ORIGINAL RESEARCH article
Front. Med.
Sec. Ophthalmology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1562809
This article is part of the Research TopicImaging in the Diagnosis and Treatment of Eye DiseasesView all 24 articles
Retinal Vessel Metric Analysis of Type 1 Diabetes Mellitus in OCT Angiography
Provisionally accepted
- 1Department of Ophthalmology, First Affiliated Hospital, Nanjing Medical University, Nanjing, Liaoning Province, China
- 2School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province, China
- 3Department of Ophthalmology, Changzhou Third People's Hospital, Changzhou, Jiangsu Province, China
- 4Department of Ophthalmology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, China
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Purpose: To investigate retinal vascular characteristics in type 1 diabetes mellitus (T1DM) patients at different stages via optical coherence tomography angiography (OCTA).Design: A retrospective observational study.: 63 T1DM patients (110 eyes) who underwent OCTA (3*3mm) examination and 40 age-matched healthy individuals (79 eyes) were included. A deep learning model was used to segment the retinal arteries and veins on OCTA images, and the vascular metrics in the macular area, including fractal dimension (FD), vessel diameter index (VDI), vascular length fraction (VLF), vascular tortuosity, and vessel density (VD) in different zones (fovea, superior parafoveal, inferior parafoveal, nasal parafoveal, and temporal parafoveal) were calculated.In accordance to the diagnostic criteria for diabetic retinopathy (DR), T1DM patients were classified into groups. There were 12 individuals (19 eyes) in the NPDR group, all of whom exhibited non-proliferative DR, and 51 (91 eyes) in the NDR (non-DR) group. The NDR group was divided into 2 subgroups according to the duration of T1DM, with 28 people (49 eyes) having a duration of less than 5 years and 23 people (42 eyes) having a duration of 5 years or more. Built-in metrics of OCTA showed that the VD in each zone of NPDR group was significantly lower than that of control group and NDR group (all p < 0.05). In addition, the VD of the inferior parafoveal vein (P = 0.022) and superior parafoveal artery (P = 0.03) were significantly decreased in the NPDR group. Comparing the VD among NDR Vessel Metric Changes Of T1DM subgroups and control group, the VD of the superficial inferior parafovea of T1DM patients of early stage (less than 5 years) was significantly lower than that of normal people (p < 0.05), while the VD of the inferior parafoveal artery increased (P = 0.012).We employed a deep learning vessel segmentation model to analyze the changes in arterial and venous metrics in OCTA images of T1DM patients. Early damage of NPDR to large vessels occurs in the inferior parafoveal vein and the superior parafoveal artery. In patients without DR, the arterial VD of the inferior parafovea has a compensatory increase.
Keywords: Diabetic Retinopathy, type 1 diabetes mellitus, OCTA, Vessel density, deep learning Word Count：2886 Figure Count：4 Table Count：2 Vessel Metric Changes Of T1DM
Received: 18 Jan 2025; Accepted: 20 May 2025.
Copyright: © 2025 Tang, Su, Zhang, Xie, Chen, Fan, Shan and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Wen Fan, Department of Ophthalmology, First Affiliated Hospital, Nanjing Medical University, Nanjing, Liaoning Province, China
Junjie Shan, Department of Ophthalmology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou, China
Songtao Yuan, Department of Ophthalmology, First Affiliated Hospital, Nanjing Medical University, Nanjing, Liaoning Province, China
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