| Literature DB >> 32372284 |
A Giussani1, M A Lopez2, H Romm3, A Testa4, E A Ainsbury5, M Degteva6, S Della Monaca7, G Etherington5, P Fattibene7, I Güclu8, A Jaworska9, D C Lloyd5, I Malátová10, S McComish11, D Melo12, J Osko13, A Rojo14, S Roch-Lefevre15, L Roy15, E Shishkina6,16, N Sotnik17, S Y Tolmachev11, A Wieser18, C Woda18, M Youngman5.
Abstract
This work presents an overview of the applications of retrospective dosimetry techniques in case of incorporation of radionuclides. The fact that internal exposures are characterized by a spatially inhomogeneous irradiation of the body, which is potentially prolonged over large periods and variable over time, is particularly problematic for biological and electron paramagnetic resonance (EPR) dosimetry methods when compared with external exposures. The paper gives initially specific information about internal dosimetry methods, the most common cytogenetic techniques used in biological dosimetry and EPR dosimetry applied to tooth enamel. Based on real-case scenarios, dose estimates obtained from bioassay data as well as with biological and/or EPR dosimetry are compared and critically discussed. In most of the scenarios presented, concomitant external exposures were responsible for the greater portion of the received dose. As no assay is available which can discriminate between radiation of different types and different LETs on the basis of the type of damage induced, it is not possible to infer from these studies specific conclusions valid for incorporated radionuclides alone. The biological dosimetry assays and EPR techniques proved to be most applicable in cases when the radionuclides are almost homogeneously distributed in the body. No compelling evidence was obtained in other cases of extremely inhomogeneous distribution. Retrospective dosimetry needs to be optimized and further developed in order to be able to deal with real exposure cases, where a mixture of both external and internal exposures will be encountered most of the times.Entities:
Keywords: Biokinetics; Biological dosimetry; EPR dosimetry; Internal dosimetry; Internal exposures
Mesh:
Substances:
Year: 2020 PMID: 32372284 PMCID: PMC7369133 DOI: 10.1007/s00411-020-00845-y
Source DB: PubMed Journal: Radiat Environ Biophys ISSN: 0301-634X Impact factor: 1.925
Fig. 1Schematic illustration of the saturation of the DC signal due to fading during chronic exposure with constant annual doses (by H. Romm). Black solid line: accumulated dose (left y-axis); black dashed lines: aberration yield assuming a survival half-life of the DC signal of 3 years (right y-axis); grey solid line: aberration yield assuming a survival half-life of the DC signal of 1.5 years (right y-axis)
Fig. 2Comparison of doses estimated by cytogenetic dosimetry and assessed intake of 137Cs (data from Brandão-Mello et al. 1991)
Fig. 3Comparison of doses estimated by cytogenetic dosimetry and committed internal absorbed dose estimated by whole-body measurements. White diamonds: data from Ramalho et al. (1988); Black squares: compilation of data from Melo et al. (1994), Tables 7.1, 7.2 and 8.2 of IAEA (1998) and Lipsztein et al. (1998). The dashed line represents the identity relation
Estimated doses received at various times after accidental intake of tritium (from Lloyd et al. 1986, 1998)
| Sampling time (days after accident) | Absorbed dose from blood (Gy) | Effective dose equivalent from blood (Sv)b | Committed dose to soft tissue from urine (Sv) | |
|---|---|---|---|---|
| Subject A | 4 | 0.41 | 0.27 | 0.21 |
| 18 | 0.54 | 0.35 | 0.37 | |
| 39 | 0.63 | 0.42 | 0.44 | |
| 50 | 0.56 | 0.37 | 0.46 | |
| 178a | 0.56 | 0.37 | 0.47 (± 20%) | |
| 6 years | 0.74 ± 0.14 | |||
| 11 years | 0.76 ± 0.12 | |||
| Subject B | 4 | 0.19 | 0.15 | 0.006 |
| 18 | 0.19 | 0.15 | 0.011 | |
| 50 | 0.17 | 0.14 | 0.013 | |
| 178 | 0.17 | 0.14 | 0.014 |
aAs shown by the urine data, virtually all the committed dose had been delivered by day 50. Due to the possible decline of lymphocytes with time, 178 days post-exposure is not the optimal time point to compare the doses obtained by urine analysis and the measurement of dicentrics
bCalculated from the absorbed dose to lymphocytes (second column) as described in the text
Mean alpha dose rates in tissues of the RES and in the kidney of patients with long-term burdens of intravascularly injected Thorotrast (Kaul and Noffz 1978)
| Organ | Injected amount (mL) | Mean tissue dose rate | ||
|---|---|---|---|---|
| (rad year−1) | (Gy year−1) | |||
| Liver | 10 | 0.852 | 12.5 | 0.125 |
| 30 | 0.648 | 28.4 | 0.284 | |
| 50 | 0.522 | 38.1 | 0.381 | |
| 100 | 0.379 | 55.4 | 0.554 | |
| Spleen | 10 | 0.498 | 41.5 | 0.415 |
| 30 | 0.321 | 80.3 | 0.803 | |
| 50 | 0.285 | 118.8 | 1.188 | |
| 100 | 0.227 | 189.2 | 1.892 | |
| Red bone marrow | 10 | 0.972 | 3.8 | 0.038 |
| 30 | 0.919 | 10.7 | 0.107 | |
| 50 | 0.871 | 16.8 | 0.168 | |
| 100 | 0.766 | 29.6 | 0.296 | |
| Kidneys | 10 | 1 | 0.17 | 0.0017 |
aFraction of emitted α-energy escaping the aggregates
Fig. 4Summarized data of chromosomal aberrations compared with dose rate to RBM—males and females combined
Fig. 5Linear dependence of radiation-induced translocation yields measured for 26 donors on their individual RBM dose from strontium radioisotopes (Vozilova et al. 2014). Bars indicate SE. Dashed lines indicate 95% confidence intervals of the linear regression