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Slide 1 The U.S. Transuranium & Uranium Registries (USTUR): The Fifth Decade of Nuclear Worker Follow-up Anthony C. James, PhD, CRadP USTUR Director, Research.

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Presentation on theme: "Slide 1 The U.S. Transuranium & Uranium Registries (USTUR): The Fifth Decade of Nuclear Worker Follow-up Anthony C. James, PhD, CRadP USTUR Director, Research."— Presentation transcript:

1 Slide 1 The U.S. Transuranium & Uranium Registries (USTUR): The Fifth Decade of Nuclear Worker Follow-up Anthony C. James, PhD, CRadP USTUR Director, Research Professor College of Pharmacy Richland, WA , USA Forschungszentrum Karlsruhe (FZK) Seminar Karlsruhe Institute of Technology (KIT) Nuclear Safety Research Program Tuesday, April 7 th, 2009 “Learning from Plutonium and Uranium Workers”

2 Slide 2 USTUR: Learning from Plutonium and Uranium Workers The USAEC Vision

3 Slide 3 USTUR: Learning from Plutonium and Uranium Workers The US Transuranium Registry (USTR)

4 Slide 4 USTUR: Learning from Plutonium and Uranium Workers The U.S. Transuranium & Uranium Registries – 2009

5 Slide 5 Overview of USTUR Registrant Scope, Status and Procedures. National Human Tissue Repository (NHRTR) - Specimen storage/inventory/tracking database. Radiochemistry - Improved actinide separation procedure - Introduction of ICP-MS. Internal Database and Web Publication of Case Data - Case Narratives/Pathology/Radiochemistry/Health Physics. Example of Biokinetic Case Study - Bayesian analysis of uncertainty in model parameter values and tissue doses (HPA-RPD collaboration). This Presentation FZK/KIT Seminar – ACJ – April 7 th, 2009

6 Slide 6 Registrant Status USTUR: Learning from Plutonium and Uranium Workers As of March 31 st, 2008 Total Deceased and Active (Living) Registrants: 424 Living Registrants: 92 Potential Partial-body Donors: 72 Potential Whole-body Donors: 13 Special Studies: 7 Deceased Registrants: 332 Partial-body Donations: 291 Whole-body Donations: 36 Special Studies: 5 Inactive Registrants: 447 Total Number of Registrants: 871

7 Slide 7 USTUR: Learning from Plutonium and Uranium Workers The Registries: Historical Profile of Partial Body Donations (“Routine” Autopsy Cases)

8 Slide 8 USTUR: Learning from Plutonium and Uranium Workers Major USTR Landmark: 1st Whole Body Donation (1979) Donor (radiochemist) worked with unsealed 241 Am source in his doctoral research ( ) First indication of intake was detection of 241 Am in urine sample (1958 routine surveillance program) – No chelation therapy Contemporary estimate of intake 0.23 – 1.1 μCi (~ 8 – 40 kBq!)

9 Slide 9 USTUR: Learning from Plutonium and Uranium Workers USTUR: Historical Profile of Whole Body Donations

10 Slide 10 USTUR: Learning from Plutonium and Uranium Workers Year of Intake for USTUR Whole Body Donors

11 Slide 11 USTUR: Learning from Plutonium and Uranium Workers

12 Slide 12 USTUR: Learning from Plutonium and Uranium Workers USTUR: Trends in Donations (This Decade)

13 Slide 13 USTUR: Learning from Plutonium and Uranium Workers FY2008 Whole-Body Donations January: 87-y-old 239 Pu-contaminated puncture wound(s) (Hanford – 1960s). March: 95-y-old 239 PuO 2 acute inhalation (Rocky Flats – 1965 Pu fire – high intake). March: 72-y-old 241 AmO 2 chronic inhalation (U.S. Radium Corporation – 1960s – very high intake – heavily chelated). September: 83-y-old U 3 O 8 -fume acute inhalation (Hanford – 1948 – up to 300 μg-U/d in urine).

14 Slide 14 USTUR: Learning from Plutonium and Uranium Workers USTUR Web Site – Case Narrative for Registrant 0846

15 Slide 15 USTUR: Learning from Plutonium and Uranium Workers USTUR Web Site – Narrative File Downloads for Registrant 0846

16 Slide 16 USTUR: Learning from Plutonium and Uranium Workers Case #0846 Urine Data – Years 2-3

17 Slide 17 USTUR: Learning from Plutonium and Uranium Workers Post Mortem 241 Am External Counts (PNNL) – With and Without Lungs

18 Slide 18 USTUR: Learning from Plutonium and Uranium Workers Case #0846: External Counts Pre- and Post-Autopsy

19 Slide 19 USTUR: Learning from Plutonium and Uranium Workers NHRTR – FY2008: THEMIS Bar-coded Sample Inventory Chain of Custody/Database System

20 Slide 20 USTUR: Learning from Plutonium and Uranium Workers THE Management Information System (THEMIS™) Integrates with barcode scanner to inventory:  USTUR tissues, histopathologic slides, and acid solutions.  National Human Tissue Repository (NHRTR) tissues and bone ash.  National Radiobiology Archives (NRA) histopathologic slides, tissue blocks, and documents.

21 Slide 21 USTUR: Learning from Plutonium and Uranium Workers The Management Information System (THEMIS)  Assigns a unique barcode to each individual sample.  Records a sample’s mass or volume.  Tracks the sample’s current location as it is moved within the NHRTR facility (e.g., from one freezer to another).  Tracks the sample’s location (e.g., as it is ‘shipped’ for radiochemical analysis).

22 Slide 22 USTUR: Learning from Plutonium and Uranium Workers NHRTR also holds thousands of acid-dissolved tissue samples!

23 Slide 23 USTR & USUR (pre-1992) - Analyses carried out primarily by Los Alamos (LASL/LANL). USTUR ( ) - Analyses carried out by Washington State University (WSU) - Nuclear Radiation Center (NRC), Pullman, WA. USTUR ( ) - Limited analyses carried out in temporary (leased) laboratory at Columbia Basin College, Pasco, WA (no tissue digestion facilities). - Tried “full-service” commercial laboratories. - New separations procedures and ICP-MS. USTUR (2009+) - New (leased) “in-house” radiochemistry facilities. Radiochemistry: Tissue Sample Actinide Separation and Measurement HPA/CRCE Seminar – ACJ – April 2 nd, 2009

24 Slide 24 9) Pu Elution: 30 mL 0.1M HCl M HF M rongalite 5) Beaker rinse: 5 mL 6MHN0 3 6) Separate cartridges 7) TEVA rinse: 15 mL 3M HNO 3 8) Rinse: 25 mL 9M HCl (Th) 1)Sample in 12 mL warm 6M HN0 3 and 12mL 2M Al(NO 3 ) 3 2)Add 0.75 mL 1.5M Sulfamic Acid + 3 mL 1.5M Ascorbic Acid 3)Add 2.5 mL 3.5 M Sodium Nitrite 4)Sample loading (1 drop sec -1 ) 2 mL TEVA Resin (  m) 2 mL TRU-Resin (  m) Alpha spectrometry (USTUR-600) Electrodeposition (USTUR-510) 2 mL DGA-Resin (  m) Waste (4 – 8) Radiochemistry: Actinide Column Separation - New Method (Adapted from Maxwell & Faison, 2008) Radiochemistry in USTUR Program (6) (9)

25 Slide 25 Actinide Column Separation (II) 10) Am to DGA: 15 mL 4M HCl 11) Separate cartridges Waste (10) 2 mL TRU-Resin (  m) 2 mL DGA-Resin (  m) TRU – DGA cartridges from (I) Step 6 14) Am Elution: 10 mL 0.25M HCl Alpha spectrometry (USTUR-600) Electrodeposition (USTUR-510) 12) Rinse: 3 mL 1M HNO 3 13) Rinse: 10 mL 0.1M HNO 3 (U) Waste (12,13) Radiochemistry in USTUR Program (11) (14)

26 Slide 26 Radiochemistry Actinide Separation: Comparison of Results (a) 239 Pu(b) 241 Am

27 Slide 27 Radiochemistry Comparison of Analytical Performance: USTUR vs. TEVA-TRU-DGA DescriptionUSTUR TEVA-TRU-DGA Separation technique Extraction chromatography + anion exchange (gravity fed) Extraction chromatography (vacuum-assisted) Sample loading3 timesonce Number of samples in batch1824 Reagents used345 mL/sample110 mL/sample Time for Pu/Am separation5+ days1 day

28 Slide 28 SF/ICP-MS: Anthropogenic 236 U Uranium (nat.) atom ratio: 235 U/ 238 U = U/ 235 U = U/ 238 U = Not previously measurable in USTUR/NHRTR samples (liver) ICP-MS in USTUR Program

29 Slide 29 SF/ICP-MS: Determination of 241 Pu 241 Pu T 1/2 = 14.1 y,  -emitter not detectable by  -spectrometry 241 Pu was detected in: (liver) (femur, PE) (humerus, PE) (lung) (liver) ICP-MS in USTUR Program

30 Slide 30 SF/ICP-MS (at NAU) vs  -spectrometry ICP-MS in USTUR Program

31 Slide 31 Benefits & Limitations of ICP-MS Rapid analysis (10 min vs 42 hr for  -spectrometry) Low detection limits High precision (1-3 %) 240 Pu/ 239 Pu isotopic ratio measurement 236 U and 241 Pu detection Limited for 241 Am and 238 Pu determination c.f. AS ICP-MS in USTUR Program

32 Slide 32 New Frontier: Laser Ablation ICP-MS LA-ICP-MS in USTUR Program Philip Doble, Ph.D., Senior Lecturer, Department of Chemistry & Forensic Science, University of Technology, Sydney, Australia

33 Slide 33 Application of LA-ICP-MS to USTUR/NHRTR LA-ICP-MS: Potential Applications to USTUR/NHRTR Spatial distribution of actinides, 226 Ra and major matrix elements (Ca, Mg, Sr, P) in autopsy samples Actinide and 226 Ra concentration measurements Others?

34 Slide 34 USTUR: Learning from Plutonium and Uranium Workers Web Publication of Tissue Analysis Results

35 Slide 35 Self-selected for relatively “high” (recorded) intakes of transuranium elements – primarily 239 Pu/ 238 Pu/ 241 Am. Additional exposure to external radiation (  /n). In majority of cases, there is also additional exposure to industrial toxic materials - Beryllium (Be), asbestos, toxic chemicals, organic solvents, benzene/toluene. Any pathological findings are SUMMED effects of “natural” disease incidence (including “normal” incidence of malignant cancer in matched, non-exposed population) and ALL occupational exposure factors. Some self-selection for existing cancer (Rocky Flats Plant). Exposure Characteristics of USTUR Registrants USTUR: Learning from Plutonium and Uranium Workers

36 Slide 36 USTUR: Learning from Plutonium and Uranium Workers USTUR Internal Database – Pathology

37 Slide 37 USTUR: Learning from Plutonium and Uranium Workers Pathology Database – Case Report

38 Slide 38 Malignant Neoplasms as Primary Cause of Death in USTUR Registrants (with Exposure Co-Factors): 1. ICD-10 Codes C02.9 – C20 SEER: Surveillance, Epidemiology & End Results - Case No. SourceICD-10SiteFraction (85%) Smoker BeAsbestosToxic_ChemSolvents Benzene/ Toluene SEER All NeoplasmsCount =111/ % 0047DC02.9Tongue AC12Hypopharynx2.7%YNYYY-1.9% 0640AC14.0Pharynx YNNNN- 0055DC15.9Esophagus DC15.9Esophagus3.6% % 0206AC15.9Esophagus AC15.9Esophagus YYYYYY 0015DC16.9Stomach Y--Y-Y 0030DC16.9Stomach3.6%-NNNNN3.0% 0142DC16.9Stomach AC16.9Stomach YY-YY- 0644AC18.5ColonYNYYYN 0183DC18.9Colon-NNNNN 0458AC18.9Colon4.5%YYYYYY 0503DC18.9ColonN % 0325AC18.9ColonYYY-Y- 0095DC19Rectum DC19Rectum2.7% DC20Rectum YNNNNN

39 Slide 39 Malignant Neoplasms as Primary Cause of Death in USTUR Registrants (with Exposure Co-Factors): 2. ICD-10 Codes C22 – C25.9 USTUR: Learning from Plutonium and Uranium Workers Case No. SourceICD-10SiteFractionSmokerBeAsbestosToxic_ChemSolvents Benzene/ Toluene SEER DC22.0LiverNY AC22.1LiverYNNNYN 0147DC22.9Liver5.4%YNNNNN1.9% 0371AC22.9LiverYN-YY- 0446AC22.9LiverYYYNYY 1054DC22.9Liver DC24.1Gallbladder0.9% % 0099DC25.0Pancreas AC25.0PancreasYNNNNN 0461AC25.2Pancreas4.5%YNNNNN4.9% 0341AC25.9PancreasNYNNNN 0846DC25.9PancreasNY--NY

40 Slide 40 Malignant Neoplasms as Primary Cause of Death in USTUR Registrants (with Exposure Co-Factors): 3. ICD-10 Codes C34.1 – C41.4 USTUR: Learning from Plutonium and Uranium Workers Case No.SourceICD-10SiteFractionSmokerBeAsbestosToxic_ChemSolventsBenzene/TolueneSEER AC34.1Lung YNNYYN 0255AC34.1Lung YNYYYN 0005AC34.9Lung Y AC34.9Lung YNNNNN 0011DC34.9Lung Y DC34.9Lung Y AC34.9Lung NNNNNN 0064AC34.9Lung YNNYNN 0081DC34.9Lung Y DC34.9Lung DC34.9Lung AC34.9Lung YNNNNN 0103DC34.9Lung AC34.9Lung YNNN DC34.9Lung Y DC34.9Lung DC34.9Lung Y DC34.9Lung DC34.9Lung YN-YY- 0203DC34.9Lung31.5% % 0205AC34.9Lung NC34.9Lung YNNNNN 0226DC34.9Lung YNYYN- 0232AC34.9Lung AC34.9Lung NNYYN- 0252DC34.9Lung YN-YY- 0334AC34.9Lung YYYYYN 0375AC34.9Lung Y AC34.9Lung YNNNNN 0720AC34.9Lung YYNNNN 0727AC34.9Lung YY-YY- 0779DC34.9Lung Y---N- 0841AC34.9Lung YNY-Y- 1036AC34.9Lung Y--Y AC34.9Lung Y-Y-YY 1059AC40.2Bone1.8% % 0769AC41.4Bone------

41 Slide 41 Malignant Neoplasms as Primary Cause of Death in USTUR Registrants (with Exposure Co-Factors): 4. ICD-10 Codes C43.6 – C63.9 USTUR: Learning from Plutonium and Uranium Workers Case No.SourceICD-10SiteFractionSmokerBeAsbestosToxic_ChemSolventsBenzene/TolueneSEER AC43.6Skin (Melanoma) DC43.9Skin (Melanoma)3.6% % 0102DC43.9Skin (Melanoma) YNYYN- 0245AC43.9Skin (Melanoma) YNYYN- 0084DC45.0MesotheliomaN DC45.0MesotheliomaYYYYY- 0648AC45.0Mesothelioma5.4%NYYYY DC45.0Mesothelioma-N-YY- 0677AC45.7MesotheliomaN--Y DC45.9MesotheliomaNNNYNN 0020DC50.9Breast0.9%Y DC55Uterus0.9%YNNNNN- 0022DC61ProstateYN-YN- 0058DC61Prostate DC61ProstateY DC61Prostate6.3% % 0269AC61ProstateYNNNNN 0425AC61ProstateNY AC61ProstateYYYYYY 1030AC63.9Penis0.9%YNN-NN0.0%

42 Slide 42 Malignant Neoplasms as Primary Cause of Death in USTUR Registrants (with Exposure Co-Factors): 5. ICD-10 Codes C64 – D46.9 USTUR: Learning from Plutonium and Uranium Workers Case No. SourceICD-10SiteFractionSmokerBeAsbestosToxic_ChemSolvents Benzene/ Toluene SEER DC64Kidney DC64Kidney2.7% % 1007AC64KidneyY--Y DC67.9Bladder Y AC67.9Bladder2.7% % 0992AC67.9Bladder YYYY DC71.9Brain-NNNNN 0049DC71.9Brain DC71.9Brain DC71.9Brain6.3%Y % 0216DC71.9Brain DC71.9Brain AC72.4Nervous System DC78.5Lung/Colon (Met) YN-YY DC79.0Kidney (Met) DC79.0Kidney (Met)YYNNYN 0032AC85.0Lymphosarcoma0.9%-NNNNN- 1044DC85.9NH Lymphoma0.9%YY-YN-3.4% 0794AC90.0Multiple Myeloma0.9%YNNNY-1.7% 0035DC91.0AL Leukemia0.9% % 0194DC92.1CM Leukemia0.9% % 1001DC95.0AU Leukemia Thorotrast Injection (Female) 0274AD45Polycythaemia vera0.9%Y--Y AD46.9 Myelodysplastic syndrome 0.9%YNNN---

43 Slide 43 USTUR: Learning from Plutonium and Uranium Workers USTUR Pathology Database – Now on the Web (April 6 th, 2009)!

44 Slide 44 USTUR: Learning from Plutonium and Uranium Workers Summary of Preliminary Findings on USTUR Registrants (Through 2008) No significant association found between [preliminary/rough estimates of ] tissue-weighted equivalent dose received and malignant cancer as a primary (or secondary) cause of death (α = 0.05). Statistically significant associations found between cause of death due to any type of cancer and exposure to: - benzene or toluene (odds ratio = 5.71; 95% CI: 1.04 to 31.34) - smoking habit (odds ratio = 5.41; 95% CI: 1.42 to 20.67) - rate of cigarette smoking (odds ratio = 2.70; 95% CI: 1.37 to 5.30). Lung cancer deaths found to be related to exposure to: - chlorinated solvents (odds ratio = 10.85; 95% CI: 1.02 to ) - duration of exposure to these materials (odds ratio = 1.12; 95% CI: 1.01 to 1.24). Source: Fallahian,N. A. “Study of the Association Between Exposure to Transuranic Radionuclides and Cancer Death,” PhD Dissertation, Idaho State University, 2008

45 Slide 45 USTUR: Learning from Plutonium and Uranium Workers USTUR Data Enable Detailed Reconstructions of Tissue Doses Received by Individual Donors – Example of USTUR Case 0262 Worked as engineer at Hanford ( ). Died 1990 – at age 71 y. Cause of death: - hepatocellular carcinoma (ICD-10 Code C22.0) - with metastases in diaphragm, lungs and liver. At autopsy: - all major soft tissue organs harvested, including axillary lymph node (for radiochemistry and NHRTR sample storage); - Skin of both hands saved for histology/autoradiography; - Bones from half skeleton dissected out – for radiochemistry; - Contents of 238 Pu, Pu, 241 Am measured for all tissues/organs.

46 Slide 46 USTUR: Learning from Plutonium and Uranium Workers Health Physics/Incident Data for USTUR Case 0262 Two suspected Pu inhalation intakes (1956) – of nominally ‘fresh’ weapons grade material: - 1,834 days after starting Pu work, exposed to substantial airborne Pu concentration (no respirator); - 2 weeks later, both hands contaminated (  10,000 dpm Pu); - Inhalation intakes from both incidents indicated by measurable Pu α- activity in prompt urine sample – subsequent samples negative (i.e., < dpm per 24-h sample). Third Pu intake occurred about 500 d later – by puncture wound of left thumb (broken drill bit through glove) while working in glove box: - No general airborne release; - Initial count rate (α-probe) from contaminated wound surface  500 cpm.

47 Slide 47 USTUR: Learning from Plutonium and Uranium Workers “Biokinetic” Model for Wound/Inhalation Plutonium Uptake and Tissue Retention Source: James, A.C., et al. “USTUR Whole Body Case 0262: 33-y Follow-up of PuO2 in a Skin Wound and Associated Axillary Node.” Radiat. Prot. Dosim. 127: (2007)

48 Slide 48 USTUR: Learning from Plutonium and Uranium Workers Measured and “Modeled” Excretion of 239 Pu in Urine for Case 0262 Source: James, A.C., et al. “USTUR Whole Body Case 0262: 33-y Follow-up of PuO2 in a Skin Wound and Associated Axillary Node.” Radiat. Prot. Dosim. 127: (2007)

49 Slide 49 USTUR: Learning from Plutonium and Uranium Workers Measured and “Modeled” 239 Pu Content of Tissues (At Autopsy) for Case 0262 Source: James, A.C., et al. “USTUR Whole Body Case 0262: 33-y Follow-up of PuO2 in a Skin Wound and Associated Axillary Node.” Radiat. Prot. Dosim. 127: (2007)

50 Slide 50 USTUR: Learning from Plutonium and Uranium Workers Use “Modeled” Biokinetics (Intake and Absorption Behavior) to Calculate Equivalent Dose Received by Liver in Each Year (After Intakes)

51 Slide 51 USTUR: Learning from Plutonium and Uranium Workers NIOSH-IREP “Probability of Causation” Software - on the Web

52 Slide 52 USTUR: Learning from Plutonium and Uranium Workers Run Calculated Annual Equivalent Doses Through “Interactive RadioEpidemiological Program” (NIOSH-IREP) – as Done for EEOICPA

53 Slide 53 USTUR: Learning from Plutonium and Uranium Workers NIOSH-IREP “Probability of Causation” Results – Case 0262 Legal Standard EEOICPA Standard

54 Slide 54 USTUR: Learning from Plutonium and Uranium Workers Distribution of Equivalent Dose Rate to Liver (Measured at Death) for USTUR Registrants

55 Slide 55 USTUR: Learning from Plutonium and Uranium Workers Distribution of Equivalent Dose Rate to Liver (Measured at Death) for USTUR Registrants

56 Slide th International Congress of the International Radiation Protection Association (IRPA) Buenos Aires, Argentina October 8 th - 24 th, 2008 Uncertainty in Internal Doses: Using Bayes to Transfer Information from One Worker to Another Scenario Comprehensive bioassay follow-up of a worker who accidentally inhaled 241 AmO 2 yields knowledge of the lung absorption behavior of this material. Can this knowledge be applied rigorously to improve dose estimates for another worker inhaling same material (with relatively sparse bioassay data and unknown time of intake)? Demonstrate use of the Weighted Likelihood Monte Carlo Sampling (WeLMoS) method (Puncher and Birchall, 2008) to derive posterior probability distributions of doses for the second worker. Scenario Comprehensive bioassay follow-up of a worker who accidentally inhaled 241 AmO 2 yields knowledge of the lung absorption behavior of this material. Can this knowledge be applied rigorously to improve dose estimates for another worker inhaling same material (with relatively sparse bioassay data and unknown time of intake)? Demonstrate use of the Weighted Likelihood Monte Carlo Sampling (WeLMoS) method (Puncher and Birchall, 2008) to derive posterior probability distributions of doses for the second worker. 5-month aqueous suspension James, A.C., 1 Birchall, A. 2 and Puncher, M. 2 1 United States Transuranium and Uranium Registries, 1854 Terminal Drive, Richland, WA 99354, USA 2 Health Protection Agency-Radiation Protection Division, Chilton, Oxon OX11 0RQ, UK

57 Slide 57 USTUR Case 0855 – “Special Bioassay Study” James, Birchall & Puncher: IRPA 2008 – TS-I.1.2 Accidental, single acute inhalation— Examining old ‘sealed’ 241 AmO 2 powder source. Loose 241 Am contamination in work area (hotspots > 1 kBq/100 cm 2 ). Healthy, 38-y-old non-smoker. 6 weeks after intake volunteered for USTUR “Special Study”—long-term bioassay. 6-y follow-up published by Kathren et al. (2003). Bioassay data re-analyzed here using IMBA Professional Plus (IPP). ICRP68 Type ‘M’:  2 = 2,470; NDF = 30 ICRP68 Type ‘M’:  2 = 2,470; NDF = 30 Does NOT behave like Type ‘M’ (or ‘S’) material.

58 Slide 58 Bayesian Analysis of Case 0855 Bioassay Data James, Birchall & Puncher: IRPA 2008 – TS-I.1.2

59 Slide 59 Clean-up Worker – Classical Analysis (Maximum Likelihood) James, Birchall & Puncher: IRPA 2008 – TS-I.1.2 Actual time-course of intake not known. Must be inferred from periodic (routine) urine samples. Earliest ‘positive’ urine collected at d after start of employment. Previous ‘negative’ at 24 d. Assume constant chronic intake throughout this interval. Assume modal absorption parameters from Case 0855 Calculated χ 2 = 13.0; NDF = 8; P = ‘Most likely’ point estimates of intake/dose: I = 1,229 Bq E = 38 mSv H BS = 685 mSv H lungs = 46 mSv. What are uncertainties in these estimates?

60 Slide 60 Clean-up Worker – Bayesian Analysis (Un-informative Priors) James, Birchall & Puncher: IRPA 2008 – TS-I.1.2 Resulting mean estimates of dose: E = 47 mSv (95% credible interval 34 – 62 mSv) H BS = 929 mSv (95% credible interval 661 – 1,249 mSv). These estimates were produced with NO explicit knowledge (assumption) of absorption rates from the lungs.

61 Slide 61 Clean-up Worker – Bayesian Analysis (Informative Priors) James, Birchall & Puncher: IRPA 2008 – TS-I.1.2

62 Slide 62 Using Bayes - Conclusion James, Birchall & Puncher: IRPA 2008 – TS-I.1.2 In this particular example (of an exposed clean-up worker), the quality of the bioassay data is sufficient to define reasonably accurately the posterior distributions of dose—even without any information on the absorption behavior of inhaled 241 AmO 2. Thus, the reduction in uncertainty using specific information of absorption is not as great as it could be. In cases with less reliable bioassay data, the Bayesian method automatically places greater reliance on prior knowledge. In cases with no bioassay data, i.e., prospective dose assessments, absolute reliance must be placed on prior knowledge (or assumptions) about the applicable Human Respiratory Tract Model (HRTM) parameter values.

63 Slide 63 USTUR: Learning from Plutonium and Uranium Workers Current Active Registrants: Potential Whole-Body Donors Total Registrants (WB) = 13: Average age 78 y (± 14 y) Excluding #0263: Average age 81 y (± 8 y) Case NoBirth DateAge, ySite LOS HAN ROC HAN ROC ROC LOS LOS HAN HAN CHI ROC MND (As of March 25 th, 2009)

64 Slide 64 USTUR: Learning from Plutonium and Uranium Workers USTUR Organization – FY2009 (Planned)

65 Slide 65 USTUR: Learning from Plutonium and Uranium Workers USDOE Headquarters Organization

66 Slide 66 Karlsruhe Institute of Technology (KIT), Germany, April 7 th, 2009 Disclaimer: “This presentation was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.”


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