Abstract

<h3>Purpose/Objective(s)</h3> Present planning practices for radiation therapy are based on generic dose-constraints for organs-at-risk (OAR) extrapolated from those defined in the QUANTEC guidance. We have developed a web-based dashboard to determine individualized dose constraints based on summary estimates of achieved doses in prior approved plans in prostate cancer. In this study, we prospectively evaluated the feasibility and improvements achieved in doses to OARs with this approach. <h3>Materials/Methods</h3> A set of 24 cases previously planned using generic constraints to a dose of 60 Gy in 20 fractions was de-identified and replanned using individualized constraints derived from summary statistics of a subset of cases with similar target, OAR and overlap volumes from a reference library of 94 approved plans on a web-based dashboard. From the similar case subset for each study patient, the 25th and 50th percentile of achieved V59 Gy, V56 Gy, V53 Gy, V47 Gy, V40 Gy for the rectum and bladder and V57 Gy for the planning target volume (PTV) were defined as the ideal and acceptable set of individualized dose-constraints. The goal was to assess the improvement in mean doses and the specified dose volumes. Planners were blinded to the prior achieved doses and penalties. Sample size estimation was based on an estimated 3 percentage point improvement in V53 Gy for rectum and bladder with a paired evaluation using Wilcoxon sign-rank test. Python v3.7 was used for creating the dashboard and statistical comparisons. <h3>Results</h3> The differences in reference and replanned cases using individualized dose constraints are charted in table 1. There was a numerically robust and statistically significant reduction of mean doses and percentage volumes of all the discrete dose points for both bladder and rectum, including a 4% and 6.8% reduction in the primary endpoint of V53 Gy. All the plans generated had a D95 of at least 95% for the PTV. <h3>Conclusion</h3> Treatment planning based on individualized dose constraints is feasible and leads to improvement at clinically important dose volumes in prostate cancer treatment planning.

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