Automatic Treatment Planning for Radiation Therapy: A Cross-Modality and Protocol Study.

ABSTRACT:

Purpose

This study investigated the applicability of 3-dimensional dose predictions from a model trained on one modality to a cross-modality automated planning workflow. Additionally, we explore the impact of integrating a multicriteria optimizer (MCO) on adapting predictions to different clinical preferences.

Methods and materials

Using a previously created 3-stage U-Net in-house model trained on the 2020 American Association of Physicists in Medicine OpenKBP challenge data set (340 head and neck plans, all planned using 9-field static intensity modulated radiation therapy [IMRT]), we retrospectively generated dose predictions for 20 patients. These dose predictions were, in turn, used to generate deliverable IMRT, VMAT, and tomotherapy plans using the fallback plan functio

SUBMITTER: Szalkowski G 

PROVIDER: S-EPMC11566342 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature