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用于互联肌肉骨骼和视觉系统的精准诊断与手术干预的机器学习进展

Advancements in Machine Learning for Precision Diagnostics and Surgical Interventions in Interconnected Musculoskeletal and Visual Systems.

作者信息

Kumar Rahul, Gowda Chirag, Sekhar Tejas C, Vaja Swapna, Hage Tami, Sporn Kyle, Waisberg Ethan, Ong Joshua, Zaman Nasif, Tavakkoli Alireza

机构信息

Rush Medical College, Rush University Medical Center, Chicago, IL 60612, USA.

Miller School of Medicine, University of Miami, Miami, FL 33146, USA.

出版信息

J Clin Med. 2025 May 23;14(11):3669. doi: 10.3390/jcm14113669.

DOI:10.3390/jcm14113669
PMID:40507433
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12156424/
Abstract

Artificial intelligence (AI) is reshaping precision medicine by revealing diagnostic links between ocular biomarkers and systemic musculoskeletal disorders. This review synthesizes clinical evidence on the associations between optical coherence tomography (OCT)-derived parameters, such as retinal nerve fiber layer (RNFL) thinning and choroidal thickness, and conditions including osteoporosis, cervical spine instability, and inflammatory arthritis. The findings, based on an analysis of studies that integrate AI with ocular and musculoskeletal imaging, highlight consistent correlations between ocular microstructural changes and systemic degenerative pathologies. These results suggest that the eye may serve as a non-invasive window into biomechanical dysfunction. This review also discusses the emerging role of AI-assisted surgical systems informed by ocular metrics. Overall, AI-driven ocular analysis offers a promising avenue for early detection and management of musculoskeletal disease, supporting its clinical relevance and interdisciplinary potential.

摘要

人工智能（AI）正在通过揭示眼部生物标志物与全身性肌肉骨骼疾病之间的诊断联系，重塑精准医学。本综述综合了关于光学相干断层扫描（OCT）衍生参数（如视网膜神经纤维层（RNFL）变薄和脉络膜厚度）与骨质疏松症、颈椎不稳和炎性关节炎等病症之间关联的临床证据。基于对将AI与眼部和肌肉骨骼成像相结合的研究分析结果，突出了眼部微观结构变化与全身性退行性病变之间的一致相关性。这些结果表明，眼睛可能是生物力学功能障碍的无创窗口。本综述还讨论了由眼部指标提供信息的AI辅助手术系统的新兴作用。总体而言，AI驱动的眼部分析为肌肉骨骼疾病的早期检测和管理提供了一条有前景的途径，支持其临床相关性和跨学科潜力。

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