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First published online May 15, 2007, 10.2967/jnumed.106.038000
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Journal of Nuclear Medicine Vol. 48 No. 6 1008-1016
© 2007 by Society of Nuclear Medicine

doi: 10.2967/jnumed.106.038000

Basic Science Investigation

Three-Dimensional Radiobiologic Dosimetry: Application of Radiobiologic Modeling to Patient-Specific 3-Dimensional Imaging–Based Internal Dosimetry

Andrew R. Prideaux1, Hong Song1, Robert F. Hobbs1, Bin He1, Eric C. Frey1, Paul W. Ladenson1,2, Richard L. Wahl1 and George Sgouros1

1 Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland; and 2 Division of Endocrinology and Metabolism, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland

Correspondence: For correspondence or reprints contact: George Sgouros, PhD, Department of Radiology, Johns Hopkins University, School of Medicine, CRB II 4M.61, 1550 Orleans St., Baltimore, MD 21231. E-mail: gsgouros{at}jhmi.edu

Phantom-based and patient-specific imaging-based dosimetry methodologies have traditionally yielded mean organ-absorbed doses or spatial dose distributions over tumors and normal organs. In this work, radiobiologic modeling is introduced to convert the spatial distribution of absorbed dose into biologically effective dose and equivalent uniform dose parameters. The methodology is illustrated using data from a thyroid cancer patient treated with radioiodine. Methods: Three registered SPECT/CT scans were used to generate 3-dimensional images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT scan were provided as input into an EGSnrc-based Monte Carlo calculation: The cumulated activity image was used to define the distribution of decays, and an attenuation image derived from CT was used to define the corresponding spatial tissue density and composition distribution. The rate images were used to convert the spatial absorbed dose distribution to a biologically effective dose distribution, which was then used to estimate a single equivalent uniform dose for segmented volumes of interest. Equivalent uniform dose was also calculated from the absorbed dose distribution directly. Results: We validate the method using simple models; compare the dose-volume histogram with a previously analyzed clinical case; and give the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for the tumor were 57.7, 58.5, and 25.0 Gy, respectively. Corresponding values for normal lung tissue were 9.5, 9.8, and 8.3 Gy, respectively. Conclusion: The analysis demonstrates the impact of radiobiologic modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose nonuniformity in the tumor and a corresponding reduced likelihood of achieving a tumor response. Such analyses are expected to be useful in treatment planning for radionuclide therapy.

Key Words: dosimetry • radiobiology • 3D-ID • patient-specific dosimetry • treatment planning

COPYRIGHT © 2007 by the Society of Nuclear Medicine, Inc.


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