Shahzad Hania, Saade Aziz, Tse Shannon, Simister Samuel, Viola Anthony, Muthu Sathish, Singh Hardeep, Ambrosio Luca, Tavakoli Javad, Vetter Sven Yves, Louie Philip, Cho Samuel, Yoon Sangwook Tim, Jain Amit, Le Hai
UC Davis Health, Sacramento, CA, USA.
University of Connecticut Health Center, Farmington, CT, USA.
Global Spine J. 2025 Apr 4:21925682251329340. doi: 10.1177/21925682251329340.
Study DesignA narrative review of the current literature on the application of Computer-Assisted Navigation (CAN) in cervical spine surgeries.ObjectiveTo analyze the perioperative integration, types of CAN systems, technical considerations, and clinical applications of CAN in cervical spine surgeries, as well as to assess the associated complications and potential strategies to minimize these risks.MethodsA comprehensive review of published studies between 2015 and 2024 was conducted to evaluate the usage, benefits, and challenges of CAN in cervical spine surgeries. The review covered perioperative integration, system types, complications, and emerging technologies, including augmented reality (AR) and robotics.ResultsThe use of CAN in cervical spine surgeries provides improved accuracy in screw placement and reduced neurovascular complications. However, the review identified several limitations, such as a steep learning curve, cost considerations, and potential inaccuracies related to cervical spine mobility.ConclusionsCAN offers significant benefits in cervical spine surgeries, including enhanced precision and reduced complications. Despite the current limitations, advancements in AR and robotics hold promise for improving the safety and effectiveness of CAN in cervical procedures. The future focus should be on overcoming the existing challenges to increase the adoption of CAN in cervical spine surgeries.
研究设计 对当前关于计算机辅助导航(CAN)在颈椎手术中应用的文献进行叙述性综述。 目的 分析CAN在颈椎手术中的围手术期整合、CAN系统类型、技术考量及临床应用,同时评估相关并发症以及将这些风险降至最低的潜在策略。 方法 对2015年至2024年发表的研究进行全面综述,以评估CAN在颈椎手术中的使用情况、益处和挑战。该综述涵盖围手术期整合、系统类型、并发症以及新兴技术,包括增强现实(AR)和机器人技术。 结果 CAN在颈椎手术中的应用提高了螺钉置入的准确性,并减少了神经血管并发症。然而,该综述发现了一些局限性,如学习曲线陡峭、成本考量以及与颈椎活动度相关的潜在不准确性。 结论 CAN在颈椎手术中具有显著益处,包括提高精度和减少并发症。尽管存在当前的局限性,但AR和机器人技术的进步有望提高CAN在颈椎手术中的安全性和有效性。未来的重点应是克服现有挑战,以增加CAN在颈椎手术中的应用。
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