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当代脊柱外科的挑战:手术、技术及患者特异性问题的全面综述

Challenges in Contemporary Spine Surgery: A Comprehensive Review of Surgical, Technological, and Patient-Specific Issues.

作者信息

Mensah Emmanuel O, Chalif Joshua I, Baker Jessica G, Chalif Eric, Biundo Jason, Groff Michael W

机构信息

Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.

Department of Behavioral Neuroscience, Northeastern University, Boston, MA 02115, USA.

出版信息

J Clin Med. 2024 Sep 14;13(18):5460. doi: 10.3390/jcm13185460.

Abstract

Spine surgery has significantly progressed due to innovations in surgical techniques, technology, and a deeper understanding of spinal pathology. However, numerous challenges persist, complicating successful outcomes. Anatomical intricacies at transitional junctions demand precise surgical expertise to avoid complications. Technical challenges, such as underestimation of the density of fixed vertebrae, individual vertebral characteristics, and the angle of pedicle inclination, pose additional risks during surgery. Patient anatomical variability and prior surgeries add layers of difficulty, often necessitating thorough pre- and intraoperative planning. Technological challenges involve the integration of artificial intelligence (AI) and advanced visualization systems. AI offers predictive capabilities but is limited by the need for large, high-quality datasets and the "black box" nature of machine learning models, which complicates clinical decision making. Visualization technologies like augmented reality and robotic surgery enhance precision but come with operational and cost-related hurdles. Patient-specific challenges include managing postoperative complications such as adjacent segment disease, hardware failure, and neurological deficits. Effective patient outcome measurement is critical, yet existing metrics often fail to capture the full scope of patient experiences. Proper patient selection for procedures is essential to minimize risks and improve outcomes, but criteria can be inconsistent and complex. There is the need for continued technological innovation, improved patient-specific outcome measures, and enhanced surgical education through simulation-based training. Integrating AI in preoperative planning and developing comprehensive databases for spinal pathologies can aid in creating more accurate, generalizable models. A holistic approach that combines technological advancements with personalized patient care and ongoing education is essential for addressing these challenges and improving spine surgery outcomes.

摘要

由于手术技术、技术手段的创新以及对脊柱病理学更深入的理解,脊柱手术取得了显著进展。然而,众多挑战依然存在,使成功的手术结果变得复杂。过渡节段的解剖复杂性需要精确的手术专业知识以避免并发症。技术挑战,如对固定椎骨密度、个体椎体特征和椎弓根倾斜角度的低估,在手术过程中带来了额外风险。患者的解剖变异和既往手术增加了难度层次,通常需要进行全面的术前和术中规划。技术挑战涉及人工智能(AI)与先进可视化系统的整合。AI具有预测能力,但受限于对大量高质量数据集的需求以及机器学习模型的“黑箱”性质,这使临床决策变得复杂。增强现实和机器人手术等可视化技术提高了精准度,但存在操作和成本相关的障碍。特定患者的挑战包括处理术后并发症,如相邻节段疾病、内固定失败和神经功能缺损。有效的患者手术结果测量至关重要,但现有指标往往无法全面反映患者的经历。正确选择手术患者对于将风险降至最低并改善手术结果至关重要,但标准可能不一致且复杂。需要持续的技术创新、改进针对特定患者的手术结果测量方法,并通过基于模拟的培训加强手术教育。在术前规划中整合AI并为脊柱病理学开发综合数据库有助于创建更准确、更具普遍性的模型。将技术进步与个性化患者护理和持续教育相结合的整体方法对于应对这些挑战并改善脊柱手术结果至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa86/11432351/4be6d516fc73/jcm-13-05460-g001.jpg

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