Minhaj Alam1, David Le1, Jennifer I Lim2, Xincheng Yao1,2. 1. Departments of Bioengineering; and. 2. Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois.
Abstract
PURPOSE: This study aimed to verify the feasibility of using vascular complexity features for objective differentiation of controls and nonproliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) patients. METHODS: This was a cross-sectional study conducted in a tertiary, subspecialty, academic practice. The cohort included 20 control subjects, 60 NPDR patients, and 56 PDR patients. Three vascular complexity features, including the vessel complexity index, fractal dimension, and blood vessel tortuosity, were derived from each optical coherence tomography angiography image. A shifting-window measurement was further implemented to identify local feature distortions due to localized neovascularization and mesh structures in PDR. RESULTS: With mean value analysis of the whole-image, only the vessel complexity index and blood vessel tortuosity were able to classify NPDR versus PDR patients. Comparative shifting-window measurement revealed increased sensitivity of complexity feature analysis, particularly for NPDR versus PDR classification. A multivariate regression model indicated that the combination of all three vascular complexity features with shifting-window measurement provided the best classification accuracy for controls versus NPDR versus PDR. CONCLUSION: Vessel complexity index and blood vessel tortuosity were the most sensitive in differentiating NPDR and PDR patients. A shifting-window measurement increased the sensitivity significantly for objective optical coherence tomography angiography classification of diabetic retinopathy.
PURPOSE: This study aimed to verify the feasibility of using vascular complexity features for objective differentiation of controls and nonproliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) patients. METHODS: This was a cross-sectional study conducted in a tertiary, subspecialty, academic practice. The cohort included 20 control subjects, 60 NPDR patients, and 56 PDR patients. Three vascular complexity features, including the vessel complexity index, fractal dimension, and blood vessel tortuosity, were derived from each optical coherence tomography angiography image. A shifting-window measurement was further implemented to identify local feature distortions due to localized neovascularization and mesh structures in PDR. RESULTS: With mean value analysis of the whole-image, only the vessel complexity index and blood vessel tortuosity were able to classify NPDR versus PDR patients. Comparative shifting-window measurement revealed increased sensitivity of complexity feature analysis, particularly for NPDR versus PDR classification. A multivariate regression model indicated that the combination of all three vascular complexity features with shifting-window measurement provided the best classification accuracy for controls versus NPDR versus PDR. CONCLUSION: Vessel complexity index and blood vessel tortuosity were the most sensitive in differentiating NPDR and PDR patients. A shifting-window measurement increased the sensitivity significantly for objective optical coherence tomography angiography classification of diabetic retinopathy.
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