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新兴的人工智能与有限元分析整合为脊柱手术带来变革。

Revolutionizing spine surgery with emerging AI-FEA integration.

作者信息

Franceschini Christopher, Ahmadi Mohsen, Zhang Xuanzong, Wu Kelly, Lin Maohua, Weston Ridge, Rodio Angela, Tang Yufei, Engeberg Erik, Pires Gui, Cheema Talha S, Vrionis Frank D

机构信息

College of Medicine, Florida Atlantic University, Boca Raton, FL, USA.

Department of Electrical and Computer Science, Florida Atlantic University, Boca Raton, FL, USA.

出版信息

J Robot Surg. 2025 Sep 18;19(1):615. doi: 10.1007/s11701-025-02772-w.

DOI:10.1007/s11701-025-02772-w
PMID:40965805
Abstract

This study explores the integration of artificial intelligence (AI) and finite element analysis (FEA) in spine surgery, highlighting their complementary roles across preoperative planning, intraoperative execution, and postoperative outcome prediction. The synergy between AI and FEA is reshaping modern spine care by improving biomechanical modeling, enhancing surgical precision, and enabling personalized treatment strategies. In the preoperative phase, AI-augmented FEA supports the design of patient-specific surgical plans, optimizing implant placement and simulating mechanical responses under various loading conditions. Intraoperatively, AI enables real-time image-guided navigation, robotic assistance, and automated anatomical recognition, reducing the risk of surgical error. Postoperatively, predictive models built on FEA simulations and patient data assist in tracking recovery, forecasting complications, and informing rehabilitation protocols. Together, these technologies contribute to a data-driven paradigm shift toward precision spine surgery. As intelligent feedback systems, digital twins, and autonomous surgical platforms continue to evolve, AI-FEA integration is poised to play a transformative role in delivering safer, more efficient, and individualized spine care.

摘要

本研究探讨了人工智能(AI)与有限元分析(FEA)在脊柱手术中的整合,突出了它们在术前规划、术中执行和术后结果预测中的互补作用。AI与FEA之间的协同作用正在重塑现代脊柱护理,通过改进生物力学建模、提高手术精度以及实现个性化治疗策略。在术前阶段,AI增强的FEA支持设计针对患者的手术方案,优化植入物放置并模拟各种负载条件下的机械反应。术中,AI实现实时图像引导导航、机器人辅助和自动解剖识别,降低手术失误风险。术后,基于FEA模拟和患者数据构建的预测模型有助于跟踪恢复情况、预测并发症并为康复方案提供依据。这些技术共同推动了向精准脊柱手术的数据驱动范式转变。随着智能反馈系统、数字孪生和自主手术平台不断发展,AI-FEA整合有望在提供更安全、高效和个性化的脊柱护理方面发挥变革性作用。

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Progression of Thoracic Kyphosis After Lower Thoracic Fusion in Lumbar Flatback Deformity: Analysis of Risk Factors and Clinical Consequences.腰椎平背畸形下胸段融合术后胸椎后凸的进展:危险因素及临床后果分析
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