OCTA评价抗VEGF治疗DME的研究进展

Research Progress on OCTA in Evaluating Anti-VEGF Therapy for Diabetic Macular Edema

摘要: 糖尿病性黄斑水肿(DME)是导致糖尿病视网膜病变(DR)患者视力下降甚至失明的主要原因。它的发生涉及多个因素，比如血–视网膜屏障受损、血管内皮生长因子(VEGF)过度表达、炎症反应以及神经退行性变等。目前，抗VEGF治疗是DME的一线疗法，但不同患者的疗效差异很大，临床上亟需能够准确评估疗效和预测预后的生物标志物。光学相干断层扫描血管成像(OCTA)是一种无创、快速、高分辨率的眼底血流成像技术，可以三维量化黄斑区的微循环参数，对DME的早期诊断、治疗和预后评估均有重要帮助。本综述系统梳理了DME的病理机制、抗VEGF治疗的现状，以及OCTA的关键量化参数——包括黄斑中心凹无血管区(FAZ)、血流密度(VD)、视网膜深层毛细血管丛(DCP)、视网膜高反射点(HRF)以及FAZ周边300 μm血流密度(FD-300)——在抗VEGF治疗中的应用价值。这些参数与患者的视功能和眼底解剖学预后显著相关。随着技术进步，OCTA在疗效预测和个性化治疗指导方面展现出巨大潜力。特别是基于OCTA构建的深度学习模型，有望实现DME的精准诊断和个体化治疗，为糖尿病眼病的临床管理带来革命性变化。

Abstract: Objective: Diabetic macular edema (DME) is a leading cause of visual impairment and blindness in patients with diabetic retinopathy (DR). Its pathogenesis is associated with multiple factors, including disruption of the blood-retinal barrier, overexpression of vascular endothelial growth factor (VEGF), inflammatory responses, and neurodegenerative changes. Currently, anti-VEGF therapy is the first-line treatment for DME; however, there is considerable inter-individual variability in treatment response, highlighting an urgent clinical need for biomarkers that can accurately assess therapeutic efficacy and predict prognosis. Optical coherence tomography angiography (OCTA) is a non-invasive, rapid, and high-resolution imaging technique for retinal microvasculature that enables three-dimensional quantification of microcirculation parameters in the macular region, offering significant value for the early diagnosis, treatment, and prognostic evaluation of DME. This review systematically examines the pathological mechanisms of DME, the current status of anti-VEGF therapy, and the application value of key OCTA quantitative parameters—including foveal avascular zone (FAZ), vessel density (VD), deep capillary plexus (DCP), hyperreflective foci (HRF), and FAZ perimeter vessel density at 300 μm (FD-300)—in the context of anti-VEGF treatment for DME. These parameters have demonstrated significant correlations with both functional visual outcomes and anatomical prognosis. With ongoing technological advancements, OCTA has shown considerable potential in treatment response prediction and guidance of personalized therapy. In particular, deep learning models based on OCTA hold promise for achieving precise diagnosis and individualized treatment of DME, potentially leading to transformative changes in the clinical management of diabetic eye disease.