This retrospective study aims to develop an AI-assisted 3D modeling system to improve staging accuracy for stage II-III locally advanced rectal cancer (LARC). High-quality CT images from Taichung Veterans General Hospital will be used to reconstruct tumor boundaries and spatial relationships. The AI model will be trained and validated against MRI and pathology results to predict circumferential resection margin (CRM) status. Outcomes include sensitivity, specificity, accuracy, and agreement with standard imaging. This system seeks to support precise tumor staging and inform future clinical decision-making.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Sensitivity and specificity of the AI-assisted 3D imaging model for predicting circumferential resection margin (CRM) negativity
Timeframe: Day 1 (At the time of retrospective imaging analysis)