An Interpretable Planning Bot for Pancreas Stereotactic Body Radiation Therapy.

ABSTRACT:

Purpose

Pancreas stereotactic body radiation therapy (SBRT) treatment planning requires planners to make sequential, time-consuming interactions with the treatment planning system to reach the optimal dose distribution. We sought to develop a reinforcement learning (RL)-based planning bot to systematically address complex tradeoffs and achieve high plan quality consistently and efficiently.

Methods and materials

The focus of pancreas SBRT planning is finding a balance between organ-at-risk sparing and planning target volume (PTV) coverage. Planners evaluate dose distributions and make planning adjustments to optimize PTV coverage while adhering to organ-at-risk dose constraints. We formulated such interactions between the planner and treatment planning system into a finite-h

SUBMITTER: Zhang J 

PROVIDER: S-EPMC7902297 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature