Methodology to Incorporate Biologically Effective Dose and Equivalent Uniform Dose in Patient-Specific 3-Dimensional Dosimetry for Non-Hodgkin Lymphoma Patients Targeted with 131I-Tositumomab Therapy

A 3-dimensional (3D) imaging-based patient-specific dosimetry methodology incorporating antitumor biologic effects using biologically effective dose (BED) and equivalent uniform dose (EUD) was developed in this study. The methodology was applied to the dosimetry analysis of 6 non-Hodgkin lymphoma patients with a total of 10 tumors. Methods: Six registered SPECT/CT scans were obtained for each patient treated with I-131-labeled antibody. Three scans were obtained after tracer administration and 3 after therapy administration. The SPECT/CT scans were used to generate 3D images of cumulated activity. The cumulated activity images and corresponding CT scans were used as input to Monte Carlo dose-rate calculations. The dose-rate distributions were integrated over time to obtain 3D absorbed dose distributions. The time-dependent 3D cumulative dose distributions were used to generate 3D BED distributions. Techniques to incorporate the effect of unlabeled antibody (cold protein) in the BED analysis were explored. Finally, BED distributions were used to estimate an EUD for each tumor volume. Model parameters were determined from optimal fits to tumor regression data. The efficiency of dose delivery to tumors-the ratio of EUD to cumulative dose-was extracted for each tumor and correlated with patient response parameters. Results: The model developed in this study was validated for dosimetry of non-Hodgkin lymphoma patients treated with I-131-labeled antibody. Correlations between therapy efficiency generated from the model and tumor response were observed using averaged model parameters. Model parameter determination favored a threshold for the cold effect and typical magnitude for tumor radiosensitivity parameters. Conclusion: The inclusion of radiobiologic effects in the dosimetry modeling of internal emitter therapy provides a powerful platform to investigate correlations of patient outcome with planned therapy.