1. ASSESSMENT OF OCCUPATIONAL EXPOSURE DUE TO INTAKES OF RADIONUCLIDES
Uncertainties and Performance Criteria

2. Interpretation of Measurement Results – Unit Objectives
The objective of this unit to identify and define the criteria that are used to characterize the quality of the measurement process for both direct and indirect methods. It will also identify sources of uncertainty in measurement and interpretation and give an estimate of expected magnitudes.
At the completion of this unit, the student should understand how to calculate Minimum Detectable Activity and establish adequate accuracy criteria for measurement bias and precision.

3. Interpretation of Measurement Results - Unit Outline
Measurement Uncertainties
Intake and Dose Assessment Uncertainties
Performance Criteria: Accuracy
Performance Criteria: Sensitivity
MDAs - Examples

4. Measurement Uncertainties

5. Dose determination uncertainties
Measurement
Interpretation
Direct or indirect
measurements
e(g)j
m(t)
Estimated
intake
Committed
effective dose ?2 ?3
Body/organ content, M or
Excretion rate, R ?1
Body/organ content, M or
Excretion rate, R
There are three sources of uncertainty in the internal dose assessment process
individual monitoring measurements, ?1
assessment of intake from the measurements, ?2, and
assessment of dose from the intake, ?3.
The overall uncertainty in assessed dose is a combination of the uncertainties from these three sources. The uncertainty associated with each source and the effort required to quantify it depend on the radionuclides involved, the extent of information on the level of exposure and its time course, and the time of sampling or measurement.

6. Measurement uncertainties
Usually most straightforward to estimate
Counting statistics dominate at low activities
For radionuclides that are,
Easily detected, and
In sufficient quantity,
counting statistics are small compared to other uncertainties
Systematic uncertainties are important
Correction for activity remaining previously measured intakes may be necessary
Generally, the uncertainties in the measurement are the most straightforward to estimate. When activity levels are low and close to the limit of detection, uncertainties due to counting statistics may dominate the overall uncertainty. For radionuclides that are easily detected and present in sufficient quantity, uncertainties due to counting statistics will be small compared to other sources of uncertainty. Consideration must also be given to systematic uncertainties in other parts of the measurement procedure, e.g. calibration, or for in vivo measurements, correction for body size.

7. Common measurement uncertainties
Statistical counting errors
Distribution in the body
Absorption by overlying tissue (low energy photons)
External contamination of the subject or measurement system
Calibration errors
Source activity
Simulation accuracy
Taking into account the main affecting sources of uncertainties in direct in vivo radioactivity measurements the typical values of uncertainties can be expected to be between 10% and 90% depending on the radionuclide involved and the monitoring method applied. This value can be even higher in case of measurement of transuranic elements
Errors in assessment of distribution in the body, or even specific organs such as lung counting for plutonium, are highly dependent on several factors including: radionuclide, mode of intake, and time after intake. At higher levels – near or above the relevant limits – special counting can be performed to make improve the determination of body distribution.
As indicated the absorption of overlying tissues is primarily an issue for lower energy photons (< keV). If that is a concern, special techniques such as ultrasound measurements can be employed.

8. Estimated Direct Measurement uncertainties*
Source of uncertainty
Estimated magnitude
1 σ
Chest wall thickness determination
15% to 300% worst case for 17 keV
Geometry errors – Subject size and shape departure from single-size calibration model
10% for good geometries (I m arc, linear w/front /back counts)
15-20% for common geometries (linear w/counts from 1 side, 50 cm arc)
40% for poor geometries (detector in contact w/body)
Positioning of subject
10-15% for whole body
* From ANSI (1996)

9. Typical uncertainties for assessing fission product isotopes*
Source of Uncertainty
Estimated
Uncertainty
Depth
Length  Width
Height-Weight
Analysis Technique
Calibration
Counting Statistics
Total Estimated Uncertainty
12% 5% 7% 3%
40%
This illustrates typical estimated uncertainties for assessing fission product body burdens by in direct measurement. It can be seen in comparison with uncertainties for uranium and plutonium lung counting in the next two slides.
* From Toohey, et al,

10. Typical uncertainties for U lung counting
Source of Uncertainty
Estimated Uncertainty
Chest Depth
Chest Wall Thickness
Activity Location
Detector Placement
Subject Background
Calibration
Counting Statistics
Total Estimated Uncertainty
12%
15% 5%
10%
40%
90%
This illustrates typical estimated uncertainties for assessing uranium lung burdens by in vivo counting. The major impact derives from the low energy of the photons, and the lower body levels of activities. The main impact is on statistics.
* From Toohey, et al,

11. Typical uncertainties for Pu lung counting
Source of error
Uncertainty
Subject background
50%
Counting statistics
Chest wall thickness
40%
Non-uniform distribution
70%
Calibration
20%
Overall uncertainty
110%
The uncertainties become even greater for plutonium lung counting, primarily because of the very low photon energy – 17 keV.
* From Toohey, et al,

12. Estimated Indirect Measurement uncertainties
Several parameters contribute to indirect measurement uncertainties
The uncertainty associated with most are highly variable
Typical uncertainties associated with the radiochemistry are of the order of 3%
More details can be found in the USDOE Laboratory Accreditation Program report – ANSI N and ISO

13. INTRODUCTION OF SF
The recently developed IDEAS Guidelines for the assessment of internal doses from monitoring data suggest default measurement uncertainties (i.e. scattering factors, SF) to be used for different types of monitoring data.
The SF values represent the geometric standard deviation of the distribution of all results, supposed to be approximated by log-normal distribution.

14. The IDEAS guidelines consider two types of uncertainty :
INTRODUCTION OF SF
The IDEAS guidelines consider two types of uncertainty :
Type A : connected to counting statistic and decreasing with the increasing of activity and counting time (Poisson distribution)
Type B : all other components of uncertainty also connected with inter and intra-subject variability (e.g. in excretion)

15. INTRODUCTION OF SF SF values are important. For these issues.
They are needed to assess the uncertainty in the estimated intake and dose.
They determine the relative weighting of data in fitting process and can effect the estimated intake when different types of monitoring data are used simultaneously.
They enable rogue data to be identified objectively
They enable objective (statistical) criteria (goodness-of-fit) to be calculated, which are used to determine whether the predictions of the biokinetic model (with a given set of parameter values) used to assess the intake and dose are inconsistent with the measurement data.

16. INTRODUCTION OF SF
The IDEAS Guidelines assume the overall uncertainty on an individual monitoring value can be described in terms of a lognormal distribution and the SF is defined as the geometric standard deviation (GSD).
This approximation is valid if Type A errors are relatively small (<30%). Thus, it is assumed that if the measurements could be repeated, hypothetically at the same time, then the distribution of the measurement results could be described by a lognormal distribution.

17. INTRODUCTION OF SF
SF values depend on type of monitoring measurement. Default values are reported in the following slides.
When the type A component of the uncertainty is small (< 30%) the type B component alone could be used for uncertainty.

18. SF default values for in-vivo measurements
SF values depend on type of monitoring measurement. For in-vivo measurement types:
In vivo measurements
SF values (Type B uncertainty)
Low photon energy
E < 20 keV
2.1
Intermediate photon energy
20 keV < E < 100 keV
1.3
High photon energy
E > 100 keV
1.2

19. SF default values for in-vivo measurements
SF values depend on type of monitoring measurement. For in-vitro measurement types:
In vitro
measurements
SF values
(Type B uncertainty)
URINE
For HTO after inhalation
1.1
Normalized 24 h excretion
1.7
Spot urine data
2.0
FECES
Inhalation (Pu-Am)
2.5
Wound (Pu)
3.1

20. Intake and Dose Assessment Uncertainties

21. Some sources of assessment uncertainty
Mode of intake
Physical and chemical form of material
Particle size (AMAD) of the aerosol
Time pattern of intake (acute vs. chronic)
Errors in biokinetic and dosimetric models
Individual variability in biokinetic and dosimetric parameters

22. Intake assessment uncertainties
Difficult to quantify in routine monitoring - measurements are made at pre-determined times are unrelated to time of intakes
Compromise between measurement interpretation quality and the practical limitations linked to measurement frequency
Monitoring intervals should be selected so that underestimates due to unknown time of intake are ≤ 3
The uncertainty in the assessment of intake may be difficult to quantify in a routine monitoring programme, where measurements are made at pre-determined times, unrelated to the times of intakes. It is necessary to have a compromise between the quality of the interpretation of the measurement results and the practical limitations linked to the frequency of the measurements. A simple rule has to be defined to limit the possible error on estimate of intake due to the unknown time of exposure. Monitoring intervals should be selected so that any underestimation introduced by the unknown time of intake is no more than a factor of three.

23. Intake assessment uncertainties
Practically, this is a maximum since the actual distribution of the exposure in time is unknown
Statistically, the error is not systematically the same for all the assessments
The random distribution of the exposure makes such an error clearly lower than a factor of 3
If intake occurs just before sampling or measurement, it could be overestimated ≥ 3
Indeed, in practice, this underestimate is a maximum because the actual distribution of the exposure in time is unknown, so that, statistically, the error is not systematically the same for all the assessments. The stochastic distribution of the exposure makes such an error clearly lower than a factor of three. If a substantial part of the intake occurs just before sampling or measurement, the intake could be overestimated by more than a factor of three.

24. Intake assessment uncertainties
Particularly important for excreta monitoring  daily fractions excreted can change rapidly immediately after intake
If a high result is found in routine monitoring, it would be appropriate to repeat the sampling or measurement a few days later  adjust the estimate of intake accordingly
Samples could also be collected after a period of non-exposure, e.g. after weekend or holiday
This may be particularly important in the case of excreta monitoring, since the fraction excreted each day may change rapidly with time in the period immediately following the intake. If an unexpectedly high result is found in a routine monitoring programme, it would be appropriate to repeat the sampling or measurement a few days later, and adjust the estimate of intake accordingly. Alternatively, if appropriate and if convenient, the sample could be collected or the measurement made after a period of non-exposure, for example after a weekend or holiday.

25. Assessment uncertainties
Models used to describe radionuclide behavior are used to assess intake and dose
Reliability of dose estimates depends on the accuracy of the models, and limitations on their application
This will depend upon many factors, including:
Knowledge of the time of intake, and
Whether the intake was acute or chronic
From an assessment of the activity in the whole body or in samples of tissues or excreta, the models used to describe the behaviour of radionuclides in the body are then used to assess intake and dose. The reliability of the estimates of dose therefore depend upon the accuracy of the models, and any limitations on their application in particular circumstances. This will depend upon many factors. In particular, knowledge of the time of the intake(s) and of whether the intake was acute or chronic is essential for a reliable dose estimate.

26. Assessment uncertainties
If the sampling period does not enable the estimation of the biological half-life, assumption of a long body retention may lead to an underestimate of the intake and the committed effective dose
The degree of over- or under-estimation of the dose depends on the body retention pattern
When the sampling period does not enable the biological half-life of the radionuclide to be estimated, assuming a long period of retention in the body for the purpose of dose assessment may result in an underestimate of the intake, and hence of the committed effective dose. The degree of over- or under-estimation of the dose will depend upon the overall pattern of retention in the body.

27. Assessment uncertainties
Radionuclide behavior in the body depends upon their physicochemical characteristics
Particle size of inhaled radionuclides is a particularly important for influencing deposition in the respiratory system
Gut absorption factor f1 substantially influences effective dose following ingestion
The behaviour of radionuclides that enter the body by ingestion or inhalation will depend upon their physicochemical characteristics. For inhaled radionuclides, the particle size is particularly important in influencing deposition in the respiratory system, while for ingestion the gut absorption factor f1 can substantially influence effective dose.

28. Assessment uncertainties
When exposures during routine monitoring are well within limits on intake, default parameters may be sufficient to assess intake
If exposures approach or exceed these limits, more specific information on;
Physical form and chemical form of the intake, and
Characteristics of the individual,
may be needed to improve the accuracy of the model predictions
For routine monitoring when exposures are well within limits on intake, the default parameters recommended in the BSS may be sufficient for assessing intakes. For exposures approaching or exceeding these limits, however, more specific information on the physical and chemical form of the intake, and the characteristics of the individual, may be needed to improve the accuracy of the model predictions.

29. Intake fraction, m(t) depends on several factors1
10-1
10-2
10-3
10-4
10-5
10-6
10-7
10-8
60Co, inhalation type M
m(t)
Whole body
Lungs
Urine
Feces 10
100
1000
10000
This figure illustrates the factors which can contribute to the uncertainty in the intake fraction, m(t), a major component of uncertainty in determining intake from body content. The The value of the intake fraction depends on several factors: Intake pattern; Elapsed time from intake, Absorption rate; Deposition site; Particle size; and Mode of intake. Careful consideration needs to be given to each of these parameters to establish the most likely values before making a determination of M(t).
Time after intake, d
Intake pattern (acut. vs. chr.) Deposition site
Time after intake Particle size Absorption rate (F, M or S) Mode of intake

30. Performance Criteria: Accuracy

31. Performance criteria Accuracy Bias (Systematic errors)
How well can a given measurement be reproduced.
Repeatability or Precision (Random errors)
How close is the mean of a series of measurements to the true value
Sensitivity (MDA)
What is the lowest value of a quantity that can be measured?
Two basic performance criteria are considered for direct and indirect measurements – Accuracy and Sensitivity. Accuracy, in turn has two components – Bias and Precision.
Bias, which refers to the systematic errors, may be defined as, “The deviation of a single measured value of a random variable from a corresponding expected value, or a fixed mean deviation from the expected value that remains constant over replicated measurements within the statistical precision of the measurement. (Systematic error).”
Precision, which refers to the random errors, is “A concept employed to describe dispersion of measurements with respect to a measure of location or central tendency.”
Sensitivity refers to the minimum value of a quantity that can be detected – Minimum detectable activity (MDA).

32. Performance criteria - Bias
Definition:
where: Bri = relative bias for the ith measurement
Ai = measured activity
Aai = actual activity for the ith measurement

33. Performance criteria - Bias
For a test or measurement category,
Where: Br = Relative bias for the category
n = number of replicate measurements

34. Performance criteria – Repeatability*
Definition:
where: SBr = measurement repeatability for the test or measurement category
* Also termed Precision

35. Accuracy - How close is close enough?
When the activity Aai is at or above the specified Minimum Testing Level (MTL),
Relative bias, Br
 Br  +0.50
Relative repeatability, SBr
SBr  0.40
These values used by ISO and USDOE Laboratory Accreditation Program
Accuracy requirements for internal dosimetry have been addressed by only a few national regulatory bodies. In the United States, the Department of Energy emphasized its Laboratory Accreditation Program, DOELAP, for external and, now internal, dosimetry services. DOELAP accuracy requirements address measurement accuracy through specification of relative bias, Br and relative precision, SB, which together provide the required accuracy specification. Although other definitions may be found, bias is defined as, “The deviation of a single measured value of a random variable from a corresponding expected value, or a fixed mean deviation from the expected value that remains constant over replicated measurements within the statistical precision of the measurement. (Systematic error).”(22), and precision is “A concept employed to describe dispersion of measurements with respect to a measure of location or central tendency.”(22).

36. MTL Values for Direct Measurements
Measurement Category
Type
Radionuclide
MTL
I. Transuranium elements via L x-rays
Lung
238Pu
9 kBq
II. Americium-241
241Am
0.1 kBq
III. Thorium 234
234Th in equilibrium w/ parent 238U
0.5 kBq
IV. Uranium-235
235U
30 kBq
V. Fission and activation products
Any two: 54Mn, 58Co, 60Co, 144Ce +
134Cs & 137Cs/137Ba
3 kBq
VI. Fission and activation products
Total body
All of: 134Cs, 137Cs/137mBa, 60Co & 54Mn
VII. Radionuclides in the thyroid
Thyroid
131I or 125I
The values MTL categories and values presented here are recommended both by ISO and the USDOE Laboratory Accreditation Program..

37. MTL Values for Indirect Measurements
Measurement category
Radionuclide
MTL
(per L or per sample)
I. BETA activity: average energy < 100keV
3H, 14C
35S
228Ra
2 kBq
20 kBq
0.9 kBq
II. BETA activity: average energy ≤ 100 keV
32P
89, 90Sr or 90Sr
4 Bq
III. ALPHA activity: isotopic analysis
228,/230Th or 232Th
234/235U or 238U
237Np
238Pu or 239/240Pu
241Am
0.02 Bq
0.01 Bq
IV. Elements (mass/volume)
Uranium
20 μg
V. GAMMA (photon) activity
137Cs/137mBa
60Co
125I
2 Bq
0.4 kBq

38. Accuracy - How close is close enough?
ICRP Publication 75, General Principles for the Radiation Protection of Workers:
For external dosimetry a factor of 1.5 at the limits (20 mSv/year)
The overall uncertainty in the dose from internal exposure, is likely to be greater than for external exposure
In searching for guidance on acceptable accuracy, ICRP Publication 75 is a starting point. It recognizes the problems and uncertainties associated with individual dose assessment, and sets a factor of 1.5 at the limits (20 mSv/year) as a starting point for external dosimetry. However, it is recognized that the problems encountered in internal dose assessment can be significantly greater….

39. Accuracy - How close is close enough?
ICRP Publication 75, General Principles for the Radiation Protection of Workers:
Sampling frequencies should be chosen to avoid errors due to intake uncertainties of more than about a factor 3
For less simple programs, e.g. for insoluble plutonium, total uncertainties may be about one order of magnitude.
The recommendation is that the sampling frequencies for direct measurement, and/or indirect measurement such be chosen to avoid errors due to intake uncertainties of no more than about a factor of three. For more complicated situations, such as assessment of insoluble plutonium, the uncertainties can be about an order of magnitude. This also implies that a knowledge of the radiation hazard (nuclides, quantities, forms, etc.) is an a priori requirement.

40. Performance Criteria: Sensitivity

41. Two terms describe sensitivity
Minimum Detectable Activity (MDA) (a priori)
Minimum activity that can be detected
Probability, α, of false positive (Type I error)
Probability, β, of false negative (Type II error)
Decision level, LC, (a posteriori)
The total count value or final measurement of a statistical quantity, LC, at or above which the decision is made that the result is positive
Minimum Detectable Activity (MDA) (detection limit, lower limit of detection, limit of detection) is a calculated a priori value which specifies the minimum body contribution (true activity) that can be detected by a defined measurement method, i.e. which would give the registered pulses below the decision threshold based on the Type I error () with given probability of a Type II (). The detection limit is an a priori value that can be compared with guideline values.
Decision level (minimum significant activity, decision threshold, lower limit of decision, critical level ) is an a posteriori (i.e. after measurement) calculated value at which the decision can be made, with a given probability of Type I error (), for each measurement result whether the registered pulses include contributions by the body or are solely due to background (e.g. a peak of a gamma line of a nuclide in question). Otherwise, it should be assumed in each case that there is no sample contribution in the region of interest.
If the decision rule is observed, a wrong decision that there is a real contribution in the region of interest when in fact only a background effect exists occurs with the probability,  (Type I error).

42. Confidence levels and k valuesα
1-β k
0.001
0.999
3.090
0.005
0.995
2.576
0.010
0.990
2.326
0.025
0.975
1.960
0.050
0.950
1.645
0.100
0.900
1.282
0.200
0.800
0.842
0.250
0.750
0.675
0.300
0.700
0.525
0.400
0.600
0.254
0.500

43. Standard Deviation
where: s = standard deviation of a set of N measurements
xi = ith measurement in the set
x = mean of the set of measurements
Estimate of the relative standard deviation for a single measurement:
sB = standard deviation of the appropriate blank sample
s0 = standard deviation of the net subject or sample count

44. Illustration of LC and MDA relationshipLc
MDA
0 – Value of background distribution
LC – The likelihood that the sample distribution characterized by LC was not really positive (false positive) is α
MDA – The likelihood that a sample distribution characterized by the MDA will be missed (false negative) is β and is not really positive (false positive) is α sB α
(b)
(a)
kαsB  s0
Because of the shape of the distributions, it should be stressed that these are not photopeaks. They represent the distribution of a large number of replicate measurements of the same quantity.
(c)
kβs0
Background
Detected
Not detected
May be
Will be

45. Minimum detectable activity - MDA
Values assigned to MDA depends on the risk of making an error, false positive or false negative.
Simplification: Assume β = α, and β = α = 0.05
Then kα = k1-β = = k
where: s0 = standard deviation of net subject counts
K = efficiency
T = subject counting time
The minimum detectable activity (MDA), often termed the detection limit (LD), corresponds to the level of activity which is needed to ensure, with some chosen level of confidence β, that the net signal will be detected, according to the criterion that it exceed the MSA. The mathematical treatment is simplified, as in the following section, if β=σ, and by common convention 0.05 is adopted for both.

46. Minimum detectable activity - MDA
where: sB1 = standard deviation in subject counts with no actual activity
sB0 = standard deviation in unadjusted blank counts
It can be assumed that sB1 = sB0 = s0, and m = 1
Then, s0 = sB2 = 1.415sB, where sB is the standard deviation of a total blank count

47. Minimum detectable activity - MDA
For direct measurements, MDA becomes:
For indirect measurements:
where: R = chemical recovery
λ = radiological decay constant
Δt = elapsed time between reference time and time of count

48. Direct measurement MDAs*
Measurement category
Organ
MDA
I. Transuranium elements via x-rays
Lungs
185 Bq/A
II. 241Am
26 Bq
III. 234Th
110 Bq
IV. 235U
7.4 Bq
V. Fission and activation products
740 Bq/A
VI. Fission and activation products
Whole body
VII. Radionuclides in the thyroid
Thyroid
* From ANSI 13.30
A is the number of photons per nuclear transformation – L x-rays for transuranium elements, and gamma rays for fission and activation products
Equivalent values of MDA and MDC (minimum detectable concentration) are presented in ICRP Publication 78. Those values are generally lower than those of ANSI However, MDA depends on several factors, including counting geometry, analytical techniques and counting time.
The difference ranges from very little (20 Bq for 241Am) to very significant (50 Bq for 137Cs compared with 890 Bq after correction for photon abundance). A short comparison follows:
ICRP 78 ANSI 13.30*
238Pu 103 Bq 1.7103 Bq
239Pu 2103 Bq 4.0103 Bq
241Am 20 Bq 26 Bq
235U 200 Bq 7.4 Bq
58/60Co 100 Bq 740 Bq
137Cs 50 Bq 890 Bq
131I 100 Bq 830 Bq

49. Indirect measurement MDCs (urine)*
Measurement Category
Nuclide
MDC
I Beta - Average energy ≤ 100 keV
3H, 14C, 35S
147Pm
210Pb, 228Ra, 241Pu
370 Bq/L
0.37 Bq/L
0.19 Bq/L
II. Beta – Average energy > 100 KeV
32P, 89/90Sr or 90Sr
131I
0.74 Bq/L
3.7 Bq/L
III. Alpha – Isotopic specific measurements
210Po, 226Ra, 228/230/232Th, 234/235/238U
237Np, 238/239/240Pu, 241Am, 242/244Cm
3.7 mBq/L
2.2 mBq/L
IV. Mass determination
Uranium (natural)
5 μg/L
V. Gamma or x-rays
Emitters with photons ≤ 100 keV
2 Bq L-1/A
VI. Gamma or x-rays
Emitters with photons > 100 keV
For urinalysis, the ICRP 78 values are typically a factor of 2-4 lower than those of ANSI Differences in assumed parameters and analytical techniques can result in significant differences in the nominal MDC values. Those reported in Publication 78 are likely to represent MDCs that can be achieved under the best of conditions. Incidentally, the reason for the odd values in ANSI (370, .37, 2.2, etc.) is not high accuracy, but the continuing use of the unit, Curie in the U.S. These quantities were established curies (e.g. 10 nCi/L) with a conversion to Becquerels (370 Bq/L).
* From ANSI 13.30
A is the number of photons per nuclear transformation – L x-rays for transuranium elements, and gamma rays for fission and activation products

50. Indirect measurement MDAs (faeces)*
Measurement Category
Nuclide
MDA
VII. Alpha – Isotope specific measurements
234/235/238U, 228/230/232Th, 238/239/240Pu, 241Am
37 mBq/sample
VIII. Beta – Average energy > 100 keV
89/90Sr or 90Sr
0.74 Bq/sample
IX. Gamma or x-rays
Emitters with photons ≤ 100 keV
2/A Bq/sample
X. Gamma or x-rays
Emitters with photons > 100 keV
MDAs for faecal analysis reported ICRP Publication 78 are moderately to significantly lower than the ANSI MDAs. ICRP78 presents the following for comparison:
234/235/238U and 228/232Th 10 mBq vs. 37 mBq
238/239/240Pu mBq vs. 37 mBq
241Am mBq vs. 37 mBq
58/60Co, 134/137Cs mBq vs. ~2 mBq depending on photon abundance
* Minimum detectable concentration - From ANSI 13.30
A is the number of photons per nuclear transformation – L x-rays for transuranium elements, and gamma rays for fission and activation products

51. MDAs – Examples

52. Determination of MDA - Example
90Sr by Beta Gas Flow Proportional Counting
20 reagent blanks were counted for 1 hour each – 3600 s
Total counts 83 69 53 72 59 77 70 62 88 66 73 55 74 65 68 61

53. Determination of MDA - Example
90Sr by Beta Gas Flow Proportional Counting
B = 67.4 counts
SB =  [(Xi – 67.4)2/19] = 9.4
Counting efficiency, K = 0.36
Chemical yield = 0.81

54. Determination of MDA - Example
Whole body counting for fission and activation products
Radionuclide
137Cs
60Co
Organ
Body
Lungs
Counts in peak region - B 9 8
SB =B 3
2.8
Count time, T – s
600
Calibration factor, K
1.3510-4
2.9710-4
MDA - Bq
209 90

55. References
HEALTH PHYSICS SOCIETY, Performance Criteria for Radiobioassy, An American National Standard, HPS N (1996).
INTERNATIONAL ATOMIC ENERGY AGENCY, Occupational Radiation Protection, Safety Guide No. RS-G-1.1, ISBN (1999).
INTERNATIONAL ATOMIC ENERGY AGENCY, Assessment of Occupational Exposure Due to Intakes of Radionuclides, Safety Guide No. RS-G-1.2, ISBN (1999).
INTERNATIONAL ATOMIC ENERGY AGENCY, Indirect Methods for Assessing Intakes of Radionuclides Causing Occupational Exposure, Safety Guide, Safety Reports Series No. 18, ISBN (2002).
International Standards Organization, Radiation Protection – Performance Criteria for Radiobioassay – Part 1: General Principles, ISO TC 85/SC2 (1999).