A METHOD FOR DETERMINING ORGAN DOSE FROM EXTERNAL EXPOSURE

MONITORING DATA

T. D. Taulbee, J. W. Neton, L. J. Elliott

National Institute for Occupational Safety and Health, 4676 Columbia Parkway, Cincinnati,

Ohio, United States of America, 45226, Fax: 513-458-7125, email: t&!~cdc.gov

Abstract

To estimate the probability of causation in an occupational radiation exposure compensatioIf

~gram, it is necessary to reconstruct the dose for the tissue or organ that was diagnosed with a

primary cancer. In occupational monitoring programs, dosimeter badges are commonly used to

assess compliance with prescribed exposure limits. Because the dosimeter badges measure the

dose delivered at a specific point on the body, and not to the actual organ, a method has been

developed to convert the regulatory compliance dose (monitored dose) to a dose to the affected

organ or tissue. The method takes into consideration: 1) the response of the monitoring device;

2) the exposure photon energy; and, 2) the exposure geometry. The combination of these three

factors results in a time, facility, and task specific organ dose conversion factor (DCF). This

paper describes the technical approach used in developing these organ specific dose conversion

factors. Examples of the relative importance of accounting for differences between regulatory

compliance dose and the organ dose are provided for selected exposure conditions.

1. Introduction

Under the U.S. Energy Employees Occupational lllness Compensation Program Act [1], the

National Institute for Occupational Safety and Health (NIOSH) is tasked with reconstructing

internal and external organ doses for certain U.S. Department of Energy (DOE) facility workers

who are covered under the provisions of the Act. Since most historical radiation monitoring

data has been perfOI'JDed for regulatory compliance purposes, NIOSH has evaluated the

applicability of compliance based external dose monitoring results against the needs of a worker

compensation program that uses probability of causation as the deciding factor.

A review of the literature indicates that early external dosimetry monitoring data was based on a

measure of radiation exposure in Roengten (R). More recently the ambient dose equivalent

(H.(lO» or the personal deep dose equivalent (Hp(lO» have been used to represent the external

dose to a worker. Each of these values, however, estimate the exposure or dose at a single point

on the body and were not intended to be representative of the dose to individual organs. In this

paper, we have used the values tabulated in ICRP Publication 74 [2] and ICRU Publication -43

[3] as the basis for developing a method that could be used to evaluate the differences between

these monitored doses and organ doses.

To convert any of the above monitored doses to an accurate estimate of organ dose, the photon

energy of the exposure must be considered. While knowledge of the facility specific energy

spectrum would be ideal, in most cases, only photon doses within broad energy intervals are

likely to be known. At DOE facilities in the United States for example, film badges in the mid1960s used multiple absorbers to determine the dose from low energy x-rays, intermediate

energy photons, and high energy photons. With these broad energy intervals, a mean or

effective dose conversion factor is needed for organ dose determination.

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-

The following section describes the technical approach used to develop a method for converting

monitored dose to organ dose for each of the factors discussed above.

2. Methods

2.1. Monitoring Device Conversion

Many of the coefficients necessary to convert monitored dose to organ dose are contained in

ICRP Publication 74 [2]. These are listed in that document by tissue of interest, exposure

geometry, and radiation energy. These coefficients can be used to convert from ambient dose

equivalent (H*(10» and personal dose equivalent (Hp(IO» to free-in-air KERMA (Ka ) for

various photon energies. Also included in ICRP 74 are the coefficients necessary to convert

Hp(IO) to Ka. Since most early monitoring data was reported in units of exposure, and not a

deep dose at 10 mm, the conversion from exposure in Roengten to ambient deep dose requires

an additional step. This was accomplished using the factors provided in ICRU Publication 43

[3]. Once the monitored dose is converted to free-air KERMA, the organ dose is calculated as

the product of free-air KERMA and the dose conversion factors (DT/Ka). Equation 1 provides

the general foImula that can be used to convert Hp(lO) to organ dose for a given monitoring

device.

DCF( DAf.Hp(lOJ-+D,.)= D1 Equation 1

x-

!!.!.~ K.

K.

2.2. Energy Interval Estimation

Equation 2

577
..0

i)

~

c

..

6

~

C

~

CI

.

0

~

~

g

c

}:

2

~

Photon Encrgy (MeV)

Figure 1. Red Bone Marrow Dose Conversion Factor (DCF) for the anterior-posterior

geometry a5 a function of photon energy

2.3. Exposure geometry

There are six basic radiation exposure geometries in the worlc enviromnent. With respect to the

incident radiation these are: 1) anterior to posterior (AP); 2) posterior to anterior (P A); 3) left

lateral (LLAT); 4) right lateral (RLAT); 5) rotational (ROT); an~ 6) isotropic (ISO). Of these,

only four (AP, P ~ ROT, and ISO) are of primary interest in most occupational settings. While

the AP exposure orientation is the most common geometry experienced by workers who handled

radioactive materials. there are other jobs with different exposure orientations. For example. the

isotropic exposure geometry might be representative of a worker assigned to a dnnI1 storage

warehouse. A reactor worker refuelling a graphite reactor would likely receive their exposure in

both the AP and ROT geometry. Some occupational medical exposures are in the P A exposure

geometry. -

Job specific exposure geometries. based on process evaluation and interviews, should be

determined for each worker, however, the use of professional judgment may be required when

detailed infonnation is not available. In many circmnstances workers may have multiple

exposure geometries. To account for these different geometries, the organ doses can be

weighted based on the amount of time spent in each exposure orientation, which results in a

work specific Dose Conversion Factor (DCF w) as shown in equation 3. As indicated, the

geometry specific dose conversion factors are functions of the monitoring device and photon

energy .

Equation 3 +wNDCF(DJI,EY)~A +

. +wSJDCF(DJI,Ey)m

Jx:F(DAt,Er). = w,DCF(DAt,Er),

w.".DCF (DAt ,Er)WJ1

578

>- "-

~

0

..

c

~

'<

'0

=-.

~

Q
3. Discussion

The type of monitoring device~ the exposure energy~ and the exposure geometry can have a large

impact on the estimated organ dose. With the exception of the thyroid, testes and bone surfaces

at low energies~ the modem monitored dose is always greater than the organ dose. Figure 2

provides organ dose conversion factors for bone marrow, breast and lung for exposure to 100

keY photons.

As indicated in Figure 2, the dose conversion factors from exposure measurements to organ dose

are greater than the Hp(IO) to organ dose conversion factors. This is primarily the result of the

inclusion of backscatter radiation in the calculation of personal dose equivalent. It should be

noted that in the intermediate energy band, the DCF could vary by 40% depending on

monitoring device alone.

'1-p; :~

:. . I I-¥~ I

i.1 T.» j ~ Dr"--(a) I

~

= ~ ~aJ

~~ t

. .

~ ~ o~

. 2 r

-: 0

~~ O~I-

~ ...

I ' !

~ :s o~

ug.& ~ o~

I

BcmcM2mJW l.I8C Brast (FeaIaIe)

Figure 2. Comparison of organ dose conversion factors for selected organs at 100 keV

irradiation

The sequence in how the dose conversion factor is computed can affect the value of the final

dose conversion factor. The sequence of computation should be perfOmled from the most

specific or best-la1own data to the least specific data. In many cases, the monitoring device and

calibration methodology is latown. In addition, the energy intervals are mandated by the

probability of causation methodology. Therefore these two components are calculated first and

then the exposure geometry specific dose conversion factor is computed. However, if the

exposure geometry were known more precisely than the energy spectrum, a work specific dQse

conversion factor as a function of energy should be developed before the energy interval

integration. Finally, the integration under the curve to obtain effective dose conversion

coefficients assumes a uniform distribution across the energy interval of interest. This

assumption might not be applicable in all circumstances. When the photon energy spectrum can

be well characterized, this information should be used.

While the methodology presented in this paper is described for photon exposures; the same

methodology could be applied to external neutron and electron exposures. For neutron

expo~ some consideration must be given to the ability of the monitoring device to detect

different energy neutrons and the radiation weighting factors that might be applied.

579
4. Conclusions

It is possible using published infonnation to convert monitored badge results into organ doses

relatively easily. Using the methodology described in this paper, the magnitude of the

differences between monitored external dose and organ dose can be evaluated. If desired, these

differences could be accounted for in a worker's external dose reconstruction effort.

References

[1

[2]

[3]

The Energy Employees Occupational lllness Compensation Program Act, Public La~

106-398, 114 Stat. 1654, 1654A-1231 (October 2000), enacted as Title XXXVI of the

Floyd D. Spence National Defense Authorization Act for Fiscal Year 2001.

International Commission on Radiological Protection. Conversion Coefficients for Use in

Radiological Protection Against External Radiation, ICRP Publication 74; AIm. ICRP

26(3/4); Pergamon Press, Oxford, England (1996).

International Commission on Radiation Units and Measurements. Determination of Dose

Equivalents From External Radiation Sources - Part 2, ICRU Report 43, International

Commission on Radiation ICRU Units and Measurements, Bethesda Maryland. (1988).

580