<ul data-eligibleForWebStory="true"><li>Researchers investigated the use of reinforcement learning (RL) for high-dose-rate (HDR) prostate brachytherapy to optimize needle placement based on patient anatomy.</li><li>The RL agent adjusts needle positions and dwell times to maximize a reward function, with multiple rounds played until all needles are optimized.</li><li>Data from 11 patients were included, showing RL plans had similar prostate coverage and rectum dose compared to clinical plans, but lower prostate hotspot and urethra dose.</li><li>RL plans used, on average, two fewer needles than clinical plans, demonstrating potential for improved efficiency and plan quality.</li><li>This study showcases the feasibility of RL in autonomously generating practical HDR prostate brachytherapy plans, offering standardized planning and enhanced patient outcomes.</li></ul>

Automatic Treatment Planning using Reinforcement Learning for High-dose-rate Prostate Brachytherapy

Discover more