Three-dimensional radiobiologic dosimetry: Application of radiobiologic modeling to patient-specific 3-dimensional imaging-based internal dosimetry

Andrew R. Prideaux, Hong Song, Robert F. Hobbs, Bin He, Eric C. Frey, Paul W. Ladenson, Richard L. Wahl, George Sgouros

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1008-1016
Number of pages9
JournalJournal of Nuclear Medicine
Volume48
Issue number6
DOIs
StatePublished - Jun 2007

Keywords

  • 3D-ID
  • Dosimetry
  • Patient-specific dosimetry
  • Radiobiology
  • Treatment planning

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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