Detection of retinal capillary nonperfusion in fundus fluorescein angiogram of diabetic retinopathy

Abstract

Introduction: Retinal capillary nonperfusion (CNP) is one of the retinal vascular diseases in diabetic retinopathy (DR) patients. As there is no comprehensive detection technique to recognize CNP areas, we proposed a different method for computing detection of ischemic retina, non-perfused (NP) regions, in fundus fluorescein angiogram (FFA) images. Methods: Whilst major vessels appear as ridges, non-perfused areas are usually observed as ponds that are surrounded by healthy capillaries in FFA images. A new technique using homomorphic filtering to correct light illumination and detect the ponds surrounded in healthy capillaries on FFA images was designed and applied on DR fundus images. These images were acquired from the diabetic patients who had referred to the Nikookari hospital and were diagnosed for diabetic retinopathy during one year. Our strategy was screening the whole image with a fixed window size, which is small enough to enclose areas with identified topographic characteristics. To discard false nominees, we also performed a thresholding operation on the screen and marked images. To validate its performance we applied our detection algorithm on 41 FFA diabetic retinopathy fundus images in which the CNP areas were manually delineated by three clinical experts. Results: Lesions were found as smooth regions with very high uniformity, low entropy, and small intensity variations in FFA images. The results of automated detection method were compared with manually marked CNP areas so achieved sensitivity of 81%, specificity of 78%, and accuracy of 91%.The result was present as a Receiver operating character (ROC) curve, which has an area under the curve (AUC) of 0.796 with 95% confidence intervals. Conclusion: This technique introduced a new automated detection algorithm to recognize non-perfusion lesions on FFA. This has potential to assist detecting and managing of ischemic retina and may be incorporated into automated grading diabetic retinopathy structures.

An automated framework to quantify areas of regional ischemia in retinal vascular diseases with OCT angiography

“…Retinal ischemia or capillary nonperfusion (CNP) is an important characteristic of many retinal disorders such as retinal vein occlusion (RVO), retinal artery occlusion and diabetic retinopathy (DR) . Quantification of retinal ischemia can be clinically useful in monitoring disease progression and the effect of treatment . Manual quantification of CNP areas can be tedious .…”

“…Quantification of retinal ischemia can be clinically useful in monitoring disease progression and the effect of treatment . Manual quantification of CNP areas can be tedious . It can vary from person to person and cannot be applied for clinical use on a daily basis .…”

“…Manual quantification of CNP areas can be tedious . It can vary from person to person and cannot be applied for clinical use on a daily basis . Fundus fluorescein angiography (FA) is considered to be the gold standard for imaging patients with retinal pathologies .…”

“…Fundus fluorescein angiography (FA) is considered to be the gold standard for imaging patients with retinal pathologies . Few studies have shown automated segmentation of CNP regions in fundus fluorescein angiography (FFA) images .…”

“…[1]. Quantification of retinal ischemia can be clinically useful in monitoring disease progression and the effect of treatment [2]. Manual quantification of CNP areas can be tedious [2,3].…”