Abstract
Intra- and inter-observer contour uncertainty is a continuous challenge in treatment planning for radiotherapy. Our proposed solution to address this challenge is the use of partial contours for treatment planning, focusing on uninvolved or non-overlapping portions of the organs-at-risk (OARs) with the planning target volume (PTV). The partial contours systematically eliminate overlapping regions. The partial contours were evaluated against fully contoured OARs. We incorporated advanced tools like knowledge-based planning (KBP) to create treatment plans and artificial intelligence (AI) to create auto-segmented contours. We developed two models, Rapid Plan (RP) and Rapid Plan partial uninvolved (RP_Part_Un), using 70 previous clinically approved volumetric arc therapy (VMAT) plans each prescribed with 70 Gy/28 fractions. From these models, we created three plans, RP, RP_Part_Un, and MIM AI_Part_Un. In this retrospective study, 60 prostate patients were analyzed using the three plans. For determining OAR sparing, Dmax and Dmean along the percent volume receiving a dose over a range (V10 Gy V70 Gy) between each plan were compared. Geometric evaluations, dice similarity coefficient (DSC), and overlay index (OI) between the OAR contours from partial-contoured manual structure sets and partial-contoured AI structure sets were analyzed. When comparing the DSC and OI for full contours to the partial contours, in both groups, all comparisons were significantly increased for both organs. This indicated the partial contours had a higher degree of concordance. In patients with SpaceOAR, RP_Part_Un plans exhibited significantly reduced bladder Dmax and Dmean compared to RP plans, while rectum Dmax and Dmean showed no significant differences. For patients without SpaceOAR, RP_Part_Un significantly lowered rectum Dmean. MIM AI_Part_Un plans demonstrated lower rectum Dmax in both patient groups. Partial contours, defined at a specified distance from the PTV, yielded dosimetry comparable to fully contoured plans, highlighting their potential efficacy in treatment planning.
Published Version
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