Breast radiotherapy planning: A decision-making framework using deep learning.

Background: Effective breast cancer treatment planning requires balancing tumor control while minimizing radiation exposure to healthy tissues. Choosing between intensity-modulated radiation therapy (IMRT) and three-dimensional conformal radiation therapy (3D-CRT) remains pivotal, influenced by patient anatomy and dosimetric constraints.

Purpose: This study aims to develop a decision-making framework utilizing deep learning to predict dose distributions, aiding in the selection of optimal treatment techniques.