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[摘要]
高度近视(HM)是导致不可逆性视力损害的主要眼病之一,其病理改变涉及眼轴延长及眼底生物参数的多维度异常。文章系统综述了HM患者眼底生物参数(包括视网膜、视盘、黄斑及脉络膜的生物参数特征)在多模态成像技术(如OCT、OCTA等)下的动态变化特征及其与HM进展和并发症的关联。文章重点探讨了多模态成像技术协同应用的策略与优势,以及人工智能(AI)与多模态成像融合在HM患者眼底生物参数自动分析、病变识别、风险分层及临床决策中的前沿进展和潜在挑战。文章旨在为HM的早期预警、精准干预及个体化管理提供循证依据,有助于推动HM诊疗模式由“被动治疗”向“主动健康管理”的转变。
[Key word]
[Abstract]
High myopia(HM)is one of the leading causes of irreversible visual impairment, characterized by pathological changes such as axial elongation and multidimensional abnormalities in fundus biometric parameters. This review systematically summarizes the dynamic characteristics of fundus biometric parameters(including those of the retina, optic disc, macula, and choroid)in HM patients, as visualized via multimodal imaging techniques \〖e.g., optical coherence tomography(OCT)and optical coherence tomography angiography(OCTA)\〗, and their association with HM progression and related complications. The article further highlights the strategies and advantages of multimodal imaging integration and discusses recent advances and challenges in combining artificial intelligence(AI)with these imaging modalities to automate fundus parameter analysis, lesion detection, risk stratification, and clinical decision-making for HM. This review aims to provide an evidence-based foundation for the early warning, precise intervention, and personalized management of HM, thereby facilitating a clinical paradigm shift from “reactive treatment” to “active health management”.
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