A tool for computer-aided diagnosis of retinopathy of prematurity

In this paper we present improvements to a software application, named ROPtool, that aids in the timely and accurate detection and diagnosis of retinopathy of prematurity (ROP). ROP occurs in 68% of infants less than 1251 grams at birth, and it is a leading cause of blindness for prematurely born infants. The standard of care for its diagnosis is the subjective assessment of retinal vessel dilation and tortuosity. There is significant inter-observer variation in those assessments. ROPtool analyzes retinal images, extracts user-selected blood vessels from those images, and quantifies the tortuosity of those vessels. The presence of ROP is then gauged by comparing the tortuosity of an infant's retinal vessels with measures made from a clinical-standard image of severely tortuous retinal vessels. The presence of such tortuous retinal vessels is referred to as 'plus disease'. In this paper, a novel metric of tortuosity is proposed. From the ophthalmologist's point of view, the new metric is an improvement from our previously published algorithm, since it uses smooth curves instead of straight lines to simulate 'normal vessels'. Another advantage of the new ROPtool is that minimal user interactions are required. ROPtool utilizes a ridge traversal algorithm to extract retinal vessels. The algorithm reconstructs connectivity along a vessel automatically. This paper supports its claims by reporting ROC curves from a pilot study involving 20 retinal images. The areas under two ROC curves, from two experts in ROP, using the new metric to diagnose 'tortuosity sufficient for plus disease', varied from 0.86 to 0.91.