Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes

Purpose The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). Methods Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. Results For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm2, 16.0 ± 3.9 mm/mm2, and 16.5 ± 3.6 mm/mm2, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87–0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland–Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). Conclusions Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

Corneal confocal microscopy predicts 4-year incident peripheral neuropathy in Type 1 diabetes

OBJECTIVE This study determined if deficits in corneal nerve fiber length (CNFL) assessed using corneal confocal microscopy (CCM) can predict future onset of diabetic peripheral neuropathy (DPN). RESEARCH DESIGN AND METHODS CNFL and a range of other baseline measures were compared between 90 nonneuropathic patients with type 1 diabetes who did or did not develop DPN after 4 years. The receiver operator characteristic (ROC) curve was used to determine the capability of single and combined measures of neuropathy to predict DPN. RESULTS DPN developed in 16 participants (18%) after 4 years. Factors predictive of 4-year incident DPN were lower CNFL (P = 0.041); longer duration of diabetes (P = 0.002); higher triglycerides (P = 0.023); retinopathy (higher on the Early Treatment of Diabetic Retinopathy Study scale) (P = 0.008); nephropathy (higher albumin-to-creatinine ratio) (P = 0.001); higher neuropathy disability score (P = 0.037); lower cold sensation (P = 0.001) and cold pain (P = 0.027) thresholds; higher warm sensation (P = 0.008), warm pain (P = 0.024), and vibration (P = 0.003) thresholds; impaired monofilament response (P = 0.003); and slower peroneal (P = 0.013) and sural (P = 0.002) nerve conduction velocity. CCM could predict the 4-year incident DPN with 63% sensitivity and 74% specificity for a CNFL threshold cutoff of 14.1 mm/mm2 (area under ROC curve = 0.66, P = 0.041). Combining neuropathy measures did not improve predictive capability. CONCLUSIONS DPN can be predicted by various demographic, metabolic, and conventional neuropathy measures. The ability of CCM to predict DPN broadens the already impressive diagnostic capabilities of this novel ophthalmic marker.