IEFInternational Education Forum3083-49022981-8605Bio-Byword Scientific Publishing Pty. Ltd.10.26689/ief.v3i7.11578ArticleInnovative Teaching of Pelvic Tumor Embolization in the Era of Precision Medicine: From Anatomical Variation Identification to AIassisted Decision Making in Clinical Practicehttps://artdesignp.com/journal/IEF/3/7/10.26689/ief.v3i7.11578JiangSuzhen,XinZhi2025372025-08-07Preoperative vascular embolization for pelvic tumors is a key technique to reduce intraoperative bleeding and improve tumor resection rates, but its teaching needs systematic improvement to address complex anatomy and operational risks. This article proposes an integrated teaching improvement plan of “3D anatomical reconstruction—multimodal imaging navigation—hierarchical technical training—intelligent feedback”: Preoperative teaching: Build dynamic 3D vascular models based on CT/MRI fusion technology, combined with a graded case library of target blood vessels (grades I–III) and in vitro simulation experiments with embolization materials to strengthen the ability to identify anatomical variations and make material selection decisions; Intraoperative teaching: Establish standardized operating procedures through DSA real-time image-guided superselective catheterization (error ≤1 mm) and emergency response drills for complications (such as a 5-minute response to spinal artery misembolization), and integrate AI-assisted segmentation (U-Net algorithm) and ICG fluorescence navigation to improve operational accuracy; Postoperative teaching: Establish a quantitative evaluation system and MDT review mechanism, combined with a VR simulation platform and hierarchical certification (Junior NAE/Senior SAE) to achieve closed-loop skill management. The teaching support system introduces forward-looking courses on biodegradable embolization agents (PLGA drug-loaded microspheres) and robot-assisted technology. Through dynamic OSCE assessment and electronic file tracking, improve the technical success rate of students and reduce the complication rate. In the future, it is necessary to promote the construction of a multi-center teaching alliance to facilitate personalized teaching optimization based on real-world data.

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