Jiang Ligang, Ji Yimei, Liu Mengting, Fang Ruolin, Zhu Zhentao, Zhang Meizhen, Tong Yuhua
Quzhou Aliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou, Zhejiang, China.
Department of Ophthalmology, The Second Xiangya Hospital, Hunan Clinical Research Centre of Ophthalmic Disease, Central South University, Changsha, Hunan, China.
Front Cell Dev Biol. 2025 Jan 8;12:1532939. doi: 10.3389/fcell.2024.1532939. eCollection 2024.
Gestational diabetes mellitus (GDM) is a temporary metabolic disorder in which small retinal vessels may have experience subtle changes before clinical lesions of the fundus retina appear. An innovative artificial intelligence image processing technology was applied to locate and analyze the small retinal vessel morphology and accurately evaluate the changes of the small retinal vessels in GDM patients and pregnant women with normal blood glucose and non-pregnant women with normal blood glucose.
The subjects were divided into three groups:GDM group, pregnant control group (PC), and normal control group (NC). Use optical coherence tomography angiography (OCTA) to collect OCT images of subjects,and perform quantitative identification and analysis of retinal vessel parameters based on artificial intelligence measurement software integrated the prior knowledge supervised edge-aware multi-task network (PKSEA-Net): Retinal arteriolar lumen diameter (RALD), retinal arteriolar outer diameter (RAOD), retinal venular lumen diameter (RVLD),retinal venular outer diameter (RVOD),arterial wall thickness (AWT),venular wall thickness (VWT),arterial wall to lumen ratio (AWLR),venular wall to lumen ratio (VWLR),arterial wall cross-sectional area (AWCSA),venular wall cross-sectional area (VWCSA), arteriovenous ratio (AVR).
This study revealed significant differences in RVOD, RVLD, VWT, VWCSA and AVR between the GDM group and the PC group ( = 0.005, < 0.027, = 0.008, = 0.001, = 0.022), significant differences in RVOD, RVLD, VWT, VWCSA and AVR between the GDM group and the NC group ( < 0.001, = 0.001, < 0.001, < 0.001, = 0.001). In GDM group, RVOD, RVLD, VWT and VWCSA increased, while AVR decreased. There were no significant differences in RVOD, RVLD, VWT, VWCSA and AVR between PC group and NC group ( = 0.139, = 0.263, = 0.107, = 0.059, = 0.218), and no significant differences in VWLR among the three groups ( > 0.05). No significant difference was observed in retinal artery vascular parameters (RAOD, RALD, AWT, AWLR, AWCSA) across the three groups ( > 0.05).
There were increases in RVOD, RVLD, VWT, and VWCSA, decrease in AVR in patients with GDM. However, no significant difference of retinal vascular parameters was shown between normal pregnant women and normal non-pregnant women. PKSEA-Net can assist to identify changes in retinal vascular morphology and diagnose micro-vascular lesion early in normal pregnant women and high-risk groups of GDM.
妊娠期糖尿病(GDM)是一种暂时性代谢紊乱疾病,在眼底视网膜出现临床病变之前,视网膜小血管可能已经发生了细微变化。一种创新的人工智能图像处理技术被应用于定位和分析视网膜小血管形态,以准确评估GDM患者、血糖正常的孕妇以及血糖正常的非孕妇视网膜小血管的变化。
将受试者分为三组:GDM组、妊娠对照组(PC)和正常对照组(NC)。使用光学相干断层扫描血管造影(OCTA)收集受试者的OCT图像,并基于集成了先验知识监督边缘感知多任务网络(PKSEA-Net)的人工智能测量软件对视网膜血管参数进行定量识别和分析:视网膜小动脉管腔直径(RALD)、视网膜小动脉外径(RAOD)、视网膜小静脉管腔直径(RVLD)、视网膜小静脉外径(RVOD)、动脉壁厚度(AWT)、静脉壁厚度(VWT)、动脉壁与管腔比值(AWLR)、静脉壁与管腔比值(VWLR)、动脉壁横截面积(AWCSA)、静脉壁横截面积(VWCSA)、动静脉比值(AVR)。
本研究显示,GDM组与PC组之间在RVOD、RVLD、VWT、VWCSA和AVR方面存在显著差异( = 0.005, < 0.027, = 0.008, = 0.001, = 0.022),GDM组与NC组之间在RVOD、RVLD、VWT、VWCSA和AVR方面存在显著差异( < 0.001, = 0.001, < 0.001, < 0.001, = 0.001)。在GDM组中,RVOD、RVLD、VWT和VWCSA增加,而AVR降低。PC组与NC组之间在RVOD、RVLD、VWT、VWCSA和AVR方面无显著差异( = 0.139, = 0.263, = 0.107, = 0.059, = 0.218),三组之间的VWLR无显著差异( > 0.05)。三组之间在视网膜动脉血管参数(RAOD、RALD、AWT、AWLR、AWCSA)方面未观察到显著差异( > 0.05)。
GDM患者的RVOD、RVLD、VWT和VWCSA增加,AVR降低。然而,正常孕妇与正常非孕妇之间的视网膜血管参数无显著差异。PKSEA-Net可协助识别正常孕妇和GDM高危人群视网膜血管形态的变化,并早期诊断微血管病变。