Predicting the net administered activity in 90Y-radioembolization patients from post-procedure 90Y-SPECT/CT

BackgroundThe calculation of the net administered activity (A(admin)) in patients undergoing Y-90-radioembolization is essential for dosimetry and radiation safety, yet current methods for measuring residual Y-90 activity are often associated with high uncertainty. Therefore, an accurate, robust, and clinically viable method for the determination of A(admin) across approved Y-90 microsphere devices is desirable. PurposeWe report on a novel method to determine A(admin) by leveraging the quantitative capabilities of SPECT/CT to measure Y-90-emission in vivo from patients following Y-90-radioembolization with glass or resin microspheres. Methods(90)Y-SPECT/CT attenuation-corrected count data from 147 sequential Y-90-radioembolization patients was used for this analysis. A(admin) was calculated as part of routine clinical practice via the exposure rate differences between the initial Y-90-vial and the Y-90-residual jar. This served as our gold standard measure of A(admin). Patient data for each microsphere device were separated into training and testing cohorts to first develop regression models and then to independently assess model performance. The training cohorts were divided into four groups: first, based on the microsphere device (glass or resin), and second, based on the SPECT volume used to calculate counts (the full SPECT field of view (FOV) or liver only (VOIliver)). Univariate linear regression models were generated for each group to predict A(admin) based on Y-90-SPECT data from the training cohorts. Leave-one-out cross validation was implemented to estimate variability in model parameters. To assess performance, linear models derived from the training cohort were applied to Y-90-SPECT data from the testing cohort. A comparison of the models between microspheres devices was also performed. ResultsLinear models derived from the glass and resin training cohorts demonstrated a strong, positive correlation between Y-90-SPECT image counts and A(admin) for VOIliver and FOV with R-2 > 0.98 in all cases. In the glass training cohort, model accuracy (100%-absolute mean prediction error) and precision (95% prediction intervals of mean prediction error) were 99.0% and 15.4% for the VOIliver and 99.7% and 17.5% for the FOV models, respectively. In the resin training cohort, the corresponding values were 98.6% and 16.7% for VOIliver and > 99.9% and 11.4% for the FOV models, respectively. The application of these linear models to Y-90-SPECT data from the testing cohort showed A(admin) prediction errors to have high accuracy and precision for both microsphere devices. For the glass testing cohort, accuracy (precision) was 96.9% (19.6%) and 98.8% (21.1%) for the VOIliver and FOV models, respectively. The corresponding values for the resin training cohort were 97.3% (26.2%) and 98.5% (25.7%) for the VOIliver and FOV models, respectively. The slope of the linear models between the two microsphere devices was observed to be significantly different with resin microspheres generating 48%-49% more SPECT counts for equivalent Y-90 activity based on each device manufacturer's activity calibration process. Conclusion(90)Y-SPECT image counts can reliably predict (accuracy > 95% and precision < 18%) A(admin) after Y-90-radioembolization, with performance characteristics essentially equivalent for both glass and resin microspheres. There is a clear indication that activity calibrations are fundamentally different between the two microsphere devices.