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Impact of Knowledge-based Plan Model Improvement on Plan Complexity and Deliverability in VMAT For Prostate Cancer: A Multi-institutional Study

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Abstract Background/Aim: This study evaluated the impact of knowledge-based plan (KBP) model improvement on plan complexity and delivery accuracy in volumetric modulated arc therapy (VMAT) for prostate cancer at multiple… Click to show full abstract

Abstract Background/Aim: This study evaluated the impact of knowledge-based plan (KBP) model improvement on plan complexity and delivery accuracy in volumetric modulated arc therapy (VMAT) for prostate cancer at multiple institutions. Materials and Methods: Five institutions created the first KBP model before April 2017 and subsequently devised a new model (second model) based on feedback from the first KBP and the efforts of planners after April 2019. The dose–volume histogram (DVH) parameters were validated for two prostate cancer cases between the first and second KBPs. Plan complexity metrics, of the modulation complexity score for VMAT (MCSv), closed leaf score (CLS), small aperture score (SAS), and leaf travel (LT), were compared. The delivery accuracy metrics of γ pass rate and point dose discrepancy (plan vs. measurement) at isocenter were also compared. Results: There were no significant differences in DVH parameters between the KBPs. Conversely, V50% of the rectum and bladder was reduced in 6/10 and 8/10 patients, respectively, and these variations were also converged from the first KBP to the second KBP. The mean±1SDs of MCSv, CLS, SAS20mm, and LT (first KBP vs. second KBP) were 0.27±0.033 vs. 0.26±0.044, 0.062±0.032 vs. 0.14±0.091, 0.59±0.048 vs. 0.70±0.14, and 411.91±32.08 mm vs. 548.33±127.50 mm, respectively. The delivery accuracy did not differ, whereas MCSv was moderately correlated with the point dose discrepancy. Conclusion: Multi-leaf collimator motion could be more complex with KBP model improvement, which had the potential to deteriorate the delivery accuracy.

Keywords: prostate cancer; model improvement; plan complexity; complexity; plan

Journal Title: AntiCancer Research
Year Published: 2022

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