Performance of an artificial intelligence foundation model for prostate radiotherapy segmentation
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This article is not in any list yet, why not save it to one of your lists.Abstract
Importance
Artificial intelligence (AI) foundation models such as Segment Anything Model 2 (SAM 2) offer potential for semi-automated image segmentation with minimal fine-tuning, but their performance in specialized clinical tasks like radiation therapy planning are not well characterized.
Objective
To evaluate the performance of SAM 2 in segmenting pre-operative intact prostate and post-operative prostate fossa targets for prostate radiotherapy planning.
Design, Setting, Participants
Retrospective cohort study deploying and testing a foundation model for AI segmentation for prostate radiotherapy planning. CT simulation images and radiation plans were obtained from a single academic institution for patients undergoing prostate cancer treatment. Data analysis was performed from September 2024 to February 2025.
Exposures
AI segmentation with varying levels of human intervention, ranging from intervals of every 2nd to every 10th ground truth slice provided as input.
Main Outcome and Measures
Segmentation accuracy measured by Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD) for intact and post-operative prostate target delineation.
Results
While SAM 2 outperformed interpolation in DSC and HD for both intact and post-operative prostate cancer patient cases, the AI segmentation accuracy was significantly better in the intact pre-operative patient cases where anatomic boundaries were better defined than post-operative patient cases. This is especially evident when sparse ground truth was provided simulating lower levels of human intervention.
Conclusions and Relevance
AI foundation models show promising application for specialized medical tasks such as prostate cancer radiotherapy segmentation with limited need for fine-tuning or retraining, although their clinical application will require further understanding of task-specific performance.
