged in 3,484 healthy volunteers 3.55 ± 1.3694 and are listed in official society publications as 3.54 (range 1.86–​4.33) and as 4.07 (range 3.88–​4.47) for N-​13 ammonia and Rb-​82 flow measurements.7 Besides technical and methodologic issues, biologic factors account for some of the variability of flow estimates at both rest and stress. MBFs both at rest and during stress are higher in women than in men, while flow reserves are comparable.100–​103 Flows at rest increase with age, largely because of higher arterial blood pressures and thus higher RPPs, but also because of an attenuation of the hyperemic flow response, especially in individuals older than 65 years, so that MFR declines with increasing age in apparently “healthy” volunteers (Figure 9.12).97,101,104,105 High-​risk serum lipoprotein patterns, history of smoking, endothelial dysfunction, and preclinical atherosclerosis further contribute to the variability of flows, especially those obtained with pharmacologic vasodilation, in apparently normal volunteers.95,101,106 M B F M easurement by P E T

Despite their sensitivity to MBF at rest, using MFR as a metric of disease severity and especially a predictor of cardiac risk offers advantages. One is that flows at rest contain predictive information, as for example higher flows in patients with hypertension. A second and important one relates to methodologic limitations. Method-​related inaccuracies of measured flows at rest and during stress will cancel in the ratio of stress over rest flow, an argument that is supported by the fact that estimates of stress and rest flows can differ significantly between software packages, while MFRs are generally comparable. Further, MFRs have proved to be more powerful predictors of cardiac risk than hyperemic flows.3,107,108 Global MFRs, used widely in clinical practice, contain comprehensive information on the structural and functional integrity of the coronary circulation. Values greater than 2.0 have consistently been found to be associated with event-​free survival, whereas flow reserves of less than 2 and, especially, of less than 1.5 consistently predicted a moderate or high risk for major adverse cardiac events, a risk that is further influenced by the presence or absence of flow defects and their severity on the myocardial perfusion images.1–​3,109 Yet, it is important to emphasize the strong dependence of MFR on blood flow at rest. An unusually low flow may raise the MFR above the threshold of greater than 2 even when the hyperemic flow response is greatly reduced. Conversely, an elevated flow at rest, as for example seen in patients with hypertension, may yield an abnormally low

 

Figure 9.12  Age and MBF at rest and stress and MFR. Flows in this study were measured with the O-​15 water technique in three age groups of patients

without evidence of obstructive coronary artery disease. Hyperemic flows and flow reserves were significantly reduced in the oldest age group  Data plotted from Danad et al 101

flow reserve even if hyperemic flows were in the normal range. In these situations, correction of the MBF at rest for cardiac work (or RPP) may alleviate the undue effect of an abnormal rest on the flow reserve, even though it might be argued that the flow does contain predictive information that is relevant for the assessment of cardiac risk. Alternatively, the cardiac risk indicated by MFR should further be evaluated within the context of flow achieved during vasodilator stress as employed in a risk assessment strategy that includes the “coronary flow capacitance” as an arbitrator for resolving disparities between risk predictors.110 S UM M A RY AN D O UTLO O K PET measurements of MBF enhance and broaden the diagnostic capability of MPI and improve risk stratification of patients with suspected or angiographically documented coronary disease. Not only do quantitative flows ascertain the adequacy of hyperemic responses to pharmacologic vasodilation, they also uncover the presence of main left or of triple-​vessel disease that frequently remain unappreciated on standard myocardial perfusion images. Importantly, quantification of hyperemic flows contributes to a more comprehensive assessment of functional consequences of discrete stenoses or of diffuse nonobstructive disease of the epicardial conduit vessels. Most remarkable, however, is the potential 204

of quantitative flows for identifying abnormalities at the level of the coronary microcirculation that largely escape detection by most other diagnostic tools. It is this particular still largely unexplored component of the coronary circulatory system that is likely to benefit most from quantitative flow measurements in terms of underlying pathophysiology, targets of treatment, and assessment of therapeutic efficacy. The clinical acceptance of PET flow measurements has been accompanied by an increasing availability of highly sophisticated and robust analysis software packages. Estimates of flow derived with different software packages generally but not always agree, so that use of a particular software package may affect the risk classification. This then mandates standardization of quantitative flow measurements that can become universally accepted and comparable across institutions. Finally, improvements in accuracy of regional, global, and transmural myocardial flows are likely with further advances in imaging devices, image reconstruction, and image analysis. R E F E R E NC E S 1. Herzog BA, Husmann L, Valenta I, et al. Long-​term prognostic value of 13N-​ammonia myocardial perfusion positron emission tomography added value of coronary flow reserve. J Am Coll Cardiol. 2009;54(2):150–​156. 2. Murthy VL, Naya M, Foster CR, et al. Improved cardiac risk assessment with noninvasive measures of coronary flow reserve. Circulation. 2011;124(20):2215–​2224.

 

3. Ziadi MC, Dekemp RA, Williams KA, et al. Impaired myocardial flow reserve on rubidium-​82 positron emission tomography imaging predicts adverse outcomes in patients assessed for myocardial ischemia. J Am Coll Cardiol. 2011;58(7):740–​748. 4. Gebhard C, Fiechter M, Herzog BA, et al. Sex differences in the long-​term prognostic value of (13)N-​ammonia myocardial perfusion positron emission tomography. Eur J Nucl Med Mol Imaging. 2018;45(11):1964–​1974. 5. Klein R, Beanlands RS, deKemp RA. Quantification of myocardial blood flow and flow reserve: Technical aspects. J Nucl Cardiol. 2010;17(4):555–​570. 6. Moody JB, Lee BC, Corbett JR, et al. Precision and accuracy of clinical quantification of myocardial blood flow by dynamic PET: A technical perspective. J Nucl Cardiol. 2015;22(5):935–​951. 7. Murthy VL, Bateman TM, Beanlands RS, et al. Clinical quantification of myocardial blood flow using PET: Joint position paper of the SNMMI Cardiovascular Council and the ASNC. J Nucl Med. 2018;59(2):273–​293. 8. Bergmann SR, Herrero P, Markham J, et al. Noninvasive quantitation of myocardial blood flow in human subjects with oxygen-​ 15-​labeled water and positron emission tomography. J Am Coll Cardiol. 1989;14(3):639–​652. 9. Danad I, Uusitalo V, Kero T, et al. Quantitative assessment of myocardial perfusion in the detection of significant coronary artery disease: Cutoff values and diagnostic accuracy of quantitative [(15)O] H2O PET imaging. J Am Coll Cardiol. 2014;64(14):1464–​1475. 10. Harms HJ, Nesterov SV, Han C, et al. Comparison of clinical non-​ commercial tools for automated quantification of myocardial blood flow using oxygen-​15-​labelled water PET/​CT. Eur Heart Journal Cardiovasc Imaging. 2014;15(4):431–​441. 11. Gerber BL, Melin JA, Bol A, et al. Nitrogen-​13-​ammonia and oxygen-​ 15-​water estimates of absolute myocardial perfusion in left ventricular ischemic dysfunction. J Nucl Med. 1998;39(10):1655–​1662. 12. Schelbert HR, Phelps ME, Huang SC, et al. N-​13 ammonia as an indicator of myocardial blood flow. Circulation. 1981;63(6):1259–​1272. 13. Renkin EM. Transport of potassium-​42 from blood to tissue in isolated mammalian skeletal muscles. Am J Physiol. 1959;197:1205–​1210. 14. Crone C. The permeability of capillaries in various organs as determined by use of the “indicator diffusion” method. Acta Physiol Scand. 1963;58:292–​305. 15. Benz DC, Ferro P, Safa N, et al. Role of quantitative myocardial blood flow and (13)N-​ammonia washout for viability assessment in ischemic cardiomyopathy. J Nucl Cardiol. 2021;28(1):263–​273. 16. Pieper J, Patel VN, Escolero S, et al. Initial clinical experience of N13-​ ammonia myocardial perfusion PET/​CT using a compact superconducting production system. J Nucl Cardiol. 2021;28(1):295–​299. 17. Huang SC, Williams BA, Krivokapich J, et al. Rabbit myocardial 82Rb kinetics and a compartmental model for blood flow estimation. Am J Physiol. 1989;256(4 Pt 2):H1156–​H1164. 18. Goldstein RA, Mullani NA, Marani SK, et al. Myocardial perfusion with rubidium-​82. II. Effects of metabolic and pharmacologic interventions. J Nucl Med. 1983;24(10):907–​915. 19. Mullani NA, Goldstein RA, Gould KL, et al. Myocardial perfusion with rubidium-​82. I. Measurement of extraction fraction and flow with external detectors. J Nucl Med. 1983;24(10):898–​906. 20. Gould KL, Yoshida K, Hess MJ, et al. Myocardial metabolism of fluorodeoxyglucose compared to cell membrane integrity for the potassium analogue rubidium-​82 for assessing infarct size in man by PET. J Nucl Med. 1991;32(1):1–​9. 21. vom Dahl J, Muzik O, Wolfe ER, Jr., et al. Myocardial rubidium-​82 tissue kinetics assessed by dynamic positron emission tomography as a marker of myocardial cell membrane integrity and viability. Circulation. 1996;93(2):238–​245. 22. Moody JB, Hiller KM, Lee BC, et al. The utility of (82)Rb PET for myocardial viability assessment: Comparison with

M B F M easurement by P E T

perfusion-​metabolism (82)Rb-​(18)F-​FDG PET. J Nucl Cardiol. 2019;26(2):374–​386. 23. Huisman MC, Higuchi T, Reder S, et al. Initial characterization of an 18F-​labeled myocardial perfusion tracer. J Nucl Med. 2008;49(4):630–​636. 24. Nekolla SG, Reder S, Saraste A, et al. Evaluation of the novel myocardial perfusion positron-​emission tomography tracer 18F-​BMS-​ 747158–​02: comparison to 13N-​ammonia and validation with microspheres in a pig model. Circulation. 2009;119(17):2333–​2342. 25. Sherif HM, Nekolla SG, Saraste A, et al. Simplified quantification of myocardial flow reserve with flurpiridaz F 18: Validation with microspheres in a pig model. J Nucl Med. 2011;52(4):617–​624. 26. Packard RR, Huang SC, Dahlbom M, et al. Absolute quantitation of myocardial blood flow in human subjects with or without myocardial ischemia using dynamic flurpiridaz F 18 PET. J Nucl Med. 2014;55(9):1438–​1444. 27. Maddahi J, Bengel F, Czernin J, et al. Dosimetry, biodistribution, and safety of flurpiridaz F 18 in healthy subjects undergoing rest and exercise or pharmacological stress PET myocardial perfusion imaging. J Nucl Cardiol. 2019;26(6):2018–​2030. 28. Maddahi J, Czernin J, Lazewatsky J, et al. Phase I, first-​in-​human study of BMS747158, a novel 18F-​labeled tracer for myocardial perfusion PET: Dosimetry, biodistribution, safety, and imaging characteristics after a single injection at rest. J Nucl Med. 2011;52(9):1490–​1498. 29. Berman DS, Maddahi J, Tamarappoo BK, et al. Phase II safety and clinical comparison with single-​photon emission computed tomography myocardial perfusion imaging for detection of coronary artery disease: Flurpiridaz F 18 positron emission tomography. J Am Coll Cardiol. 2013;61(4):469–​477. 30. Maddahi J, Lazewatsky J, Udelson JE, et al. Phase-​III clinical trial of fluorine-​18 flurpiridaz positron emission tomography for evaluation of coronary artery disease. J Am Coll Cardiol. 2020;76(4):391–​401. 31. Huang SC, Schwaiger M, Carson RE, et al. Quantitative measurement of myocardial blood flow with oxygen-​15 water and positron computed tomography: An assessment of potential and problems. J Nucl Med. 1985;26(6):616–​625. 32. Krivokapich J, Smith GT, Huang SC, et al. 13N ammonia myocardial imaging at rest and with exercise in normal volunteers: Quantification of absolute myocardial perfusion with dynamic positron emission tomography. Circulation. 1989;80(5):1328–​1337. 33. Choi Y, Huang SC, Hawkins RA, et al. Quantification of myocardial blood flow using 13N-​ammonia and PET: Comparison of tracer models. J Nucl Med. 1999;40(6):1045–​1055. 34. El Fakhri G, Kardan A, Sitek A, et al. Reproducibility and accuracy of quantitative myocardial blood flow assessment with (82) Rb PET: Comparison with (13)N-​ammonia PET. J Nucl Med. 2009;50(7):1062–​1071. 35. El Fakhri G, Sitek A, Guerin B, et al. Quantitative dynamic cardiac 82Rb PET using generalized factor and compartment analyses. J Nucl Med. 2005;46(8):1264–​1271. 36. Lortie M, Beanlands RS, Yoshinaga K, et al. Quantification of myocardial blood flow with 82Rb dynamic PET imaging. Eur J Nucl Med Mol Imaging. 2007;34(11):1765–​1774. 37. Moody JB, Poitrasson-​Rivière A, Hagio T, et al. Added value of myocardial blood flow using (18)F-​flurpiridaz PET to diagnose coronary artery disease: The flurpiridaz 301 trial. J Nucl Cardiol. 2021;28(5):2313–​2329. 38. Johnson NP, Gould KL. Regadenoson versus dipyridamole hyperemia for cardiac PET imaging. JACC Cardiovascular imaging. 2015;8(4):438–​447. 39. Hoffman EJ, Huang SC, Phelps ME. Quantitation in positron emission computed tomography: 1. Effect of object size. J Comput Assist Tomogr. 1979;3(3):299–​308. 40. Lance Gould K, Bui L, Kitkungvan D, et al. Pitfalls in quantitative myocardial PET perfusion I: Myocardial partial volume correction. J Nucl Cardiol. 2020;27(2):386–​396.

 

41. Brunken RC, Perloff JK, Czernin J, et al. Myocardial perfusion reserve in adults with cyanotic congenital heart disease. Am J Physiol Heart Circ Physiol. 2005;289(5):H1798–​H1806. 42. Hutchins GD, Schwaiger M, Rosenspire KC, et al. Noninvasive quantification of regional blood flow in the human heart using N-​13 ammonia and dynamic positron emission tomographic imaging. J Am Coll Cardiol. 1990;15(5):1032–​1042. 43. Hutchins GD, Caraher JM, Raylman RR. A region of interest strategy for minimizing resolution distortions in quantitative myocardial PET studies. J Nucl Med. 1992;33(6):1243–​1250. 44. Turco A, Nuyts J, Duchenne J, et al. Analysis of partial volume correction on quantification and regional heterogeneity in cardiac PET. J Nucl Cardiol. 2020;27(1):62–​70. 45. Robson PM, Dey D, Newby DE, et al. MR/​PET imaging of the cardiovascular system. JACC Cardiovasc Imaging. 2017;10(10 Pt A):1165–​1179. 46. Iida H, Rhodes CG, de Silva R, et al. Myocardial tissue fraction correction for partial volume effects and measure of tissue viability. J Nucl Med. 1991;32(11):2169–​2175. 47. Iida H, Takahashi A, Tamura Y, et al. Myocardial blood flow: Comparison of oxygen-​15-​water bolus injection, slow infusion and oxygen-​15-​carbon dioxide slow inhalation. J Nucl Med. 1995;36(1):78–​85. 48. Iida H, Tamura Y, Kitamura K, et al. Histochemical correlates of (15)O-​water-​perfusable tissue fraction in experimental canine studies of old myocardial infarction. J Nucl Med. 2000;41(10):1737–​1745. 49. Levin CS, Hoffman EJ. Calculation of positron range and its effect on the fundamental limit of positron emission tomography system spatial resolution. Physics Med Biol. 1999;44(3):781–​799. 50. Schelbert HR, Dahlbom M. A good beginning with an uncertain future. J Nucl Cardiol. 2019;26(3):810–​813. 51. Moody JB, Ficaro EP, Murthy VL. Simplified quantification of PET myocardial blood flow: The need for technical standardization. J Nucl Cardiol. 2020;27(3):829–​832. 52. Kuhle WG, Porenta G, Huang SC, et al. Quantification of regional myocardial blood flow using 13N-​ammonia and reoriented dynamic positron emission tomographic imaging. Circulation. 1992;86(3):1004–​1017. 53. Muzik O, Beanlands RS, Hutchins GD, et al. Validation of nitrogen-​ 13-​ammonia tracer kinetic model for quantification of myocardial blood flow using PET. J Nucl Med. 1993;34(1):83–​91. 54. Rosenspire KC, Schwaiger M, Mangner TJ, et al. Metabolic fate of [13N]ammonia in human and canine blood. J Nucl Med. 1990;31(2):163–​167. 55. Keiding S, Sørensen M, Munk OL, Bender D. Human (13) N-​ammonia PET studies: The importance of measuring (13)N-​ ammonia metabolites in blood. Metab Brain Dis. 2010;25(1):49–​56. 56. Bellina CR, Parodi O, Camici P, et al. Simultaneous in vitro and in vivo validation of nitrogen-​13-​ammonia for the assessment of regional myocardial blood flow. J Nucl Med. 1990;31(8):1335–​1343. 57. Nienaber CA, Ratib O, Gambhir SS, et al. A quantitative index of regional blood flow in canine myocardium derived noninvasively with N-​13 ammonia and dynamic positron emission tomography. J Am Coll Cardiol. 1991;17(1):260–​269. 58. Yoshida K, Mullani N, Gould KL. Coronary flow and flow reserve by PET simplified for clinical applications using rubidium-​82 or nitrogen-​13-​ammonia. J Nucl Med. 1996;37(10):1701–​1712. 59. Chang CY, Hung GU, Hsu B, et al. Simplified quantification of (13) N-​ammonia PET myocardial blood flow: A comparative study with the standard compartment model to facilitate clinical use. J Nucl Cardiol. 2020;27(3):819–​828. 60. Bergmann SR, Fox KA, Rand AL, et al. Quantification of regional myocardial blood flow in vivo with H215O. Circulation. 1984;70(4):724–​733. 61. Lautamaki R, George RT, Kitagawa K, et al. Rubidium-​82 PET-​CT for quantitative assessment of myocardial blood flow: Validation

206

in a canine model of coronary artery stenosis. Eur J Nucl Med Mol Imaging. 2009;36(4):576–​586. 62. Nitzsche EU, Choi Y, Czernin J, et al. Noninvasive quantification of myocardial blood flow in humans: A direct comparison of the [13N]ammonia and the [15O]water techniques. Circulation. 1996;93(11):2000–​2006. 63. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–​310. 64. Klein R, Ocneanu A, Renaud JM, et al. Consistent tracer administration profile improves test-​retest repeatability of myocardial blood flow quantification with (82)Rb dynamic PET imaging. J Nucl Cardiol. 2018;25(3):929–​941. 65. Hove JD, Iida H, Kofoed KF, et al. Left atrial versus left ventricular input function for quantification of the myocardial blood flow with nitrogen-​13 ammonia and positron emission tomography. Eur J Nucl Med Mol Imaging. 2004;31(1):71–​76. 66. Klein R, Renaud JM, Ziadi MC, et al. Intra-​ and inter-​operator repeatability of myocardial blood flow and myocardial flow reserve measurements using rubidium-​82 pet and a highly automated analysis program. J Nucl Cardiol. 2010;17(4):600–​616. 67. Nagamachi S, Czernin J, Kim AS, et al. Reproducibility of measurements of regional resting and hyperemic myocardial blood flow assessed with PET. J Nucl Med. 1996;37(10):1626–​1631. 68. Kitkungvan D, Johnson NP, Roby AE, et al. Routine clinical quantitative rest stress myocardial perfusion for managing coronary artery disease: Clinical relevance of test-​retest variability. JACC Cardiovasc Imaging. 2017;10(5):565–​577. 69. Koenders SS, van Dijk JD, Jager PL, et al. How to detect and correct myocardial creep in myocardial perfusion imaging using Rubidium-​ 82 PET? J Nucl Cardiol. 2019;26(3):729–​734. 70. Otaki Y, Lassen ML, Manabe O, et al. Short-​term repeatability of myocardial blood flow using (82)Rb PET/​CT: The effect of arterial input function position and motion correction. J Nucl Cardiol. 2021;28(4):1718–​1725. 71. Poitrasson-​Rivière A, Murthy VL. Optimizing accuracy and precision with motion correction of PET myocardial blood flow measurements. J Nucl Cardiol. 2021;28(4):1726–​1729. 72. Dekemp RA, Declerck J, Klein R, et al. Multisoftware reproducibility study of stress and rest myocardial blood flow assessed with 3D dynamic PET/​CT and a 1-​tissue-​compartment model of 82Rb kinetics. J Nucl Med. 2013;54(4):571–​577. 73. Nesterov SV, Deshayes E, Sciagrà R, et al. Quantification of myocardial blood flow in absolute terms using (82)Rb PET imaging: The RUBY-​10 Study. JACC Cardiovasc Imaging. 2014;7(11):1119–​1127. 74. Tahari AK, Lee A, Rajaram M, et al. Absolute myocardial flow quantification with (82)Rb PET/​CT: Comparison of different software packages and methods. Eur J Nucl Med Mol Imaging. 2014;41(1):126–​135. 75. Oliveira JB, Sen YM, Wechalekar K. Intersoftware variability impacts classification of cardiac PET exams. J Nucl Cardiol. 2019;26(6):2007–​2012. 76. Armstrong IS, Tonge CM, Arumugam P. Impact of point spread function modeling and time-​of-​flight on myocardial blood flow and myocardial flow reserve measurements for rubidium-​82 cardiac PET. J Nucl Cardiol. 2014;21(3):467–​474. 77. Hsu DFC, Ilan E, Peterson WT, et al. Studies of a next-​generation silicon-​photomultiplier-​based time-​of-​flight PET/​CT system. J Nucl Med. 2017;58(9):1511–​1518. 78. Koenders SS, van Dalen JA, Jager PL, et al. Value of SiPM PET in myocardial perfusion imaging using Rubidium-​82. J Nucl Cardiol. 2022;29(1):204–​212. 79. Gould KL, Pan T, Loghin C, Johnson NP, et al. Frequent diagnostic errors in cardiac PET/​CT due to misregistration of CT attenuation and emission PET images: A definitive analysis of causes, consequences, and corrections. J Nucl Med. 2007;48(7):1112–​1121.

 

80. Martinez-​Möller A, Souvatzoglou M, Navab N, et al. Artifacts from misaligned CT in cardiac perfusion PET/​CT studies: Frequency, effects, and potential solutions. J Nucl Med. 2007;48(2):188–​193. 81. Rajaram M, Tahari AK, Lee AH, et al. Cardiac PET/​CT misregistration causes significant changes in estimated myocardial blood flow. J Nucl Med. 2013;54(1):50–​54. 82. Renaud JM, Wu KY, Gardner K, et al. Saline-​push improves rubidium-​ 82 PET image quality. J Nucl Cardiol. 2019;26(6):1869–​1874. 83. Vasquez AF, Johnson NP, Gould KL. Variation in quantitative myocardial perfusion due to arterial input selection. JACC Cardiovasc Imaging. 2013;6(5):559–​568. 84. Rubeaux M, Doris MK, Alessio A, Slomka PJ. Enhancing cardiac PET by motion correction techniques. Curr Cardiol Rep. 2017;19(2):14. 85. Lee BC, Moody JB, Poitrasson-​Rivière A, et al. Automated dynamic motion correction using normalized gradient fields for (82)rubidium PET myocardial blood flow quantification. J Nucl Cardiol. 2020;27(6):1982–​1998. 86. Piccinelli M, Votaw JR, Garcia EV. Motion correction and its impact on absolute myocardial blood flow measures with PET. Curr Cardiol Rep. 2018;20(5):34. 87. Böttcher M, Czernin J, Sun KT, et al. Effect of caffeine on myocardial blood flow at rest and during pharmacological vasodilation. J Nucl Med. 1995;36(11):2016–​2021. 88. Kubo S, Tadamura E, Toyoda H, et al. Effect of caffeine intake on myocardial hyperemic flow induced by adenosine triphosphate and dipyridamole. J Nucl Med. 2004;45(5):730–​738. 89. Kitkungvan D, Bui L, Johnson NP, et al. Quantitative myocardial perfusion positron emission tomography and caffeine revisited with new insights on major adverse cardiovascular events and coronary flow capacity. Eur Heart J Cardiovasc Imaging. 2019;20(7):751–​762. 90. Campisi R, Czernin J, Schoder H, et al. Effects of long-​term smoking on myocardial blood flow, coronary vasomotion, and vasodilator capacity. Circulation. 1998;98(2):119–​125. 91. Czernin J, Sun K, Brunken R, et al. Effect of acute and long-​term smoking on myocardial blood flow and flow reserve. Circulation. 1995;91(12):2891–​2897. 92. Quillen JE, Rossen JD, Oskarsson HJ, et al. Acute effect of cigarette smoking on the coronary circulation: Constriction of epicardial and resistance vessels. J Am Coll Cardiol. 1993;22(3):642–​647. 93. Zevin S, Gourlay SG, Benowitz NL. Clinical pharmacology of nicotine. Clin Dermatol. 1998;16(5):557–​564. 94. Gould KL, Johnson NP, Bateman TM, et al. Anatomic versus physiologic assessment of coronary artery disease: Role of coronary flow reserve, fractional flow reserve, and positron emission tomography imaging in revascularization decision-​making. J Am Coll Cardiol. 2013;62(18):1639–​1653. 95. Sdringola S, Johnson NP, Kirkeeide RL, et al. Impact of unexpected factors on quantitative myocardial perfusion and coronary flow reserve in young, asymptomatic volunteers. JACC Cardiovasc Imaging. 2011;4(4):402–​412.

M B F M easurement by P E T

96. Krivokapich J, Stevenson LW, Kobashigawa J, et al. Quantification of absolute myocardial perfusion at rest and during exercise with positron emission tomography after human cardiac transplantation. J Am Coll Cardiol. 1991;18(2):512–​517. 97. Czernin J, Muller P, Chan S, et al. Influence of age and hemodynamics on myocardial blood flow and flow reserve. Circulation. 1993;88(1):62–​69. 98. Gewirtz H, Dilsizian V. Integration of quantitative positron emission tomography absolute myocardial blood flow measurements in the clinical management of coronary artery disease. Circulation. 2016;133(22):2180–​2196. 99. Johnson NP, Gould KL. Physiological basis for angina and ST-​ segment change PET-​verified thresholds of quantitative stress myocardial perfusion and coronary flow reserve. JACC Cardiovasc Imaging. 2011;4(9):990–​998. 100. Duvernoy CS, Meyer C, Seifert-​Klauss V, et al. Gender differences in myocardial blood flow dynamics: Lipid profile and hemodynamic effects. J Am Coll Cardiol. 1999;33(2):463–​470. 101. Danad I, Raijmakers PG, Appelman YE, et al. Coronary risk factors and myocardial blood flow in patients evaluated for coronary artery disease: A quantitative [15O]H2O PET/​CT study. Eur J Nucl Med Mol Imaging. 2012;39(1):102–​112. 102. Sunderland JJ, Pan XB, Declerck J, Menda Y. Dependency of cardiac rubidium-​82 imaging quantitative measures on age, gender, vascular territory, and software in a cardiovascular normal population. J Nucl Cardiol. 2015;22(1):72–​84. 103. Range FT, Kies P, Schäfers KP, et al. Sex differences in absolute myocardial perfusion: Non-​invasive H2(15)O-​PET in young healthy adults. Nuklearmedizin Nucl Med. 2016;55(5):196–​202. 104. Senneff MJ, Geltman EM, Bergmann SR. Noninvasive delineation of the effects of moderate aging on myocardial perfusion. J Nucl Med. 1991;32(11):2037–​2042. 105. Uren NG, Camici PG, Melin JA, et al. Effect of aging on myocardial perfusion reserve. J Nucl Med. 1995;36(11):2032–​2036. 106. Dayanikli F, Grambow D, Muzik O, et al. Early detection of abnormal coronary flow reserve in asymptomatic men at high risk for coronary artery disease using positron emission tomography. Circulation. 1994;90(2):808–​817. 107. Murthy VL, Naya M, Foster CR, et al. Association between coronary vascular dysfunction and cardiac mortality in patients with and without diabetes mellitus. Circulation. 2012;126(15):1858–​1868. 108. Patel KK, Spertus JA, Chan PS, et al. Extent of myocardial ischemia on positron emission tomography and survival benefit with early revascularization. J Am Coll Cardiol. 2019;74(13):1645–​1654. 109. Naya M, Murthy VL, Taqueti VR, et al. Preserved coronary flow reserve effectively excludes high-​risk coronary artery disease on angiography. J Nucl Med. 2014;55(2):248–​255. 110. Johnson NP, Gould KL. Integrating noninvasive absolute flow, coronary flow reserve, and ischemic thresholds into a comprehensive map of physiological severity. JACC Cardiovasc Imaging. 2012;5(4):430–​440.

 

10. MEASUREMENT OF MYOCARDIAL BLOOD FLOW BY SPECT Juliana Brenande de Oliveira Brito, Gary R. Small, Kathryn J. Ascah, R. Glenn Wells, and Terrence D. Ruddy

K EY P OINTS 1. Sensitivity for detection of obstructive CAD improves with the addition of stress MBF and MFR to relative MPI. Specificity may decrease depending on the threshold chosen for sensitivity and the presence of diffuse mild CAD and microvascular disease. 2. The addition of SPECT MBF measurement to routine SPECT MPI may greatly increase the use of MBF with MPI. 3. Measurement of stress MBF is important to confirm the adequacy of the hyperemic response to pharmacologic stress. 4. New dedicated camera systems using solid-​state CZT crystals and new collimator designs permit dynamic imaging with high temporal resolution and better count density. These camera systems make SPECT MBF measurement much more possible and practical. 5. The accuracy of CZT SPECT measurement of MBF and MFR has been validated in a preclinical porcine study with very good microsphere MBF correlations and in clinical studies with comparisons to angiographic and PET data. 6. Reduced global stress MBF and MFR may identify the presence of high-​risk MVD, which is uncommon in patients with preserved stress MBF and MFR. 7. Regional reductions in stress MBF and MFR have high diagnostic accuracy for specific vessel CAD. 8. Reduced global and regional SPECT MFR may predict reduced global and regional PET MFR.

9. SPECT measurement of MBF and MFR has good day-​to-​day repeatability and interobserver variability. 10. Multicenter studies are necessary to better define the diagnostic value of CZT SPECT MBF for evaluation of patients with suspected or known CAD and the incremental prognostic value of SPECT MBF measurement compared to relative MPI. AB B R E V IAT IONS AC ATP AUC BB CAD CCS CHF CT COV CZT ECG EF eGFR FFR LAD LCX LITA LV MBF MBq MC MFR

attenuation correction adenosine triphosphate area under the ROC curve red blood cell binding correction coronary artery disease Canadian Cardiovascular Society congestive heart failure computed tomography coefficient of variation cadmium-​zinc-​telluride electrocardiogram ejection fraction estimated glomerular filtration rate fractional flow reserve left anterior descending coronary artery left circumflex coronary artery left internal thoracic artery left ventricle myocardial blood flow megabecquerel morion corection myocardial flow reserve

 

MI MPI mSv MVD NSTEMI PET RCA ROC SPECT

myocardial infarction myocardial perfusion imaging millisievert multivessel CAD non-​ST-​elevation myocardial infarction positron emission tomography right coronary artery receiver operating curve single-​photon emission computed tomography SSS summed stress score SYNTAX synergy between percutaneous coronary intervention with Taxus and cardiac surgery score INTRODUCTI O N CLINICAL IMPORTANCE OF MEASUREMENT OF MBF AND MFR WITH MPI

Conventional stress MPI is widely used for diagnosis and for determining prognosis in patients with suspected or known CAD. However, a major limitation of MPI is the use of relative perfusion, which is the comparison of a specific region to the region with the highest radiotracer uptake and presumed to have normal perfusion. This “normal” region may have reduced perfusion, as in patients with severe multivessel CAD, and may lead to underestimation of the extent of obstructive CAD, particularly with SPECT MPI.1–​4 To offset this limitation, MBF and MFR can be measured with PET and provide additional diagnostic and prognostic value over relative PET MPI for obstructive CAD.5 Sensitivity for obstructive CAD improves with the addition of stress MBF and MFR to PET relative to MPI. Specificity may decrease depending on the threshold chosen for sensitivity and the presence of diffuse mild CAD and microvascular disease.5 Similarly, SPECT measurement of MBF may improve the clinical value of SPECT MPI with improved diagnosis of obstructive CAD based on reduced global or regional MBF and better risk stratification with MFR. NEED FOR SPECT MEASUREMENT OF MBF

Clinical MBF measurements with PET are available in larger centers, are well validated, and are now reimbursed in the United States by the Centers of Medicare and Medicaid Services as a Category 1 add-​on code for a PET MPI study.

M B F M easurement by S P E C T

Still, PET is less widely used for MPI (