Prospective study of artificial intelligence-based decision support to improve head and neck radiotherapy plan quality.

ABSTRACT:

Background and purpose

Volumetric modulated arc therapy (VMAT) planning for head and neck cancer is a complex process. While the lowest achievable dose for each individual organ-at-risk (OAR) is unknown a priori, artificial intelligence (AI) holds promise as a tool to accurately estimate the expected dose distribution for OARs. We prospectively investigated the benefits of incorporating an AI-based decision support tool (DST) into the clinical workflow to improve OAR sparing.

Materials and methods

The DST dose prediction model was based on 276 institutional VMAT plans. Under an IRB-approved prospective trial, the physician first generated a custom OAR directive for 50 consecutive patients (physician directive, PD). The DST then estimated OAR doses (AI directive, AD).

SUBMITTER: Sher DJ 

PROVIDER: S-EPMC8196054 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature