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Background: Radiopharmaceutical therapy (RPT) is an increasingly adopted modality for treating cancer. There is evidence that the optimization of the treatment based on dosimetry can improve outcomes. However, standardization of the clinical dosimetry workflow still represents a major effort. Among the many sources of variability, the impact of using different Dose Voxel Kernels (DVKs) to generate absorbed dose (AD) maps by convolution with the time-integrated activity (TIA) distribution has not been systematically investigated., Purpose: This study aims to compare DVKs and assess the differences in the ADs when convolving the same TIA map with different DVKs., Methods: DVKs of 3 × 3 × 3 mm 3 sampling-nine for 177 Lu, nine for 90 Y-were selected from those most used in commercial/free software or presented in prior publications. For each voxel within a 11 × 11 × 11 matrix, the coefficient of variation (CoV) and the percentage difference between maximum and minimum values (% maximum difference) were calculated. The total absorbed dose per decay (SUM), calculated as the sum of all the voxel values in each kernel, was also compared. Publicly available quantitative SPECT images for two patients treated with 177 Lu-DOTATATE and PET images for two patients treated with 90 Y-microspheres were used, including organs at risk ( 177 Lu: kidneys; 90 Y: liver and healthy liver) and tumors' segmentations. For each patient, the mean AD to the volumes of interest (VOIs) was calculated using the different DVKs, the same TIA map and the same software tool for dose convolution, thereby focusing on the DVK impact. For each VOI, the % maximum difference of the mean AD between maximum and minimum values was computed., Results: The CoV (% maximum difference) in voxels of normalized coordinates [0,0,0], [0,1,0], and [0,1,1] were 5%(21%), 9%(35%), and 10%(46%) for the 177 Lu DVKs. For the case of 90 Y, these values were 2%(9%), 4%(14%), and 4%(16%). The CoV (% maximum difference) for SUM was 9%(33%) for 177 Lu, and 4%(15%) for 90 Y. The variability of the mean tumor and organ AD was up to 19% and 15% in 177 Lu-DOTATATE and 90 Y-microspheres patients, respectively., Conclusions: This study showed a considerable AD variability due exclusively to the use of different DVKs. A concerted effort by the scientific community would contribute to decrease these discrepancies, strengthening the consistency of AD calculation in RPT., (© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Unlabelled: Treatment with Tositumomab and 131I tositumomab anti-CD20 radioimmunotherapy (Bexxar) yields a nonradioactive antibody antitumor response (the so-called cold effect) and a radiation response. Numerical parameter determination by least-squares (LS) fitting was implemented for more accurate parameter estimates in equivalent biological-effect calculations., Methods: One hundred thirty-two tumors in 37 patients were followed using five or six SPECT/CT studies per patient, three each (typical) post-tracer (0.2 GBq) and post-therapy (∼3 GBq) injections. The SPECT/CT data were used to calculate position- and time-dependent dose rates and antibody concentrations for each tumor. CT-defined tumor volumes were used to track tumor volume changes. Combined biological-effect and cell-clearance models were fit to tumor volume changes. Optimized parameter values determined using LS fitting were compared to previous fitted values that were determined by matching calculated to measured tumor volume changes using visual assessment. Absorbed dose sensitivity (α) and cold-effect sensitivity (λp) parameters were the primary fitted parameters, yielding equivalent biological-effect (E) values., Results: Individual parameter uncertainties were approximately 10% and 30% for α and λp, respectively. LS versus previously fit parameter values were highly correlated, although the averaged α value decreased and the averaged λp value increased for the LS fits compared to the previous fits. Correlation of E with 2-month tumor shrinkage data was similar for the two fitting techniques. The LS fitting yielded improved fit quality and likely improved parameter estimation.

Unlabelled: For optimal treatment planning in radionuclide therapy, robust tumor dose-response correlations must be established. Here, fully 3-dimensional (3D) dosimetry was performed coupling SPECT/CT at multiple time points with Monte Carlo-based voxel-by-voxel dosimetry to examine such correlations., Methods: Twenty patients undergoing (131)I-tositumomab for the treatment of refractory B-cell lymphoma volunteered for the study. Sixty tumors were imaged. Activity quantification and dosimetry were performed using previously developed 3D algorithms for SPECT reconstruction and absorbed dose estimation. Tumors were outlined on CT at multiple time points to obtain absorbed dose distributions in the presence of tumor deformation and regression. Equivalent uniform dose (EUD) was calculated to assess the biologic effects of the nonuniform absorbed dose, including the cold antibody effect. Response for correlation analysis was determined on the basis of the percentage reduction in the product of the largest perpendicular tumor diameters on CT at 2 mo. Overall response classification (as complete response, partial response, stable disease, or progressive disease) used for prediction analysis was based on criteria that included findings on PET., Results: Of the evaluated tumor-absorbed dose summary measures (mean absorbed dose, EUD, and other measures from dose-volume histogram analysis), a statistically significant correlation with response was seen only with EUD (r = 0.36 and P = 0.006 at the individual tumor level; r = 0.46 and P = 0.048 at the patient level). The median value of mean absorbed dose for stable disease, partial response, and complete response patients was 196, 346, and 342 cGy, respectively, whereas the median value of EUD for each of these categories was 170, 363, and 406 cGy, respectively. At a threshold of 200 cGy, both mean absorbed dose and EUD had a positive predictive value for responders (partial response + complete response) of 0.875 (14/16) and a negative predictive value of 1.0 (3/3)., Conclusion: Improved dose-response correlations were demonstrated when EUD incorporating the cold antibody effect was used instead of the conventionally used mean tumor-absorbed dose. This work demonstrates the importance of 3D calculation and radiobiologic modeling when estimating absorbed dose for correlation with outcome.

Background: Radiopharmaceutical therapy (RPT) is an increasingly adopted modality for treating cancer. There is evidence that the optimization of the treatment based on dosimetry can improve outcomes. However, standardization of the clinical dosimetry workflow still represents a major effort. Among the many sources of variability, the impact of using different Dose Voxel Kernels (DVKs) to generate absorbed dose (AD) maps by convolution with the time‐integrated activity (TIA) distribution has not been systematically investigated. Purpose: This study aims to compare DVKs and assess the differences in the ADs when convolving the same TIA map with different DVKs. Methods: DVKs of 3 × 3 × 3 mm3 sampling—nine for 177Lu, nine for 90Y—were selected from those most used in commercial/free software or presented in prior publications. For each voxel within a 11 × 11 × 11 matrix, the coefficient of variation (CoV) and the percentage difference between maximum and minimum values (% maximum difference) were calculated. The total absorbed dose per decay (SUM), calculated as the sum of all the voxel values in each kernel, was also compared. Publicly available quantitative SPECT images for two patients treated with 177Lu‐DOTATATE and PET images for two patients treated with 90Y‐microspheres were used, including organs at risk (177Lu: kidneys; 90Y: liver and healthy liver) and tumors' segmentations. For each patient, the mean AD to the volumes of interest (VOIs) was calculated using the different DVKs, the same TIA map and the same software tool for dose convolution, thereby focusing on the DVK impact. For each VOI, the % maximum difference of the mean AD between maximum and minimum values was computed. Results: The CoV (% maximum difference) in voxels of normalized coordinates [0,0,0], [0,1,0], and [0,1,1] were 5%(21%), 9%(35%), and 10%(46%) for the 177Lu DVKs. For the case of 90Y, these values were 2%(9%), 4%(14%), and 4%(16%). The CoV (% maximum difference) for SUM was 9%(33%) for 177Lu, and 4%(15%) for 90Y. The variability of the mean tumor and organ AD was up to 19% and 15% in 177Lu‐DOTATATE and 90Y‐microspheres patients, respectively. Conclusions: This study showed a considerable AD variability due exclusively to the use of different DVKs. A concerted effort by the scientific community would contribute to decrease these discrepancies, strengthening the consistency of AD calculation in RPT. [ABSTRACT FROM AUTHOR]