Patient-Specific Dosimetry and Radiobiological Modeling of Targeted Radionuclide Therapy Grant - final report

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, radiobiological 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-D images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT were provided as input into an EGSnrc-based Monte Carlo calculation; the cumulated activity image defined the distribution of decays while 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 (BED) distribution which was then used to estimate a single Equivalent Uniform Dose (EUD) for segmented volumes of interest. EUD was also calculated from the absorbed dose distribution directly. RESULTS: Validation using simple models and also comparison of the dose-volume histogram to a previously analyzed clinical case is shown as well as the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative clinical case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean BED and EUD for tumor was 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 radiobiological modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose non-uniformity 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.