Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.

ABSTRACT: This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic cancer using a prototype DL-based automated planning support system, named RatoGuide, to evaluate its clinical validity. In our hospital, 110 patients with gynecologic cancer were registered. The prescribed dose was 50.4 Gy/28 fr. A DL-based three-dimensional dose prediction model was first trained by the dose distribution and structure data of whole pelvic VMAT (n = 100) created on the Monaco treatment planning system (TPS). The structure data of the test data (n = 10) were then input to RatoGuide, and RatoGuide predicted the dose distribution of the whole pelvic VMAT plan (PreDose). We established deliverable plans with Monaco and Eclipse T

SUBMITTER: Xiao Y 

PROVIDER: S-EPMC12043927 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature