Subject(s)
COVID-19 , Chilblains , Scleroderma, Systemic , Humans , Microscopic Angioscopy , Chilblains/diagnosis , Chilblains/etiology , Cross-Sectional Studies , Vascular Endothelial Growth Factor A , COVID-19/complications , Nails/diagnostic imaging , Capillaries/diagnostic imaging , Vascular Endothelial Growth FactorsABSTRACT
Capillaries are the smallest vessels in the body which are responsible for delivering oxygen and nutrients to surrounding cells. Various life-threatening diseases are known to alter the density of healthy capillaries and the flow velocity of erythrocytes within the capillaries. In previous studies, capillary density and flow velocity were manually assessed by trained specialists. However, manual analysis of a standard 20-s microvascular video requires 20 min on average and necessitates extensive training. Thus, manual analysis has been reported to hinder the application of microvascular microscopy in a clinical environment. To address this problem, this paper presents a fully automated state-of-the-art system to quantify skin nutritive capillary density and red blood cell velocity captured by handheld-based microscopy videos. The proposed method combines the speed of traditional computer vision algorithms with the accuracy of convolutional neural networks to enable clinical capillary analysis. The results show that the proposed system fully automates capillary detection with an accuracy exceeding that of trained analysts and measures several novel microvascular parameters that had eluded quantification thus far, namely, capillary hematocrit and intracapillary flow velocity heterogeneity. The proposed end-to-end system, named CapillaryNet, can detect capillaries at ~0.9 s per frame with ~93% accuracy. The system is currently used as a clinical research product in a larger e-health application to analyse capillary data captured from patients suffering from COVID-19, pancreatitis, and acute heart diseases. CapillaryNet narrows the gap between the analysis of microcirculation images in a clinical environment and state-of-the-art systems.
Subject(s)
COVID-19 , Capillaries , Capillaries/diagnostic imaging , Erythrocytes , Humans , Microcirculation , MicroscopyABSTRACT
PURPOSE: This study investigated changes in retinal vessel density in macular and papillary regions in post-SARS-CoV-2 pneumonia patients by means of optical coherence tomography angiography (OCTA). DESIGN: Prospective, observational, cohort study. METHODS: Forty eyes of 40 patients (mean age: 49.7 ± 12.6 years old) post-SARS-CoV-2 infection and 40 healthy subjects were enrolled in this study. COVID-19 patients had to be fully recovered from COVID-19 pneumonia and were evaluated 6 months after COVID-19 infection. The primary outcome resulted from OCTA studies of the following vascular structures: vessel density (VD) in the retinal superficial capillary plexus (SCP), deep capillary plexus (DCP), and radial peripapillary capillaries (RPC) compared to those of controls. Structural spectral domain (SD)-OCT parameters were also evaluated: ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL). RESULTS: The patients showed a significant reduction in VD of the SCP in whole images and in the DCP in all sectors compared to those in healthy subjects (P <.05). COVID-19 patients featured a reduced VD of the RPC compared to that in controls (P <.001). No differences were found in the GCC, whereas the RNFL was reduced in the COVID-19 group compared to that in controls (P = .012). Significant correlations were found between the RNFL and VD of the SCP, DCP, RPC, and FAZ area in the COVID-19 group (P <.05). CONCLUSIONS: OCTA showed retinal vascular changes in subjects fully recovered from COVID-19 pneumonia. These findings could be a consequence of a thrombotic microangiopathy that affected retinal structures as well as other systemic organs. OCTA could represent a valid, noninvasive biomarker of early vascular dysfunction after SARS-CoV-2 infection.