膝关节精准治疗:从结构修复到功能重塑的演进与展望OA
Precision treatment of the knee:evolution and prospects from structural repair to functional remodeling
膝关节精准治疗正从结构修复迈向功能重塑与个体化决策的深度融合.在运动医学领域,交叉韧带重建依托多模态图像融合与机器人导航可实现骨道的亚毫米级定位,增强现实技术已初步融入术前规划与术中导航,联合新型生物材料与内支架增强技术共同提升移植物愈合质量;半月板与软骨损伤则借助免结全内缝合装置、3D打印个性化支架、干细胞及外泌体负载生物材料,推动了修复技术向再生性转型.在关节置换方面,计算机导航与手术机器人显著提升力线与假体安放的精准度,但早期功能优势在中远期尚未转化为稳定临床获益;个性化截骨工具联合3D打印骨模型在复杂病例与住院医师培训中具有补充价值,三维术前规划则以更低成本实现精准手术的普惠性.人工智能辅助技术已贯穿围术期全流程,从术前三维规划、假体型号预测,到术中机器人自主策略学习与软组织平衡实时感知,再到术后风险预测与可穿戴设备康复监测,初步构建起数据驱动的智能决策体系.当前,该领域仍面临长期随访证据欠缺、技术成本高昂、基层推广不足及AI模型泛化能力有限等挑战.未来需依托多中心研究建立符合中国人群特点的诊疗规范与数据库,推动技术整合与成本优化,有望实现从精准技术向普惠临床的有效转化.
Precision treatment of the knee is moving from structural repair toward deep integration of functional remodeling and individualized decision-making.In the field of sports medicine,anterior cruciate ligament reconstruction enables submillimeter-level positioning of bone tunnels based on multimodal image fusion and robotic navigation,and augmented reality has been preliminarily integrated into preoperative planning and intraoperative navigation,which,together with novel biomaterials and internal brace augmentation,collectively improve graft healing quality.For meniscal and cartilage injuries,knotless all-inside suture devices,3D-printed personalized scaffolds,and stem cell-and exosome-loaded biomaterials have driven the transition from repair techniques toward regenerative transformation.In joint arthroplasty,computer navigation and surgical robots significantly improve the accuracy of alignment and prosthesis positioning,but the early functional advantages have not yet translated into stable clinical benefits at mid-to long-term follow-up.Patient-specific instrumentation combined with 3D-printed bone models offers supplementary value in complex cases and residency training,while 3D preoperative planning enables the accessibility of precise surgery at a lower cost.Artificial intelligence(AI)-assisted techniques have been applied to the entire perioperative workflow,ranging from preoperative 3D planning and prosthesis size prediction through intraoperative autonomous strategy learning by robots and real-time soft tissue balance perception,to postoperative risk prediction and wearable device-based rehabilitation monitoring,initially establishing a data-driven intelligent decision-making system.Currently,the field still faces challenges such as insufficient long-term follow-up evidence,high technical costs,limited grassroots promotion,and limited generalization ability of AI models.In the future,it is necessary to establish diagnosis and treatment guidelines and databases tailored to the characteristics of the Chinese population based on multicenter studies,promote technical integration and cost optimization,and realize the effective transformation from precise techniques to accessible clinical applications.
郭林;刘力铭
陆军军医大学(第三军医大学)第一附属医院运动医学中心,重庆陆军军医大学(第三军医大学)第一附属医院江北院区(陆军第九五八医院)骨科,重庆
医药卫生
膝关节精准治疗运动医学人工关节置换人工智能
knee jointprecision treatmentsports medicineartificial joint arthroplastyartificial intelligence
《陆军军医大学学报》 2026 (12)
1637-1647,11
国家自然科学基金青年基金项目(82502964)陆军军医大学第一附属医院临床孵化项目(2024IITZDB16)陆军军医大学第一附属医院江北院区创新人才培育基金(2025YG009) Supported by the National Natural Science Foundation for Young Scholars of China(82502964),the Clinical Incubation Project of the First Affiliated Hospital of Army Medical University(2024IITZDB16),and the Innovative Talent Cultivation Fund of Jiangbei Campus,First Affiliated Hospital of Army Medical University(2025YG009).
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