EANM Dosimetry Committee guidelines for bone marrow and whole-body dosimetry

  • Cecilia HindorfEmail author
  • Gerhard Glatting
  • Carlo Chiesa
  • Ola Lindén
  • Glenn Flux



The level of administered activity in radionuclide therapy is often limited by haematological toxicity resulting from the absorbed dose delivered to the bone marrow. The purpose of these EANM guidelines is to provide advice to scientists and clinicians on data acquisition and data analysis related to bone-marrow and whole-body dosimetry.

Materials and methods

The guidelines are divided into sections “Data acquisition” and “Data analysis”. The Data acquisition section provides advice on the measurements required for accurate dosimetry including blood samples, quantitative imaging and/or whole-body measurements with a single probe. Issues specific to given radiopharmaceuticals are considered. The Data analysis section provides advice on the calculation of absorbed doses to the whole body and the bone marrow. The total absorbed dose to the bone marrow consists of contributions from activity in the bone marrow itself (self-absorbed dose) and the cross-absorbed dose to the bone marrow from activity in bone, larger organs and the remainder of the body.


As radionuclide therapy enters an era where patient-specific dosimetry is used to guide treatments, accurate bone-marrow and whole-body dosimetry will become an essential element of treatment planning. We hope that these guidelines will provide a basis for the optimization and standardization of the treatment of cancer with radiopharmaceuticals, which will facilitate single- and multi-centre radionuclide therapy studies.


Internal dosimetry Radionuclide therapy Bone marrow 



This work was developed under the close supervision of the Dosimetry Committee of the EANM (M. Bardiès, C. Chiesa, G. Flux, M. Konijnenberg, M. Lassmann, M. Monsieurs, S.-E. Strand). In addition, the authors wish to acknowledge the contribution from S. Savolainen, past member of the EANM Dosimetry Committee.


  1. 1.
    Wahl RL, Zasadny K, MacFarlane D, et al. Iodine-131 anti-B1 antibody for B-cell lymphoma: an update on the Michigan Phase I experience. J Nucl Med 1998;39(8 Suppl):21S–7S.PubMedGoogle Scholar
  2. 2.
    Shen S, Meredith RF, Duan J, et al. Improved prediction of myelotoxicity using a patient-specific imaging dose estimate for non-marrow-targeting 90Y-antibody therapy. J Nucl Med 2002;43(9):1245–53.PubMedGoogle Scholar
  3. 3.
    Wessels BW, Bolch WE, Bouchet LG, et al. Bone marrow dosimetry using blood-based models for radiolabeled antibody therapy: a multiinstitutional comparison. J Nucl Med 2004;45(10):1725–33.PubMedGoogle Scholar
  4. 4.
    Forrer F, Krenning EP, Kooij PP, et al. Bone marrow dosimetry in peptide receptor radionuclide therapy with [177Lu-DOTA(0),Tyr(3)]octreotate. Eur J Nucl Med Mol Imaging 2009;36(7):1138–46.PubMedCrossRefGoogle Scholar
  5. 5.
    Breitz HB, Fisher DR, Wessels BW. Marrow toxicity and radiation absorbed dose estimates from rhenium-186-labeled monoclonal antibody. J Nucl Med 1998;39(10):1746–51.PubMedGoogle Scholar
  6. 6.
    Shen S, Meredith RF, Duan J, et al. Comparison of methods for predicting myelotoxicity for non-marrow targeting I-131-antibody therapy. Cancer Biother Radiopharm 2003;18(2):209–15.PubMedCrossRefGoogle Scholar
  7. 7.
    O'Donoghue JA, Baidoo N, Deland D, et al. Hematologic toxicity in radioimmunotherapy: Dose-response relationships for 131-I labeled antibody therapy. Cancer Biother Radiopharm 2002;17(4):435–43.PubMedCrossRefGoogle Scholar
  8. 8.
    Behr T, Béhé M, Sgouros G. Correlation of red marrow radiation dosimetry with myelotoxicity: Empirical factors influencing the radiation-induced myelotoxicity of radiolabeled antibodies, fragments and peptides in pre-clinical and clinical settings. Cancer Biother Radiopharm 2002;17(4):445–64.PubMedCrossRefGoogle Scholar
  9. 9.
    Hindorf C, Lindén O, Tennvall J, et al. Evaluation of methods for red marrow dosimetry based on patients undergoing radioimmunotherapy. Acta Oncol 2005;44:579–88.PubMedCrossRefGoogle Scholar
  10. 10.
    Lindén O, Tennvall J, Hindorf C, et al. 131I-labelled anti-CD22 MAb (LL2) in patients with B-cell lymphomas failing chemotherapy. Treatment outcome, haematologic toxicity and absorbed dose to bone marrow. Acta Oncol 2002;41(3):297–303.PubMedCrossRefGoogle Scholar
  11. 11.
    International Commission on Radiological Protection, Basic anatomical and physiological data for use in radiological protection: the skeleton. 1995, Pergamon: Oxford, UKGoogle Scholar
  12. 12.
    International Commission on Radiological Protection, Basic anatomical and physiological data for use in radiological protection: reference values. 2002, Pergamon: Oxford, UKGoogle Scholar
  13. 13.
    Cristy M. Active bone marrow distribution as a function of age in humans. Phys Med Biol 1981;26(3):389–400.PubMedCrossRefGoogle Scholar
  14. 14.
    Bradley EW. Bone marrow physiology and radiobiology. Antibody Immunoconjug Radiopharm 1990;3(4):289–91.Google Scholar
  15. 15.
    Fliedner TM, Graessle D, Paulsen C, et al. Structure and function of bone marrow hemopoiesis: mechanisms of response to ionizing radiation exposure. Cancer Biother Radiopharm 2002;17(4):405–26.PubMedCrossRefGoogle Scholar
  16. 16.
    Loevinger R, Budinger TF, Watson EE. MIRD primer for absorbed dose calculations. New York: The Society of Nuclear Medicine; 1991.Google Scholar
  17. 17.
    Siegel JA, Thomas SR, Stubbs JB, et al. MIRD Pamphlet No 16: Techniques for quantitative radiopharmaceutical biodistribution data acquisition and analysis for use in human radiation dose estimates. J Nucl Med 1999;40(2):37s–61s.PubMedGoogle Scholar
  18. 18.
    Chittenden S, Pratt BE, Pomeroy K, et al. Optimization of equipment and methodology for whole body activity retention measurements in children undergoing targeted radionuclide therapy. Cancer Biother Radiopharm 2007;22(2):243–9.PubMedCrossRefGoogle Scholar
  19. 19.
    He B, Wahl RL, Du Y, et al. Comparison of residence time estimation methods for radioimmunotherapy dosimetry and treatment planning – Monte Carlo simulation studies. IEEE Trans Med Imaging 2008;27(4):521–30.PubMedCrossRefGoogle Scholar
  20. 20.
    Koral K, Dewaraja Y, Li J, et al. Initial results for hybrid SPECT – conjugate-view tumor dosimetry in 131I-anti-B1 antibody therapy of previously untreated patients with lymphoma. J Nucl Med 2000;41(9):1579–86.PubMedGoogle Scholar
  21. 21.
    Sgouros G, Kolbert K, Sheikh A, et al. Patient-specific dosimetry for 131I thyroid cancer therapy using 124I PET and 3-dimensional-internal dosimetry (3D-ID) software. J Nucl Med 2004;45(8):1366–72.PubMedGoogle Scholar
  22. 22.
    Hobbs RF, Wahl RL, Lodge MA, et al. 124I PET-based 3D-RD dosimetry for a pediatric thyroid cancer patient: real-time treatment planning and methodologic comparison. J Nucl Med 2009;50(11):1844–7.PubMedCrossRefGoogle Scholar
  23. 23.
    Perk LR, Visser OJ, Stigter-van Walsum M, et al. Preparation and evaluation of 89Zr-Zevalin for monitoring of 90Y-Zevalin biodistribution with positron emission tomography. Eur J Nucl Med Mol Imaging 2006;33:1337–45.PubMedCrossRefGoogle Scholar
  24. 24.
    Ogawa K, Harata Y, Ichihara T, et al. A practical method for position-dependent Compton-scatter correction in single photon emission CT. IEEE Trans Med Imaging 1991;10(3):408–12.PubMedCrossRefGoogle Scholar
  25. 25.
    Macey DJ, Grant EJ, Bayouth JE, et al. Improved conjugate view quantitation of I-131 by subtraction of scatter and septal penetration events with a triple energy window method. Med Phys 1995;22(10):1637–43.PubMedCrossRefGoogle Scholar
  26. 26.
    Fleming JS. A technique for the measurement of activity using a gamma camera and computer. Phys Med Biol 1979;24(1):176–80.PubMedCrossRefGoogle Scholar
  27. 27.
    Thomas SR, Maxon HR, Kereiakes JG. In vivo quantitation of lesion radioactivity using external counting methods. Med Phys 1976;3(4):253–5.CrossRefGoogle Scholar
  28. 28.
    Siegel JA, Lee RE, Pawlyk DA, et al. Sacral scintigraphy for bone marrow dosimetry in radioimmunotherapy. Nucl Med Biol 1989;16(6):553–9.Google Scholar
  29. 29.
    Chang LT. A method for attenuation correction in radionuclide computed tomography. IEEE Trans Nucl Sci 1978;25:638–43.CrossRefGoogle Scholar
  30. 30.
    Shepp LA, Vardi Y. Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imaging 1982;1:113–22.PubMedCrossRefGoogle Scholar
  31. 31.
    Lange K, Carson R. EM reconstruction algorithms for emission and transmission tomography. J Comp Assist Tomogr 1984;8:306–16.Google Scholar
  32. 32.
    Stabin MG, Siegel JA, Sparks RB. Sensitivity of model-based calculations of red marrow dosimetry to changes in patient-specific parameters. Cancer Biother Radiopharm 2002;17(5):535–43.PubMedCrossRefGoogle Scholar
  33. 33.
    Bolch WE, Patton PW, Shah AP, et al. Considerations of anthropomorphic, tissue volume, and tissue mass scaling for improved patient specificity of skeletal S values. Med Phys 2002;29:1054–70.PubMedCrossRefGoogle Scholar
  34. 34.
    Brindle JM, Myers SL, Bolch WE. Correlations of total pelvic spongiosa volume with both anthropometric parameters and computed tomography-based skeletal size measurements. Cancer Biother Radiopharm 2006;21(4):352–63.PubMedCrossRefGoogle Scholar
  35. 35.
    Brindle JM, Trindade AA, Shah AP, et al. Linear regression model for predicting patient-specific total skeletal spongiosa volume for use in molecular radiotherapy dosimetry. J Nucl Med 2006;47(11):1875–83.PubMedGoogle Scholar
  36. 36.
    Pichardo JC, Trindade AA, Brindle JM, et al. Method for estimating skeletal spongiosa volume and active marrow mass in the adult male and adult female. J Nucl Med 2007;48(11):1880–8.PubMedCrossRefGoogle Scholar
  37. 37.
    Bolch WE, Eckerman KF, Sgouros G, et al. MIRD Pamphlet No. 21: a generalized schema for radiopharmaceutical dosimetry – standardization of nomenclature. J Nucl Med 2009;50(3):477–84.PubMedCrossRefGoogle Scholar
  38. 38.
    Glatting G, Kletting P, Reske SN, et al. Choosing the optimal fit function: Comparison of the Akaike information criterion and the F-test. Med Phys 2007;34(11):4285–92.PubMedCrossRefGoogle Scholar
  39. 39.
    Snyder WS, Ford MR, Warner GG, et al. “S”, absorbed dose per unit cumulated activity for selected radionuclides and organs. New York: The Society of Nuclear Medicine; 1975.Google Scholar
  40. 40.
    ICRP Publication 30, Part 1, Limits for intakes of radionuclides by workers. Ottawa: International Commission on Radiological Protection. 1980Google Scholar
  41. 41.
    Stabin MG. MIRDOSE: personal computer software for internal dose assessment in nuclear medicine. J Nucl Med 1996;37(3):538–46.PubMedGoogle Scholar
  42. 42.
    Stabin MG, Sparks RB, Crowe E. OLINDA/EXM: The second-generation personal computer software for internal dose assessment in nuclear medicine. J Nucl Med 2005;46(6):1023–7.PubMedGoogle Scholar
  43. 43.
    Beddoe AH, Darley PJ, Spiers FW. Measurements of trabecular bone structure in man. Phys Med Biol 1976;21(4):589–607.PubMedCrossRefGoogle Scholar
  44. 44.
    Beddoe AH. Measurements of the microscopic structure of cortical bone. Phys Med Biol 1977;22(2):298–308.PubMedCrossRefGoogle Scholar
  45. 45.
    Whitwell JR, Spiers FW. Calculated beta-ray dose factors for trabecular bone. Phys Med Biol 1976;21(1):16–38.PubMedCrossRefGoogle Scholar
  46. 46.
    Eckerman KF, Stabin MG. Electron absorbed fractions and dose conversion factors for red marrow and bone by skeletal regions. Health Phys 2000;78(2):199–214.PubMedCrossRefGoogle Scholar
  47. 47.
    Stabin MG, Siegel JA. Physical models and dose factors for use in internal dose assessment. Health Phys 2003;85(3):294–310.PubMedCrossRefGoogle Scholar
  48. 48.
    Bouchet LG, Bolch WE. A three-dimensional transport model for determining absorbed fractions of energy for electrons within cortical bone. J Nucl Med 1999;40(12):2115–24.PubMedGoogle Scholar
  49. 49.
    Bouchet LG, Jokisch DW, Bolch WE. A three-dimensional transport model for determining absorberd fractions of energy for electrons within trabecular bone. J Nucl Med 1999;40(11):1947–66.PubMedGoogle Scholar
  50. 50.
    Bouchet LG, Bolch WE, Howell RW, et al. S values for radionuclides localized within the skeleton. J Nucl Med 2000;41(1):189–212.PubMedGoogle Scholar
  51. 51.
    Watchman CJ, Jokisch DW, Patton PW, et al. Absorbed fractions for alpha-particles in tissues of trabecular bone: considerations of marrow cellularity within the ICRP reference male. J Nucl Med 2005;46(7):1171–85.PubMedGoogle Scholar
  52. 52.
    Stabin MG, Eckerman KF, Bolch WE, et al. Evolution and status of bone and marrow dose models. Cancer Biother Radiopharm 2002;17(4):427–33.PubMedCrossRefGoogle Scholar
  53. 53.
    Sgouros G, Stabin M, Erdi Y, et al. Red marrow dosimetry for radiolabeled antibodies that bind to marrow, bone, or blood components. Med Phys 2000;27(9):2150–64.PubMedCrossRefGoogle Scholar
  54. 54.
    Shah AP, Bolch WE, Rajon DA, et al. A paired-image radiation transport model for skeletal dosimetry. J Nucl Med 2005;46(2):344–53.PubMedGoogle Scholar
  55. 55.
    Petoussi-Henss N, Bolch WE, Zankl M, et al. Patient-specific scaling of reference S-values for cross-organ radionuclide S-values: What is appropriate? Radiat Prot Dosim 2007;127:192–6.CrossRefGoogle Scholar
  56. 56.
    Shen S, DeNardo GL, Sgouros G, et al. Practical determination of patient-specific marrow dose using radioactivity concentration in blood and body. J Nucl Med 1999;40(12):2102–6.PubMedGoogle Scholar
  57. 57.
    Sgouros G. Bone marrow dosimetry for radioimmunotherapy: theoretical considerations. J Nucl Med 1993;34(4):689–94.PubMedGoogle Scholar
  58. 58.
    Siegel JA, Wessels BW, Watson EE, et al. Bone marrow dosimetry and toxicity for radioimmunotherapy. Antibody Immunoconjug Radiopharm 1990;3(4):213–33.Google Scholar
  59. 59.
    Sgouros G. Blood and bone marrow dosimetry in radioiodine therapy of thyroid cancer. J Nucl Med 2005;46(5):899–900.PubMedGoogle Scholar
  60. 60.
    Hindorf C, Lindén O, Tennvall J, et al. Time dependence of activity concentration ratio of red marrow to blood and implications for red marrow dosimetry. Cancer 2002;94(4 suppl):1235–9.PubMedCrossRefGoogle Scholar
  61. 61.
    Sgouros G, Jureidini IM, Scott AM, et al. Bone marrow dosimetry: regional variability of marrow-localizing antibody. J Nucl Med 1996;37:695–8.PubMedGoogle Scholar
  62. 62.
    Traino AC, Ferrari M, Cremonesi M, et al. Influence of total-body mass on the scaling of S-factors for patient-specific, blood-based red-marrow dosimetry. Phys Med Biol 2007;52:5231–48.PubMedCrossRefGoogle Scholar
  63. 63.
    Matthay KK, Panina C, Huberty J, et al. Correlation of tumor and whole-body dosimetry with tumor response and toxicity in refractory neuroblastoma treated with 131I-MIBG. J Nucl Med 2001;42(11):1713–21.PubMedGoogle Scholar
  64. 64.
    Buckley SE, Chittenden S, Saran FH, et al. Whole-body dosimetry for individualized treatment planning of 131I-MIBG radionuclide therapy for neuroblastoma. J Nucl Med 2009;50(9):1518–24.PubMedCrossRefGoogle Scholar
  65. 65.
    Seldin DW. Techniques for using bexxar for the treatment of non-Hodgkin's lymphoma. J Nucl Med Technol 2002;30(3):109–14.PubMedGoogle Scholar
  66. 66.
    Divoli A, Chiavassa S, Ferrer L, et al. Effect of patient morphology on dosimetric calculations for internal irradiation as assessed by comparisons of Monte Carlo versus conventional methods. J Nucl Med 2009;50(2):316–23.PubMedCrossRefGoogle Scholar
  67. 67.
    Kwok CS. Backscattering of low energy electrons at bone/bone marrow interfaces. Antibody Immunoconjug Radiopharm 1990;3(4):251–7.Google Scholar
  68. 68.
    Kwok CS, Bialobzyski PJ, Yu SK. Effect of tissue inhomogneity on dose distribution of continuous activity of low-energy electrons in bone marrow cavities with different topologies. Med Phys 1991;18(3):533–41.PubMedCrossRefGoogle Scholar
  69. 69.
    Watchman CJ, Bourke VA, Lyon JR, et al. Spatial distribution of blood vessels and CD34+ hematopoietic stem and progenitor cells within the marrow cavities of human cancellous bone. J Nucl Med 2007;48(4):645–54.PubMedCrossRefGoogle Scholar
  70. 70.
    Daldrup-Link HE, Henning T, Link TM. MR imaging of therapy-induced changes of bone marrow. Eur Radiol 2007;17:743–61.PubMedCrossRefGoogle Scholar
  71. 71.
    Beshara S, Sörensen J, Lubberink M, et al. Pharmacokinetics and red cell utilization of 52Fe/59Fe-labelled iron polymaltose in anaemic patients using positron emission tomography. Br J Haematol 2003;120:853–9.PubMedCrossRefGoogle Scholar
  72. 72.
    Agool A, Schot BW, Jager PL, et al. 18F-FLT PET in hematologic disorders: a novel technique to analyze the bone marrow compartment. J Nucl Med 2006;47(10):1592–8.PubMedGoogle Scholar
  73. 73.
    Blumenthal RD, Lew W, Juweid M, et al. Plasma FLT3-L levels predict bone marrow recovery from myelosuppressive therapy. Cancer 2000;88(2):333–43.PubMedCrossRefGoogle Scholar
  74. 74.
    Siegel JA, Yeldell D, Goldenberg DM, et al. Red marrow radiation dose adjustment using plasma FLT3-L cytokine levels: improved correlations between hematologic toxicity and bone marrow dose for radioimmunotherapy patients. J Nucl Med 2003;44(1):67–76.PubMedGoogle Scholar
  75. 75.
    Bertho JM, Demarquay C, Frick J, et al. Level of flt3-level in plasma: a possible new bio-indicator for radiation-induced aplasia. Int J Radiat Biol 2001;77(6):703–12.PubMedCrossRefGoogle Scholar

Copyright information

© EANM 2010

Authors and Affiliations

  • Cecilia Hindorf
    • 1
    Email author
  • Gerhard Glatting
    • 2
  • Carlo Chiesa
    • 3
  • Ola Lindén
    • 4
  • Glenn Flux
    • 5
  1. 1.Imagerie MédicaleONIRIS - Ecole Nationale Vétérinaire, Agroalimentaire et d’Alimentation Nantes AtlantiqueNantesFrance
  2. 2.Klinik für NuklearmedizinUniversität UlmUlmGermany
  3. 3.Nuclear Medicine DivisionFoundation IRCCS Istituto Nazionale TumoriMilanoItaly
  4. 4.Department of OncologyLund University HospitalLundSweden
  5. 5.Joint Department of PhysicsRoyal Marsden Hospital & Institute of Cancer ResearchLondonUK

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