Automatic Evaluation of Corneal Nerve Tortuosity in Images from In-vivo Confocal Microscopy

Purpose. An algorithm and a computer program for the automatic grading of corneal nerve tortuosity are proposed and evaluated. Methods. Thirty images of the corneal subbasal nerve plexus with different grades of tortuosity were acquired with a scanning laser confocal microscope in normal and pathologic subjects. Nerves were automatically traced with an algorithm previously developed, and a tortuosity measure was computed with the proposed method, based on the number of changes in the curvature sign and on the amplitude (maximum distance of the curve from the underlying chord) of the nerve curves. These measures were evaluated according to their capability to reproduce the expert classification of images into three groups of tortuosity (low, mid, and high). This classification was also compared with measures provided by other methods proposed in the literature to evaluate nerve tortuosity. Results. Among all considered methods, the one proposed herein allows a minimum of classification errors (only 2 in 30 images) and the highest Krippendorff concordance coefficient (0.96). Furthermore, it is the only one that can provide a significant difference (P < 0.01) between all pairs of tortuosity classes. Conclusions. The results provided by the proposed system confirmed its ability to perform a clinically significant evaluation of corneal nerve tortuosity