Journal of applied clinical medical physics · 2025
The implementation of knowledge-based planning with partial OAR contours for prostate radiotherapy.
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Osipitan Ositomiwa O, Wiant David, Liu Han
Аннотация
PURPOSE: 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).
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: Partial contours, defined at a specified distance from the PTV, yielded dosimetry comparable to fully contoured plans, highlighting their potential efficacy in treatment planning.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: Partial contours, defined at a specified distance from the PTV, yielded dosimetry comparable to fully contoured plans, highlighting their potential efficacy in treatment planning.