关节内软骨评估与治疗先进系统展示早期可行性并转向整合人工智能：一项范围综述
简介
本系统综述评估了人工智能（AI）与计算机导航技术在术中软骨评估与治疗中的早期可行性。共纳入7项研究，包括3项AI软骨绘图与分割系统、3项计算机辅助导航系统及1项混合系统。关键发现：AI分割的Dice系数为0.68-0.90，交并比最高达92%，但低质量图像下精度下降；导航系统在骨软骨移植中可将移植物获取、钻孔及放置的角度误差从徒手>12°降至<4°，混合系统…
英文摘要
PURPOSE: To review the current literature evaluating AI and advanced technologies for intraoperative cartilage management. METHODS: A comprehensive search of PubMed, Embase, and Scopus was conducted in March 2026 according to PRISMA guidelines. Eligible studies included cadaveric, in-vivo, or clinical investigations using AI-based or computer navigation systems for real-time intraoperative diagnosis, mapping, or treatment of cartilage lesions. Studies limited to preoperative planning, static imaging segmentation, or non-surgical applications were excluded. Two reviewers screened studies, extracted data on design, population, technology type, and outcomes, and assessed risk of bias using CLAIM, QUADAS-2, or MINORS criteria. Findings were synthesised narratively. RESULTS: Seven studies met inclusion criteria. These included three studies evaluating AI-based cartilage mapping and segmentation systems, three assessing computer-assisted navigation systems, and one describing a hybrid system integrating mapping with navigation. AI-based segmentation and mapping systems demonstrated Dice coefficients of 0.68-0.90 and intersection-over-union scores up to 92%, with performance comparable to human reference masks but reduced accuracy in low-quality images. Navigation systems for osteochondral grafting reduced angular errors in graft harvest, coring, and placement from >12° freehand to <4° with navigation, and hybrid systems decreased plug orientation error from 15.4° to 6.5°. Stereo-endoscopic platforms achieved sub-millimetre 3D reconstruction but exceeded clinically acceptable orientation thresholds. Intraoperative 3D laser scanning achieved mean defect measurement error of 0.46 mm and reduced workflow times to <4 min compared with approximately 15 min conventionally. CONCLUSION: Early studies support the feasibility and accuracy of computer-assisted and navigation-based technologies, as well as AI-driven mapping, for real-time cartilage assessment and treatment. Further clinical evaluation is needed to establish safety and effectiveness in real-world surgical environments. LEVEL OF EVIDENCE: Level IV, scoping review.