Jin Haochen, Wang Kaiyue, Ren Changhong, He Shan, Gao Yuan, Liang Xiaofang, Zhang Xuxiang
Department of Ophthalmology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
Department of Ophthalmology, Tiantan Hospital, Capital Medical University, Beijing 100070, China; Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China.
Photodiagnosis Photodyn Ther. 2025 Aug;54:104716. doi: 10.1016/j.pdpdt.2025.104716. Epub 2025 Jul 9.
To determine the ability of peripapillary neurovascular units (NVU) to detect early changes in the retinal microvasculature and microstructure, and to explore systemic factors linked to the peripapillary NVU injury in type 2 diabetic patients without clinically detectable retinopathy (NDR).
Fifty-two NDR patients (mean age 51.08 ± 9.60 years; 24 females; diabetes duration 8.74 ± 6.71 years) and 42 age- and sex-matched healthy controls (mean age 50.24 ± 7.97 years; 20 females) were recruited for this prospective, cross-sectional study. Retinal microvascular and microstructural networks were visualized using spectral domain optical coherence tomography angiography. Quantitative analysis of radial peripapillary capillary (RPC) density and peripapillary retinal nerve fiber layer (p-RNFL) thickness was automatically performed using the device's software, with segmentation of retinal regions into intra-optic disc and peripapillary zones. The peripapillary area was further subdivided into eight sectors for detailed regional assessments.
Compared to controls, the RPC density in eight sectors and p-RNFL thickness in four sectors were significantly reduced in NDR patients (P < 0.05). Receiver operating characteristic curve analysis showed that the composite index of the RPC density and p-RNFL thickness was generally superior to those of each single indicator in differentiating NDR patients from controls (the highest AUC = 0.745, P < 0.001). Univariate linear regression analyses revealed significant correlations between glycated hemoglobin (HbA1c), urinary microalbuminuria, blood urea, albumin to creatinine ratio, and decreased RPC density (P < 0.05). Additionally, age, intraocular pressure, blood urea, blood creatinine and estimated glomerular filtration rate (eGFR) were significantly correlated with p-RNFL thickness thinning (P < 0.05). Multivariate linear regression analysis showed that HbA1c and blood urea were the most significant factors for RPC impairment, while eGFR was correlated with p-RNFL defects (P < 0.05).
Peripapillary NVU assessment may be valuable for diagnosing, monitoring and intervening in retinal microvascular and microstructural changes associated with DM. HbA1c level and renal function indicators represented by blood urea and eGFR, were the most important systemic factors underlying peripapillary NVU changes.
确定视乳头周围神经血管单元(NVU)检测视网膜微血管和微观结构早期变化的能力,并探索与2型糖尿病无临床可检测视网膜病变(NDR)患者视乳头周围NVU损伤相关的全身因素。
招募了52例NDR患者(平均年龄51.08±9.60岁;女性24例;糖尿病病程8.74±6.71年)和42例年龄及性别匹配的健康对照者(平均年龄50.24±7.97岁;女性20例)进行这项前瞻性横断面研究。使用光谱域光学相干断层扫描血管造影术对视网膜微血管和微观结构网络进行可视化。使用设备软件自动对视乳头周围放射状毛细血管(RPC)密度和视乳头周围视网膜神经纤维层(p-RNFL)厚度进行定量分析,将视网膜区域分割为视盘内和视乳头周围区域。视乳头周围区域进一步细分为八个扇形区进行详细的区域评估。
与对照组相比,NDR患者八个扇形区的RPC密度和四个扇形区的p-RNFL厚度显著降低(P<0.05)。受试者工作特征曲线分析表明,RPC密度和p-RNFL厚度的综合指数在区分NDR患者和对照组方面总体上优于各单一指标(最高AUC=0.745,P<0.001)。单因素线性回归分析显示糖化血红蛋白(HbA1c)、尿微量白蛋白、血尿素、白蛋白与肌酐比值与RPC密度降低之间存在显著相关性(P<0.05)。此外,年龄、眼压、血尿素、血肌酐和估算肾小球滤过率(eGFR)与p-RNFL厚度变薄显著相关(P<0.05)。多因素线性回归分析表明,HbA1c和血尿素是RPC损伤的最重要因素,而eGFR与p-RNFL缺陷相关(P<0.05)。
视乳头周围NVU评估对于诊断、监测和干预与糖尿病相关的视网膜微血管和微观结构变化可能具有重要价值。HbA1c水平以及以血尿素和eGFR表示的肾功能指标是视乳头周围NVU变化的最重要全身因素。