多模态成像联合人工智能在高度近视眼底生物参数中的研究OA

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".