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中华眼科医学杂志(电子版) ›› 2025, Vol. 15 ›› Issue (04) : 247 -251. doi: 10.3877/cma.j.issn.2095-2007.2025.04.010

综述

多模态影像技术在糖尿病性视网膜病变早期诊断中的应用进展
胡怡凡1,2, 罗莎莎2,()   
  1. 1214000 江南大学无锡医学院眼科
    2214000 江南大学无锡市第二人民医院(江南大学附属中心医院)眼科
  • 收稿日期:2025-06-22 出版日期:2025-08-28
  • 通信作者: 罗莎莎
  • 基金资助:
    江苏省科学技术厅社会发展面上项目(BE2022696); 无锡市"双百"拔尖人才项目(BJ2023038); 无锡市科技局"太湖之光"科技攻关基础研究项目(K20221031)

The applications and advances on the multimodal imaging in the early diagnosis of diabetic retinopathy

Yifan Hu1,2, Shasha Luo2,()   

  1. 1Department of Ophthalmology, Jiangnan University Wuxi School of Medicine, Wuxi 214000, China
    2Department of Ophthalmology, Wuxi No.2 People′s Hospital, Jiangnan University Medical Center, Wuxi 214000, China
  • Received:2025-06-22 Published:2025-08-28
  • Corresponding author: Shasha Luo
引用本文:

胡怡凡, 罗莎莎. 多模态影像技术在糖尿病性视网膜病变早期诊断中的应用进展[J/OL]. 中华眼科医学杂志(电子版), 2025, 15(04): 247-251.

Yifan Hu, Shasha Luo. The applications and advances on the multimodal imaging in the early diagnosis of diabetic retinopathy[J/OL]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2025, 15(04): 247-251.

近年来,多模态影像技术的协同应用显著提升了糖尿病性视网膜病变(DR)的早期诊断效能。光学相干断层血管成像(OCTA)技术结合量化微血管密度、黄斑无血管区(FAZ)形态及分形维数(FD)等新型生物标志物揭示了DR早期表现为微血管网络复杂性改变;超宽视野OCTA已将周边视网膜缺血的检出率提升至82%;人工智能(AI)驱动的新型算法在影像分割与分级中已达到专家级精度,并实现了彩色眼底照相(CFP)向荧光素眼底血管成像(FFA)图像的跨模态生成效果。作为血管网络复杂性的量化指标,FD与DR进展及视力预后显著相关,其临床应用潜力亟待深入挖掘。本文中笔者就多模态影像技术在DR早期诊断中的应用研究进展进行综述。

In recent years, the synergistic application of multi-modal imaging technologies has significantly improved the early diagnostic efficacy of diabetic retinopathy (DR). In terms of research progress, optical coherence tomography angiography (OCTA) has quantified microvascular density, the morphology of the foveal avascular zone (FAZ), and fractal dimension (FD), which revealing changes in the complexity of the microvascular network in the early stages of DR; the widespread adoption of ultra-wide-field imaging technology has increased the detection rate of peripheral retinal ischemia to 82%; and artificial intelligence (AI)-driven novel algorithms have achieved expert-level accuracy in image segmentation and grading, and have enabled cross-modal generation from color fundus photography (CFP)to fluorescein angiography (FFA) images. FD, as a quantitative indicator of vascular network complexity, has been shown in recent years to be significantly associated with DR progression and visual prognosis, and its clinical application potential warrants further exploration. The latest research advances in multi-modal imaging technologies in the early DR diagnostic strategies was systematically reviewed.

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