Automated plan generation for prostate radiotherapy patients using deep learning and scripted optimization.

Background And Purpose: Treatment planning is a time-intensive task that could be automated. We aimed to develop a "single-click" workflow, fully deployed within a commercial treatment planning system (TPS), for autoplanning prostate radiotherapy treatment plans using predictions from a deep learning model (DLM).

Materials And Methods: Automatically generated treatment plans were created with a single script, executed from within a commercial TPS scripting environment, that performed two stages sequentially.