New Method for the Automated Assessment of Corneal Nerve Tortuosity Using Confocal Microscopy Imaging

Abstract

Featured Application: Characterization of the corneal nerve fibers is gaining popularity for objective assessment of anterior segment anomalies such as dry eye disease. Confocal microscopy provides high-resolution imaging of the sub-basal plexus; thus, several parameters such as corneal length, density or tortuosity can be analyzed. However, the analysis of these images is usually performed based on manual or semiautomated methods, many of which are subjective and time consuming. In this work, a fully automated tortuosity corneal nerve fiber analysis method is proposed. This new tool may be very useful to obtain an accurate evaluation of nerve alterations, to monitor changes over time and/or in response to treatment, to ensure comparisons across different studies or even to improve the diagnosis of ocular surface diseases. An automated tool for corneal nerve fiber tortuosity quantification from in vivo confocal microscopy (IVCM) is described and evaluated. The method is a multi-stage process based on the splitting of the corneal nerve fibers into individual segments, whose endpoints are an extreme or intersection of white pixels on a binarized image. Individual segment tortuosity is quantified in terms of the arc-chord ratio. Forty-three IVCM images from 43 laser-assisted in situ keratomileusis (LASIK) surgery patients were used for evaluation. Images from symptomatic dry eye disease (DED) post-LASIK patients, with ((Formula presented.)) and without ((Formula presented.)) ocular pain, and non-DED post-LASIK controls ((Formula presented.)) were assessed. The automated tortuosity measure was compared to a manual grading one, obtaining a moderate correlation (Spearman’s rank correlation coefficient = (Formula presented.), (Formula presented.)). The new tortuosity index was significantly higher in post-LASIK patients with ocular pain than in control patients ((Formula presented.)), while no significant differences were detected with manual measurement ((Formula presented.)). The tortuosity quantification was positively correlated with the ocular surface disease index (OSDI) and a numeric rating scale (NRS) assessing pain ((Formula presented.) and (Formula presented.), respectively). The results show good performance of the proposed automated methodology for the evaluation of corneal nerve tortuosity.