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

Abstract

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 (n=16) and without (n=7) ocular pain, and non-DED post-LASIK controls (n=20) were assessed. The automated tortuosity measure was compared to a manual grading one, obtaining a moderate correlation (Spearman’s rank correlation coefficient = 0.49, p=0.0008). The new tortuosity index was significantly higher in post-LASIK patients with ocular pain than in control patients (p=0.001), while no significant differences were detected with manual measurement (p>0.28). The tortuosity quantification was positively correlated with the ocular surface disease index (OSDI) and a numeric rating scale (NRS) assessing pain (p=0.0012 and p=0.0051, respectively). The results show good performance of the proposed automated methodology for the evaluation of corneal nerve tortuosity.

Keywords

• in vivo confocal microscopy
• corneal subbasal nerve plexus
• corneal nerve
• automatic image analysis
• tortuosity index
• ocular pain