Author: Ramesh Boggula, Lincoln Houghton 👨🔬
Affiliation: Karmanos Cancer Institute, Wayne State University 🌍
Purpose: To evaluate an approach that selectively applies adaptive re-planning only when needed to reduce clinical workload while maintaining treatment quality. Daily adaptive radiotherapy (ART) has typically shown better target coverage and organ at risk (OAR) sparing; however, the time and resources required for such a workflow can be burdensome.
Methods: We retrospectively analyzed 10 prostate cancer patients treated with a prescribed dose of 7000 cGy over 28 fractions on the Ethos adaptive radiotherapy system. For each fraction, two treatment plans were generated: (1) a scheduled plan with original beam fluences recalculated on the daily cone-beam CT and (2) an adapted plan that re-optimizes beam fluences. Minimum thresholds were established for both target coverage (PTV V98% > 95% of prescription dose) and OAR sparing (rectum & bladder V45Gy). Target coverages and OAR doses were calculated for hypothetical scenarios where the number of scheduled plans selected for treatment ranged from none to all of the 28 delivered fractions. For each given scenario, a threshold was calculated to determine the lowest PTV coverage of a plan without sacrificing quality.
Results: It is possible to deliver at least 5 scheduled fractions per patient without compromising target coverage or OAR sparing. Each of these five scheduled fractions require the PTV V98% to be greater than the calculated threshold: 81.5% of prescription dose. These five scheduled plans could be implemented based on convenience (e.g., every fifth fraction or consecutively). For the majority of patients, 9 or more scheduled fractions could have been administered with a coverage threshold of 89%.
Conclusion: By selectively integrating scheduled treatments in a systematic manner, we observed no substantial compromise in target coverage or OAR sparing over the entire treatment course. Our results show that this approach could help reduce the daily workload for clinicians without sacrificing clinical outcomes.