Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis.

Publications // Sheibani Lab // Apr 01 2016

PubMed ID: 27186534

Author(s): Ghanian Z, Staniszewski K, Jamali N, Sepehr R, Wang S, Sorenson CM, Sheibani N, Ranji M. Quantitative assessment of retinopathy using multi-parameter image analysis. J Med Signals Sens. 2016 Apr-Jun;6(2):71-80. PMID 27186534

Journal: Journal Of Medical Signals And Sensors, Volume 6, Issue 2,

A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner.