Dose-Response in Radionuclide Therapy

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Targeted radionuclide therapy is being actively investigated as a potential cancer therapy modality. The relationship between absorbed dose and tumor response or normal organ toxicity is important in optimizing radionuclide therapy. Current understanding of this relationship is almost completely derived from external beam rather than radionuclide therapy experience. Using data derived from clinical radionuclide therapy studies we propose to evaluate the potential role of radionuclide dosimetry in trial design and tumor response or toxicity prediction. The following questions will be addressed by this proposal: 1. What is the relationship between estimated absorbed dose and tumor and normal organ response? 2. Does patient specific, 3-D imaging-based dosimetry provide an advantage over a simpler, standard phantom-based approach? 3. Does radiobiologic modeling that accounts for differences in absorbed dose rate and uniformity improve response prediction? 4. How does prior therapy influence hematologic toxicity and the dose-response relationship? Using 3D-ID, a patient-specific 3-D dosimetry package developed by the PI with previous NIH support, the following aims are proposed to address these questions 1.Incorporate radiobiologic modeling in 3D-ID to utilize and interpret dose-rate and spatial uniformity information in evaluating response probability. 2.1.Obtain dose-response relationships in thyroid disease patients treated with 1-131. 2.2. Obtain dose-response relationships for non-hodgkins lymphoma patients treated with non- myeloablative Tositumomab (Bexxar; 131l-anti-CD20) and Ibritumomab Tiuxetan (Zevalin; 90Y-anti-CD20). 3. Compare dose-responserelationships obtained by accounting for dose-rate, non-uniformity and patient- specific anatomy (i.e., using 3D-ID) with those obtained using a simpler, standard-phantom based methodology (OLINDA); in the NHL studies, evaluate the role of FL.T3 ligand in improving thedose-response relationship for hematologic toxicity. Dosimetry has been assumed to be the best predictor of response following radionuclide treatment. Standardized, rigorous dosimetric analyses of radionuclide therapy data are needed to evaluate this assumption, identify the level of complexity required and to understand how other factors can impact the absorbed dose vs response relationship.