Reduced macula microvascular densities may be an early indicator for diabetic peripheral neuropathy - Deng, Xiaoyu; Wang, Shiqi; Yang, Yan; Chen, Aizhen; Lu, Jinger; Hao, Jinkui; Wu, Yufei; Lu, Qinkang (Frontiers in Cell and Developmental Biology, 2022)
Abstract Purpose: To assess the alteration in the macular microvascular area in type 2 diabetic patients with peripheral neuropathy (DPN) and without peripheral neuropathy (NDPN) by optical coherence tomography angiography (OCTA) and explore the correlation between retinal microvascular abnormalities and DPN disease. Methods: Twenty-seven healthy controls (42 eyes), 36 NDPN patients (62 eyes), and 27 DPN patients (40 eyes) were included. OCTA was used to image the macula in the superficial vascular complex (SVC) and deep vascular complex (DVC). In addition, a state-of-the-art deep method learning method was employed to quantify the microvasculature of the two capillary plexuses in all participants using vessel length density (VLD). Results: Compared with the healthy control group, the average VLD values of patients with DPN in SVC (P = 0.010) and DVC (P = 0.011) were significantly lower. Compared with NDPN, DPN patients showed significantly reduced VLD values in the SVC (P = 0.006) and DVC (P = 0.001). Also, DPN patients showed lower VLD values (P < 0.05) in the nasal, superior, temporal and inferior sectors of the inner ring of the SVC when compared with controls; VLD values in NDPN patients were lower in the nasal and superior sections of the inner ring of SVC (P < 0.05) compared with healthy controls. VLD values in the DVC (AUC = 0.736, P < 0.001) showed a higher ability to discriminate between microvascular damage in DPN and NDPN. Conclusions: OCTA based on deep learning could be potentially used in clinical practice as a new indicator in the early diagnosis of DM with and without DPN. Keywords: diabetic retinopathy, microvasculature, vessel length density, optical coherence tomography angiography, diabetic peripheral neuropathy