Fluence-Based and Microdosimetric Event-Based Methods for Radiation Protection in Space (Ncrp Report, No. 137) 0929600703, 9780929600703, 9781429498913

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NCRP Report No. 137

Fluence-Based and Microdosimetric Event-Based Methods for Radiation Protection in Space

Recommendations of the NATIONAL COUNCIL ON RADIATION PROTECTION AND MEASUREMENTS

Issued August 24, 2001

National Council on Radiation Protection and Measurements 7910 Woodmont Avenue, Suite 800 / Bethesda, Maryland 20814

LEGAL NOTICE This Report was prepared by the National Council on Radiation Protection and Measurements (NCRP). The Council strives to provide accurate, complete and useful information in its documents. However, neither the NCRP, the members of NCRP, other persons contributing to or assisting in the preparation of this Report, nor any person acting on the behalf of any of these parties: (a) makes any warranty or representation, express or implied, with respect to the accuracy, completeness or usefulness of the information contained in this Report, or that the use of any information, method or process disclosed in this Report may not infringe on privately owned rights; or (b) assumes any liability with respect to the use of, or for damages resulting from the use of any information, method or process disclosed in this Report, under the Civil Rights Act of 1964, Section 701 et seq. as amended 42 U.S.C. Section 2000e et seq. (Title VII) or any other statutory or common law theory governing liability.

Library of Congress Cataloging-in-Publication Data Fluence-based and microdosimetric event-based methods for radiation protection in space. p. ; cm. — (NCRP report ; no. 137) ‘‘August 2001.’’ Prepared by the Scientific Committee 88 on Fluence as the Basis for a Radiation Protection System for Astronauts. Includes bibliographical references and index. ISBN 0-929600-70-3 1. Extraterrestrial radiation—Safety measures. 2. Radiation dosimetry. 3. Microdosimetry. 4. Manned space flight—Safety measures. I. National Council on Radiation Protection and Measurements. Scientific Committee 88 on Fluence as the Basis for a Radiation Protection System for Astronauts. II. Series. [DNLM: 1. Radiation Protection—methods. 2. Aerospace Medicine. 3. Astronauts. 4. Extraterrestrial Environment. 5. Space Flight. WN 650 F646 2001] RC1151.R33F59 2001 616.9⬘80214—dc21 2001044184

Copyright © National Council on Radiation Protection and Measurements 2001 All rights reserved. This publication is protected by copyright. No part of this publication may be reproduced in any form or by any means, including photocopying, or utilized by any information storage and retrieval system without written permission from the copyright owner, except for brief quotation in critical articles or reviews.

[For detailed information on the availability of NCRP publications see page 101.]

Preface In NCRP Report No. 98, Guidance on Radiation Received in Space Activities (NCRP, 1989), the Council applied the conventional metric at the time of modifying the absorbed dose with a quality factor (Q) based on the Q/LET relationship given in ICRP Publication 26, Recommendations of the International Commission on Radiological Protection (ICRP, 1977). In this Report, more recent guidance from NCRP Report No. 116, Limitation of Exposure to Ionizing Radiation (NCRP, 1993) and NCRP Report No. 132, Radiation Protection Guidance for Activities in Low-Earth Orbit (NCRP, 2000) on the methodology for estimating equivalent dose and effective dose is reviewed together with a fluencebased and a microdosimetric event-based approach to the radiation exposures of astronauts on extended missions. The strengths, weaknesses, and degree of difficulty in implementing the three approaches are presented. The partial support provided by the National Aeronautics and Space Administration for the completion of this work is sincerely appreciated. Serving on Scientific Committee 88 on Fluence as the Basis for a Radiation Protection System for Astronauts were: Stanley B. Curtis, Chairman Fred Hutchinson Cancer Research Center Seattle, Washington Members Leslie A. Braby Texas A&M University College Station, Texas

Peter G. Groer University of Tennessee Knoxville, Tennessee

John F. Dicello Johns Hopkins Oncology Center Baltimore, Maryland

Warren K. Sinclair National Council on Radiation Protection and Measurements Bethesda, Maryland

Michael N. Gould University of Wisconsin Madison, Wisconsin

Marco A. Zaider Memorial Sloan-Kettering Cancer Center New York, New York iii

iv

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PREFACE

Advisor R.J. Michael Fry Indianapolis, Indiana NCRP Secretariat Marvin Rosenstein, Consultant (2000–2001) Jonelle K. Drugan, Visiting Staff Scientist (1999–2000) Eric E. Kearsley, Staff Scientist (1998–1999) William M. Beckner, Senior Staff Scientist (1991–1998) Cindy L. O’Brien, Managing Editor The Council wishes to express its appreciation to the Committee members for the time and effort devoted to the preparation of this Report.

Charles B. Meinhold President

Contents Preface ........................................................................................

iii

1. Summary ...............................................................................

1

2. Introduction ......................................................................... 2.1 The Radiation of Space ................................................. 2.2 Particle-Traversal Frequencies .................................... 2.3 Microdosimetric-Event Frequencies ............................. 2.4 Various Types of Radiation Field Descriptors and Their Relationship to Risk Estimation ........................ 2.5 Variation of Risk with Other Quantities ..................... 2.6 Content of the Report ...................................................

2 2 4 4

3. Conventional Method for Assessing Risk from the Mixed High and Low Linear Energy-Transfer Radiation Environment in Space ................................... 3.1 Conventional Procedure ................................................ 3.2 Total Cancer Risk and Cancer Tissue Weighting Factors ........................................................................... 3.3 Radiation Transport and Risk Calculations ................ 3.4 Limitations of the Conventional System ..................... 3.5 Applicability of the Conventional System ................... 4. Fluence-Based and Microdosimetric Event-Based Systems .................................................................................. 4.1 Fluence-Based Approach .............................................. 4.1.1 Introduction ........................................................ 4.1.2 Idealized Application of the Fluence-Based System ................................................................. 4.1.3 Relation to the Conventional System ................ 4.1.4 Low Linear Energy-Transfer Baseline Value of Risk Cross Section .......................................... 4.1.5 Treatment of Photons and Neutrons ................. 4.1.6 Strengths and Limitations ................................. 4.2 The Microdosimetric Event-Based Approach .............. 4.2.1 Introduction ........................................................ 4.2.2 Microdosimetric-Based Quality Functions ........ v

6 8 8

10 10 13 14 17 20

22 22 22 24 25 26 28 28 30 30 34

vi

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CONTENTS

4.2.3 Low Linear Energy-Transfer Baseline from the Hiroshima Data ............................................ 4.2.4 Strengths and Limitations ................................

37 38

5. Practical Aspects of Radiation Measurements ............ 5.1 Introduction ................................................................... 5.2 The Conventional Approach ......................................... 5.2.1 Introduction ........................................................ 5.2.2 Cavity Ion Dosimeters ........................................ 5.2.3 Thermoluminescent Dosimeters ........................ 5.2.4 Solid-State Nuclear Track Detectors ................. 5.2.5 Current Practice ................................................. 5.3 The Fluence-Based Approach ....................................... 5.3.1 Introduction ........................................................ 5.3.2 Charged-Particle Telescopes .............................. 5.3.3 Bubble Detectors ................................................. 5.3.4 Neutron Recoil Spectrometers ........................... 5.3.5 Solid-State Nuclear Track Detectors ................. 5.4 The Microdosimetric Event-Based Approach .............. 5.4.1 Introduction ....................................................... 5.4.2 Lineal-Energy Spectrometers ............................ 5.4.3 Variance Method for Measuring Dose-Mean Lineal Energy ..................................................... 5.5 Comparison of the Practical Limitations to Implement Each Methodology ......................................

40 40 40 40 41 42 42 43 43 43 44 45 45 46 46 46 46

6. The Biological Data Necessary ........................................ 6.1 Review of Available Data ............................................. 6.2 The Mouse Leukemia and the Rat Mammary Carcinoma Model Systems ........................................... 6.3 Experimental Design Considerations ..........................

50 50

7. Implementation and Comparison of Methods ............. 7.1 Introduction ................................................................... 7.2 Risk Assessment ............................................................ 7.3 The Fluence-Based System .......................................... 7.4 The Microdosimetric Event-Based System .................. 7.5 Comparison of Fluence-Based and Microdosimetric Event-Based Systems .................................................... 7.6 Comparison of All Three Methods for a Given Space Radiation Scenario ........................................................ 7.6.1 Introduction ........................................................ 7.6.2 Conventional Method ......................................... 7.6.3 Risk Cross-Section Approach ............................. 7.6.4 Microdosimetric Event-Based Approach ........... 7.6.5 Comparison of Risks ...........................................

48 49

52 54 56 56 56 57 60 61 64 64 65 67 71 76

CONTENTS

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vii

8. Conclusions, Recommendations and Suggestions for Future Research .................................................................. 8.1 Conclusions .................................................................... 8.2 Recommendations .......................................................... 8.3 Suggestions for Future Research .................................

79 79 81 81

Glossary ......................................................................................

82

References .................................................................................

85

The NCRP ..................................................................................

92

NCRP Publications .................................................................. 101 Index ........................................................................................... 111

1. Summary Long-term space missions of the future will subject space travelers to a unique radiation environment not experienced by Earth-bound populations. The space radiation environment is dominated by highenergy protons, helium ions, and to a lesser extent heavier ions. These particles are highly penetrating and many can traverse the shielding provided by the spacecraft and the self-shielding of the travelers’ bodies. This circumstance plus the nuclear fragmentation of those particles that do interact create a radiation environment containing a relatively large component of highly ionizing radiation. Because it is known that different biological effects can occur from different particles of the same linear energy transfer (LET), it was suggested that perhaps introducing another formulation allowing explicitly for the variation of risk with particle type as well as LET might provide advantage over the conventional treatment utilizing the singled-valued quality function versus LET formulation. This Report explores two possible methodologies to circumvent this problem, the fluence-based approach and the microdosimetric approach. A description of the methodologies is presented, and advantages and disadvantages of each are identified. The result of an analysis where each of the approaches was applied to the same idealized shielding situation in space revealed that under the specified conditions, the difference in the risk calculated by each was less than a factor of two. Because of the closeness of these results and our present lack of biological data in the region of high-energy high-LET radiation, it was concluded that the reason to move to another methodology at present is not compelling. It is suggested that as new data become available and dosimetric techniques become more refined, the question should be revisited and that in the future, significant improvement might be realized.

1

2. Introduction 2.1 The Radiation of Space High-energy protons and heavier atomic nuclei are the major contributors to the radiation environment in space. Since life on Earth is shielded from this radiation by the atmosphere and geomagnetic field, the space radiation dose rate at sea level is less than 10 percent of the natural background radiation to which man has always been exposed (UNSCEAR, 1988). However, a spacecraft operating outside Earth’s protective shielding will be bombarded by constant cosmic radiation, sporadic solar-particle radiation, and highly variable charged particle radiation from the trapped radiation belts. Many of these particles have such high energies that they easily penetrate spacecraft walls and can create secondary radiation such as neutrons in the walls and within the bodies of the space travelers. Effective shielding such as that provided by the atmosphere is not possible for a spacecraft for reasons of weight. Thus, a space traveler will encounter a different radiation environment than that prevalent on Earth to which radiation workers or members of the general population are exposed. The extent of radiation-induced biological damage to a given entity (i.e., a molecule, cell tissue, organ or organism) varies with the manner in which energy is transferred to it. Different types of ionizing particles are typically described by classifying them as to the value of the rate at which they lose energy as they pass through matter, i.e., their LET. This quantity is the mean energy loss per unit track length of matter traversed by the particle. Most biological effects vary strongly with the LET of the radiation causing them. To account for these variations, risk-related quantities are typically normalized by weighting them by factors that depend on the LET of the particles in the environment (see Sections 2.4 and 3.1). On Earth, ionizing radiation environments of concern comprise both high- and low-LET radiation. High-LET radiations from radon daughters are part of the natural background radiation of concern in mines and in some homes, while neutrons are important around reactors and to a lesser extent, around high-intensity and highenergy accelerators, as well as in the natural environment in 2

2.1 THE RADIATION OF SPACE

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3

high-flying aircraft. Low-LET radiations of most concern are gamma rays and x rays. All these radiations, however, ultimately manifest themselves within the body mainly as short-ranged charged particles. Electrons cause the damage in the case of low-LET radiation; recoil protons, alpha particles, and heavy nuclei cause the damage from neutrons; and alpha particles from the decay of radon progeny cause the major damage from radon inhalation. These charged particles travel very short distances in the human body. In space, on the other hand, the radiation environment consists of high-energy charged particles of many different types. Outside Earth’s magnetic field, space travelers will encounter galactic cosmic rays (GCR), which are comprised of roughly 87 percent protons, 12 percent helium ions, one percent high atomic number (Z) highenergy particles (HZE particles), and two percent electrons and positrons (e.g., Heinrich, 1994). HZE particles are rare within Earth’s magnetic field and have distinct biological effects (summarized in NAS/NRC, 1973; NCRP, 1989). There are more even-Z than odd-Z ions and there is significantly enhanced abundance of fully stripped iron (Z ⳱ 26) ions. The fluence rates and energy distributions of these ions also vary with solar activity. The major fraction of the energy deposited by charged particles is from atomic interactions including ionizations and excitations. Heavy charged particle tracks through tissue can be described as consisting of a central region of high-density energy deposition close to the trajectory (within tens of nanometers) and a larger region containing secondary electrons (delta rays) which can extend several micrometers around the trajectory. The particles also undergo nuclear interactions with mean free paths (i.e., mean distance between nuclear interactions) that, for the heavier particles, are on the order of the thickness of the expected spacecraft walls (⬃10 g cmⳮ2 in areal density)1 and body self-shielding. All initial particle-energy spectra peak at several hundred million electron volts (MeV) per nucleon (Simpson, 1983), and particle ranges are typically on the order of or greater than the thickness of the human body. Mean absorbed doses and organ dose equivalents (see Section 3.1) within the body can be estimated from measured abundances and energy distributions of incident particles using radiation transport codes to account for the slowing down and nuclear fragmentation caused by spacecraft walls and body self-shielding. Because of known differences in biological effect at the same LET (discussed in Section 3.4) and because these differences may be particularly 1

Thicknesses are given in this Report in terms of the areal density which is the product of the true thickness and the density of the material.

4

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2. INTRODUCTION

important for the high-energy high-LET particles found in the GCR of the space environment, it has been suggested that it might be appropriate to develop approaches, other than the conventional one, that take these differences explicitly into account to estimate risk from space radiation. The purpose of this Report is to explore the advantages and disadvantages of replacing the conventional method with other formulations using either a fluence-based system or an event-based (microdosimetric) system.

2.2 Particle-Traversal Frequencies From the perspective of a cell within the body, the radiation environment in space consists of a charged particle traversal through the cell, or perhaps a similar traversal through a neighboring cell, followed by long intervals of time between additional traversals. It has been estimated that for a typical shielding configuration, the track-traversal frequency through a 100 ␮m2 cell nucleus at solar minimum conditions outside the geomagnetosphere would be one proton every few days and one helium ion every month (Curtis and Letaw, 1989). Heavier particles traverse the given cell nucleus at even lower frequencies with, for example, a traversal from an iron ion occurring about once every 100 y. This corresponds very roughly to one iron ion per second hitting the surface of the body (assuming a body ‘‘cross-sectional area’’ of 0.3 m2) (Curtis, 1993). With a further assumption that each iron-ion track on the average traverses some 104 cells (i.e., has a range at the body surface of 10 cm, a very crude approximation, of course), this results in 104 cells being traversed by iron ions every second. Such a radiation environment lends itself to a description in terms of the fluence of particles at the point of interest. Fluence is defined in this Report as the quotient of dN by da where dN is the number of particles, excluding delta rays, incident on a sphere of cross-sectional area da. This is consistent with the definition for fluence given in ICRU Report 60 (ICRU, 1998) with delta rays excluded. Delta rays are excluded in this definition for convenience, but are accounted for, of course, in the measured biological effects from experiments which define the variation of risk with radiation quality.

2.3 Microdosimetric-Event Frequencies A microdosimetric event (also referred to as, in brief, event) denotes traversal of a region by a particle and/or its secondaries

2.3 MICRODOSIMETRIC-EVENT FREQUENCIES

/

5

with concomitant energy deposition in that region (ICRU, 1983). This definition recognizes the fact that energy depositions in a site (ionizations or excitations) that result from a charged particle traversing the site are spatially correlated; however, different events are generally statistically independent. There are two essential differences between the notions of a microdosimetric event and a particle traversal, as used in the preceding section. Firstly, particle traversal refers to the geometric intersection of a particle trajectory with a site, irrespective of whether energy deposition occurred in the site, although for a site-size 6 ␮m in diameter (i.e., a cell nucleus) any charged particle traversing the site will have high probability for producing an event. Secondly, fluence, defined as the number of particle traversals per unit area, may refer to arbitrarily chosen particle types; for instance, as in this Report, fluence can be defined for the heavy charged particles, i.e., primary and secondary protons and heavier, without including delta rays. In contrast, a microdosimetric event must include all statistically correlated energy transfers in the site, whether produced by the primary track, by nuclear secondaries, or by delta rays. For instance, a heavy charged particle traveling outside the cellular volume and injecting a secondary electron into the cell will count as one event associated with that heavy charged particle, but would not be considered a traversal of the cell by the heavy particle. Consequently, the sum of all events is directly related to the dose, but individual events do not provide a way to identify the charge or velocity of the particles that produced them. Most microdosimetric events associated with high-LET HZE particles of the kind found in the GCR spectrum result from traversals by low-LET secondary electrons, not from the traversal of the HZE particle itself. For instance, the mean number of events per unit dose within a given volume is related to zF, which is the frequencymean of the energy imparted per unit mass (i.e., the mean specific energy per event) within the site. At a given absorbed dose (D) the mean number of events within the site is D/zF. An illustration of the difference between the frequency of microdosimetric events and the number of traversals expected in a 10 ␮m diameter cell nucleus from two components in the GCR spectrum is given here. For a 250 MeV proton, zF ⳱ 0.0008 Gy, and for a 350 MeV amuⳮ1 iron ion, zF ⳱ 0.012 Gy (Zaider, 1997).2 Thus, assuming these energies as mean energies for each of these components of the GCR, an annual D of 0.12 Gy from protons yields 150 events 2

Zaider, M.A. (1997). Personal communication (Memorial Sloan-Kettering Cancer Center, New York).

6

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2. INTRODUCTION

per year and 0.004 Gy of iron ions yields 0.33 iron-ion events per year in the cell nucleus. For protons, this event frequency is close to the number of proton track traversals of a cell nucleus per year (Section 2.2); but for iron ions, it is 33 times larger than the number of iron-ion track traversals per cell nucleus. The difference is due to the large number of delta-ray events in the cell nucleus caused by passing iron ions whose primary trajectories do not actually traverse the cell nucleus.

2.4 Various Types of Radiation Field Descriptors and Their Relationship to Risk Estimation Risk (R) is defined here as the probability of a deleterious outcome incurred by a system (cell, tissue, organ) exposed to a given radiation environment. In general, biological effects and risk can be related to radiation fields. Using x to represent the physical quantity being used to describe the radiation fields: R⳱k

兰 ⑀(x) p(x) dx

(2.1)

where p(x) is a probability density function (i.e., the probability distribution of x), the kernel ⑀ (x) represents the probability of the biological effect at x, and k is a constant that converts the result of the integration to R.3 The purpose of this Report is to consider various physical quantities, as choices for x, for use in estimating R from radiation that is present in space. This Report deals mainly with cancer as the endpoint since cancer is the principal stochastic effect that occurs at low doses. The discussion here will center around (1) the conventional approach with x identified with LET, as discussed in Section 3; (2) the fluence approach with x identified with either particle kinetic energy (E)4 or LET as discussed in Section 4.1; and (3) the microdosimetric approach where x is identified with lineal energy (y) as discussed in Section 4.2. The conventional risk-estimation methodology as used in space activities can be formulated such that the result of the integration 3

Strictly speaking, this definition of R applies to a point where p(x) is defined. In order to obtain R for an organ or tissue, a suitable mean over a representative number of points in the organ or tissue must be obtained (see Section 3.1). 4 E is defined as kinetic energy (or energy, for short) per atomic mass unit (amu) in this Report, which is tantamount to using particle velocity since E ⳱ 938.3 [(1 ⳮ ␤2)ⳮ1/2 ⳮ 1)] where ␤ is the particle velocity relative to that of light in vacuum.

2.4 VARIOUS TYPES OF RADIATION FIELD DESCRIPTORS

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7

is identified with the dose equivalent at a point (H) (see Section 3.1); x is identified with LET (L); ⑀ (x) is identified with Q(L), the quality factor (Q) as a function of L; and p(x) is identified with D(L), the (unnormalized) dose distribution in L: RQ ⳱ kQ

兰 Q(L) D(L) dL

(2.2)

Here D(L) dL is the dose absorbed from charged particles in the interval (L, L Ⳮ dL), i.e., D ⳱ 兰 D(L) dL. The microdosimetric event-based system utilizes the distribution of y in the site of interest (e.g., a stem cell in a particular organ): R q ⳱ kq

兰 q(y) D(y) dy

(2.3)

where k q is the microdosimetric risk constant; q(y) is the microdosimetric analog of Q and has been termed specific quality function (Zaider and Brenner, 1985); and D(y) dy is the absorbed dose from charged particles that deposit energy in the lineal-energy interval (y, y Ⳮ dy). In an equivalent formulation, q(y)y has been termed the hit-size effectiveness function (HSEF) (Bond and Varma, 1982). For all the quantities defined in Equations 2.2 and 2.3, the particle type (i) does not appear explicitly. The equations can be viewed as approximations to the more general expression: R⳱

兺兰

r

␴i (E) ␸i (E) dE

(2.4)

i

where ␸i (E) dE is the fluence of particles of the ith type in the energy interval (E, E Ⳮ dE). Here r␴i (E) is the risk cross section, the risk of a particular excess cancer mortality per particle fluence of the ith particle type at energy E, where the fluence is the mean for the organ of interest (Curtis et al., 1992). The assumption is implicit here, as in all the above equations, that there is no interaction of biological effect between statistically independent charged-particle tracks, i.e., that the fluence rate is low enough that the final response is not modified by an interaction term arising from the passage of two independent tracks. For any of these methods, the kernel function may be determined by solving the inverse problem, if adequate experimental data on R exist and measured (or calculated) physical spectra [D(L), D(y), ␸i(E)] also exist. Ideally for all these approaches, initial slopes of dose- or fluence-response curves from appropriately chosen biological systems irradiated in high-energy charged-particle beams provide the biological data for their implementation. These solutions are not

8

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2. INTRODUCTION

mechanistic models but are meant as interpolation tools to be used for situations where data on R do not exist but where physical descriptors [D(L), D(y), ␸i(E)] can be specified.

2.5 Variation of Risk with Other Quantities In addition to the variation of risk with absorbed dose and quality of radiation, we know that risk also varies with such factors as organ type and exposure interval. These are accounted for independently by means of tissue weighting factors, and the DDREF (dose and dose-rate effectiveness factor), respectively. Tissue weighting factors will be discussed in Section 3.1. DDREF has been taken to be equal to two as suggested by the International Commission on Radiological Protection (ICRP, 1991) and the National Council on Radiation Protection and Measurements (NCRP, 1993), in order to convert the risk coefficients as derived from the atomic-bomb survivors (an acute radiation exposure) to situations where the exposure intervals are on the order of several years or longer. From recent studies of the application of a two stage clonal expansion model to lung cancer mortality in the Colorado Plateau miner population, it has been suggested that, for protracted high-LET exposures, alphaparticle-induced initiation (i.e., mutation) is negligible compared to alpha-particle-induced promotion (modification of cell kinetics of already-initiated cells) (Luebeck et al., 1999). One implication of this result is that for high-LET radiation, DDREFs are probably much less than one (an inverse dose rate effect). This would imply that there is a strong variation of DDREF both on LET and on exposure interval that should be accounted for in assessing risk on long-term missions in space (Curtis et al., 2001). Such effects are not addressed in this Report.

2.6 Content of this Report In Section 3, the conventional method of estimating risk from a mixed radiation field of high- and low-LET components (Equation 2.2) is discussed. Section 4 examines the fluence- and event-related methodologies, using the risk cross section (Equation 2.4) in Section 4.1 and a specific quality function (Equation 2.3) in Section 4.2. In Section 5, some practical aspects of radiation measurements in space

2.6 CONTENT OF THIS REPORT

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9

are treated. Biological experiments needed to validate the approaches are discussed in Section 6. Section 7 presents a comparison of the approaches for a given particle spectrum and shielding scenario. In Section 8, conclusions and recommendations are presented.

3. Conventional Method for Assessing Risk from the Mixed High and Low Linear Energy-Transfer Radiation Environment in Space

3.1 Conventional Procedure The procedure for calculating the risk of cancer mortality has traditionally been to estimate the dose equivalent at points in the various organs or tissues of interest within the individual. It is assumed that the same dose equivalent for each radiation type results in the same risk. Explicitly taken into account in the calculation of dose equivalent is the quality of the radiation represented by a quality factor (Q). Q is a universal function of particle LET and is defined under the assumption that the same radiobiological effectiveness is obtained for different particles with the same LET at the point of interest. The dose equivalent at a point (H) is given by (ICRU, 1993): H⳱QD

(3.1)

where Q, the mean quality factor, is given by: Q⳱

1 D


Q(L) D(L) dL

(3.2)

and D, the absorbed dose at a point, is given by: D⳱


D(L) dL

(3.3)

L (sometimes designated L) is the unrestricted LET or linear collision stopping power, and D(L) dL is the contribution to D from all 10

3.1 CONVENTIONAL PROCEDURE

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11

particle types in the interval (L, L Ⳮ dL) at the point of interest.5 The function D(L) is  Di(L), where the summation runs over all i

particle types. The distribution Di(L) dL can be written: Di (L) dL ⳱

1  (L) L dL  i

(3.4)

where i (L) dL is the fluence of particles of the ith type with LET in the interval (L, L Ⳮ dL), with  the density of the medium, and where secondary electron equilibrium exists and radiative losses and those due to elastic nuclear collisions are negligible.6 In subsequent equations, we make the conventional assumption of unit density medium (i.e.,  ⳱ 1 g cmⳮ3) so that L can be express in keV mⳮ1 without the need to carry  in the equations. The dependence of Q(L) on LET has changed from the earlier (ICRP, 1977) to the most recent (ICRP, 1991) recommendations, but in both cases is a defined function of LET and is independent of particle type. The presently recommended functional relationship is shown in Figure 3.1. The expressions for Q are:

Quality Factor (Q)

40

30

20

10

0 0.1

1

10 LET (keV

100

1,000

10,000

µm–1)

Fig. 3.1. The most recent recommendation for the variation of Q with LET to approximate the radiation weighting factor for high-LET radiation (Curtis et al., 1995; ICRP, 1991; NCRP, 1993). 5

D(L) is used in this Report to denote the ‘‘distribution of absorbed dose in linear energy transfer,’’ given as DL in ICRU (1993). 6 In cases where these conditions are not satisfied, the appropriate quantity is the cema (converted energy per unit mass) instead of absorbed dose (ICRU, 1998).

12

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3. CONVENTIONAL METHOD FOR ASSESSING RISK

for: L  10 keV mⳮ1

Q⳱1

for: 10 ⱕ L ⱕ 100 keV mⳮ1

Q ⳱ 0.32 L ⳮ 2.2

(3.5)

for: L  100 keV mⳮ1

Q ⳱ 300 Lⳮ1/2

The ICRP (1991) introduced the new quantity, equivalent dose (HT) which was defined to be the product of the radiation weighting factor and the mean absorbed dose to an organ (DT). Unlike Q, the radiation weighting factor is determined by the radiation incident on the body rather than by the LET spectrum at each organ. This change was made to both simplify calculations of the radiation protection quantities and to discourage the perception of an unwarranted precision of biological information implied by complex calculations. The NCRP agreed with this approach in Report No. 116 (NCRP, 1993). In some cases, however, this recommendation has proved to be more difficult to implement than was anticipated. NCRP (2000) has adopted the organ dose equivalent (HT) as the surrogate for equivalent dose (HT) for the radiation environment experienced in space.7 HT is given (ICRU, 1993) by: HT ⳱ Q T DT ⳱

1 mT



Q(L) D(L) dL dm

T

m

T

(3.6)

L

where QT is the mean Q for the organ, DT is the mean absorbed dose in the organ, Q(L) is given by Equation 3.5, D(L) is the LET spectrum of all the particles in the radiation field at a given point, the LET integration is over the LET range of all the particles at the point, and the integration over mT yields a mean value for a suitable number of points within the organ or tissue in question. For instance, for the bone marrow, the mean has typically been obtained from 33 points in the marrow within the computerized male or female model. HT is an acceptable approximation to HT in the organ or tissue in 7

The dose equivalent at a point (H) is a defined and directly measurable quantity (ICRU, 1993). For the complex mixtures of high- and low-LET radiations experienced in space, it is common practice in the space radiation protection community to integrate the point quantity H over an appropriate number of points within the organ of interest using computational models to obtain an ‘‘organ dose equivalent’’ (ICRU, 1993), which is not directly measurable, but required for radiation protection purposes. NCRP (2000) adopted the ‘‘organ dose equivalent’’ thus obtained as an acceptable approximation for HT for stochastic effects. In this Report, the symbol HT is used for the quantity ‘‘organ dose equivalent.’’ For radiation protection purposes in the space environment, the quantities HT and HT are interchangeable. Throughout this Report, the term organ dose equivalent is used whenever the quantity or value mentioned is obtained by the above practice of computing HT for an organ or tissue. The term dose equivalent (H) is used whenever the quantity or value mentioned is obtained at a point.

3.2 TOTAL CANCER RISK

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13

question and can be used, for example, for subsequent calculation of effective dose (NCRP, 2000).

3.2 Total Cancer Risk and Cancer Tissue Weighting Factors The risk of fatal cancer is estimated by ICRP (1991) and NCRP (1993) to be 4 ⳯ 10ⳮ2 Svⳮ1 for an adult population and to be distributed among the different tissues or organs as shown in the first column of Table 3.1. The total health detriment for each organ (other than the gonads) includes the risk of fatal cancer, an accounting for the detriment associated with nonfatal cancer, and for the gonads, the risk of severe hereditary disorders (ICRP, 1991, Annex B). The numerical value for the detriment associated with all nonfatal cancers is estimated to be 0.8 ⳯ 10ⳮ2 Svⳮ1 and the risk of severe TABLE 3.1—Probabilities of fatal cancer (lifetime) and tissue weighting factors (ICRP, 1991; NCRP, 1993).

Tissue or Organ

Probalities of Fatal Cancer (lifetime risk coefficient) (kc or kc,T)a (10ⳮ2 Svⳮ1)

Tissue Weighting Factors (wT) (total health detriment)

Stomach Colon Lung Bone marrow Bladder Esophagus Breast Liver Ovary Thyroid Bone surface Skin Remainder Gonads

0.88 0.68 0.68 0.40 0.24 0.24 0.16 0.12 0.08 0.06 0.04 0.02 0.40 —

0.12 0.12 0.12 0.12 0.05 0.05 0.05 0.05 (in gonads) 0.05 0.01 0.01 0.05 0.20

Total

4.00b

1.00

a kc is the lifetime risk coefficient for the total; kc,T is the lifetime risk coefficient for each organ or tissue. b Uncertainty in the value for total fatal cancers is a factor between 2.5 and 3 (NCRP, 1997).

14

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3. CONVENTIONAL METHOD FOR ASSESSING RISK

hereditary disorders at another 0.8 ⳯ 10ⳮ2 Svⳮ1, for a total detriment, including the risk of all fatal cancers, of 5.6 ⳯ 10ⳮ2 Svⳮ1 for adults (ICRP, 1991). The values for detriment calculated for each organ result in a set of tissue weighting factors (Table 3.1) representing the fractional contribution to the total detriment from each organ or tissue (ICRP, 1991; NCRP, 1993). The effective dose is the sum of the equivalent doses to these individual organs or tissues multiplied by their respective tissue weighting factors. In protection of workers on the ground, the effective dose then is compared with the limits recommended by ICRP (1991) or NCRP (1993).

3.3 Radiation Transport and Risk Calculations In the space radiation risk assessment community, the computerized anatomical man model (Billings and Yucker, 1973) and computerized anatomical female model (Yucker and Huston, 1990) have been incorporated into radiation transport computer programs. Considerable work has been done to measure the necessary nuclear interaction cross sections for inclusion into the codes (Schimmerling et al., 1989; Zeitlin et al., 1996a). Comparisons between predictions from the codes and the measurement of LET spectra in charged particle beams lend confidence that the codes are not excluding important contributions to the absorbed dose at depth (Zeitlin et al., 1996b). Using these models, DT and HT for organs or tissues of interest can be calculated from radiation spectra averaged over representative depths in the organs of interest. A comprehensive review of work in the area of space radiation transport and risk calculations up to 1990 can be found in a National Aeronautics and Space Administration (NASA) reference publication [Wilson et al. (1991) with more recent calculations appearing in Wilson et al. (1997)]. In particular, HT for organs or tissues, such as the bone marrow, were calculated for the GCR outside the geomagnetosphere behind various shielding configurations, for various times throughout the solar cycle, with the old and new Q versus LET functional relationships. When comparison is then made with DT calculated for the same situations, QT, the ratio of HT to DT, can be obtained for that particular selection of shielding configuration, time in the solar cycle, and Q-dependence on LET. Q T is a measure of the importance of high- versus low-LET radiation in the selected situation; the greater the value is above unity, the more important are the high-LET radiation components in the overall risk. For example, it has been

3.3 RADIATION TRANSPORT AND RISK CALCULATIONS

/

15

calculated for the bone marrow that at solar minimum in 1977, behind 10 g cmⳮ2 aluminum shielding plus body self-shielding, QT would be 3.1, the annual HT would be 0.59 Sv, and the annual DT would be 0.19 Gy (Wilson et al., 1997). Figure 3.2 shows the variation of these quantities as a function of aluminum shielding thickness of the spacecraft. To obtain the risk of mortality (Rc,T) from a cancer in a specific organ or tissue (T), the value of HT calculated for that specific organ can be multiplied by the lifetime risk coefficient specific to the organ: (kc,T): Rc,T ⳱ kc,T HT

(3.7)

The values for kc,T are given in the second column of Table 3.1. For instance, the lifetime risk for fatal leukemia for a 1 y exposure to the GCR would be 0.59 ⳯ 0.4 ⳯ 10ⳮ2 ⳱ 2.4 ⳯ 10ⳮ3 (or between two and three in a thousand), using a kc,T of 0.4 ⳯ 10ⳮ2 Svⳮ1 for bone marrow for the adult population (Table 3.1). The natural incidence of fatal leukemia in a lifetime is about 0.8 percent (average for both sexes) (SEER, 1997). Therefore, an exposure of 0.59 Sv would increase the risk of leukemia by about 30 percent. But leukemia is a comparatively rare disease and the relative consequences are 10

Q T, mean quality factor (bone marrow)

1

H T, organ dose equivalent (Sv) D T, mean absorbed dose (Gy) 0.1 0

5

10

15

20

25

30

35

Aluminum Shielding Thickness (g

40

45

50

cm–2)

Fig. 3.2. The variation for bone marrow of QT, annual HT (in sievert), and annual DT (in gray) as a function of aluminum thickness for a GCR spectrum at solar minimum in 1977 (Wilson et al., 1997).

16

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3. CONVENTIONAL METHOD FOR ASSESSING RISK

actually less if any type of fatal cancer is considered. The likelihood of any cancer resulting from an effective dose of 0.59 Sv in an adult is 0.59 ⳯ 0.4 ⳯ 10ⳮ2 ⳱ 2.4 ⳯ 10ⳮ2 or 2.4 percent. The natural incidence of fatal cancer in the United States population is about 20 percent in a lifetime. Consequently, an effective dose of 0.59 Sv results in an increase of about 12 percent in the natural incidence of cancer. For risks to a crew member of a specific age and gender, standard techniques are available to estimate lifetime risks (see, e.g., NCRP, 2000). It is instructive to plot the integrands in Equations 3.2 and 3.3 as a function of LET in order to determine the relative contributions of the various high- and low-LET components to H and to D, respectively, at a point in a typical environment that might be found in space. These are shown in Figures 3.3 and 3.4 behind 1 and 10 g cmⳮ2 of aluminum shielding, respectively. The calculation was made for GCR outside the geomagnetosphere at solar minimum using the presently recommended Q versus LET function. Here

L D(L) or Q(L) L D(L)

80

60

40

20

0 0.1

1

10

100

1,000

10,000

LET (keV µm–1)

Fig. 3.3. Comparison of Q(L) L D(L) (solid line) and L D(L) (dashed line) distributions in LET for GCR spectrum at a point behind 1 g cmⳮ2 aluminum shielding at solar minimum. The shaded portion is the difference in the two distributions caused by Q differing from unity above 10 keV mⳮ1. The presently recommended Q versus LET relationship is used (ICRP, 1991; NCRP, 1993).

3.4 LIMITATIONS OF THE CONVENTIONAL SYSTEM

/

17

50

L D(L) or Q(L) L D(L)

40

30

20

10

0 0.1

1

10 LET (keV

100

1,000

10,000

µm–1)

Fig. 3.4. Comparison of Q(L) L D(L) (solid line) and L D(L) (dashed line) distributions in LET for a GCR spectrum at a point behind 10 g cmⳮ2 aluminum shielding at solar minimum. The shaded portion is the difference in the two distributions caused by Q differing from unity above 10 keV mⳮ1. The presently recommended Q versus LET relationship is used (Curtis, 1994a; ICRP, 1991; NCRP, 1993).

the integrands in Equations 3.2 and 3.3 are multiplied by the LET so that equal areas under the curves have equal contributions to the integral in this semi-logarithmic plot. The shaded areas show the difference between H and D distributions. The analysis indicates that there is a considerable contribution to the risk arising from radiation in the LET region between 30 and 500 keV mⳮ1. This conclusion applies for spacecraft shielding thicknesses up to at least 10 g cmⳮ2. The relative contribution of the high-LET components, as well as overall risk, depends not only on the type and amount of shielding available, but also on the functional dependence on LET assumed for Q.

3.4 Limitations of the Conventional System In the current system (ICRP, 1991; NCRP, 1993), the physical descriptor of the radiation field is its dose distribution in LET. The

18

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3. CONVENTIONAL METHOD FOR ASSESSING RISK

choice of LET alone for characterizing the biological effectiveness of a radiation is convenient because of its simplicity. LET-based Q were first introduced in the early 1950s and have been refined over the years to arrive at the current radiation protection system. This system is generally accepted as adequate in a wide variety of circumstances. In these situations, however, the high-LET component is often small. In circumstances where high-LET components play a major role, the uncertainties are greater and may require alternative approaches as discussed in this Report. It has long been asserted that LET by itself is not completely satisfactory as a physical indicator or predictor of biological effectiveness (e.g., Blakely et al., 1979; Chatterjee and Schaefer, 1976; Curtis, 1970; 1971; ICRU, 1970; 1983; 1986; Rossi, 1959; 1964). Many important insights in the way radiation interacts with biological targets have occurred, and now it is recognized that an examination is warranted of the limitations of LET and whether different approaches have more merit. There are three limitations of LET: (1) LET is a measure of energy lost not energy absorbed in the target; there are situations where these two quantities bear little relation to each other and, as shown below, particles with identical LET may have very different spectra of energy deposition and dissimilar biological effectiveness; (2) even in the case where LET is a good approximation of energy deposition to a sensitive volume (i.e., the energy deposited is approximately equal to the energy lost), because LET is a simple linear mean of events within the volume, it would not be a suitable predictor for biological effects that depend in a nonlinear manner on energy deposition; and (3) LET cannot be measured directly, but has to be approximated from measurements in, for example, silicon detectors and plastic sheets, with certain ‘‘corrections’’ made to provide measures of the LET distributions in tissue. The LET alone cannot characterize the spatial pattern in energy deposition. Radially-restricted or radial cutoff LET (Lr) is defined as the energy lost per unit track length deposited within a given distance (r) from the track trajectory (Chatterjee and Schaefer, 1976; Chatterjee et al., 1973). Figure 3.5 (Chen and Kellerer, 1998)8 presents the ratio of this quantity and the LET as a function of radial distance in water vapor for different ions that have the same LET (here 90 keV mⳮ1). For distances greater than 10 nm, these particles show vastly different patterns of radial energy deposition. Values for Lr are already means, and the stochastics of energy deposition 8

Chen, J. and Kellerer, A.M. (1998). Personal communication (Radiobiological Institute of the University of Munich, Munich).

3.4 LIMITATIONS OF THE CONVENTIONAL SYSTEM

L ∞ = 896.6 MeV cm2 g–1

/

19

Ions in water vapor

1.0 0.9

α

Be4+

C6+ Ca20+

0.8

Lr /L

∞

0.7 0.6 α 5.00 MeV Be4+ 70.7 MeV C6+ 256 MeV O8+ 690 MeV Ne10+ 1.54 GeV

0.5 0.4

Mg12+ 3.01 GeV Si14+ 5.48 GeV S16+ 9.70 GeV Ar18+ 19.8 GeV Ca20+ 37.8 GeV

0.3 10–4

10–2

1

100

104

Radial Distance (r ) (µm)

Fig. 3.5. The ratio of the radial LET (Lr) and LET (L) in water vapor as a function of radial distance from the track trajectory for various charged particle tracks from 4He to 20Ca. The LET chosen was 89.66 keV mⳮ1 (Chen and Kellerer, 1998).9

will introduce yet additional randomness in this process. The biological consequences of the physical differences (again, at the same LET) can be seen in Figure 3.6, which shows data obtained by Blakely et al. (1979) on the inactivation of human T-1 cells by high-energy heavy-ion beams. Clearly at LET greater than 100 to 200 keV mⳮ1, different particles of the same, LET, e.g., 500 keV mⳮ1, can produce different biological effects. More recent survival cell data obtained at the Heavy Ion Medical Accelerator in Japan with 3He, 12C, and 20 Ne ion beams with a human salivary gland tumor and V79 Chinese hamster cells provide additional evidence of the variation of survival at the same LET (Furusawa et al., 2000). Results of relative biological effectiveness (RBE) at 10 percent survival versus LET for the two cell lines are shown in Figure 3.7. 9

Chen, J. and Kellerer, A.M. (1998). Personal communication (Radiobiological Institute of the University of Munich, Munich).

20

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3. CONVENTIONAL METHOD FOR ASSESSING RISK

4 3

Aerobic

2

RBE10

1 0 5

Hypoxic

4 3 2 1 0

101

102

103

Mean LET (keV µm–1) Fig. 3.6. RBE at 10 percent survival for human T-1 cells as a function of the mean LET (track-averaged): carbon data are the solid circles and squares, neon data are the half-filled circles and squares, and the argon data are the open circles and squares. Error bars show the 95 percent confidence limits (Blakely et al., 1979).

Thus for high-LET radiations in particular, the description of a radiation by its LET is not a unique indication of its biological effectiveness, and other parameters might be sought for a more accurate description. In Section 4, two alternative methods for doing this are described.

3.5 Applicability of the Conventional System The conventional system based on LET as a description of radiation quality has been widely useful in most radiation protection circumstances on Earth. In spite of the availability of the more

3.5 APPLICABILITY OF THE CONVENTIONAL SYSTEM

/

21

5 RBE at 10% Survival

4 3 2

1

V79

5 RBE at 10% Survival

4 3 2

HSG

1 20

100

500

Dose-Averaged LET (keV µm–1) Fig. 3.7. RBE at 10 percent survival plotted against dose-averaged LET for a V79 Chinese hamster cell line (V79, upper panel) and for a human salivary gland tumor cell line (human salivary gland, lower panel) obtained at the Heavy Ion Medical Accelerator in Japan. The ion beams used were 3He (triangles), 12C (circles), and 20Ne (inverted triangles) (Furusawa et al., 2000).

recently developed and more flexible microdosimetric quantities, the conventional system continues to be widely used because of its simplicity and broad acceptance. Comments have been provided on the limitations of the LET concept in Section 3.4 and will be further noted in Section 8.1. Although these limitations lead to consideration of other dosimetric systems for application to the space radiation environment, the conventional system is likely to continue to be used for radiation protection applications on Earth.

4. Fluence-Based and Microdosimetric EventBased Systems

4.1 Fluence-Based Approach

4.1.1 Introduction An individual cell within the body may experience a primary track traversal (or perhaps an electron track), but it generally will not experience the absorbed dose defined in Equation 3.3. Thus, suggestions have been made to reorient our thinking to concepts other than absorbed dose, quality factor, and dose equivalent (e.g., Bond et al., 1985). One approach to address the limitations of LET as a universal descriptor is to define appropriate functions for each charged-particle type that depend on some kinetic quantity or property of the particle and would be used simply as its kinetic ‘‘tag.’’ The functions are assumed to be smoothly varying with the kinetic property (e.g., energy, velocity or LET) and unique to the charged-particle type. Specifically for the space radiation environment, this problem was studied some time ago (Curtis et al., 1966), and more recently a methodology has been developed that depends on charged-particle fluence (Curtis, 1993; 1994b; Curtis et al., 1992; 1995). In developing a fluence-based system, a new quantity, the risk cross section, was introduced (Curtis et al., 1992). Its definition for a particular particle type with a given energy (or LET) is the probability per unit fluence (mean for the organ) of producing the risk (e.g., tumor induction) in the organ in question. The risk is usually assumed to be caused by the modification of a single cell from a particle causing an event in that cell. For example, one can obtain this quantity from experiments in which a small mean number of tumors (i.e., less than one) per animal is produced by a graded series of fluences of a given particle type and energy. In this case, the cross section is the response per unit fluence or the slope of the response versus fluence curve at low fluences (one track or less per cell nucleus, 22

4.1 FLUENCE-BASED APPROACH

/

23

on average) or low fluence rates (one track or less per cell nucleus, on average, per mean lesion repair time). For a mixed radiation environment that includes different charged-particle types each with its own energy spectrum, and when the mean number of traversals per target (i.e., cell nucleus or other relevant radiosensitive area) is much less than one, the total probability of deleterious outcome (or risk), as stated in Equation 2.4 is: R⳱

兺兰

␴i (E) ␸ i (E) dE

(4.1)

r

i

Here R is the total risk of the endpoint of interest and r␴i (E) is the probability per unit fluence (the fluence-related risk coefficient or risk cross section) of producing the endpoint, and ␸ i (E) is the differential energy spectrum so that ␸ i (E) dE is the number of particles of the ith type per unit area in the interval (E, E Ⳮ dE) at the points of interest, e.g., the sites of transformable cells in the case of carcinogenesis. The summation is over all the different particle types in the spectrum. The function r␴ is called a cross section because it has the dimension of an area and is entirely analogous to a nuclear interaction cross section, which describes the probability per unit fluence of a particular nuclear process occurring. The target or targets within the cells need not be specified explicitly. It only needs to be assumed that whatever the targets are, the fluence is low enough that the resulting biological effect is not modified by interaction between the passage of two or more statistically independent tracks. R can be written in equivalent form in terms of the particles’ LET: R⳱

兺兰

␴i (L) ␾i (L) dL

(4.2)

冤 冥

(4.3)

r

i

where:

␾i (L) ⳱ ␸ i (E)

dL dE

ⳮ1

␴i, the mean value of r␴i, can be defined:

r

␴ (L) ␾ (L) dL ␴ (L) ␾ (L) dL 兰 兰 ␴ ⳱ ⳱ ⌽ ␾ (L) dL 兰 r

r

i

i

r

i

i

i

(4.4)

i

i

where ⌽i is the total fluence of the ith particle type. Then R can be written:

24

/

4. FLUENCE- AND EVENT-BASED SYSTEMS

R⳱

兺

␴i⌽i ⳱ r␴ ⌽

r

(4.5)

i

where:

兺 ␴⳱

r

␴i ⌽i

r

i

⌽

,

(4.6)

the summation is over the types of particles present, and ⌽ is the total particle fluence. With information (either from knowledge of mechanisms or from relevant experimental data) on the energy (or LET) dependence of the probability per fluence of such particles (i.e., protons, alpha particles, and heavier ions) to induce cancer, R in Equation 4.1 (or Equation 4.2) reduces to integrations of the product of the risk cross sections and the energy spectra (or LET spectra) of the charged particles over E (or LET), at the point of interest. In the present stage of radiation transport code development, electrons and other electromagnetic radiation produced in nuclear reactions of the protons and heavier particles are neglected. The above approach derives R at a point in the organ of interest. Since there will be a variation of the spectrum from point-to-point throughout a given organ due to the varying shielding provided by the rest of the body and the spacecraft shielding in different directions, a mean organ risk can be obtained from Equation 4.1 or 4.2 by taking an average of risk calculated at representative points within the organ or a region within the organ where cells at risk are located.

4.1.2 Idealized Application of the Fluence-Based System In an idealized situation for a given organ within the body, information would be available on the two quantities in Equation 4.2 (or Equation 4.1), the risk cross sections for cancer as a function of LET (or E) and the LET (or E) spectra for each particle type at representative points where the cells of interest reside within the organ. The total risk of cancer would be the sum of the mean risks in each organ. The cross section for each particle type can be considered a smooth function of its LET or E. Thus, the assumption is made that interpolation between experimental points for a given particle type can be made with confidence.

4.1 FLUENCE-BASED APPROACH

/

25

The experimental endpoints to be used as surrogates for human cancer, however, are presently open to question (as discussed in Section 6). The cancer risk cross sections can be anchored at a lowLET point using the data from the atomic-bomb survivors (as given, for instance, in Table 3.1) in the manner described in the next section. Given that surrogate biological endpoints can be found that reflect the energy dependence of the cross sections for human cancer, the problem reduces to: (1) determining the energy dependence of the cross sections (i.e., slopes of fluence-response curves at low fluence) for enough particle types and energies so that the important components in the environment have been included; and (2) determining the energy spectra to the required accuracy within the organs of interest. The first requires an experimental program in which lowfluence responses of the chosen biological surrogate endpoints are obtained for selected particle types and energies, as will be discussed in Section 6. Low fluence is defined here as a fluence such that interactive effects between tracks can be neglected. Fluences less than a mean of one traversal per cell nucleus, or, in terms of fluence rates, less than a mean of one traversal of a nucleus per mean lesion repair time are required for low fluence conditions. This would yield linear fluence-response curves. The second requires knowledge of the incident particle energy spectra of identified particles plus the use of radiation transport codes (adequately validated) to transport the radiation through known shielding configurations to the points of interest. The spectra can be obtained either from prior knowledge of the environment (for risk prediction purposes) or from appropriately placed particle spectrometers outside the spacecraft or habitat (for risk assessment purposes). These two distinctly different applications are discussed at more length in Section 7.2.

4.1.3 Relation to the Conventional System In the conventional system for a mixed radiation environment as described in Section 3, the risk at a point (R) is proportional to the dose equivalent (H) at the point: R ⳱ KH ⳱ K

兺 兰 Q(L) L ␾ (L) dL i

(4.7)

i

assuming secondary electron equilibrium and the summation is over the different particle types. We note that L ␾i (L) dL ⳱ Di (L) dL (Equation 3.4). To make a connection between the fluence-based and conventional approaches, a risk cross section can be derived for the conventional

26

/

4. FLUENCE- AND EVENT-BASED SYSTEMS

approach by comparing Equations 4.2 and 4.7. If the risk coefficient is brought inside the summation and integral signs, a function, r␴C(L), the conventional risk cross section, can be defined as follows:

␴C(L) ⳱ K Q(L) L.

(4.8)

r

With this value of the risk cross section, the method reduces to the conventional procedure described in Section 3. This fact is used below to determine the low-LET baseline value of the risk cross section.

4.1.4 Low Linear Energy-Transfer Baseline Value of Risk Cross Section The low-LET or ‘‘baseline’’ value of the cross section will be Equation 4.8 with Q(L) equal to unity. Equation 4.2 then becomes for low-LET radiation: R⳱K

兰 L ␾ (L) dL ⳱ K D

(low-LET)

e

(4.9)

where, ␾ e (L) is the fluence spectrum of electrons as function of LET with: D⳱

兰 L ␾ (L) dL,

(4.10)

e

and assuming secondary electron equilibrium. The integral is over the LET range for all the electrons from the gamma-ray field, and electrons are the only charged-particle type present. From the definition of frequency-average LET (LF) which is the fluence-to-dose conversion factor: L ␾ (L) dL 兰 兰 L ⳱ 兰␾ e

⳱

F

e

(L) dL

L ␾e (L) dL

⌽

,

(4.11)

the product LF ⌽ can be substituted for the integral in Equation 4.10 obtaining: R ⳱ K LF ⌽

(low-LET)

(4.12)

where now ⌽ is the total fluence of electrons. Since the dose is 兰 L ␾e(L) dL under condition of particle equilibrium, the relationship converting fluence to dose is:

4.1 FLUENCE-BASED APPROACH

D ⳱ LF ⌽

/

27 (4.13)

The first two factors in Equation 4.12 can be identified with the low-LET risk cross section: r

␴C ⳱ K LF

(low-LET)

(4.14)

Conventional Risk Cross Section [rOC(L) (µm2)]

This provides the low-LET ‘‘baseline’’ or ‘‘anchor point’’ for the conventional expression that relates cross section and LET. Using the electron energy spectrum in bone marrow at 1,500 m ground distance at Hiroshima (Kaul et al., 1987), the value of LF is 2.4 keV ␮mⳮ1. For illustrative purposes, a value for K of 0.04 Svⳮ1 (or Gyⳮ1 at lowLET) is adopted here (i.e., kc in Table 3.1). This would be applicable to a human exposure situation in which all body organs uniformly received the identical dose equivalent (H), so that effective dose equaled H. This yields the numerical value for r␴C of 1.5 ⳯ 10ⳮ2 ␮m2 [using a value of 0.16 Gy ␮m3 keVⳮ1 (with the density of the medium equal to 1 g cmⳮ3) to take proper account of units]. The value of r␴C can then be plotted at L F for the electron spectrum, and r ␴ C (L) can be calculated from Equation 4.8 as a function of LET. This is shown in Figure 4.1 using the Q versus LET relationship from Figure 3.1.

100

10 1

0.1 0.01

0.001 0.1

1

10

100

1,000

LET (keV µm–1)

Fig. 4.1. The conventional risk cross section r␴C(L), is shown as a function of LET (Equation 4.8) where K equals kc (Curtis et al., 1995). The presently recommended value of Q as a function of LET was used (ICRP, 1991).

28

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4. FLUENCE- AND EVENT-BASED SYSTEMS

4.1.5 Treatment of Photons and Neutrons Since the approach delineated above is based on charged particle fluences, it is necessary to discuss how photons and neutrons are treated. The level of absorbed dose (and biological effects) within the space travelers from incident photon and neutron spectra is assumed to be negligible compared with that from the spectra of the charged particles and their secondaries in the GCR spectrum. Significant numbers of photons or neutrons have not been detected in the incident radiation. In addition, the absorbed dose from photons generated by the charged particles is assumed small and so is neglected here. We note, however, that there can be an albedo contribution (back scatter neutrons) from massive objects, and astronauts on the lunar or Marsian surface will receive considerable fluxes of incident neutrons. Neutrons resulting from nuclear interactions of singly or doubly charged particles (protons, deuterons, tritons, and helium ions) are included, however, through the spectra of secondary charged particles they generate as calculated by the computer code. In the results referred to later in Section 7.6, neutrons produced in the aluminum shielding material and bone marrow from particles with charge equal to one or two are propagated through the absorbing medium, and the charged particles from the nuclear interactions are further propagated to the center of the sphere. A very small dose (0.003 of the total dose) is calculated, due to recoil nuclei from interactions of neutrons with target nuclei (carbon, nitrogen, oxygen) depositing energy locally in the bone marrow. The codes generating the neutron components are continually being improved. Current codes, however, cannot reproduce measured fluxes below 10 MeV in space to better than a factor of two to three. These results acquire additional weight in the fluence-based risk estimation system because of its heavier reliance on a transport model than the traditional method. There are still limitations in the accuracy of the neutron calculations due to lack of experimental data on nuclear cross sections in certain energy ranges. If nuclear reactors are employed to provide power for long-term interplanetary missions, exposure from such a source should of course be factored into the risk calculation when determining the total radiation risk involved in a mission.

4.1.6 Strengths and Limitations The approach is straightforward; information is gathered on the identities of the particles and their energies constituting the

4.1 FLUENCE-BASED APPROACH

/

29

radiation environment. Use can be made of knowledge at hand on the types and energies of the incident particles known to be in the GCR spectrum. The physics of particle interaction and propagation are known well enough so that reasonably accurate spectra at points of interest within bodies of the space travelers can be calculated, given incident spectra and the detailed shielding characteristics of the spacecraft or habitat and the human body. Explicit acknowledgment is made of the possibility that different particles of the same LET may have different biological consequences. Different risk cross-section functions will be developed for each particle type. The assumption that the risk cross section will be a continuous and smoothly varying function of the particle energy for a given particle type is reasonable and allows a confident interpolation of the cross section between experimentally determined data points. For a limited range of LET and particle types, the cross sections are expected to vary smoothly with the atomic number (Z). This will give confidence that the total data set depicting the dependence of the risk cross sections on LET (or energy) will fit into a coherent picture. This will keep the amount of data to be collected to a minimum. LET spectra can be easily calculated for use with the conventional risk assessment method. In fact, one can consider the fluence-based approach as just the conventional approach reoriented to emphasize particle fluence rather than absorbed dose, with the additional feature that different ‘‘quality weighting’’ functions are provided for each particle type, thus allowing different risks from different particle types having the same LET. The physical data that must be obtained (e.g., energy spectra from the different particle types) can be archived and other analyses and risk assessments can be made if new approaches are developed in the future. On the other hand, the approach requires good information on the radiation environment within the tissues of interest and depends heavily on radiation transport codes to transport the incident radiation through matter. This places considerable importance on the acquisition of data concerning the types and energy spectra of particles incident on the spacecraft or habitat, as well as a knowledge of the shielding characteristics surrounding the tissues of interest and an adequate radiation transport code. Such codes are still being developed and experimentally verified, and the neutron contribution is still somewhat in doubt. To collect the necessary data, several particle spectrometers with appropriate solid-angle collection efficiencies properly calibrated must be positioned in the ambient exterior radiation environment.

30

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4. FLUENCE- AND EVENT-BASED SYSTEMS

A calculational facility must be provided in the vehicle or habitat, or else the data must be stored and transferred back to Earth. The latter requires considerable data storage and transfer capability. Finally, the approach requires considerable biological data to be obtained at low fluence rates using biological endpoints that are surrogates for human carcinogenesis. The particle components of importance in the radiation environment in space (protons, oxygen, iron, etc.) must be used at energies typical of those to be encountered (⬃200 to 2,000 MeV amuⳮ1). Specific suggestions for particle types and energies are given in Section 6.3.

4.2 The Microdosimetric Event-Based Approach

4.2.1 Introduction The simplest descriptor one can imagine is the energy deposited in the sensitive site of the biological object given, of course, that the size of the sensitive site is known. This can be quantified in terms of either specific energy (z) or lineal energy (y) (ICRU, 1983; Rossi, 1959). Both z and y are stochastic quantities and thus subject to probability distributions, f (z) or f (y) within the site. The selection of z as physical descriptor means that there must be an effect function [␧ (z)] that describes the biological damage for a given system, endpoint and site size. The mean effect (␧) is then: ␧⳱

兰

⬁

␧(z) f (z) dz

(4.15)

0

If ␧ (z) depends linearly on z [i.e., ␧(z) ⳱ kz], then: ␧⳱k

兰

⬁

z f (z) dz ⳱ kz ⳱ kD

(4.16)

0

Because by definition, k is independent of the quality (i.e., kind) of radiation, it follows that all radiations in this case will have the same effectiveness per unit dose; therefore, RBE will be unity for all of them. Since biological data show that RBE is not equal to unity for all radiations, this means that the simple assumptions underlying either Equation 4.15 or 4.16 are incorrect. Assuming then some (nonlinear) function ␧ (z), the distribution f (z) is needed to find ␧. Several factors contribute to the shape of f (z): (1) fluctuations in the number of energy deposition events, (2) the

4.2 THE MICRODOSIMETRIC EVENT-BASED APPROACH

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31

f(y) (arbitrary units)

LET distribution of the particles, (3) the path-length distribution in the site, (4) energy straggling, and (5) the amount of energy retained in the site (i.e., not escaping as delta radiation). The conditions under which LET is a reasonable substitute for lineal energy (y) can now be stated explicitly: the distributions f (y) or f (z) must be dominated by fluctuations of the Type 1, 2, and 3 and not by 4 and 5. An example of this situation is given in Figure 4.2 which shows the microdosimetric spectrum obtained when a 1 m diameter counter is exposed to 5.3 MeV alpha particles. f (y) is dominated by the pathlength distribution in the sphere. Cobalt-60 gamma radiation is an example for which the spectrum is almost totally dominated by energy straggling; in this case, the concept of LET will be inapplicable (Figure 4.3). A dramatic example where fluctuations of the Type 5 above are the main contributor to f (y) is energy deposition in a 1 m sphere by 350 MeV amu ⳮ1 iron ions. The frequency-mean lineal energy (yF) is about 6 keV mⳮ1 while the LET of these ions is 253 keV mⳮ1, i.e., some 40 times larger. Microdosimetry deals with the stochastics of energy deposition by ionizing radiation in specified targets. The key element in

0

20

40

60

y (keV

80

100

120

µm–1)

Fig. 4.2. Theoretical chord-length distribution in a sphere (solid line) and experimental linear energy spectrum for 5.3 MeV alpha particles in a 1 m diameter site (Glass and Braby, 1969).

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4. FLUENCE- AND EVENT-BASED SYSTEMS

10

1

zf(z)

10–1

10–2

10–3

10–4 10–4

10–3

10–2

10–1

1

10

z (Gy) Fig. 4.3. Specific energy (z) distribution from electrons produced by 60Co gamma radiation in simulated 1 m sites of material with density 1 g cmⳮ3. Solid curve: actual calculated distribution. Dashed curve: spectrum calculated on the basis of track length and LET distributions but omitting straggling. Dotted curve: spectrum calculated on the basis of straggling with the omission of track length and LET distributions (Kellerer, 1968).

microdosimetry is therefore the recognition that in describing radiation effects: (1) the quantity of interest is not the energy lost by a charged particle in traversing a medium but the actual spatial (and temporal) distribution of energy deposition events in the target of interest, and (2) the process of energy absorption in the target is random and subject to well-defined probability laws that result from the physics of the radiation field. These two observations correspond to the two basic quantities used in microdosimetry: specific energy (z), defined as the energy absorbed per unit mass of the reference volume, and its microdosimetric spectrum [f (z) dz] that determines the probability that specific energy in the interval (z, z Ⳮ dz) is deposited in the target. Advantages of lineal energy over LET include: (1) it can be directly measured [e.g., with tissue equivalent proportional counters (TEPC)]

4.2 THE MICRODOSIMETRIC EVENT-BASED APPROACH

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33

(ICRU, 1983; Rossi, 1968), (2) it is related to the energy actually deposited in a possibly relevant site and therefore could be expected to be more directly related to induced biological effect, (3) it is stochastic and thus contains no inherent averaging procedure although mean values of various quantities can be defined and are used, and (4) it allows an unambiguous definition of the ‘‘low dose’’ domain (see below). Although methods for measuring distributions of lineal energy are mainly limited to gas-phase materials, they are becoming more widely used in practical applications (e.g., Badhwar et al., 1994a; Braby et al., 1994). In the case of high-energy heavy ions such as those which are of particular interest in this Report, an additional problem termed the wall effect (ICRU, 1983) occurs in gas-filled (but not in solid) detectors. Four kinds of wall effects, which may lead to significant distortions in the measured spectra, have been characterized: the ‘‘delta-ray effect,’’ the ‘‘re-entry effect,’’ the ‘‘V-effect,’’ and the ‘‘scattering effect.’’ The ‘‘delta-ray effect’’ is caused by a charged particle and one of its delta rays entering the measuring cavity simultaneously. The distance between the two entry points may be large enough that either the primary or the delta ray, but not both, would enter a single microscopic volume (diameter ⬃1 ␮m) in a medium with constant density. In the latter case, the two passages should be considered two separate events. This effect will be the most important for highenergy heavy charged particles (ICRU, 1983). The error introduced by this effect has been calculated theoretically (Kellerer, 1971); the calculated frequency of such double events is about 15 percent for protons above 5 MeV. This effect will also cause distortion for the ‘‘indirect’’ events, i.e., those in which a heavy charged particle passes outside the region of interest but injects one or more delta rays into it (ICRU, 1983). The delta-ray effect may introduce significant errors in the frequency-mean microdosimetric quantities, yF and z F, by decreasing the number of events and increasing the apparent energy deposited in the remaining events. This has been shown in a recent study of wall effects from 1.05 GeV amuⳮ1 iron ions at a high-energy heavy-ion accelerator (Rademacher et al., 1998). It was shown that although the mean absorbed dose is accurately measured by a walled detector, the lineal-energy distribution can be significantly distorted by the presence of the wall. The ‘‘re-entry effect’’ is caused by an electron re-entering the measuring cavity after it has left. This is due to its highly curled (i.e., scattered) trajectory. The points of exit and re-entrance can be far enough apart that the electron would not re-enter the actual

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4. FLUENCE- AND EVENT-BASED SYSTEMS

microscopic region. This effect is important only for electrons up to 1 MeV, and can probably be neglected in space radiation applications. The ‘‘V-effect’’ is caused by nuclear interactions, in which one or two nuclear fragments (created by a primary) originate outside the measuring cavity and two or more tracks traverse it. The entrance points might be far enough apart so that all tracks would not traverse the microscopic volume and so should be considered as separate events. This effect may become important above 10 MeV for neutrons (ICRU, 1983), and can cause very large events. The ‘‘scattering effect’’ is caused by neutral particles undergoing two separate interactions close enough together so that both resultant charged secondaries traverse the larger measuring cavity, while only one would have traversed the microscopic cavity. This effect is important for photons and neutrons under multiple scattering conditions and will probably be negligible in the application considered here. None of these effects, however, has been evaluated in relation to the resulting modifications to the microdosimetric distributions as measured in the space environment with walled detectors. These distributions of the lineal-energy measurements must be understood prior to applying microdosimetric methods to dosimetry in space. 4.2.2 Microdosimetric-Based Quality Functions Two largely equivalent approaches termed, respectively, hit size effectiveness and specific quality function have been developed for the purpose of using lineal energy in radiation protection (Bond and Varma, 1982; Zaider and Brenner, 1985). Consider a biological system exposed to an absorbed dose (D). The probability density function of specific energy (z) is given by: ⬁

f(z D) ⳱

兺 冤e

ⳮn

␯⳱0

冥

n␯ f␯ (z) ␯!

(4.17)

f(z兩D) is known as the multi-event microdosimetric spectrum. Equation 4.17 then states the following: let zF represent the mean specific energy in single events; if f1 (z) is the single event spectrum, then: zF ⳱

兰

⬁

z f1 (z) dz

(4.18)

0

and n is the mean number of events in the volume at D: n⳱

D . zF

(4.19)

Since, by definition, microdosimetric events are statistically independent, the probability of exactly ␯ events is given by a Poisson

4.2 THE MICRODOSIMETRIC EVENT-BASED APPROACH

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35

n in Equation 4.17. Finally, f (z) is the microdosi! metric spectrum in exactly  events, with the convention:

冤

冥

distribution eⳮn

f0 (z) ⳱ (z)

(4.20)

( is the Dirac delta function). The function f (z) may be obtained interactively by successive convolutions: f (z) ⳱

兰

z

f␯ⳮ1 (z ⳮ z⬘) f1 (z⬘) dz⬘

(4.21)

0

In particular, at low values of D (defined by n Ⰶ 1), Equation 4.17 becomes:

冤

f(z兩D) ⬇ eⳮD/zF ␦ (z) Ⳮ

冥

D f1 (z) zF

(4.22)

Assume, for a particular biological endpoint, one can now define a quantity, ␧ (z), termed HSEF, that satisfies:10 ␧(D) ⳱

兰

⬁

␧(z) f(z兩D) dz

(4.23)

0

where ␧ (D) is the microdosimetric analog of H. Both ␧ (D) and ␧ (z) refer to a specified biological endpoint. Furthermore, at low values of D (the domain of interest here), one obtains from Equation 4.22: ␧(D) ⬇ D

兰

0

⬁

␧(z) f1 (z) dz ⳱ D zF

兰

0

⬁

冤

冥

␧(z) z f1 (z) dz z zF

(4.24)

In writing Equation 4.24, the following property has been used: ␧(0) ⳱ 0.

(4.25)

The rearrangement of Equation 4.24 on the right-hand side is instructive in relation to the conventional definition of H in terms of Q, which is a function of LET: ␧(D) ⳱ Q D ⳱ D

兰

⬁

Q(L) ⌬ (L) dL

(4.26)

0

Here ⌬(L) dL is the fraction of absorbed dose delivered by particles in the LET interval (L, L Ⳮ dL). Thus ⌬(L) ⳱ D(L)/D. In Equation 4.24, the quantity in square brackets is the fraction of absorbed dose 10

The assumption behind Equation 4.23 is known in microdosimetry as the site model.

36

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4. FLUENCE- AND EVENT-BASED SYSTEMS

delivered by single events in the specific energy range (z, z Ⳮ dz). The function: q(z) ⳱

␧(z) z

(4.27)

is the microdosimetric analog of Q(L), and has been termed specific quality function. For a spherical volume of matter with density 1 g cmⳮ3 and diameter d (in micrometer), the values of z (in gray) and y (in keV ␮mⳮ1), are simply related by the expression: y ⳱ (4.9 d 2) z. Therefore, Equation 4.24 can be written in terms of y, yF, q(y), and integrated over y instead of z obtaining: ␧(D) ⬇

D yF

兰

⬁

q(y) y f(y) dy

(4.28)

0

Equation 4.28 is a recipe for calculating a microdosimetric-based mean quality factor, q, for any radiation field: 1 q⳱ yF

兰

⬁

q(y) y f(y) dy

(4.29)

0

As already indicated, q in Equation 4.29 refers to a specific biological endpoint. It is expected that the endpoint (or endpoints) chosen will produce a function q(y) that is representative of human carcinogenesis. Equation 4.28 shows that q may be obtained from the initial slope of the dose-response curve. As an example, for a linear-quadratic response function: ␧(D) ⳱ ␣D Ⳮ ␤D2

(4.30)

one has q ⳱ ␣ in the limit of low absorbed dose. The determination of q(y) may proceed as follows: In a series of experiments employing different radiations, one obtains the initial slopes, ␣i, corresponding to exposures to radiation ‘‘i’’ with microdosimetric spectrum fi (y). One then solves the system of integral equations:

␣i ⳱

1 (yF ) i

兰

⬁

q(y) y fi (y) dy

(4.31)

0

Generally no analytic expression for q(y) need be assumed and methods for obtaining nonparametric solutions to Equation 4.31 have been described in the literature (Zaider and Brenner, 1985). However, if the biological mechanism of radiation action is known, and one can

4.2 THE MICRODOSIMETRIC EVENT-BASED APPROACH

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37

postulate specific analytic formulae for q(y), the solution of Equation 4.31 is clearly facilitated. Critical elements in determining q(y) are the actual geometric shape and size of the sensitive (microdosimetric) volume of the cellular system. Thus, the notion of a function q(y) becomes practical only if the result of unfolding Equation 4.31 is not excessively sensitive to the site geometry and size, and if simple geometries, such as spheres or cylinders, may be used as first approximations, as has been shown to be the case (Varma et al., 1994). 4.2.3 Low Linear Energy-Transfer Baseline from the Hiroshima Data The factors defined above must be scaled to produce the appropriate risks measured in epidemiological analyses such as for the relatively well-known low-LET field of gamma rays created in the atomic-bomb explosions at Hiroshima and Nagasaki. A procedure has been introduced for scaling the specific quality functions, q(y), using the results of the assumed radiation environment after the explosion at Hiroshima (Bond et al., 1995). Let RH represent the risk per unit absorbed dose for the radiation field at Hiroshima. If H (y) is the corresponding microdosimetric distribution in y, then the risk (R) after exposure to radiation characterized by a spectrum  (y) is given by:

R ⳱ RH

兰 兰

⬁

q(y) ⌬ (y) dy

0

(4.32)

⬁

q(y) ⌬H (y) dy

0

The important aspect of the equation is that the same function q(y) is used for both radiations. Clearly, it is desirable to have distributions ⌬H (y) for each cancer-prone organ, and as a function of distance from the bomb’s hypocenter. In a calculation reported in Bond et al. (1995), gamma-ray fluence spectra in the marrow at 1,500 m ground range at Hiroshima (Kaul et al., 1987) were used as input. The microdosimetric spectrum for this field is obtained as a linear combination of spectra [f(z,Ee)] for monoenergetic electrons of Ee with coefficients proportional to the relative number of such electrons [n(Ee)] in the photon field: f(z) ⳱

兰

0

⬁

n(Ee) Ee f(z, Ee) dEe zF (Ee)

(4.33)

Here zF (Ee) is the first moment of the microdosimetric spectrum. The resulting spectrum in y is shown in Figure 4.4, along with the

38

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4. FLUENCE- AND EVENT-BASED SYSTEMS

0.4 250 kVp x rays

y (y)

0.3 Free gamma-ray field, 1,500 m Hiroshima 0.2

0.1

0.0 10–2

100

10–1

101

y (keV µm–1) Fig. 4.4. The distribution of y⌬(y) as a function of y for the free gammaray field at 1,500 m from ground zero at Hiroshima (solid line) calculated for a site diameter of 1 ␮m. The dashed line is shown for 250 kVp x rays for comparison (Bond et al., 1995).

microdosimetric spectrum for 250 kVp x rays for comparison. This spectrum will be used in Section 7.6 as the normalizing factor or baseline when examples are given of the implementation of this and the fluence-based approaches.

4.2.4 Strengths and Limitations Experimental methodology for obtaining microdosimetric spectra is readily available as detailed, for instance, in the proceedings of the past 11 symposia on microdosimetry. Microdosimetric proportional counters have been used in a variety of radiation-protection situations, and two different designs of TEPC have been flown aboard the Space Shuttle to obtain distributions of lineal-energy depositions (Badhwar et al., 1994a; 1994b). More recent results of detectors flown within polyethylene and aluminum spheres have provided important data on both the trapped and GCR components at the Mir spacecraft altitude (Badhwar and Cucinotta, 1998; 2000).

4.2 THE MICRODOSIMETRIC EVENT-BASED APPROACH

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39

A chief advantage of the microdosimetric event-based approach is that one measures directly the energy deposition responsible for the carcinogenic effect and thus there is no need to know the kind of particle or the energy of the particle that produced an energy deposition event. This assumes, of course, that there is a unique function of lineal energy that adequately describes the risk, so that it can be applied to all the radiations found in space. This assumption has yet to be verified. This approach has been tested, at least in one situation involving human exposures (Zaider and Varma, 1996). The study involved an evaluation of the effects of domestic exposure to radon based on a function q(y) for in vivo radiogenic neoplasia and on scaling atomicbomb results to radon exposure. The results were compared with epidemiological data obtained independently from the underground miners and were shown to be in good agreement. As with other approaches for estimating radiation risks, the microdosimetric system suffers from the general lack of in vivo data for radiation-induced carcinogenesis. By using a function q(y), one effectively makes up for this lack of biological information with the aid of information on the microdosimetry of the fields of interest. Accepting the assumption that there is one unique function of linear energy that describes risk reduces the amount of biological data required. From this perspective, a series of, say, four or five exposures using radiations that cover the relevant lineal-energy spectrum (0.1 to 1,000 keV mⳮ1) might be sufficient. Clearly, the accuracy in the determination of q(y) depends on the number of data sets available, as has been discussed in detail by Zaider and Brenner (1985). Gas-based proportional counters are currently used as area monitors in Earth-based radiation environments. A spacecraft on a mission to Mars would have no difficulty accommodating such a detector. The imminent advent of tissue-equivalent solid-state detectors might make them applicable (if desired) as personal dosimeters as well. Evidence that a unique specific quality function of y exists for a given site size is still lacking. It would be helpful to further validate the event-based approach if similar q(y) versus y curves could be obtained for the same biological endpoint (an appropriate surrogate for human carcinogenesis) using, on the one hand, alpha particles and, on the other, high-energy heavy ions spanning the same range of high-y values.

5. Practical Aspects of Radiation Measurements 5.1 Introduction The characteristics and limitations of practical radiation detection devices will be a factor in the implementation of any operational risk evaluation system. This Section will briefly describe some of the types of dosimeters which may be used in space applications. Since future technical developments may make current implementations of these dosimetric techniques obsolete, specific approaches will be presented in a general way, and those requirements and limitations which are inherent to the technique as well as those which are imposed by current technology will be described. Radiation measurements for radiation protection purposes are generally separated into active and passive methods. Passive dosimeters such as thermoluminescent dosimeters (TLD) generally integrate the radiation detected from the time they are activated until the time they are read. Most require some processing to reveal the data, although there are some self-reading techniques such as ion chambers with integral quartz fiber electrometers. In most radiation protection programs, passive dosimeters are used as dosimeters of record because they are inherently resistant to the types of failures that can interrupt the measurements of active dosimeters. Passive dosimeters, however, are generally unsuited to real-time measurements of dose and dose rate due to their integrating nature. Active dosimeters such as Geiger-Mu¨ller counters, charged-particle telescopes, and proportional counters are generally used for real-time dosimetry applications such as radiation area monitors, and to aid in evaluation of the radiation quality.

5.2 The Conventional Approach 5.2.1 Introduction The conventional approach requires both a measurement of the absorbed dose (D) and estimation of Q to determine the dose 40

5.2 THE CONVENTIONAL APPROACH

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41

equivalent (H). D can be measured using a variety of different types of detectors. Each type has some dependence on the energy spectrum, and typically they are calibrated in a radiation field which is thought to be representative of the radiation environment to be measured. Q can be evaluated either by determining the LET spectrum of the incident radiation or by using a detector which is known to respond in proportion to H rather than D. The latter approach is commonly used in neutron dosimetry in ground-based applications, where a single particle type and a relatively limited range of energies are encountered. However, there are no known detectors which can be relied on to respond in proportion to H in the complex radiation fields encountered in space. Thus, the LET spectrum must be determined. For directly ionizing particles, the spectrum can be determined from the type and energy of the particles. In space, portions of the spectrum of charged particles have been measured in a wide variety of experiments, most of which have been motivated by space science needs rather than by radiation protection. These spectra have served as the basis for developing models of the radiation environment which make it possible to calculate the LET spectrum at selected positions within spacecraft. These calculated distributions are presently used to evaluate Q. Instruments developed to measure lineal-energy spectra (see Section 5.3 below) can also be used. This is presently being done on Space Shuttle flights (Badhwar and Cucinotta, 1998; 2000; Badhwar et al., 1994b; 1996). The charged-particle spectrometers described in Section 5.4 can also be used to evaluate the LET spectra in order to determine Q. A prototype particle spectrometer has been flown aboard the Shuttle, and preliminary results have been reported (Badhwar et al., 1994b). Several types of passive and active detectors can be used to evaluate D for the conventional approach. They are briefly described below.

5.2.2 Cavity Ion Dosimeters Many types of cavity dosimeters can be devised, but the most common is the ion chamber. These devices are characterized by a gas volume within a medium. Ionization per unit time is determined in this volume by measuring the current. In ion chambers and most other devices, there is a relatively constant relationship between the quantity measured and the mean energy deposited per unit time. Thus for an ion chamber, the mean energy per ion pair relates the total number of ions collected to the mean energy deposited. By knowing the mass of the volume, D in the gas can be calculated. For this to properly reflect D in a uniform medium with the same

42

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5. PRACTICAL ASPECTS OF RADIATION MEASUREMENTS

composition as the detector wall, charged-particle equilibrium is necessary. This requires that the cavity wall thickness of the ion chamber be comparable to the range of the most penetrating secondary particles, but thin compared to the range of all primary radiations, an impossibility for some combinations of radiations. The composition of the medium and gas in the detection volume also influence charged-particle equilibrium and the relationship between the energy deposited and that which would be deposited in the material where D is desired. If both the medium and the volume are equivalent in atomic composition to standard tissue, or if the cavity is small enough that it does not disturb the secondary particle fluence and all secondary particles originate in the wall, such a device will measure D in tissue for all types of radiation. It cannot, however, provide information on the spectrum of the radiation or the fluence. Both active and passive ion chambers can be built. Active ion chambers, utilizing an electrometer to measure the ion current, are typically used for radiation survey meters which measure dose rate. Passive ion chambers, such as pocket ion chambers, are often used as personnel dosimeters where relatively high dose rates are expected. 5.2.3 Thermoluminescent Dosimeters Thermoluminescent materials are typical of a variety of dosimetry materials in which electrons are promoted to metastable excited states in a crystal lattice by charged-particle interactions (Shani, 1991). They are typically read by adding a controlled amount of additional energy (by heating in the case of TLD) which releases the trapped electrons to the ground state by emitting the excitation energy as one or more optical photons. This reading process generally operates on the entire sample simultaneously, resulting in a detector which responds to the product of the number of charged-particle tracks times the number of electrons trapped per track. For most radiations, this very nearly represents D; but for 6Li neutron detectors, this more nearly represents the thermal neutron fluence. It is now possible to read out small points on optically stimulated luminescence materials. If the resolution becomes high enough, it would be possible to map the concentration of trapped electrons on a larger sample, and then to determine the stopping power of individual tracks and the fluence, assuming that the fluence was not large enough to produce overlapping tracks. 5.2.4 Solid-State Nuclear Track Detectors Directly-ionizing particles passing through solid materials generally produce physical damage to the material. In some materials the

5.3 THE FLUENCE-BASED APPROACH

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43

damaged portion can be etched away preferentially, resulting in surface pits where tracks occurred. The size of the pit can be related to the LET of the particle, and D can be determined by evaluating the number and size of the pits (Benton and Nix, 1969). Stacks of detectors can be used to determine the range of the particle by plotting the course of a single particle through the stack. These data can be used to determine E and Z for the charged particle. As a result, these materials can be used as passive charged-particle spectrometers. Detection of indirectly-ionizing radiations depends on the production of directly-ionizing secondaries. The useful fluence range that can be measured is limited by the necessity to identify individual pits and trace the track of a particle through the stack of detectors. This depends on the etching technique, the resolution and accuracy of the system used to correlate tracks on different layers (Heinrich et al., 1989). 5.2.5 Current Practice The radiation protection program on the Space Shuttle relies on the three types of dosimeters described above, plus the models of the space radiation environment and the resulting LET spectrum. TLD, pocket ion chambers, and etched track dosimeters are used to evaluate D. Stacks of etched track material are also used to evaluate the LET spectrum in order to check the assumed Q (Benton, 1986). Recently, lineal-energy spectrometers (see Section 5.4.2) have been used to evaluate D and H as a function of time on Space Shuttle flights (Badhwar and Cucinotta, 1998; 2000; Badhwar et al., 1994b; 1996). Detailed modeling of the response of these detectors and comparisons with Shuttle flight data show good agreement and it has been concluded that measurements of D and H at a point are not significantly distorted by replacing LET with y and the LET distribution with the measured y distribution in the calculation (Shinn et al., 1999). The results of these measurements have been used to further refine the evaluation of Q which is used with the TLD data to determine H for individual crew members.

5.3 The Fluence-Based Approach 5.3.1 Introduction A fluence-based system requires measurement of all incident radiation, both directly ionizing and indirectly ionizing, if any, in the

44

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5. PRACTICAL ASPECTS OF RADIATION MEASUREMENTS

undisturbed environment. With these data, a radiation transport code, and a detailed knowledge of the intervening shielding, the fluence of secondary radiations at any position in the spacecraft and its occupants can be calculated. Assuming that the neutron, photon and penetrating electron components of the incident radiation in space are negligible, it is sufficient to measure the fluence and energy spectrum of positive ions (protons and heavier). This can most conveniently be done with some version of a charged-particle telescope. However, if there are incident neutrons, additional types of detectors will be needed to determine the fraction of D and H they produce.

5.3.2 Charged-Particle Telescopes Charged-particle telescopes typically measure the stopping power and total energy of the directly-ionizing charged particles. These data can be used to determine the particles’ velocities and charges. Since these devices detect individual particles, they inherently provide a measure of the fluence. A wide variety of types of thin detectors (a fraction of a gram per square centimeter) can be used to measure stopping power, and many types of thick detectors can be used to measure total energy, although solid-state detectors are commonly used due to their good energy resolution. However, all detector combinations are limited by the maximum energy of a particle that will be stopped in the detector. A particle which enters the detector and then leaves it before stopping will be reported with an erroneous total energy, and may be interpreted as a particle having a lower charge than the one producing the event. Since the GCR spectrum includes particles with ranges of many centimeters in silicon, detectors can become very large. An alternative approach is to measure both the initial stopping power and the stopping power after the particle has penetrated a thick absorber. Although this technique does not detect low-energy particles, the two techniques are often combined and, in proper configuration, can detect nearly the entire cosmic-ray spectrum. It is necessary to know that a short range particle did not exit through the side of the detector, and to get a reasonable precision in the measurement of stopping power, the approximate angle of the particle path relative to the thin detector must be determined. The particle trajectory is usually limited by requiring coincidence between two widely spaced thin detectors. This approach limits the acceptance angle of these detectors, usually to a cone around 60 degrees. Alternatively, position sensitive detectors can be included so the actual initial trajectory can be calculated. These detectors are

5.3 THE FLUENCE-BASED APPROACH

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45

inherently insensitive to indirectly ionizing radiations, and if the directly ionizing fluence is not isotropic, separate measurements must be made in several directions so that the total fluence can be determined. A three-axis charged particle spectrometer with position-sensitive detectors has been delivered to Cape Kennedy for integration into the International Space Station (Badhwar, 2000).11

5.3.3 Bubble Detectors Charged particles passing through superheated liquids can nucleate the phase transition and produce tracks of bubbles through the medium. This is the basis of the bubble chambers used in particle physics experiments, and this phenomenon can be used in passive and active radiation detectors for radiation protection (Apfel, 1979; Ing et al., 1997). Passive detectors consist of a pressurized gel material which can be activated by reducing the pressure. The LET necessary to nucleate bubble formation can be controlled by adjusting the composition of the gel. Sets of these detectors can be used as LET spectrometers. The fluence can be determined by counting tracks. The total volume of the bubbles formed can be used as a measure of D. Again, the response to indirectly-ionizing particles depends on the production of directly-ionizing secondaries, so by making the detector tissue equivalent, these detectors can be used to record D, assuming an adequately low-LET threshold for track detection. However, bubble detectors cannot be used for the determination of the total energy of the charged particles.

5.3.4 Neutron Recoil Spectrometers Neutron fluence is typically measured by detecting recoil particles produced in a material of known atomic composition. Generally recoil protons are used because of the efficient transfer of energy from neutrons to protons. Both gas-phase detectors, such as high-pressure hydrogen proportional counters, and condensed-phase detectors such as liquid scintillation detectors can be used. The spectrum of energy deposited by recoil particles is measured, and the incident neutron spectrum is unfolded using the detector response function which is determined independently. However, these detectors will also have a response for directly-ionizing particles such as protons. In

11

Badhwar, G.D. (2000). Personal communication (National Aeronautics and Space Administration, Johnson Space Center, Houston).

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principle, the directly-ionizing spectrum can be measured separately and its contribution to the spectrum measured by the recoil detector can be subtracted, but this process is subject to large errors due to limited statistics and the poor resolution of most detectors. Alternatively, the detector can be surrounded by additional detectors, operated as an anticoincidence shield. Directly-ionizing particles will produce signals in both the detector and the shield, and can be excluded from the neutron spectrum. For liquid-scintillation counters, pulse-height discrimination can be used to separate low-energy protons from minimum-ionizing secondary particles.

5.3.5 Solid-State Nuclear Track Detectors Stacks of etched track detectors, described in Section 5.2.4, for the conventional approach, can be used as passive dosimeters in a fluence-based system. These are integrating devices, of course, and cannot be used as real-time dosimeters.

5.4 The Microdosimetric Event-Based Approach

5.4.1 Introduction Microdosimetric event-based risk evaluation utilizes measured lineal-energy spectra and number of events to determine risk. Many devices which might be used to measure energy deposition in micrometer scale volumes have been proposed, but TEPC are the only type in common use. An alternative to measuring the full spectrum is to measure the first two moments of the spectrum. It has been shown (Zaider and Rossi, 1989) that the biological effectiveness of a radiation can be inferred from these moments with only a modest loss of precision relative to evaluations made using the complete spectrum.

5.4.2 Lineal-Energy Spectrometers Lineal-energy measurements are usually made using a low-pressure TEPC, although other types of detectors, including micrometer-sized solid-state detectors are being investigated. These detectors, both low-pressure gas and solid state, measure the ionization produced, and the data are typically analyzed with multichannel electronics.

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The event sizes typically range over more than four orders of magnitude, so the data are usually analyzed in at least two segments at different gains. Because ionizations are detected, the mean energy to create an ion pair limits the ultimate resolution of all detectors. Proportional counters provide a gas gain of about 300, which increases the signal relative to the electronic noise in the rest of the system. However, the electronic noise in the data acquisition system is generally the practical limiting factor. The spectrum of events is directly related to f (z) and can be used to evaluate q(z). Units with 512 channel resolution for lineal energy and which can detect changes in the environment with 5 s resolution have been used for dosimetry research on many Space Shuttle flights (Badhwar et al., 1996). The sum of the number of events times the energy in each event, when multiplied by a constant which includes the effect of the physical size of the detector, gives D. The spectrum of events has been unfolded to provide an estimate of the LET distribution for all but very short-range directly-ionizing particles, and the result can be used to calculate H by conventional methods. The unfolding process is not, however, a straightforward procedure. Lineal energy is generally measured with a tissue-equivalent detector, and assuming secondary-particle equilibrium, it measures energy deposition from directly- and indirectly-ionizing particles equally accurately. In situations where indirectly ionizing radiations with a wide range of initial energies are present, it may not be possible to obtain equilibrium for the highest energies without excessively attenuating the low-energy component, a limitation shared by all cavity dosimeters. Ideally, lineal energy would be measured in a detector consisting of a region in a medium of uniform density. The introduction of a change in density at the boundary of the detection region, that is, the use of a condensed phase wall to bound the detector, introduces the wall effect artifact described in Section 4.2. Charged particle tracks which branch, which produce energetic delta rays, or which curve significantly may produce two or more interactions in a single large cavity, while they would produce only one interaction in each of two or more sites in a uniform density situation. This reduces the number of small events and increases the lineal energy of some large events when a solid-walled detector is used. The magnitude of this effect has been measured and calculated for high-energy heavy ions (Brenner et al., 1981; Dicello, 1992; Dicello et al., 1991; Rademacher et al., 1998). The significance of these errors in measured lineal-energy spectra depends on the use to be made of the data, and in the case of calculating risk by the event-based method, on the value of the specific quality function [q(y)]. This

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increase in the lineal energy of the large events has to be accounted for if the event-based methodology were to be used in space applications. The magnitude of these differences for risk estimation has yet to be evaluated. In event-based systems, one of the practical limitations of the measurement system is the need to obtain statistically significant data for the full range of the event spectrum. The tissue volume simulated by the detector depends on the size of the sensitive volume and the density of the gas filling it. TEPC simulating a 1
m diameter volume can range from a few millimeters to many centimeters in diameter. However, the count rate in a given radiation field depends on only the physical area of the detector. Thus, the statistical precision of a measurement can be improved by increasing the projected area of the detector or the duration of the measurement. The pulse resolving time of the electronic system, which is generally limited by the increase in electronic noise with increasing bandwidth, typically limits the maximum count rate that a system can respond to with a full measurement. Thus, the physical size of a detector is generally a compromise between making it large to reduce the time needed to resolve the low probability portions of the event spectrum and making it small to avoid the chance of losing data in an abnormally high dose-rate situation (i.e., when multiple tracks pass through the volume within the resolving time).

5.4.3 Variance Method for Measuring Dose-Mean Lineal Energy It is also possible to measure the dose-mean of the lineal-energy spectrum (yD) by measuring the relative variance in repeated measurements of the total amount of ionization occurring in a detector in a fixed amount of time, assuming a constant dose rate. This is because the variance in the ionization is related to the size of the individual events. The relationship is: yD ⳱ Vrel

JW l

(5.1)

where J is the mean ionization, W is the mean energy expended per ion pair, and l is the mean chord length in the detector. The relative variance (Vrel) can be measured using cavity chambers such as lowpressure ion chambers or proportional counters, and is subject to the same wall effects that occur in the measurement of individual events. However, since gas gain is not required, smaller simulated site sizes can be used.

5.5 COMPARISON OF THE PRACTICAL LIMITATIONS

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5.5 Comparison of the Practical Limitations to Implement Each Methodology Different limitations exist for the practical implementation of each methodology. To implement the conventional methodology, LET spectra must be measured at appropriate locations. For example, an appropriately instrumented phantom might be used to obtain information on the variation of Q, the mean Q throughout the body. This combined with dose measurements within the phantom, plus a normalization point on the skin to scale similar dosimeters worn on the skin by the crew, could give an adequate approximation of the effective dose. This limitation also exists in the implementation of the eventbased methodology. Microdosimetric distributions measured within the spacecraft must be modified to reflect mean distributions in the tissues and organs of interest. The integrations over the measured lineal-energy spectrum to obtain q, the mean q value, would be the same as indicated above for the conventional approach, except that the specific quality function (as a function of y) would be used instead of the recommended Q versus LET function. At present, however, the accuracy of transport codes to estimate integrated quantities like mean absorbed dose (DT) and organ dose equivalent (HT) is good to 10 to 15 percent. This is not the case for calculating lineal-energy spectra as a function of depth (Badhwar and Cucinotta, 2000). The fluence-based approach would require a three-axis particle spectrometer outside the spacecraft to measure the primary particle spectra. These spectra would be used as input to radiation transport codes to transport the radiation first through the shielding of the spacecraft and then through the bodies of the crew to arrive at mean fluence spectra in the organs and tissues of interest. The spectra obtained could also be used to calculate (1) LET spectra in the organs of interest for implementation of the conventional approach, and (2) lineal-energy spectra in the organs of interest for the microdosimetric event-based approach.

6. The Biological Data Necessary

6.1 Review of Available Data As already discussed in Section 2, it is unlikely that an individual cell will be traversed more than once by an HZE particle or more than a few times by protons. Thus, both the fluence-based and the event-based approaches assume that the biological endpoint of risk results from the additive effects of single-particle traversals of cells and that risks from statistically-independent particle tracks are additive. If a fluence-based or microdosimetric event-based risk coefficient is to be used, it will be necessary to generate appropriate radiobiological data to help estimate risk. Ideally, the radiobiological data should be obtained by exposing biological test systems to a wide variety of particle/energy pairs. It is important to stress that these experiments should be performed at low fluences and fluence rates. These rates should translate to a probability of eⳮ1 (37 percent), or less, that no more than one track on average traverses a cell per cell-cycle time. This is an extremely stringent criterion for low-LET particles and will have to be relaxed somewhat in practice. Many of the currently available radiobiological data for HZE particles were obtained either at high dose rates or in the stopping region of the Bragg peak. Neither is ideal for estimating risk based on particle fluence. These studies may, however, suggest trends and questions that must be addressed. The RBE for high-LET particles obtained by extrapolating experimental data to low dose, RBEM, has been estimated for a variety of biological endpoints including cell killing, mutagenesis, in vitro transformation, cataract formation, and tumorigenesis in vivo. RBEM not only varies with LET or particle type but also varies with endpoint and the physical shape (flattening) and physiological condition of the cell. Although only a few tissues have been studied for each particle and endpoint, a wide range of RBE M values has been reported. For example, as summarized in NCRP Report No. 104, the RBEM for fission neutrons compared to gamma rays range from 5 to 50

6.1 REVIEW OF AVAILABLE DATA

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70 for mammalian mutation induction, from 3 to 80 for in vitro neoplastic transformation, from 10 to 46 for life shortening in the mouse, and from 16 to 59 for in vivo carcinogenesis (NCRP, 1990). Data for high-Z, high-LET particles are more limited than for lowZ, high-LET particles. Cell killing and specific locus mutagenesis data have been reported for iron, argon and lanthanum particles using human fibroblasts (Tsuboi et al., 1992). These particles ranged in LET from 150 keV
mⳮ1 (330 MeV amuⳮ1) to 920 keV
mⳮ1 (600 MeV amuⳮ1). The RBE for cell killing using gamma rays for comparison ranged from 3.7 to 1.3. Since risk estimates for space travel are chiefly based on the risk of developing cancer, it is useful to summarize the current state of information for this endpoint. In vitro neoplastic transformation data have been reported by Yang et al. (1985), but they were obtained after high doses and are not suitable for determination of RBEM. The available in vivo carcinogenic data with high-Z, high-LET particles are unfortunately very limited. Most of the available data come from experiments on radiation-induced cancers in the mouse Harderian gland. In an initial study, Fry et al. (1985) studied particles from 4He (228 MeV amuⳮ1) to 56Fe (600 MeV amuⳮ1). With the exception of 56Fe, in which the plateau beam was used, all irradiations used a spread Bragg peak. RBEM were estimated as RBEM ⳱ H / , where H is the initial slope of the dose-response curve for the heavy ions and  is the initial slope of a 60Co gamma-ray curve. The RBEM reported increased from five for 4He and reached 27 for both 40Ar and 56Fe. It is stressed that the interpretation of these results is confounded by the use of spread Bragg peaks for most but not all irradiations. In order to avoid these problems, the experiments were extended by Alpen et al. (1993). They continued to use the Harderian gland model, but exclusively used the plateau region of the beams. This study estimated the initial slope of the relationship between tumor yield and irradiation dose. Complete data were obtained for 4He ions (228 MeV amuⳮ1, 1.6 keV
mⳮ1) and 56Fe ions (350 MeV amuⳮ1, 253 keV
mⳮ1; and 600 MeV amuⳮ1, 193 keV
mⳮ1) and were compared to 60Co gamma-ray data. The RBEM for these three ions were 2.3, 20 and 40, respectively. Preliminary data for several additional ions are also reported including neon (25 keV
mⳮ1) and niobium (464 keV
m ⳮ1 ). In addition, preliminary data for lanthanum (953 keV
mⳮ1) have been published (Alpen et al., 1994). The data from these experiments were used to calculate fluencebased risk coefficients expressed as cross sections. The data can be plotted as log of the action cross section (
m2) versus log LET (keV
mⳮ1), as shown in Figure 6.1 from Alpen et al. (1993). The data can be fit with a straight line on a log-log scale for the LET range between

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6. THE BIOLOGICAL DATA NECESSARY

100

Niobium Iron–600

Cross Section (µm2)

10

1

Iron–350

Neon

0.1 Helium

Protons 0.01 Cobalt–60 0.001 0.1

1

10 LET (keV

100

1,000

µm–1)

Fig. 6.1. Experimentally determined action cross sections for Harderian gland tumor induction obtained with various mono-energetic charged particle beams as a function of LET. The line has been drawn to indicate that there is no significant deviation of the data from linearity (Alpen et al., 1993). 60

Co gamma rays and niobium. In principle, this curve should allow us to calculate risk for Harderian gland tumors for mixed irradiation in this range of LET and E. No definitive data are provided in this experiment to suggest a region in which the rate of tumor yield per unit fluence (or tumor yield cross section) reaches a plateau with increasing LET, although the data certainly do not rule out such a possibility. Figure 6.2 plots the action cross sections for the Harderian gland tumor data along with various endpoints of somatic mutation frequency and neoplastic transformation for different high-energy heavy-ion beams as a function of LET at relatively low doses (as reviewed in Curtis, 1994b; Curtis et al., 1995) as well as the conventional risk cross section (from Figure 4.1). There is evidence that the experimental cross sections might be reaching a plateau at high-LET.

6.2 The Mouse Leukemia and the Rat Mammary Carcinoma Model Systems While the data from the Harderian gland experiments serve to demonstrate the potential usefulness of a fluence-based risk

6.2 CARCINOMA MODEL SYSTEMS

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Action Cross Section (µm2)

100 10

Conventional Q Harderlan gland tumors

1

Neoplastic transformation HPRT mutants, human skin fibroblasts TK-total mutants, human lymphoblastoid cells

0.1 0.01 0.001 0.0001 0.00001 0.1

1

10 100 LET (keV µm–1)

1,000

Fig. 6.2. Action cross sections for various somatic mutation endpoints, Harderian gland tumor induction and neoplastic cell transformation obtained at various LET with high-energy heavy-ion beams. The conventional risk cross section derived using the recent recommendation of Q/LET dependence from ICRP and NCRP is also plotted (Curtis et al., 1995).

coefficient, they are admittedly limited in both physical and biological scope. The gland is not present in the human and so may not accurately reflect human carcinogenic response. While it is desirable to have extensive data on a variety of in vivo tumorigenesis models, practical limitations require careful choices. Possible choices include many experimental rodent tumorigenesis assay systems which have been previously used to study radiation carcinogenesis. These include mortality endpoints from leukemias, mammary, lung, skin, thyroid, liver and bone tumors (for examples, see Grahn et al., 1992; Raabe, 1989; Spiethoff et al., 1992; Storer and Fry, 1995). The mortality is low for thyroid and skin tumors and relatively low for liver and bone tumors. Two models are suggested here for further studies: the mouse myelogenous leukemia model and the rat mammary carcinogenesis model. Leukemia and breast cancer are prominent among the cancers associated with radiation exposure to humans. Good quantitative radiation carcinogenesis models are available for these organ sites. Baseline data are available for both low- and high-LET radiation at low doses. Importantly, these models have recently been used to define both the cellular and molecular aspects of neoplastic transformation. This may aid in interspecies extrapolation as well

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as eventually help in introducing cellular and molecular mechanisms into risk modeling studies. The mouse myeloid leukemia model has the advantage that the latent period is relatively short as well as having extensive highand low-LET baseline data for comparative studies. Radiation induction of myeloid cancer has been studied in several mouse strains with particular emphasis on the RFM (Ullrich and Preston, 1987) and CBA (Mole et al., 1983) strains. The CBA model is favored because a considerable amount is known about the molecular basis of the leukemogenic process in this strain. It should be noted that the RFM leukemia model has a neutron/gamma RBE of about three (Ullrich and Preston, 1987), a rather low value compared to other animal tumor systems. However, the data are not sufficient to determine the maximum value for stochastic effects, RBEM. Earlier studies have indicated that low-LET induced myeloid leukemia in the CBA mouse strain varies with the square of the absorbed dose, thus implying a large RBE at low doses (Mole, 1984). Studies with this model will not be easy because it will be difficult to meet the criteria of low fluence or low fluence rates and obtain significantly elevated excesses in incidence or mortality. For studying solid cancer malignancy, the rat mammary model is recommended over the lung model because the genetic and molecular etiology of the mammary model is better documented at this time. The rat model as opposed to the mouse model of mammary carcinogenesis is suggested because it is a better model of human breast cancers (Gould, 1995). While several outbred and inbred rat models have been used to study radiation carcinogenesis, an F-344 ⳯ WF hybrid rat as used by Kamiya et al. (1995) and Haag et al. (1996) would be a suitable model. The use of an F1 of two inbred strains will allow a comparative study of allelic imbalance in any resulting cancer (Haag et al., 1999). The F1 will also allow the use of pituitary isografting which will increase the sensitivity of this model.

6.3 Experimental Design Considerations Experiments with additional models should explore a wide range of ions and ion energies. These experiments should extend beyond the highest LET used to date in order to clarify the shape of the LET/cross-section curve at very high-LET because whether the curve continues to rise or approaches a constant is clearly important in determining the risk. The following ions and energies are suggested in future experiments: protons (200, 600 and 1,000 MeV), oxygen (100, 300, 600 and 1,000 MeV amuⳮ1), silicon (100, 300, 600 and

6.3 EXPERIMENTAL DESIGN CONSIDERATIONS

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1,000 MeV amuⳮ1), iron (200, 300, 600 and 1,000 MeV amuⳮ1), and niobium (300, 600 and 1,000 MeV amuⳮ1). This covers the LET range from 15 to 600 keV
mⳮ1, with overlapping values for two different ions, oxygen and silicon at 50 keV
mⳮ1, and for silicon and iron at 150 keV
mⳮ1. Attention must be paid to the ranges of these particles as some will not be appropriate for animal systems, since the variation of the LET through the target regions will be too large as the particles lose their energy. The low-LET, high-energy protons have been included because it has been suggested that nuclear target fragmentation processes will play an increasingly important role for them and an increased RBEM might be expected (Shinn et al., 1990). In addition, gamma-ray experiments should be performed to provide a strong baseline or anchor point for low-LET radiation. These recommendations are in general accord with those suggested at a workshop sponsored by the Armed Forces Radiobiology Research Institute to consider what additional biological data might be required to improve space radiation risk assessment (AFRRI, 1992). Consideration should also be given to experiments that simulate the radiation environment within the space vehicle, and thus include secondary radiations. There are few data that can be used to estimate risk from secondary neutrons that cover a broad energy range. Studies with these models should emphasize the comparison of initial slopes of tumor induction-fluence response curves at low fluences. They will thus likely require large groups of animals for statistically significant data to be acquired. Finally, not only should experiments be done with single exposures, but multiple exposures to both single and mixed-ion fields must be carried out to test the hypothesis that traversals are truly independent in biological activity and that a simple additive model of risk is appropriate (Curtis, 1994a). The mixed-ion studies can be done with spread Bragg peaks or, even better, with serial exposures to two different ions (e.g., protons and iron ions) as suggested by Dicello (1992). These experiments should also include measurements with appropriate microdosimetric instruments (i.e., TEPC), so that a continuing comparison can be made between the fluence-based and microdosimetric eventbased methodologies. In addition, appropriate in vitro models to measure mutation and chromosomal aberrations should be utilized with the beams and energies mentioned above to obtain initial slopes of fluence-response curves. In summary, the current biological data set provides initial encouragement for the use of a fluence-based risk coefficient. However, due to the limited amount of data available, many basic questions still remain unanswered. Further biological data are required before the utility of a fluence- or event-based risk assessment method can be fully realized.

7. Implementation and Comparison of Methods 7.1 Introduction Each methodology described in the previous sections has its strengths and limitations. The conventional absorbed dose and Q approach is well established in the literature of radiation protection, and workable measurement techniques for low-LET and neutron environments have been developed. Since this approach depends on mean quantities, however, it ignores the actual physical characteristics of energy deposition in cells. There is experimental evidence that biological effects are determined by characteristics of individual particle tracks traversing a cell population. This Section will show how the two radiation protection systems outlined in Section 4 might be implemented and will discuss the consequences of each in terms of equipment requirements, potential errors, and record-keeping requirements. Each system will be described in the context of a risk-based radiation protection system. That is, the numerical results will be expressed as a mean excess risk of cancer for the individual. This approach eliminates the need for absorbed dose and mean quality factor, although these quantities can be calculated from the data if necessary. If age- and sex-dependent risk coefficients are to be estimated, the instrument or system which produces the risk value must have available the relevant data on the individual being exposed.

7.2 Risk Assessment There are two different aspects of risk assessment that should be kept in mind relating to the extended space missions considered here: (1) predicting the risk to a crew member from a given mission scenario before it occurs in order to evaluate whether adequate shielding is available and/or appropriate avoidance protocols are in place in a given space transfer vehicle or environmental habitat design, and (2) assessing the risk during and after the mission, when 56

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dosimetric data will be available for determining the quality and quantity of the radiation environment to which the crew is being or has been exposed. It is possible that different types of methodologies should be used for each. For predicting risk, no dosimetric data will be available and databases must be used. Thus, heavy reliance will be placed on both the presently available knowledge of radiation environments, and computer codes that transport the incident radiation through the spacecraft walls and the bodies of the crew members into the organs of interest.

7.3 The Fluence-Based System For risk prediction, the procedure of implementation is straightforward: a table of cross sections r
i (L) [or r
i (E)] (or an algorithm for generating these values) for all combinations of i (the charged-particle type) and L (the LET) [or E (the energy)] is necessary. It is immaterial whether the cross section is expressed as a function of LET or E. The important point is that different particle types at the same LET, but having different charge and energy, may produce different biological responses (in magnitude) and, therefore, may have different risk cross sections associated with them. In the future, it may be possible to generate values of r
i (L) from a model based on a mechanistic understanding of the biological processes involved in carcinogenesis for each tissue, but at present they must come either from an assumption about the cross-section dependence on some kinetic parameter (as is done, for example, in Section 7.5) or from experimental data on endpoints that are considered surrogates for the human carcinogenic endpoint. The initial slope of a fluenceversus-response curve is the action cross section for the endpoint measured. The variation of this quantity with some kinetic variable of the particles constituting the beam (e.g., energy or LET) is assumed to describe the variation of the risk cross section for a given cancer in humans. The anchor point or baseline value at low-LET is the risk cross section for gamma rays as given in Equation 4.14, where an appropriate value for K can be obtained from Table 3.1. The procedure depends on the assumption that the risk cross section for human cancer varies with the kinetic variable (energy or LET) of the particles in the same way as the action cross sections for the experimentally observed endpoint(s). It also depends on the assumption that the endpoint(s) experimentally observed, as well as the induction of human cancer, are dominated by single-track effects at fluences in the range of interest in space radiation protection. The

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assumption, however, of a universal function applicable to all particles as a function of LET is no longer necessary, and the multivalued nature of the risk for different particle types at the same LET is explicitly acknowledged and provided for in the procedure. The values of r
i (E), where E is the particle kinetic energy per atomic mass unit, can be plotted as a three dimensional surface, and this surface will be different for each endpoint (tumor type) and for each age-at-time of exposure, as well as being different for males and females. Furthermore, it is evident that there will never be sufficient epidemiological data to determine all these risk cross sections for humans. For charged particles and neutrons, the risk cross sections will have to be extrapolated across species from data gathered from appropriate animal and cellular systems. In Section 6, several biological systems are suggested as suitable model systems from which to obtain the fluence-response curves at low fluence, and that data for protons, oxygen, silicon, iron and niobium ions would provide sufficient data to interpolate to values of r
i (E) for any radiation expected to be encountered. It will be satisfactory to apply scaling factors, based on epidemiological data, to adjust for the various tumor types, age-at-time of exposure, and gender of crew member. For missions outside the magnetosphere, the fluence spectra [ i (E)] in the organ of interest may be calculated from the experimentally (or theoretically) obtained free-space GCR spectra at appropriate times throughout the solar cycle. These data can then be used as input to experimentally validated radiation transport codes which have already been developed for this purpose. The mean excess risk can be calculated using Equation 4.1. For risk assessment, the table of values of r
i (E) or r
i (L) mentioned above is required, as well as instrumentation for measuring fluence as a function of particle type and energy. The fluence spectra of directly ionizing particles can be obtained using the active and passive devices described in Section 5. The size and complexity of some of these systems and the complex response functions of others, however, may limit their applicability. Charged-particle spectrometers will be the primary devices measuring the radiation in a particle fluence-based protection system. Since these devices respond only to directly-ionizing radiations, they will generally be located where they can measure the incident charged-particle fluence far enough outside a space vehicle or habitat so that nuclear fragmentation has not altered the spectrum and there are few indirectly-ionizing particles. In order to measure directional fluences associated with the trapped radiation belt (in the case of a space station) or solarparticle events either inside or outside the geomagnetosphere, three directional spectrometers will be necessary. On a few flights, a

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neutron-sensitive device may also be necessary inside the vehicle to measure independently the contribution of neutrons and to provide a check on the neutron component calculated by the transport codes. If two particle spectrometers are used in conjunction, one outside and one inside the spacecraft behind a known amount of shielding, a check can be made of the transport codes by using the outside spectra as input to the codes to determine how accurately the calculated and experimentally obtained spectra agree inside the shielding (Badhwar et al., 1995). The outside spectra can then be used as input to radiation transport computer codes to calculate the mean spectrum in the organs of interest within the crew members, assuming (1) knowledge of the shielding distribution of the space vehicle or habitat and (2) a computerized anatomical male and female (Billings and Yucker, 1973; Yucker and Huston, 1990). These calculations will include production of indirectly-ionizing particles and their directly-ionizing secondaries, as well as production of additional directly-ionizing particles by projectile and target-atom fragmentation processes. The movement of crew members throughout the spacecraft will cause them to experience an ‘‘effective’’ or mean shielding somewhere between the minimum and maximum shielding thickness provided by the spacecraft. It is expected that such a mean can be adequately approximated since the shielding characteristics of the spacecraft will be well-known ahead of time. The mean excess risk for an individual can then be estimated by adding the risks to all the organs of interest calculated using Equation 4.1 (or Equation 4.2) for each organ. This risk can be compared directly with the risk deemed to be acceptable for the specific activity leading to the exposure, for example, the values suggested in NCRP Report No. 132 (NCRP, 2000) for space activities in low-earth orbit or subsequent recommendations. Passive devices such as plastic nuclear track detectors can be used to record that portion of the directly-ionizing fluence that is above the LET threshold of the detector. A calibration in terms of total fluence is generally made in a representative radiation environment, with representative shielding, so that these devices can be used as badges to be worn by individuals. However, if the incident spectrum or the intervening shielding changes, this calibration would have to be redone. TLD can also be used to determine the total energy deposited, i.e., the absorbed dose, if proper corrections are made to allow for the saturation of signal at high-LET. Although these dosimeters do not provide fluence data directly, they do respond to particles with low-LET, and can be used to estimate the total fluence of particles

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below the threshold of a track etch detector by subtracting the total absorbed dose due to the fluence measured by the track detector and assuming energy spectra for the low-LET component.

7.4 The Microdosimetric Event-Based System In a lineal-energy based system, mean individual risk is calculated as indicated below in Section 7.6.4. In order to do this, one must know the function  (z), or equivalently  (y), and measure f1 (z) or f(y) and the total number of events. Radiation protection limits would be used in the same way as with a particle fluence-based system; that is, they would be based on excess risk. Risk prediction would be obtained by calculating the lineal-energy spectrum in micrometer volumes for specific locations within the bodies of the crew, using the known incident particle spectra and the radiation transport codes mentioned above. The basic assumption underlying the use of q(y) is that equal values of lineal energy produce equivalent biological responses. Thus in this system, it is possible to use q(y) relationships which have been derived from a wide variety of radiation exposures which should, of course, include high-energy heavy-ion beams. Different relationships would be found for each endpoint, and an appropriate relationship for health effects in humans would have to be determined by tissue and species extrapolations. For risk assessment, the lineal-energy density [f(y)] and the number of events would be determined directly from measurements with low-pressure TEPC which simulate a site size between 0.25 and 10 m in diameter (1 m is most commonly used). These detectors would be used with a multichannel analyzer which produces a histogram of the number of events at each pulse height. When normalized to unit area and calibrated in terms of lineal energy (using an internal calibration source or a known feature of the measured spectrum), this histogram is f(y). The total energy deposited by events in an interval dy is determined by multiplying the number of events recorded in that interval by the mean energy in the interval, and by a factor which corrects for the effect of the cross-sectional area of the detector as well as the change in units. Lineal-energy spectra can be measured at any position within or outside a space vehicle or habitat. The detectors are relatively small (size depends on the count rate required to obtain good statistics in an acceptable time interval) and can be introduced into phantoms when necessary. Two-centimeter diameter detectors have been

7.5 COMPARISON OF FLUENCE- AND EVENT-BASED SYSTEMS

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satisfactory for determining the time-dependent lineal-energy spectra on the Space Shuttle. They have been used to map changes in the position of the South Atlantic Anomaly with a resolution of a few seconds (Badhwar et al., 1994b). The response of the detectors is essentially omnidirectional, which complements the assumed random motion of crew members within the spacecraft since the timeaveraged event numbers in each organ is needed for risk prediction. Since some uncertainty remains about the impact of the wall effect on lineal-energy-spectra measured in space, experiments should be undertaken with ‘‘wall-less’’ detectors. Comparison of matched 2 cm diameter detectors in 10 and 15 cm diameter tissue-equivalent vacuum chambers with the 2 cm diameter solid-walled detector will provide the data required to evaluate the wall effect in terms of its impact on risk assessment.

7.5 Comparison of Fluence-Based and Microdosimetric Event-Based Systems Both the fluence-based and microdosimetric event-based methodologies provide a way of dealing with the major objection to the conventional system: using LET alone as a universal physical descriptor of the radiation field to determine the biological effect (i.e., the risk). The fluence-based system allows for different values of the risk cross section for different particle types having the same LET. In the event-based system, it is assumed that a universal function for biological effect (risk) exists as a function of the amount of energy deposited in an appropriate target tissue volume. Since experimental data of tumor incidence in humans as a function of radiation quality are not available now nor will data be available in the future, both approaches must rely on experimental data obtained from low-fluence or low-event-number (per cell nucleus) experiments with surrogate endpoints assumed to represent the carcinogenic process in humans. For the fluence-based approach, the experiments must be done with accelerated beams representative of the highenergy heavy particles found in the space environment. Here the identity of the incident particles is known and the energy can be easily measured. Interpolation between energies is done under the assumption that the function will vary smoothly as a function of particle energy. Interpolation between charges is done assuming that at a given energy (or LET) the function varies smoothly as a function of charge. The microdosimetric event-based approach requires a measurement of the lineal-energy spectrum by TEPC or

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7. IMPLEMENTATION AND COMPARISON OF METHODS

similar instrument, and it is necessary to establish that the simulated site size is biologically relevant. In this approach it is not necessary to know the type of radiation in the beam. The instrument should be one for which the wall-effects for the particular beam are known to be negligible. Each approach will benefit from additional new experiments with high-energy charged-particle beams in order to be implemented. The assumption that each particle type and energy may produce a different risk cross section is implicit in the particle fluence approach; therefore, data for a significant number of particle types and energies for each endpoint must be gathered. Since very little of this type of data currently exists for relevant endpoints at appropriately low fluences, new measurements will be required as outlined in Section 6. In the case of the event-based approach, all particles producing equal lineal energy are assumed to produce the same effect; therefore, a smaller number of additional experiments may need to be performed. Existing effectiveness functions, based primarily on neutron and low-energy track-segment irradiation data might be used on an interim basis, but effectiveness functions based on data over a range of energies for various high-energy particles will have to be developed. Use of lineal energy in the definition of the risk requires specification of the site size. One micrometer is generally used because it is convenient for practical measurement, and because the precise value does not appear to be critical for most combinations of currently available radiations and biological endpoints. However, this selection is essentially arbitrary, and it is not possible to use data collected for one site size to determine what the lineal-energy spectrum would be for any other site size. There is evidence that much smaller sites, on the order of a few nanometers in diameter, are critical in the production of the initial damage which leads to health effects. On the other hand, for most radiations, particularly those encountered in space, the lineal energy in micrometer-size sites is approximately proportional to that in nanometer-size sites (i.e., the energy deposited is scaled by the ratio of the site sizes). The primary difference between the lineal energy and stopping power in these small sites is the energy transported out of the site by delta rays. The fraction lost in this way depends on the delta-ray spectrum, and therefore on the ion velocity, but not on the identity of the ion. Furthermore, the fraction lost changes very slowly for ions with energies above a few million electron volts. The proportionality between energy deposited in large and small sites is lost only for very low-energy directly ionizing particles, or indirectly ionizing radiations such as x rays below 50 keV which produce low-energy secondaries. These

7.5 COMPARISON OF FLUENCE- AND EVENT-BASED SYSTEMS

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63

short-range charged-particles sometimes stop in a large site and the resulting energy deposition is interpreted as a low value of lineal energy even though the stopping power for the track segment within the detector was much larger. In the case of a 100 MeV proton which does not produce target-atom fragmentation, only 0.1 percent of the energy is deposited by the last 100 keV of the track, where the particle can stop in a micrometer-diameter site. With respect to possible future reevaluation of dosimetry data, particle fluence as a function of energy is more versatile than lineal energy. Lineal energy can be calculated unambiguously from the fluence spectrum, but the reverse cannot necessarily be done. Furthermore, any currently imaginable property of the energy transfer by charged particles can be derived from the fluence spectrum, while most other quantities cannot be derived from lineal energy. This added versatility, however, comes at the price of having to record and store a much more detailed description of the radiation field. Lineal energy can be represented with reasonable accuracy by a two-dimensional plot of a few dozen logarithmically-spaced data bins. While particle-fluence spectrometry may require a threedimensional array and potentially more data acquisition is necessary, only moderate resolution of charge and energy is needed to predict biological effects and estimate risk. The resolution in energy will depend on the time of data collection (i.e., the amount of data collected), but the charge of the particle is obtained for each track. A major difference between the two approaches in terms of practical application is the complexity of the detector and electronic systems required to implement them. Lineal energy can be measured with good precision using a self-contained system which weighs less than a kilogram. Systems of this sort, which are currently in use as Space Shuttle instruments, have essentially isotropic response and provide a display of dose equivalent and dose equivalent rate in real time at the position of the instrument. Other instruments would have to be installed, however, to obtain information on the directionality of the incoming radiation and to provide the absorbing characteristics of the fields in order to extrapolate the microdosimetric spectra to the organs of the crew members. Alternatively, microdosimeters could be installed inside human phantoms to measure y spectra at the positions of the organs at risk. Charged-particle spectrometers have been used for dosimetry as well as for physics experiments on board the shuttle. One system, which utilized the same electronic technology as the lineal-energy spectrometer described above, required approximately four times more electronics, and was approximately four times heavier than the microdosimeter. This charged-particle spectrometer was sensitive to

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particles within a 66 degree acceptance cone and would be able to collect the necessary data for risk assessment in an isotropic field such as exists for the GCR outside the geomagnetosphere. For an anisotropic field, measurements would have to be made with three different detector orientations to determine the angular distribution of the incident particles. These measurements and the resulting calculations, of course, would be time consuming. The time required for this fluence evaluation procedure could be decreased by using an omnidirectional detector or several detectors pointed in different directions, and expediting data transmission to a high-speed computer for analysis. With current technology, however, a three-axis charged-particle spectrometer would weigh approximately 12 kg. The data to characterize a single particle includes a minimum of 10 bytes (80 bits) to give the energy deposited in the 10 energy detectors plus 4 bytes to define the trajectory and another 6 bytes for coincidence flags and event identification. If the three detector systems captured a total of 100 particles per second, 16,000 bits of information would have to be recorded and stored. Data transmission requirements could be reduced by selecting specific types of events for detailed analysis. For example, selecting all data for particles of Z ⱖ 2, but only a five percent random sample of particles with Z ⳱ 1, would greatly reduce the amount of data with little loss of resolution. Advances in electronic technology will make it possible to reduce the size and weight of the electronics for both the charged-particle and the lineal-energy spectrometers. The detector sizes for both systems may also be reduced, but this would be at the cost of increasing the time required to acquire statistically significant results. In any case, lineal-energy spectrometers are likely to maintain a substantial size and weight advantage relative to charged-particle spectrometers, at least for the near future. The implementation of the fluence-based system would rely on charged-particle spectrometers to measure the incident chargedparticle spectra, before nuclear fragmentation could introduce significant numbers of neutrons and photons, along with a calculation of the directly- and indirectly-ionizing particle fluence at the position where crew members would actually be exposed, using a welldeveloped radiation transport code. 7.6 Comparison of All Three Methods for a Given Space Radiation Scenario 7.6.1 Introduction In order to compare the application of the three methodologies discussed previously (i.e., the conventional, the fluence-based, and

7.6 COMPARISON OF ALL THREE METHODS

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65

the microdosimetric event-based systems), a radiation environment was defined as follows: The 1977 (solar minimum) differential energy-fluence spectra of GCR were assumed to be isotopically incident on a spherical aluminum shell of thickness 10 g cmⳮ2. This thickness is typical of that to be expected on a rather well-shielded spacecraft outside the magnetosphere. Placed at the center of the shell is a sphere of ‘‘red bone marrow’’ of radius 2.5 g cmⳮ2. This thickness was chosen so that secondary nuclear particles (including neutrons) would be roughly in equilibrium within a hydrogenous organic material as will be the case inside a human body. Spectra of all the primary and secondary charged particles found at the point at the center of the concentric spheres were used in the analyses. The calculated spectra of all particles from protons to nickel were kindly provided to us by Drs. Francis Badavi and John Wilson of the NASA Langley Research Center using the computer code BRYNTRN/HZETRN. From these spectra, the various quantities of interest were calculated. The goal was to arrive at an excess risk of all cancers assuming a year’s exposure from this environment, and assuming an excess risk coefficient of four percent per sievert (Table 3.1). This value serves as the low-LET anchor point for the fluence-based and microdosimetric event-based systems.

7.6.2 Conventional Method Equations 3.1 to 3.4 were used to calculate the excess risk for a year’s exposure. The function D(L) dL is written: D⳱

 D(L) dL ⳱ K  L  (E) dE i

i

(7.1)

i

where Li is the LET of the ith particle type,  i (E) is the differential energy spectrum of the ith particle type, charged-particle equilibrium is assumed and summation is over all the different types of charged particles. The constant K converts the units. The expression for H at a point, Equation 3.1, becomes: H⳱K

  Q (E) L  (E) dE i

i

i

(7.2)

i

where Q at a given energy now depends on the particle type. The most recent ICRP definition of Q as a function of LET (Figure 3.1)

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7. IMPLEMENTATION AND COMPARISON OF METHODS

was used. A three-dimensional view of Q as a function of both log [energy (in MeV amuⳮ1)] and charge (Z) is shown in Figure 7.1. The summations and integrations of Equation 7.2 for this scenario yield an H of 0.67 Sv for a year’s exposure. The total D at a point for the year (from Equation 3.3) is 0.19 Gy giving a mean quality factor (Q) of 3.5. The mean quality factor for each charge contribution (Qi) is given by:

Qi ⳱



Qi (E) Li  i (E) dE



(7.3) Li  i (E) dE

and the fraction of absorbed dose contributed by each charge component is: L  (E) dE  f ⳱   L  (E) dE i

i

(7.4)

i

i

i

i

Each of these and their product, Q i ⳯ fi, are shown as a function of the charge (Z) of the particle in Figure 7.2.

Q 0 5 10 15 20 25 30

Proton peak

–4 Log

5

–2 [en

0 y (M eV

erg

2

am u –1 )]

20

4

25

15 rge ha

10 (Z)

C

Fig. 7.1. Three-dimensional plot of Q as a function of both the log of the particle energy in million electron volts per atomic mass unit and the particle charge.

7.6 COMPARISON OF ALL THREE METHODS

100

67

– Qi

10 – – Qi, fi, fi Qi

/

– fi Q i

1 0.1 0.01

fi

0.001 0.0001 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Charge (Z )

Fig. 7.2. Qi, fi (from cosmic-ray ion type i with Z) and fi times Qi are plotted against Z of the cosmic-ray ion, at the dose measurement point.

Assuming an exposure such that all organs of the human body uniformly received the calculated H of 0.67 Sv (so that effective dose equals H calculated here at a point), the kc of 0.04 Svⳮ1 can be used (Table 3.1) to arrive at 2.7 percent for an excess risk of all cancers from a 1 y exposure.

7.6.3 Risk Cross-Section Approach In principle, the determination of risk is straightforward for the risk cross-section approach using Equation 4.1. In practice, however, as mentioned in Section 4.1, the energy dependence of risk cross sections for each individual charge component, r
i (E), has not been determined. Here in order to show how the system would work, the ad hoc assumption is made that the risk cross section is a universal function of a quantity Z*2 / 2, where Z* is the effective charge of the particle [accounting for variations in charge (Z) at very low velocity due to electron pickup] and  is its velocity relative to that of light. This quantity has been suggested before as an indicator of biological effect (e.g., Curtis, 1970; 1986; Katz et al., 1971). Although a justification for its use can be given in that it is proportional to the number of electrons (delta rays) produced per unit track length (and so, perhaps, to ionization clustering), its use here is simply to show how the risk cross-section methodology would work with a function that provides different values of the cross section for different particle types at the same LET. The functional form of the cross section

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7. IMPLEMENTATION AND COMPARISON OF METHODS

was taken from the ‘‘lethal, potentially lethal cell-killing model’’ formulation (Curtis, 1986). In that development, cell killing was the endpoint, but the functional form is used here as an illustration for carcinogenesis as well. The formula for the cross section is as follows:


(  ) ⳱
1 {1 ⳮ [eⳮa  (1 Ⳮ a )] n } Ⳮ
2 aeⳮa  2

2

(7.5) 2

where  is Z* /  , and there are four constants:
1 ⳱ 20 m , a ⳱ 4 ⳯ 10ⳮ4,
2 ⳱ 3 m2, and n ⳱ 10. The constant
2 was adjusted to yield the correct value of the cross section at low-LET (low-Z), and
1 was adjusted to give values close to those at high-LET for the Harderian gland tumorigenesis mouse data (see Figure 6.1). In addition, it has been pointed out that nuclear reactions involving target fragmentation (carbon, nitrogen and oxygen in the target molecules) from the light ions (Z ⳱ 1, 2, 3) can significantly increase Q (Shinn et al., 1990) and their risk cross sections (Curtis et al., 1992) for particle energies above a few hundred million electron volts per atomic mass unit. Their risk cross sections must be included in the calculation. For this example, the cross sections calculated from Equation 7.5 were modified by the ratio of Q calculated including target fragmentation to that calculated neglecting target fragmentation. The function, Equation 7.5, without target fragmentation is shown in Figure 7.3. Since particles with the same  do not have

Risk Cross Section (µm2)

100

10

1

0.1

0.01

0.001 1

10

100

1,000

10,000

100,000

Z*2/β 2 Fig. 7.3. Risk cross section as a function of Z*2 /  2, where Z* is the particle charge and  is the velocity relative to that of light. The analytical expression is given in the text.

7.6 COMPARISON OF ALL THREE METHODS

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69

the same LET, different cross-section curves result as a function of LET for each particle. Risk cross sections versus LET for protons (Z ⳱ 1), helium ions (Z ⳱ 2) (both corrected for target fragmentation), neon ions (Z ⳱ 10), iron ions (Z ⳱ 26), and niobium ions (Z ⳱ 41) along with scaled Harderian gland tumor experimental data are shown in Figure 7.4. The proton (Z ⳱ 1) curve, neglecting target fragmentation, is also shown in the figure. This curve is used to fix the low-LET point to correspond to the gamma-ray data at Hiroshima. With this formulation, differences are noticeable for values of the cross section for particles at the same LET. This formulation, for example, predicts a difference of a factor of three in the cross sections between neon ions and helium ions at a LET of 30 keV mⳮ1. The dependence of cross section on particle velocity and charge results, of course, in a unique dependence of cross section on particle energy for each particle type. This is shown in the three-dimensional

Risk Cross Section (µm2)

100

Z = 41

10 Z=2 Z = 26 Z = 10

1

0.1

0.01

Z=1

Z = 1 (no fragmentation)

Z=1

Gamma (exp.)

Z=2

Z = 2 (exp.)

Z = 10

Z = 10 (exp.)

Z = 26

Z = 26 (exp.)

Z = 41

Z = 41 (exp.)

Z = 1 (no fragmentation)

0.001 0.1

1

10

100

1,000

10,000

LET (keV µm–1) Fig. 7.4. Risk cross sections as a function of LET for five particles (protons, helium ions, neon ions, iron ions, and niobium ions) plotted with the Harderian gland tumorigenesis data which have been normalized to match the low-LET point (gamma rays) at 0.24 keV mⳮ1. Corrections have been made for target fragmentation from the protons and helium ions. The result for no target fragmentation from protons is also shown; this is used for scaling to the gamma-ray data at low-LET.

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7. IMPLEMENTATION AND COMPARISON OF METHODS

plot in Figure 7.5, where the risk cross sections for all components in the GCR from protons to nickel (Z ⳱ 1 to 28) are plotted as a function of the logarithm of the energy per nucleon. These functions can then be used in Equation 4.1 to calculate total risk from the same energy spectra which were used in the conventional treatment above. The result is an increased risk of cancer mortality of 2.4 percent for a 1 y exposure. Neglecting the target fragmentation by light ions (Z ⳱ 1, 2, 3) yielded a 2.1 percent risk in a year’s exposure. The risk per year from each particle type is: Ri ⳱


(E)  (E) dE. i

(7.6)

i

In order to compare these results with the conventional and microdosimetric results, a quantity analogous to Qi must be defined. It is given the symbol Q i. It is the risk for each particle type (Ri) divided by the product of the risk coefficient [in risk per unit dose equivalent (H)] and the absorbed dose from that particle type (Di).

Log [e

nergy

ge har

(Z)

(in Me

V nucle

on –1)] Risk Cross Section (µm2)

C icle

Risk Cross Section (µm2)

t Par

)

ge ar

Log

e cl

[en

(Z

Ch

erg

rti Pa

y (i

nM

eV

nuc l

eon –1 )]

Fig. 7.5. Risk cross sections as a function of the logarithm of the kinetic energy (in MeV nucleonⳮ1) for all GCR particles from protons (Z ⳱ 1) to nickel (Z ⳱ 28). Corrections have been made for target fragmentation from protons, helium and lithium ions.

7.6 COMPARISON OF ALL THREE METHODS

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71

The risk per unit dose equivalent has been taken to be four percent per sievert, to be consistent with the value used for the risk cross section (see Section 4.1.4). In Figure 7.6, Q i is shown, along with the fractions of risk per year and absorbed dose per year for each particle type in the GCR spectrum from protons to nickel ions. The fraction of absorbed dose contribution from each particle, of course, does not depend on the approach taken to determine risk. The mean value of the risk per (risk coefficient ⳯ dose) for the entire spectrum, i.e., Q , the factor analogous to the mean Q (i.e., Q), is 3.1. The inclusion of target fragmentation by the light ions has increased the value from 2.7.

7.6.4 Microdosimetric Event-Based Approach

i, Fraction of Risk, Fraction of Dose

To implement the microdosimetric approach, a parallel analysis was made to obtain a universal function q(y) using the same Harderian gland tumorigenesis data (Zaider, 1996) and the same energy spectra used for the other two methodologies. The calculated values for the tumor prevalence per unit absorbed dose were taken as the

10 i, risk/(risk coefficient x dose)

1

Fraction of risk Fraction of dose

0.1

0.01

0.001

0.0001

1

5

10

15 Charge (Z )

20

25

30

Fig. 7.6. Top line is the risk/(risk coefficient ⳯ dose) Q i, middle line is the fraction of risk of excess cancer mortality from a 1 y exposure to GCR, and bottom line is the fraction of absorbed dose contributed by each particle type at the dose measurement point, all plotted as a function of particle type in the GCR (Z is the charge of the particle).

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7. IMPLEMENTATION AND COMPARISON OF METHODS

initial slopes (i) for the dose effect curves from the i different particle types. For each particle type, Monte Carlo transport programs (Zaider et al., 1983) were used to obtain microdosimetric spectra in 1 m diameter sites. These spectra are shown in Figures 7.7 and 7.8. Figure 7.7 shows the number of events in a given range of lineal energy. With the exception of protons and helium ions, most of the energy depositions (events) in 1 m diameter sites occur following traversal of low-LET secondary electrons (delta rays) and not from 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.5 0.4 0.3 0.2 0.1 0.0

Co60

He 1.6

10–2 10–1 100 101

y f (y)

Protons 0.4 keV µm–1

0.6 0.5 0.4 0.3 0.2 0.1 0.0

Ne 25

102 10–2 10–1 100 101 102 103

Fe 253

Fe 193

ε(y)

Nb 464

10–1 100 101 102 103

10–2 10–1 100 101 102

103

y (keV µm–1) Fig. 7.7. Microdosimetric spectra are shown for 60Co gamma rays, protons, helium ions, neon ions, two different energies of iron ions, and niobium ions, corresponding to the LETs given, which are relevant to the Harderian gland tumor induction experiments (Alpen et al., 1993). These are event or frequency spectra (the height is proportional to the number of events in a given lineal-energy range). The resulting hit-size effectiveness function [ (y)] is shown in the lower left (Zaider, 1996).

7.6 COMPARISON OF ALL THREE METHODS

1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 1.2 1.0 0.8 0.6 0.4 0.2 0.0

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73

Protons 0.4 keV µm–1

Co60

He 1.6

Ne 25

y d(y)

10–2 10–1 100 101 102 10–2 10–1 100 101 102 103 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

Fe 193

Fe 253

24.0 18.0

Nb 464

q(y)

10–1 100 101 102 103

12.0 6.0 0.0

10–2 10–1 100 101 102 103

y (keV µm–1) Fig. 7.8. Microdosimetric spectra are shown for 60Co gamma rays, protons, helium ions, neon ions, two different energies of iron ions and niobium ions, corresponding to the LET given, which are relevant to the Harderian gland tumor induction experiments (Alpen et al., 1993). These are fractional dose spectra (the height is proportional to the fraction of dose in a given lineal-energy range). The resulting specific quality function [q(y)] is shown in the lower left (Zaider, 1996).

the primary ions. Figure 7.8 shows the same spectra but in a representation where the curves are proportional to the fraction of absorbed dose [ (y)] from events in a given range of lineal energy. Contrary to the frequency distributions of Figure 7.7, these spectra show the dominant role (in terms of absorbed dose) of the primary ions. To unfold the function q(y), a nonparametric approach based on Bayes’ estimation and maximum entropy techniques was used

74

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7. IMPLEMENTATION AND COMPARISON OF METHODS

(Zaider and Minerbo, 1988). This insures the most unbiased estimator of q(y), given the slope. The resulting curve is shown as the hitsize effectiveness function  (y) in Figure 7.7 and as the specific quality function q(y) in Figure 7.8. No particular meaning should be attributed to the details of the shape of these curves. Their (rather unorthodox) shape reflects the entire information available from the limited amount of data available for this analysis. Any other, perhaps less jagged, solution will have in it additional assumptions which, to be included, must be justified from a priori knowledge. The mean specific quality factor (q), is: q⳱



qi (E) i (E) dE

(7.7)

0

i

where i (E) is the fraction of the total dose in the interval (E, E Ⳮ dE) from the ith particle type. The quantity qi (E) for the ith particle type is given by: qi (E) ⳱



q(z) i (z,E) dz

(7.8)

0

where i (z,E) dz is the fraction of dose delivered by microdosimetric events with specific energy in the interval (z, z Ⳮ dz) for the ith particle type with energy E. qi, the mean qi for a particle of type i, is: qi ⳱



qi (E) i (E) dE

(7.9)

0

where the fractional absorbed dose here is relative to the absorbed dose contributed by the ith particle type in the interval (E, E Ⳮ dE). In terms of these quantities, q, the mean q for all particle types, is: q⳱

f q i

i

(7.10)

i

where fi is the fraction of absorbed dose from the ith particle type. Examples of the variation of the fractional dose with the logarithm of the particle energy per atomic mass unit are given in Figure 7.9 (solid lines, left-hand ordinate). The figure shows E times (E) versus log E; consequently, the area under the curve delimited by any two energy values is proportional to the fractional absorbed dose delivered by particles with energy in that particular interval. Microdosimetric spectra have been calculated over a grid of energies for each particle type. These results have been used to obtain qi (E) from

/

7.6 COMPARISON OF ALL THREE METHODS

0.09 0.06

q–i=1.3 fi =0.64

H

q–i=1.4 fi =0.15

He

6 3

0.03

Fraction of Dose [ i (E)]

0.00 0.015 0.010

9

0

q–i=2.4 fi =0.04

O

q–i=2.2 fi =0.03

C

12 9

0.005

6 3

0.000

0

0.015 0.010 0.005

q–i=15.9 fi =0.02

q–i=2.5 fi =0.02

12 Mg

Fe

0

0.015

0.005 0.000

9 6 3

0.000

0.010

q i (E)

0.12

75

q–i=2.6 fi =0.015

12 Si

N

q–i=1.9 fi =0.012

9 6 3

0 10–1100 101 102 103 104 10–1100 101 102 103 104 105

E (MeV amu–1) Fig. 7.9. The solid lines show the variation of the fraction of absorbed dose deposited [⌬i (E)] with the logarithm of the particle energy per atomic mass unit (left-hand ordinate) for protons, helium, oxygen, carbon, iron, magnesium, silicon and nitrogen ions. The dashed lines are the specific quality factors (right-hand ordinate) as a function of energy for each ion [qi (E)]. The mean values of the specific quality factor (qi) and fractional absorbed dose (fi) are given in each panel for each ion (Zaider, 1996).

Equation 7.8, after making the conversion y ⳱ 4.9 d 2z. The dependence of qi (E) is shown in each panel of Figure 7.9 (dashed line, right-hand ordinate) as a function of energy per atomic mass unit for the eight particle types chosen. These values have been normalized to the Hiroshima spectrum as discussed in Section 4.2.3, and therefore represent the ratio of the two integrals in Equation 4.32. A summary of these results is displayed graphically in Figure 7.10 in the same format as for the other approaches. Variation is shown

76

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7. IMPLEMENTATION AND COMPARISON OF METHODS

– qi

101

– qi, fi – qi, fi

100

– f i qi

10–1

10–2

10–3

fi

10–4 0

4

8

12

16

20

24

28

Charge (Z ) Fig. 7.10. Variation of mean specific quality factor (qi) (top curve), the product fi qi (middle curve) and the fraction of absorbed dose (fi) (bottom curve) as a function of particle charge (Z) in the GCR.

as a function of charge from 1 to 28 of mean specific quality factor (qi ), fraction of absorbed dose (fi ) and the product fi qi. Summing the products over all charges yields the ratio of integrals in Equation 4.32, so that after multiplying by RH, the risk per unit absorbed dose for the GCR environment is obtained. The sum of the products is the scaling factor or mean specific quality factor (q). The value obtained is 2.2. Thus, the excess risk of a year’s exposure is 1.7 percent using the present analysis of the Harderian gland tumorigenesis data.

7.6.5 Comparison of Risks Table 7.1 presents a comparison of results of the above calculations for the risk of cancer mortality for a year’s exposure to the 1977 GCR spectrum outside the geomagnetosphere behind the given shielding conditions as obtained by the three methodologies, and the values of Q, Q and q for an annual value of D ⳱ 0.19 Gy at the center

7.6 COMPARISON OF ALL THREE METHODS

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77

TABLE 7.1—Comparison of risks from the 1977 GCR spectra, incident isotopically on a point of interest,a as determined by three different methods.

Method

Risk of Cancer Mortality per Year of Exposure

Values of Q, Q

and q

Conventional Q

2.7%

3.5 (Q)

Fluence-based risk cross sectionsb

2.4% 2.1%c

3.1 ( Q ) 2.7c

Microdosimetric event-based specific quality functionb

1.7%

2.2 (q)

a The center of two concentric spheres: (1) a 10 g cmⳮ2, thick aluminum shell; and (2) a 2.5 g cmⳮ2, radius ‘‘bone marrow’’ sphere. b Based on Harderian gland tumorigenesis data. c Without target fragmentation by low-Z ions.

of the concentric spheres. It is noted that the fluence-based and microdosimetric event-based calculations used only the Harderian gland tumor prevalence data (anchored at low-LET by the Hiroshima/Nagasaki data), while the conventional methodology used Q versus LET dependence suggested by ICRP (1991) and NCRP (1993). The table shows that all three methods predict risks which are within a factor of two of each other. A comparison of the results of the three methods as a function of charge (Z) of the GCR is shown in Figure 7.11 for the given scenario. We note that the conventional method results in greater importance being placed on the higher-Z components to the risk (i.e., higher values of Q) than the other two methods. This causes the overall risk and Q for the conventional method to be the largest. The overall low values for the microdosimetric event-based approach causes this method to predict the lowest risk. The fluence-based method provides an intermediate value.

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25 –

20

15

10 i (fluence based) 5

–

Qi (conventional), i (fluence based), q–i (microdosimetry)

Qi (conventional)

q–i (microdosimetry) 0 0

5

10

15

20

25

30

Charge (Z )

Fig. 7.11. Comparison of Q i, the conventional mean quality factor; Q i , the fluence-based risk/(risk coefficient ⳯ dose); and qi, the microdosimetric mean specific quality factor calculated by the three methodologies as a function of Z of the GCR for the chosen shielding scenario.

8. Conclusions, Recommendations and Suggestions for Future Research It is clear from the forgoing discussion that each of the three risk evaluation procedures which has been presented has specific advantages and disadvantages. No one approach appears to present an overwhelming case over the others at this stage of development. Several aspects of implementation, clarity of approach, and relevance to the space radiation environment were taken into account in developing the following recommendations. The considerations included the need for a self-consistent system which can be used for risk prediction as well as risk assessment, the availability of relevant measurement techniques which can be implemented in weight and cost-effective instrumentation, and the desirability to avoid unnecessary changes in the established system unless or until a significantly strong case can be made for such a change.

8.1 Conclusions The following conclusions form the basis of the recommendations: 1. The primary limitation on the reliability of risk estimates, particularly for radiation exposure in space, is the limited amount of relevant biological data available at low doses and dose rates. 2. The large uncertainties about the biological response, however, do not justify reducing emphasis on obtaining accurate relevant physical measurements. Risk evaluation inherently involves judgment about the ‘‘value’’ of different risks, but dosimetric quantities can be defined precisely, and exposed individuals (that is, future space crew members) should expect these quantities to be evaluated accurately. 3. The fluence-based system for risk evaluation is the most desirable in terms of technical completeness and ability to be adapted 79

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to changes in the available data on risks due to specific radiation exposures. Of the three systems considered, however, it requires the most complex instrumentation (charged-particle spectrometers), the greatest amount of data analysis (radiation transport calculations to obtain fluence spectra at the points of interest), and most detailed biological data (sufficient crosssection measurements to be able to provide an adequate threedimensional cross-section, energy, and charge surface for interpolation). Due to these requirements for risk assessment, it is considered impractical to implement a fluence-based system at the present time. 4. The microdosimetric event-based system is the easiest to implement for risk assessment purposes, being based on direct use of TEPC data. It is the most difficult, however, to implement for risk prediction since it requires calculating lineal-energy spectra from the available fluence-energy spectral data. The event-based system relies on assumptions about biological response, particularly that a unique specific quality function for carcinogenesis exists, which is independent of radiation type. This assumption requires significant new biological data to verify (including some of the same data required above in Item 3). 5. The conventional system is based on mean quantities (i.e., LET and Q) which do not correlate fully with the characteristics of energy deposition in and response of biological systems exposed to the radiation typical of the space environment. If applied properly, however, the conventional system provides risk estimates which are probably as reliable as can be achieved with the available biological data. Mean LET distributions from primary and secondary particles within specific organs of exposed individuals can be determined using radiation transport calculations within computerized human models developed specifically for this application. Risk prediction can be based on fluence-energy spectra derived from radiation environment models. Risk assessment can utilize charged-particle spectrometer data to refine knowledge of the LET spectrum, and TEPC data to provide absorbed doses and to validate the transport calculations. 6. A comparison of risk values obtained from the three different methods (Table 7.1) shows that there is less than a factor of two difference in the risks derived by any of the methods for the scenario given. Even though the details will change in a more realistic shielding configuration, it is not expected that

8.3 SUGGESTIONS FOR FUTURE RESEARCH

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with the presently available data, more accurate risks can be obtained.

8.2 Recommendations 1. At this time, radiation risk estimates and radiation protection for work in space should continue to be based on the concepts of absorbed dose, Q and dose equivalent, as discussed in Section 3.1. For these purposes, the organ dose equivalent (HT) [as a surrogate for equivalent dose (HT)] should be estimated by averaging the dose equivalent at a point (H) over representative points throughout the organs of interest and using Q(L) defined by ICRU (1993) and NCRP (1993). This is equivalent to using the fluence-based methodology with the ‘‘conventional risk cross sections’’ defined in Equation 4.7 and discussed in Section 4.1.3. 2. Periodically, the available biological data and dosimetric techniques should be evaluated to determine if significant improvement can be made by converting to an alternative system.

8.3 Suggestions for Future Research 1. Charged-particle spectrometer and TEPC (including ‘‘wall-less’’ TEPC) instrumentation could be refined for use in space to provide more precise data on event spectra. The spectrometers can be used to provide LET spectra with appropriate corrections and TEPC can provide absorbed dose measurements. The further development of these instruments may lead toward eventually making it possible to implement a fluence- or microdosimetric event-based system. 2. Biological data could be collected on representative animal tumorigenesis systems and in vitro surrogate systems with relevant high-energy heavy-ion and proton beams at low doses and dose rates. Particle-energy and event spectra should be collected during these measurements, so that the data can be utilized in developing the fluence-based and microdosimetric event-based systems as well as perhaps further validating the conventional system.

Glossary absorbed dose (D): The energy imparted to matter by ionizing radiation per unit mass of irradiated material at the point of interest. The special name for absorbed dose is the gray (Gy), where 1 Gy ⳱ 1 J kgⳮ1. conventional risk cross section ( r␴C ): The probability per unit fluence (mean for the organ or tissue of interest) of producing an endpoint of interest (e.g., cancer mortality or incidence). The conventional risk cross section is a single-valued function of LET and is proportional to Q(L) L. delta ray: An electron, stripped from an atom as a charged particle passes through matter, that has enough kinetic energy to cause subsequent ionization at a distant site. dose equivalent (H): A quantity used in measurement of radiation at a point that expresses the biological effect of all kinds of radiation on a common scale. Dose equivalent is defined as the product of the absorbed dose [D (in gray)] and the quality factor (Q) for the particular radiation, i.e., H ⳱ D Q. The special name for dose equivalent is the sievert (Sv) where 1 Sv ⳱ 1 J kgⳮ1. effective dose: The sum of the equivalent doses (HT) to individual organs or tissues multiplied by their respective tissue weighting factors (wT). The special name for effective dose is the sievert (Sv), where 1 Sv ⳱ 1 J kgⳮ1 (ICRP, 1991). equivalent dose (HT): A quantity used for radiation protection purposes that is the product of the mean absorbed dose (DT) in a tissue or organ and the radiation weighting factor. The equivalent dose allows for differences in the detriment to tissue from identical absorbed doses of various forms of ionizing radiation. The special name for equivalent dose is the sievert (Sv), where 1 Sv ⳱ 1 J kgⳮ1. fluence: Particle traversals per unit area. As used in this Report, the particles considered exclude delta rays, making fluence equal to the number of non-delta-ray particle traversals divided by the cross-sectional area of a sphere on which these particles are incident. The symbol ⌽ is used to denote total fluence. The symbols ␾ and ␸ are used in the Report for fluence as a function of LET and energy, respectively. galactic cosmic rays (GCR): The charged-particle radiation in space that is always present outside of the magnetosphere. GCR fluence is composed of approximately 87 percent protons, 12 percent helium ions, and one percent HZE particles. geomagnetosphere: The region around Earth occupied by Earth’s magnetic field. heavy ions: Positively charged nuclei of elements such as nitrogen, carbon, boron, neon, argon or iron.

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hit-size effectiveness function (HSEF): At a given absorbed dose, the ‘‘weighting’’ function of the specific energy (z) which yields the biological endpoint in question (e.g., risk of cancer) when multiplied by the distribution in z and integrated over z. high-Z, high-energy (HZE) particle: A particle having an atomic number (Z) greater than that of helium (i.e., Z ⬎ 2) and high energy. lineal energy (y): The energy imparted by a single energy-deposition event divided by the mean chord length of the volume in which the event occurs. Lineal energy can substitute for LET under certain conditions. Like LET, its units are energy per unit length and can be expressed in keV ␮mⳮ1. linear energy transfer [LET (L)]: Mean energy lost per unit of particle track length; expressed in units of keV ␮mⳮ1. high-LET: Radiation having high-energy transfer (e.g., low-energy protons, alpha particles, low- and high-energy heavy ions, interaction products of fast neutrons). low-LET: Radiation having low-energy transfer (e.g., electrons, gamma rays, x rays). mean absorbed dose (DT): The mean absorbed dose in an organ or tissue. microdosimetric event: Energy transfer within a designated site, regardless of the source of the energy (i.e., must include not only the primary particle traversal, but energy depositions from secondary radiations). The events are statistically independent from each other. organ dose equivalent (HT): The product of the mean absorbed dose (DT) and the mean quality factor (QT) in an organ or tissue (ICRU, 1993). For space radiation, it is common practice to integrate the point quantity dose equivalent (H) at an appropriate number of points within the organ or tissue of interest to obtain HT, which is used as a surrogate for equivalent dose (HT) when obtaining effective dose (NCRP, 2000). quality factor (Q): The LET-dependent factor by which absorbed dose is multiplied to obtain the dose equivalent. Quality factors are used so that absorbed doses for all kinds of ionizing radiation can be compared on a single scale when evaluating risk. radial cutoff LET (Lr): The energy lost per unit track length deposited within a given distance (r) from the track trajectory. The radial cutoff LET accounts for spatial differences in energy distribution. radiation health detriment: The total estimate for contributions to detriment from fatal cancers, nonfatal cancers, and hereditary disorders that are attributed to radiation exposure. radiation transport code: Algorithms used to determine the attenuation of ionizing radiation as it passes through various types of matter (e.g., shielding, walls, human tissue) before it interacts with the material of interest. relative biological effectiveness (RBE): A factor used to compare the biological effectiveness of absorbed doses from different types of ionizing radiation. Specifically, relative biological effectiveness is the ratio of the absorbed dose of a reference type of radiation to the absorbed dose in question to produce an identical biological effect.

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relative biological effectiveness, maximum (RBEM): The relative biological effectiveness of an ionizing radiation type when extrapolated to low absorbed dose in the linear region of the dose-response curve. risk cross section: The probability of a particular excess cancer mortality per unit fluence of a non-delta-ray particle. risk (R): The probability of a deleterious outcome incurred by a system, i.e., cell, tissue, organ, or organism, exposed to a given radiation environment. solar minimum: The portion of the 11 y solar cycle during which the solar wind (ionized gas carrying magnetic fields that can alter the radiation in interplanetary space) is at its weakest, resulting in higher levels of GCR radiation. solar maximum: The portion of the 11 y solar cycle during which the solar wind is at its most intense, resulting in lower levels of GCR radiation. specific energy (z): Energy absorbed within a given site divided by the mass of the site. Unlike lineal energy (y) specific energy may be related to more than one deposition event. specific quality function [q(z) or q(y)]: The microdosimetric analog of the quality factor as a function of LET [Q(L)]. q(y) is the specific quality function based on lineal energy (y); q(z) is the equivalent function based on specific energy (z). tissue weighting factor (wT): A factor representing the ratio of the risk of stochastic effects attributable to irradiation of a given organ or tissue (T) to the total risk when the whole body is uniformly irradiated. The tissue weighting factor is independent of the radiation type or energy (ICRP, 1991). wall effects: Distortions of microdosimetric measurements leading to an increased or decreased estimation of number and size of energy deposition events relative to the number and size of events that would occur in a given volume if the surrounding matter were of the same density as the volume of interest.

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The NCRP The National Council on Radiation Protection and Measurements is a nonprofit corporation chartered by Congress in 1964 to: 1. Collect, analyze, develop and disseminate in the public interest information and recommendations about (a) protection against radiation and (b) radiation measurements, quantities and units, particularly those concerned with radiation protection. 2. Provide a means by which organizations concerned with the scientific and related aspects of radiation protection and of radiation quantities, units and measurements may cooperate for effective utilization of their combined resources, and to stimulate the work of such organizations. 3. Develop basic concepts about radiation quantities, units and measurements, about the application of these concepts, and about radiation protection. 4. Cooperate with the International Commission on Radiological Protection, the International Commission on Radiation Units and Measurements, and other national and international organizations, governmental and private, concerned with radiation quantities, units and measurements and with radiation protection. The Council is the successor to the unincorporated association of scientists known as the National Committee on Radiation Protection and Measurements and was formed to carry on the work begun by the Committee in 1929. The participants in the Council’s work are the Council members and members of scientific and administrative committees. Council members are selected solely on the basis of their scientific expertise and serve as individuals, not as representatives of any particular organization. The scientific committees, composed of experts having detailed knowledge and competence in the particular area of the committee’s interest, draft proposed recommendations. These are then submitted to the full membership of the Council for careful review and approval before being published. The following comprise the current officers and membership of the Council:

Officers President Vice President Secretary and Treasurer Assistant Secretary

Charles B. Meinhold S. James Adelstein William M. Beckner Michael F. McBride

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Members S. James Adelstein John F. Ahearne Larry E. Anderson Benjamin R. Archer Mary M. Austin-Seymour Harold L. Beck Eleanor A. Blakely B. Gordon Blaylock John D. Boice, Jr. Thomas B. Borak Andre´ Bouville Leslie A. Braby Davi J. Brenner Antone L. Brooks Patricia A. Buffler Shih-Yew Chen Chung-Kwang Chou James E. Cleaver J. Donald Cossairt Allen G. Croff Francis A. Cucinotta Paul M. DeLuca Carter Denniston Gail de Planque John F. Dicello Sarah S. Donaldson William P. Dornsife Keith F. Eckerman Marc Edwards Stephen A. Feig H. Keith Florig

Kenneth R. Foster Ethel S. Gilbert Joel E. Gray Andrew J. Grosovsky Raymond A. Guilmette William R. Hendee David G. Hoel F. Owen Hoffman Geoffrey R. Howe Kenneth R. Kase Ann R. Kennedy David C. Kocher Ritsuko Komaki Amy Kronenberg Charles E. Land Susan M. Langhorst Richard W. Leggett Howard L. Liber James C. Lin Jill Lipoti John B. Little Jay H. Lubin C. Douglas Maynard Claire M. Mays Charles B. Meinhold Fred A. Mettler, Jr. Charles W. Miller Jack Miller Kenneth L. Miller John E. Moulder David S. Myers

Ronald C. Petersen John W. Poston, Sr. R. Julian Preston Jerome S. Puskin Genevieve S. Roessler Marvin Rosenstein Lawrence N. Rothenberg Henry D. Royal Michael T. Ryan Jonathan M. Samet Stephen M. Seltzer Edward A. Sickles David H. Sliney Paul Slovic Louise C. Strong John E. Till Lawrence W. Townsend Lois B. Travis Robert L. Ullrich Richard J. Vetter Louis K. Wagner Daniel Wartenberg David A. Weber F. Ward Whicker Chris G. Whipple J. Frank Wilson Susan D. Wiltshire Marco Zaider Pasquale Zanzonico Marvin C. Ziskin

Honorary Members Lauriston S. Taylor, Honorary President, Warren K. Sinclair, President Emeritus W. Roger Ney, Executive Director Emeritus Seymour Abrahamson Edward L. Alpen John A. Auxier William J. Bair Bruce B. Boecker Victor P. Bond Robert L. Brent Reynold F. Brown Melvin C. Carter Randall S. Caswell Frederick P. Cowan James F. Crow Gerald D. Dodd

Patricia W. Durbin Thomas S. Ely Richard F. Foster Hymer L. Friedell R.J. Michael Fry Robert O. Gorson Arthur W. Guy Eric J. Hall Naomi H. Harley John W. Healy Donald G. Jacobs Bernd Kahn Dade W. Moeller A. Alan Moghissi

Robert J. Nelsen Wesley L. Nyborg Andrew K. Poznanski Chester R. Richmond William L. Russell Eugene L. Saenger William J. Schull J. Newell Stannard John B. Storer Thomas S. Tenforde Arthur C. Upton George L. Voelz Edward W. Webster

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Lauriston S. Taylor Lecturers Herbert M. Parker (1977) The Squares of the Natural Numbers in Radiation Protection Sir Edward Pochin (1978) Why be Quantitative about Radiation Risk Estimates? Hymer L. Friedell (1979) Radiation Protection—Concepts and Trade Offs Harold O. Wyckoff (1980) From ‘‘Quantity of Radiation’’ and ‘‘Dose’’ to ‘‘Exposure’’ and ‘‘Absorbed Dose’’—An Historical Review James F. Crow (1981) How Well Can We Assess Genetic Risk? Not Very Eugene L. Saenger (1982) Ethics, Trade-offs and Medical Radiation Merril Eisenbud (1983) The Human Environment—Past, Present and Future Harald H. Rossi (1984) Limitation and Assessment in Radiation Protection John H. Harley (1985) Truth (and Beauty) in Radiation Measurement Herman P. Schwan (1986) Biological Effects of Non-ionizing Radiations: Cellular Properties and Interactions Seymour Jablon (1987) How to be Quantitative about Radiation Risk Estimates Bo Lindell (1988) How Safe is Safe Enough? Arthur C. Upton (1989) Radiobiology and Radiation Protection: The Past Century and Prospects for the Future J. Newell Stannard (1990) Radiation Protection and the Internal Emitter Saga Victor P. Bond (1991) When is a Dose Not a Dose? Edward W. Webster (1992) Dose and Risk in Diagnostic Radiology: How Big? How Little? Warren K. Sinclair (1993) Science, Radiation Protection and the NCRP R.J. Michael Fry (1994) Mice, Myths and Men Albrecht Kellerer (1995) Certainty and Uncertainty in Radiation Protection Seymour Abrahamson (1996) 70 Years of Radiation Genetics: Fruit Flies, Mice and Humans William J. Bair (1997) Radionuclides in the Body: Meeting the Challenge! Eric J. Hall (1998) From Chimney Sweeps to Astronauts: Cancer Risks in the Workplace Naomi H. Harley (1999) Back to Background S. James Adelstein (2000) Administered Radioactivity: Unde Venimus Quoque Imus Wesley L. Nyborg (2001) Assuring the Safety of Medical Diagnostic Ultrasound

Currently, the following committees are actively engaged in formulating recommendations: SC 1

SC 9 SC 46

Basic Criteria, Epidemiology, Radiobiology and Risk SC 1-4 Extrapolation of Risks from Non-Human Experimental Systems to Man SC 1-7 Information Needed to Make Radiation Protection Recommendations for Travel Beyond Low-Earth Orbit SC 1-8 Risk to Thyroid from Ionizing Radiation Structural Shielding Design and Evaluation for Medical Use of X Rays and Gamma Rays of Energies Up to 10 MeV Operational Radiation Safety

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SC SC SC SC

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SC 91

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SC 46-8 Radiation Protection Design Guidelines for Particle Accelerator Facilities SC 46-10 Assessment of Occupational Doses from Internal Emitters SC 46-13 Design of Facilities for Medical Radiation Therapy SC 46-14 Radiation Protection Issues Related to Terrorist Activities that Result in the Dispersal of Radioactive Material SC 46-15 Operational Radiation Safety Program for Astronauts SC 57-15 Uranium Risk SC 57-17 Radionuclide Dosimetry Models for Wounds Environmental Issues SC 64-19 Historical Dose SC 64-22 Design of Effective Effluent and Environmental Monitoring Programs SC 64-23 Cesium in the Environment Biological Effects and Exposure Criteria for Ultrasound Radiation Protection in Mammography Risk of Lung Cancer from Radon Radioactive and Mixed Waste SC 87-1 Waste Avoidance and Volume Reduction SC 87-2 Waste Classification Based on Risk SC 87-3 Performance Assessment SC 87-4 Management of Waste Metals Containing Radioactivity Nonionizing Electromagnetic Fields SC 89-3 Biological Effects of Extremely Low-Frequency Electric and Magnetic Fields SC 89-4 Biological Effects and Exposure Recommendations for Modulated Radiofrequency Fields SC 89-5 Biological Effects and Exposure Criteria for Radiofrequency Fields Radiation Protection in Medicine SC 91-1 Precautions in the Management of Patients Who Have Received Therapeutic Amounts of Radionuclides SC 91-2 Radiation Protection in Dentistry Public Policy and Risk Communication Radiation Measurement and Dosimetry

In recognition of its responsibility to facilitate and stimulate cooperation among organizations concerned with the scientific and related aspects of radiation protection and measurement, the Council has created a category of NCRP Collaborating Organizations. Organizations or groups of organizations that are national or international in scope and are concerned with

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scientific problems involving radiation quantities, units, measurements and effects, or radiation protection may be admitted to collaborating status by the Council. Collaborating Organizations provide a means by which the NCRP can gain input into its activities from a wider segment of society. At the same time, the relationships with the Collaborating Organizations facilitate wider dissemination of information about the Council’s activities, interests and concerns. Collaborating Organizations have the opportunity to comment on draft reports (at the time that these are submitted to the members of the Council). This is intended to capitalize on the fact that Collaborating Organizations are in an excellent position to both contribute to the identification of what needs to be treated in NCRP reports and to identify problems that might result from proposed recommendations. The present Collaborating Organizations with which the NCRP maintains liaison are as follows: Agency for Toxic Substances and Disease Registry American Academy of Dermatology American Academy of Environmental Engineers American Academy of Health Physics American Association of Physicists in Medicine American College of Medical Physics American College of Nuclear Physicians American College of Occupational and Environmental Medicine American College of Radiology American Dental Association American Industrial Hygiene Association American Institute of Ultrasound in Medicine American Insurance Services Group American Medical Association American Nuclear Society American Pharmaceutical Association American Podiatric Medical Association American Public Health Association American Radium Society American Roentgen Ray Society American Society for Therapeutic Radiology and Oncology American Society of Health-System Pharmacists American Society of Radiologic Technologists Association of University Radiologists Bioelectromagnetics Society Campus Radiation Safety Officers College of American Pathologists Conference of Radiation Control Program Directors, Inc. Council on Radionuclides and Radiopharmaceuticals Defense Threat Reduction Agency Electric Power Research Institute Electromagnetic Energy Association Federal Communications Commission

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Federal Emergency Management Agency Genetics Society of America Health Physics Society Institute of Electrical and Electronics Engineers, Inc. Institute of Nuclear Power Operations International Brotherhood of Electrical Workers National Aeronautics and Space Administration National Association of Environmental Professionals National Electrical Manufacturers Association National Institute for Occupational Safety and Health National Institute of Standards and Technology Nuclear Energy Institute Office of Science and Technology Policy Oil, Chemical and Atomic Workers Radiation Research Society Radiological Society of North America Society for Risk Analysis Society of Nuclear Medicine U.S. Air Force U.S. Army U.S. Coast Guard U.S. Department of Energy U.S. Department of Housing and Urban Development U.S. Department of Labor U.S. Department of Transportation U.S. Environmental Protection Agency U.S. Navy U.S. Nuclear Regulatory Commission U.S. Public Health Service Utility Workers Union of America The NCRP has found its relationships with these organizations to be extremely valuable to continued progress in its program. Another aspect of the cooperative efforts of the NCRP relates to the Special Liaison relationships established with various governmental organizations that have an interest in radiation protection and measurements. This liaison relationship provides: (1) an opportunity for participating organizations to designate an individual to provide liaison between the organization and the NCRP; (2) that the individual designated will receive copies of draft NCRP reports (at the time that these are submitted to the members of the Council) with an invitation to comment, but not vote; and (3) that new NCRP efforts might be discussed with liaison individuals as appropriate, so that they might have an opportunity to make suggestions on new studies and related matters. The following organizations participate in the Special Liaison Program: Atomic Energy Control Board Australian Radiation Laboratory

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Bundesamt fu¨r Strahlenschutz (Germany) Central Laboratory for Radiological Protection (Poland) China Institute for Radiation Protection Commisariat a` l’Energie Atomique Commonwealth Scientific Instrumentation Research Organization (Australia) European Commission Health Council of the Netherlands International Commission on Non-Ionizing Radiation Protection Japan Radiation Council Korea Institute of Nuclear Safety National Radiological Protection Board (United Kingdom) Russian Scientific Commission on Radiation Protection South African Forum for Radiation Protection World Association of Nuclear Operations The NCRP values highly the participation of these organizations in the Special Liaison Program. The Council also benefits significantly from the relationships established pursuant to the Corporate Sponsor’s Program. The program facilitates the interchange of information and ideas and corporate sponsors provide valuable fiscal support for the Council’s program. This developing program currently includes the following Corporate Sponsors: 3M Corporate Health Physics Commonwealth Edison Consolidated Edison Duke Energy Corporation Florida Power Corporation ICN Biomedicals, Inc. Landauer, Inc. New York Power Authority Nuclear Energy Institute Nycomed Amersham Corporation Southern California Edison The Council’s activities are made possible by the voluntary contribution of time and effort by its members and participants and the generous support of the following organizations: 3M Health Physics Services Agfa Corporation Alfred P. Sloan Foundation Alliance of American Insurers American Academy of Dermatology American Academy of Health Physics American Academy of Oral and Maxillofacial Radiology American Association of Physicists in Medicine American Cancer Society

THE NCRP

American College of Medical Physics American College of Nuclear Physicians American College of Occupational and Environmental Medicine American College of Radiology American College of Radiology Foundation American Dental Association American Healthcare Radiology Administrators American Industrial Hygiene Association American Insurance Services Group American Medical Association American Nuclear Society American Osteopathic College of Radiology American Podiatric Medical Association American Public Health Association American Radium Society American Roentgen Ray Society American Society of Radiologic Technologists American Society for Therapeutic Radiology and Oncology American Veterinary Medical Association American Veterinary Radiology Society Association of University Radiologists Battelle Memorial Institute Canberra Industries, Inc. Chem Nuclear Systems Center for Devices and Radiological Health College of American Pathologists Committee on Interagency Radiation Research and Policy Coordination Commonwealth of Pennsylvania Consumers Power Company Council on Radionuclides and Radiopharmaceuticals Defense Nuclear Agency Eastman Kodak Company Edison Electric Institute Edward Mallinckrodt, Jr. Foundation EG&G Idaho, Inc. Electric Power Research Institute Federal Emergency Management Agency Florida Institute of Phosphate Research Fuji Medical Systems, U.S.A., Inc. Genetics Society of America Health Effects Research Foundation (Japan) Health Physics Society Institute of Nuclear Power Operations James Picker Foundation Martin Marietta Corporation Motorola Foundation National Aeronautics and Space Administration

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National Association of Photographic Manufacturers National Cancer Institute National Electrical Manufacturers Association National Institute of Standards and Technology Picker International Public Service Electric and Gas Company Radiation Research Society Radiological Society of North America Richard Lounsbery Foundation Sandia National Laboratory Siemens Medical Systems, Inc. Society of Nuclear Medicine Society of Pediatric Radiology U.S. Department of Energy U.S. Department of Labor U.S. Environmental Protection Agency U.S. Navy U.S. Nuclear Regulatory Commission Victoreen, Inc. Westinghouse Electric Corporation Initial funds for publication of NCRP reports were provided by a grant from the James Picker Foundation. The NCRP seeks to promulgate information and recommen-dations based on leading scientific judgment on matters of radiation protection and measurement and to foster cooperation among organizations concerned with these matters. These efforts are intended to serve the public interest and the Council welcomes comments and suggestions on its reports or activities from those interested in its work.

NCRP Publications

Information on NCRP publications may be obtained from the NCRP website (http://www.ncrp.com), e-mail ([email protected]), by telephone (800-229-2652), or fax (301-907-8768). The address is: NCRP Publications 7910 Woodmont Avenue Suite 800 Bethesda, MD 20814-3095 Abstracts of NCRP reports published since 1980, abstracts of all NCRP commentaries, and the text of all NCRP statements are available at the NCRP website. Currently available publications are listed below.

NCRP Reports No. 8 22

25 27 30 32 35 36 37 38 40 41 42

Title Control and Removal of Radioactive Contamination in Laboratories (1951) Maximum Permissible Body Burdens and Maximum Permissible Concentrations of Radionuclides in Air and in Water for Occupational Exposure (1959) [Includes Addendum 1 issued in August 1963] Measurement of Absorbed Dose of Neutrons, and of Mixtures of Neutrons and Gamma Rays (1961) Stopping Powers for Use with Cavity Chambers (1961) Safe Handling of Radioactive Materials (1964) Radiation Protection in Educational Institutions (1966) Dental X-Ray Protection (1970) Radiation Protection in Veterinary Medicine (1970) Precautions in the Management of Patients Who Have Received Therapeutic Amounts of Radionuclides (1970) Protection Against Neutron Radiation (1971) Protection Against Radiation from Brachytherapy Sources (1972) Specification of Gamma-Ray Brachytherapy Sources (1974) Radiological Factors Affecting Decision-Making in a Nuclear Attack (1974)

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Krypton-85 in the Atmosphere—Accumulation, Biological Significance, and Control Technology (1975) Alpha-Emitting Particles in Lungs (1975) Tritium Measurement Techniques (1976) Structural Shielding Design and Evaluation for Medical Use of X Rays and Gamma Rays of Energies Up to 10 MeV (1976) Environmental Radiation Measurements (1976) Radiation Protection Design Guidelines for 0.1 - 10 MeV Particle Accelerator Facilities (1977) Cesium-137 from the Environment to Man: Metabolism and Dose (1977) Medical Radiation Exposure of Pregnant and Potentially Pregnant Women (1977) Protection of the Thyroid Gland in the Event of Releases of Radioiodine (1977) Instrumentation and Monitoring Methods for Radiation Protection (1978) A Handbook of Radioactivity Measurements Procedures, 2nd ed. (1985) Operational Radiation Safety Program (1978) Physical, Chemical, and Biological Properties of Radiocerium Relevant to Radiation Protection Guidelines (1978) Radiation Safety Training Criteria for Industrial Radiography (1978) Tritium in the Environment (1979) Tritium and Other Radionuclide Labeled Organic Compounds Incorporated in Genetic Material (1979) Influence of Dose and Its Distribution in Time on Dose-Response Relationships for Low-LET Radiations (1980) Management of Persons Accidentally Contaminated with Radionuclides (1980) Radiofrequency Electromagnetic Fields—Properties, Quantities and Units, Biophysical Interaction, and Measurements (1981) Radiation Protection in Pediatric Radiology (1981) Dosimetry of X-Ray and Gamma-Ray Beams for Radiation Therapy in the Energy Range 10 keV to 50 MeV (1981) Nuclear Medicine—Factors Influencing the Choice and Use of Radionuclides in Diagnosis and Therapy (1982) Radiation Protection and Measurement for Low-Voltage Neutron Generators (1983) Protection in Nuclear Medicine and Ultrasound Diagnostic Procedures in Children (1983) Biological Effects of Ultrasound: Mechanisms and Clinical Implications (1983) Iodine-129: Evaluation of Releases from Nuclear Power Generation (1983)

NCRP PUBLICATIONS

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Exposures from the Uranium Series with Emphasis on Radon and Its Daughters (1984) Evaluation of Occupational and Environmental Exposures to Radon and Radon Daughters in the United States (1984) Neutron Contamination from Medical Electron Accelerators (1984) Induction of Thyroid Cancer by Ionizing Radiation (1985) Carbon-14 in the Environment (1985) SI Units in Radiation Protection and Measurements (1985) The Experimental Basis for Absorbed-Dose Calculations in Medical Uses of Radionuclides (1985) General Concepts for the Dosimetry of Internally Deposited Radionuclides (1985) Mammography—A User’s Guide (1986) Biological Effects and Exposure Criteria for Radiofrequency Electromagnetic Fields (1986) Use of Bioassay Procedures for Assessment of Internal Radionuclide Deposition (1987) Radiation Alarms and Access Control Systems (1986) Genetic Effects from Internally Deposited Radionuclides (1987) Neptunium: Radiation Protection Guidelines (1988) Public Radiation Exposure from Nuclear Power Generation in the United States (1987) Ionizing Radiation Exposure of the Population of the United States (1987) Exposure of the Population in the United States and Canada from Natural Background Radiation (1987) Radiation Exposure of the U.S. Population from Consumer Products and Miscellaneous Sources (1987) Comparative Carcinogenicity of Ionizing Radiation and Chemicals (1989) Measurement of Radon and Radon Daughters in Air (1988) Quality Assurance for Diagnostic Imaging (1988) Exposure of the U.S. Population from Diagnostic Medical Radiation (1989) Exposure of the U.S. Population from Occupational Radiation (1989) Medical X-Ray, Electron Beam and Gamma-Ray Protection for Energies Up to 50 MeV (Equipment Design, Performance and Use) (1989) Control of Radon in Houses (1989) The Relative Biological Effectiveness of Radiations of Different Quality (1990) Radiation Protection for Medical and Allied Health Personnel (1989) Limit for Exposure to ‘‘Hot Particles’’ on the Skin (1989) Implementation of the Principle of As Low As Reasonably Achievable (ALARA) for Medical and Dental Personnel (1990)

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108 Conceptual Basis for Calculations of Absorbed-Dose Distributions (1991) 109 Effects of Ionizing Radiation on Aquatic Organisms (1991) 110 Some Aspects of Strontium Radiobiology (1991) 111 Developing Radiation Emergency Plans for Academic, Medical or Industrial Facilities (1991) 112 Calibration of Survey Instruments Used in Radiation Protection for the Assessment of Ionizing Radiation Fields and Radioactive Surface Contamination (1991) 113 Exposure Criteria for Medical Diagnostic Ultrasound: I. Criteria Based on Thermal Mechanisms (1992) 114 Maintaining Radiation Protection Records (1992) 115 Risk Estimates for Radiation Protection (1993) 116 Limitation of Exposure to Ionizing Radiation (1993) 117 Research Needs for Radiation Protection (1993) 118 Radiation Protection in the Mineral Extraction Industry (1993) 119 A Practical Guide to the Determination of Human Exposure to Radiofrequency Fields (1993) 120 Dose Control at Nuclear Power Plants (1994) 121 Principles and Application of Collective Dose in Radiation Protection (1995) 122 Use of Personal Monitors to Estimate Effective Dose Equivalent and Effective Dose to Workers for External Exposure to LowLET Radiation (1995) 123 Screening Models for Releases of Radionuclides to Atmosphere, Surface Water, and Ground (1996) 124 Sources and Magnitude of Occupational and Public Exposures from Nuclear Medicine Procedures (1996) 125 Deposition, Retention and Dosimetry of Inhaled Radioactive Substances (1997) 126 Uncertainties in Fatal Cancer Risk Estimates Used in Radiation Protection (1997) 127 Operational Radiation Safety Program (1998) 128 Radionuclide Exposure of the Embryo/Fetus (1998) 129 Recommended Screening Limits for Contaminated Surface Soil and Review of Factors Relevant to Site-Specific Studies (1999) 130 Biological Effects and Exposure Limits for ‘‘Hot Particles’’ (1999) 131 Scientific Basis for Evaluating the Risks to Populations from Space Applications of Plutonium (2001) 132 Radiation Protection Guidance for Activities in Low-Earth Orbit (2000) 133 Radiation Protection for Procedures Performed Outside the Radiology Department (2000) 134 Operational Radiation Safety Training (2000) 135 Liver Cancer Risk from Internally-Deposited Radionuclides (2001) 136 Evaluation of the Linear-Nonthreshold Dose-Response Model for Ionizing Radiation (2001) 137 Fluence-Based and Microdosimetric Event-Based Methods for Radiation Protection in Space (2001) Binders for NCRP reports are available. Two sizes make it possible to collect into small binders the ‘‘old series’’ of reports (NCRP Reports

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Nos. 8-30) and into large binders the more recent publications (NCRP Reports Nos. 32-137). Each binder will accommodate from five to seven reports. The binders carry the identification ‘‘NCRP Reports’’ and come with label holders which permit the user to attach labels showing the reports contained in each binder. The following bound sets of NCRP reports are also available: Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume Volume

I. NCRP Reports Nos. 8, 22 II. NCRP Reports Nos. 23, 25, 27, 30 III. NCRP Reports Nos. 32, 35, 36, 37 IV. NCRP Reports Nos. 38, 40, 41 V. NCRP Reports Nos. 42, 44, 46 VI. NCRP Reports Nos. 47, 49, 50, 51 VII. NCRP Reports Nos. 52, 53, 54, 55, 57 VIII. NCRP Report No. 58 IX. NCRP Reports Nos. 59, 60, 61, 62, 63 X. NCRP Reports Nos. 64, 65, 66, 67 XI. NCRP Reports Nos. 68, 69, 70, 71, 72 XII. NCRP Reports Nos. 73, 74, 75, 76 XIII. NCRP Reports Nos. 77, 78, 79, 80 XIV. NCRP Reports Nos. 81, 82, 83, 84, 85 XV. NCRP Reports Nos. 86, 87, 88, 89 XVI. NCRP Reports Nos. 90, 91, 92, 93 XVII. NCRP Reports Nos. 94, 95, 96, 97 XVIII. NCRP Reports Nos. 98, 99, 100 XIX. NCRP Reports Nos. 101, 102, 103, 104 XX. NCRP Reports Nos. 105, 106, 107, 108 XXI. NCRP Reports Nos. 109, 110, 111 XXII. NCRP Reports Nos. 112, 113, 114 XXIII. NCRP Reports Nos. 115, 116, 117, 118 XXIV. NCRP Reports Nos. 119, 120, 121, 122 XXV. NCRP Report No. 123I and 123II XXVI. NCRP Reports Nos. 124, 125, 126, 127 XXVII. NCRP Reports Nos. 128, 129, 130

(Titles of the individual reports contained in each volume are given above.)

NCRP Commentaries No. 1

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Title Krypton-85 in the Atmosphere—With Specific Reference to the Public Health Significance of the Proposed Controlled Release at Three Mile Island (1980) Guidelines for the Release of Waste Water from Nuclear Facilities with Special Reference to the Public Health

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NCRP PUBLICATIONS

Significance of the Proposed Release of Treated Waste Waters at Three Mile Island (1987) Review of the Publication, Living Without Landfills (1989) Radon Exposure of the U.S. Population—Status of the Problem (1991) Misadministration of Radioactive Material in Medicine— Scientific Background (1991) Uncertainty in NCRP Screening Models Relating to Atmospheric Transport, Deposition and Uptake by Humans (1993) Considerations Regarding the Unintended Radiation Exposure of the Embryo, Fetus or Nursing Child (1994) Advising the Public about Radiation Emergencies: A Document for Public Comment (1994) Dose Limits for Individuals Who Receive Exposure from Radionuclide Therapy Patients (1995) Radiation Exposure and High-Altitude Flight (1995) An Introduction to Efficacy in Diagnostic Radiology and Nuclear Medicine (Justification of Medical Radiation Exposure) (1995) A Guide for Uncertainty Analysis in Dose and Risk Assessments Related to Environmental Contamination (1996) Evaluating the Reliability of Biokinetic and Dosimetric Models and Parameters Used to Assess Individual Doses for Risk Assessment Purposes (1998)

Proceedings of the Annual Meeting No. 1

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Title Perceptions of Risk, Proceedings of the Fifteenth Annual Meeting held on March 14-15, 1979 (including Taylor Lecture No. 3) (1980) Critical Issues in Setting Radiation Dose Limits, Proceedings of the Seventeenth Annual Meeting held on April 8-9, 1981 (including Taylor Lecture No. 5) (1982) Radiation Protection and New Medical Diagnostic Approaches, Proceedings of the Eighteenth Annual Meeting held on April 6-7, 1982 (including Taylor Lecture No. 6) (1983) Environmental Radioactivity, Proceedings of the Nineteenth Annual Meeting held on April 6-7, 1983 (including Taylor Lecture No. 7) (1983) Some Issues Important in Developing Basic Radiation Protection Recommendations, Proceedings of the Twentieth Annual Meeting held on April 4-5, 1984 (including Taylor Lecture No. 8) (1985) Radioactive Waste, Proceedings of the Twenty-first Annual Meeting held on April 3-4, 1985 (including Taylor Lecture No. 9) (1986)

NCRP PUBLICATIONS

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12

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15

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Nonionizing Electromagnetic Radiations and Ultrasound, Proceedings of the Twenty-second Annual Meeting held on April 2-3, 1986 (including Taylor Lecture No. 10) (1988) New Dosimetry at Hiroshima and Nagasaki and Its Implications for Risk Estimates, Proceedings of the Twenty-third Annual Meeting held on April 8-9, 1987 (including Taylor Lecture No. 11) (1988) Radon, Proceedings of the Twenty-fourth Annual Meeting held on March 30-31, 1988 (including Taylor Lecture No. 12) (1989) Radiation Protection Today—The NCRP at Sixty Years, Proceedings of the Twenty-fifth Annual Meeting held on April 5-6, 1989 (including Taylor Lecture No. 13) (1990) Health and Ecological Implications of Radioactively Contaminated Environments, Proceedings of the Twenty-sixth Annual Meeting held on April 4-5, 1990 (including Taylor Lecture No. 14) (1991) Genes, Cancer and Radiation Protection, Proceedings of the Twenty-seventh Annual Meeting held on April 3-4, 1991 (including Taylor Lecture No. 15) (1992) Radiation Protection in Medicine, Proceedings of the Twentyeighth Annual Meeting held on April 1-2, 1992 (including Taylor Lecture No. 16) (1993) Radiation Science and Societal Decision Making, Proceedings of the Twenty-ninth Annual Meeting held on April 7-8, 1993 (including Taylor Lecture No. 17) (1994) Extremely-Low-Frequency Electromagnetic Fields: Issues in Biological Effects and Public Health, Proceedings of the Thirtieth Annual Meeting held on April 6-7, 1994 (not published). Environmental Dose Reconstruction and Risk Implications, Proceedings of the Thirty-first Annual Meeting held on April 12-13, 1995 (including Taylor Lecture No. 19) (1996) Implications of New Data on Radiation Cancer Risk, Proceedings of the Thirty-second Annual Meeting held on April 3-4, 1996 (including Taylor Lecture No. 20) (1997) The Effects of Pre- and Postconception Exposure to Radiation, Proceedings of the Thirty-third Annual Meeting held on April 2-3, 1997, Teratology 59, 181–317 (1999) Cosmic Radiation Exposure of Airline Crews, Passengers and Astronauts, Proceedings of the Thirty-fourth Annual Meeting held on April 1-2, 1998, Health Phys. 79, 466–613 (2000) Radiation Protection in Medicine: Contemporary Issues, Proceedings of the Thirty-fifth Annual Meeting held on April 7-8, 1999 (including Taylor Lecture No. 23) (1999) Ionizing Radiation Science and Protection in the 21st Century, Proceedings of the Thirty-sixth Annual Meeting held on April 5-6, 2000, Health Phys. 80, 317–402 (2001)

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Lauriston S. Taylor Lectures

No. 1 2 3

4

5

6

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8

9 10

11

12 13

14

Title The Squares of the Natural Numbers in Radiation Protection by Herbert M. Parker (1977) Why be Quantitative about Radiation Risk Estimates? by Sir Edward Pochin (1978) Radiation Protection—Concepts and Trade Offs by Hymer L. Friedell (1979) [Available also in Perceptions of Risk, see above] From ‘‘Quantity of Radiation’’ and ‘‘Dose’’ to ‘‘Exposure’’ and ‘‘Absorbed Dose’’—An Historical Review by Harold O. Wyckoff (1980) How Well Can We Assess Genetic Risk? Not Very by James F. Crow (1981) [Available also in Critical Issues in Setting Radiation Dose Limits, see above] Ethics, Trade-offs and Medical Radiation by Eugene L. Saenger (1982) [Available also in Radiation Protection and New Medical Diagnostic Approaches, see above] The Human Environment—Past, Present and Future by Merril Eisenbud (1983) [Available also in Environmental Radioactivity, see above] Limitation and Assessment in Radiation Protection by Harald H. Rossi (1984) [Available also in Some Issues Important in Developing Basic Radiation Protection Recommendations, see above] Truth (and Beauty) in Radiation Measurement by John H. Harley (1985) [Available also in Radioactive Waste, see above] Biological Effects of Non-ionizing Radiations: Cellular Properties and Interactions by Herman P. Schwan (1987) [Available also in Nonionizing Electromagnetic Radiations and Ultrasound, see above] How to be Quantitative about Radiation Risk Estimates by Seymour Jablon (1988) [Available also in New Dosimetry at Hiroshima and Nagasaki and its Implications for Risk Estimates, see above] How Safe is Safe Enough? by Bo Lindell (1988) [Available also in Radon, see above] Radiobiology and Radiation Protection: The Past Century and Prospects for the Future by Arthur C. Upton (1989) [Available also in Radiation Protection Today, see above] Radiation Protection and the Internal Emitter Saga by J. Newell Stannard (1990) [Available also in Health and Ecological Implications of Radioactively Contaminated Environments, see above]

NCRP PUBLICATIONS

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18 19 20 21 22 23

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When is a Dose Not a Dose? by Victor P. Bond (1992) [Available also in Genes, Cancer and Radiation Protection, see above] Dose and Risk in Diagnostic Radiology: How Big? How Little? by Edward W. Webster (1992)[Available also in Radiation Protection in Medicine, see above] Science, Radiation Protection and the NCRP by Warren K. Sinclair (1993)[Available also in Radiation Science and Societal Decision Making, see above] Mice, Myths and Men by R.J. Michael Fry (1995) Certainty and Uncertainty in Radiation Research by Albrecht M. Kellerer. Health Phys. 69, 446–453 (1995). 70 Years of Radiation Genetics: Fruit Flies, Mice and Humans by Seymour Abrahamson. Health Phys. 71, 624–633 (1996). Radionuclides in the Body: Meeting the Challenge by William J. Bair. Health Phys. 73, 423–432 (1997). From Chimney Sweeps to Astronauts: Cancer Risks in the Work Place by Eric J. Hall. Health Phys. 75, 357–366 (1998). Back to Background: Natural Radiation and Radioactivity Exposed by Naomi H. Harley. Health Phys. 79, 121–128 (2000). Administered Radioactivity: Unde Venimus Quoque Imus by S. James Adelstein. Health Phys. 80, 317–324, (2001).

Symposium Proceedings No. 1

2

3

Title The Control of Exposure of the Public to Ionizing Radiation in the Event of Accident or Attack, Proceedings of a Symposium held April 27-29, 1981 (1982) Radioactive and Mixed Waste—Risk as a Basis for Waste Classification, Proceedings of a Symposium held November 9, 1994 (1995) Acceptability of Risk from Radiation—Application to Human Space Flight, Proceedings of a Symposium held May 29, 1996 (1997)

NCRP Statements No. 1 2

3

Title ‘‘Blood Counts, Statement of the National Committee on Radiation Protection,’’ Radiology 63, 428 (1954) ‘‘Statements on Maximum Permissible Dose from Television Receivers and Maximum Permissible Dose to the Skin of the Whole Body,’’ Am. J. Roentgenol., Radium Ther. and Nucl. Med. 84, 152 (1960) and Radiology 75, 122 (1960) X-Ray Protection Standards for Home Television Receivers, Interim Statement of the National Council on Radiation Protection and Measurements (1968)

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NCRP PUBLICATIONS

Specification of Units of Natural Uranium and Natural Thorium, Statement of the National Council on Radiation Protection and Measurements (1973) NCRP Statement on Dose Limit for Neutrons (1980) Control of Air Emissions of Radionuclides (1984) The Probability That a Particular Malignancy May Have Been Caused by a Specified Irradiation (1992) The Application of ALARA for Occupational Exposures (1999) Extension of the Skin Dose Limit for Hot Particles to Other External Sources of Skin Irradiation (2001)

Other Documents The following documents of the NCRP were published outside of the NCRP report, commentary and statement series: Somatic Radiation Dose for the General Population, Report of the Ad Hoc Committee of the National Council on Radiation Protection and Measurements, 6 May 1959, Science, February 19, 1960, Vol. 131, No. 3399, pages 482-486 Dose Effect Modifying Factors In Radiation Protection, Report of Subcommittee M-4 (Relative Biological Effectiveness) of the National Council on Radiation Protection and Measurements, Report BNL 50073 (T-471) (1967) Brookhaven National Laboratory (National Technical Information Service Springfield, Virginia)

Index Absorbed dose (D) 10, 12, 15, 82 bone marrow 15 mean absorbed dose in an organ (DT) 12 Alpha particles 8, 19, 31 Atomic-bomb survivors 8, 25

Conventional system 10–21, 40–43, 65, 76–77, 79–80 applicability 20 comparison of results with the other two systems 76–77 limitations 17–20 radiation measurements 40–43 radiation transport code 14–17 results for a given space radiation scenario 65–67

Biological data 1, 19–20, 21, 30, 50–56, 79, 81 experimental design considerations 54–55 Harderian gland tumor induction 52 human salivary gland tumor cell line 21 human T-1 cells 19–20 human fibroblasts 51, 53 mouse leukemia 52–54 neoplastic transformation 53 rat mammary carcinoma 52–54 TK-total mutants 53 V79 Chinese hamster cell line 21 Bubble detectors 45

Dose and dose-rate effectiveness factor 8 Dose equivalent (H) 10, 12, 82 Dosimeters 40–46, 59 active 40, 42, 45 passive 40, 42–43, 45–46, 59 Effective dose 14, 16, 49, 67–68, 82 Electrons 26, 34, 37 Equivalent dose (HT) 12, 82 Fluence 4–5, 82 Fluence-based system 22–30, 43, 57–60, 61–64, 76–77, 79 comparison of results with the other two systems 76–77 comparison to microdosimetricevent-based system 61–64 idealized application 24 implementation 57–60 radiation measurements 43–46 relation to the conventional system 25 risk assessment 58 risk prediction 57 strengths and limitations 28–30 treatment of photons and neutrons 28

Cancer risk 13, 16 lifetime risk coefficients 13 natural incidence of fatal cancer 16 nonfatal cancer detriment 13 tissues or organs at risk 13 uncertainty for total fatal cancers 13 Cavity ion dosimeters 41 Charged-particle equilibrium 42 Charged-particle spectrometers or telescopes 29, 41, 44, 58–59, 63–64, 81 Charged-particle tracks 3 Cobalt-60 32 Conventional risk cross section 82

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INDEX

Galactic cosmic rays 3, 5, 15–17, 65, 82 space radiation scenario 65 Gamma rays 31, 37, 38, 51, 69, 72–73 cobalt-60 31, 51, 72–73 Hiroshima free gamma-ray field 38, 69 Gas-based proportional counters 39 Harderian gland tumor induction 52–53, 69, 72–73 Heavy ions 4, 5, 19–21, 31, 33, 51, 53–55, 65, 67, 69, 70–76, 78, 81–83 argon 19, 20, 51 beryllium 19 carbon 19, 20, 21, 74 calcium 19 helium 4, 21, 51, 69, 72, 73, 74 iron 4, 5, 31, 33, 51, 55, 69, 72, 73, 74 lanthanum 51 magnesium 19, 74 neon 19, 20, 21, 51, 69, 72, 73 niobium 51, 55, 69, 72–73 nitrogen 51, 74 oxygen 19, 55, 74 sulfur 19 silicon 19, 55, 74 Heavy ion medical accelerator 19 Hereditary disorders 13 Hit-size effectiveness function 7, 34–37, 72, 74, 83 Human fibroblasts 51–53 Human salivary gland tumor cell line 21 Human T-1 cells 19–20 International Space Station 45 Leukemia 15 natural incidence 15 Lineal energy (y) 30, 48, 62–64, 83 dose mean 48 specification of the site size 62 spectrometers 64

Linear energy transfer 1–2, 10, 18, 26, 83 frequency-average 26 limitations 18 unrestricted 10 Mean absorbed dose in an organ (DT) 12, 83 Microdosimetric event-based system 4–5, 30–39, 46–48, 60–64, 71–77, 80, 83 comparison of results with the other two systems 76–77 comparison to fluence-based system 61–64 implementation 60–61 low linear energy-transfer baseline 37 microdosimetric-based quality functions 34 radiation measurements 46–48 results for a given space radiation scenario 71–76 risk assessment 60 risk prediction 60 strengths and limitations 38 Microdosimetry 31 Mir Space Station 38 Natural background radiation 2 Neoplastic transformation 53 Neutrons 28, 34, 45, 59 albedo neutrons 28 from nuclear interactions 28 Neutron recoil spectrometers 45 Organ dose equivalent (HT) 12, 15, 83 bone marrow 15 Particle traversal 4–5 Photons 28 Plastic nuclear track detectors 59 Protons 4–5, 33, 45, 52, 54, 63, 69, 70, 72–74, 81

INDEX

Quality factor (Q) 7, 10–11, 36, 83 dependence on linear energy transfer 11 microdosimetric-based mean quality factor 36

Radiation measurements 40–49 practical limitations 49 Radiation transport codes 3, 14, 24–25, 28–29, 44, 49, 59, 83 interaction cross sections 14 Relative biological effectiveness 19–21, 30, 50–51, 54, 83–84 maximum 50–51, 54, 84 Risk 6–8, 23–24, 84 Risk assessment 56 during and after the mission 56 risk prediction 56 Risk cross sections 7, 22, 24, 26–27, 29, 53–58, 61, 67–71, 84 conventional risk cross section 26–27, 53 low linear energy-transfer baseline value 26–27 results for a given space radiation scenario 67–71 Risk estimation 6–8, 81 conventional system 6–8 fluence-based system 7 microdosimetric event-based system 7

Solid-state nuclear track detectors 42, 46 South Atlantic Anomaly 61 Space radiation environment 1, 2 Space radiation scenario 65, 77, 80 risk of cancer mortality 77 Space Shuttle 41, 43, 47, 61, 63 Specific energy (z) 30, 32, 84 Specific quality factors 75 Specific quality function 7, 34–37, 73–74, 84

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Target fragmentation 69 Thermoluminesent dosimeters 42, 59 optically stimulated luminescent materials 42 TK-total mutants 53 Tissue equivalent proportional counters 32, 38, 46, 48, 60–61, 81 Tissue-equivalent solid-state detectors 39 Tissue weighting factors (wT) 13, 84 V79 Chinese hamster cell line 21 Wall effects 33–34, 47, 61–62, 84 X rays 38, 62