Purpose: The corneal nerves within the sub-basal nerve plexus (SBNP) display a distinctive whorl-like pattern, a highly dynamic structure that could be a marker of diseases. Previous studies have reported a decrease in whorl nerve density in patients with diabetes, indicating an avenue for noninvasive monitoring of diabetic neuropathy. However, conflicting results have since been reported, highlighting the need for improved quantitative analysis of the corneal whorl. We present an automated algorithm to characterize the whorl shape and test the hypothesis that the whorl organization is affected by diabetic neuropathy.
Methods: The SBNP whorl was analyzed as a vector field, from which seven whorl metrics were calculated. The efficacy of these whorl metrics was demonstrated in synthetic images, ex vivo mouse corneas, and in a publicly available dataset of wide-field in vivo confocal microscopy (IVCM) images of diabetic and control subjects. Linear discriminant analysis and the Peacock test were used to test for statistical differences. Our analysis code is made freely available.
Results: Using our whorl metrics, we were able to quantify different whorl patterns in our patient population and statistically compare cohorts. We determined that whorl patterns tend to present bilaterally in patients (P < 0.001), but there were no significant differences between whorl patterns in patients with diabetes and control subjects, nor between patients with or without neuropathy symptoms.
Conclusions: We present a generalizable framework to statistically compare corneal nerve patterns in cohorts of patients.
Translational relevance: SBNP whorl patterns could serve as a noninvasive marker for ocular diseases, whereas few quantitative IVCM endpoints have been identified to date.