从个性化假体到动态适配：3D打印技术在 骨肉瘤治疗中的临床转化与创新

From Personalized Prostheses to Dynamic Adaptation: Clinical Translation and Innovation of 3D Printing Technology in Osteosarcoma Treatment

摘要: 骨肉瘤保肢治疗一直面临切除边界难控、重建匹配不足及并发症较多等问题。3D打印技术凭借患者特异性的数字化设计与增材制造能力，正在重塑骨肉瘤的精准切除与功能重建路径。本文系统梳理了该技术在骨肉瘤治疗中的完整技术链条及临床转化进展：从CT/MRI多模态融合、三维重建与个性化手术导板，到个体化假体的材料选择、结构优化与制造一体化，为肿瘤精准切除和生物力学匹配重建奠定基础。临床证据显示，3D打印技术不仅提高了标准部位及复杂节段缺损重建的成功率，而且可通过MSTS等客观指标在疼痛缓解、功能恢复和情感接受度提升等维度体现优势；不同解剖部位在支具依赖、行走能力、步态或上肢精细功能恢复上的获益仍存在差异。与此同时，3D打印正与生物活性材料、人工智能及传感监测技术加速融合：前者推动“结构支撑–骨整合–局部抗肿瘤/抗感染”一体化支架发展，后者则为结合动态运动学数据的个性化设计和术后闭环管理提供可能。当前，动态适配智能假体仍面临长期安全性、可靠性、供能与成本等挑战。未来，多学科深度协同有望推动骨肿瘤重建由静态替代迈向“感知–预测–响应”的智能化阶段。

Abstract: Limb-salvage surgery for osteosarcoma remains a major clinical challenge, primarily due to difficulties in achieving precise tumor resection, reconstructing complex defects, and minimizing postoperative complications. Three-dimensional (3D) printing, as a paradigm-shifting technology enabling patient-specific digital design and additive manufacturing, has emerged as a key solution to address these limitations. This review provides a comprehensive and structured overview of the full workflow of 3D printing in osteosarcoma management, spanning multimodal imaging fusion (CT/MRI), three-dimensional surgical planning, patient-specific instrumentation, and personalized prosthesis fabrication with optimized materials and architectures. We further synthesize current clinical evidence and emphasize functional outcomes assessed by the Musculoskeletal Tumor Society (MSTS) score. Beyond overall score improvement, 3D printing-assisted reconstruction demonstrates domain-specific benefits, particularly in pain relief, baseline function, and emotional acceptance, while recovery of weight-bearing capacity, gait, and upper-limb dexterity remains site-dependent and variable. Importantly, emerging trends indicate a shift from isolated technological applications toward multidisciplinary integration. Bioactive interfaces combining porous structures with region-specific coatings and localized drug delivery are enhancing osseointegration and infection control. Concurrently, artificial intelligence (AI) is advancing from static topology optimization to dynamic, data-driven design paradigms that integrate anatomical, kinematic, and biomechanical loading information for truly personalized reconstruction. Despite these advances, intelligent, dynamically adaptive prostheses remain in early-stage development, constrained by challenges related to long-term safety, mechanical reliability, energy supply, and cost-effectiveness. Looking forward, the convergence of 3D printing, AI, biofunctional materials, and sensing technologies is expected to drive a transition from static structural replacement toward intelligent, responsive reconstruction systems characterized by a “sensing-prediction-response” framework.