Diagnostic Accuracy of Corneal and Epithelial Thickness Map Parameters to Detect Keratoconus and Suspect Keratoconus

Aim. To establish the diagnostic accuracy of corneal and epithelial thickness measurements obtained by spectral-domain optical coherence tomography (SD-OCT) in detecting keratoconus (KC) and suspect keratoconus (SKC). Methods. This retrospective study reviewed the data of 144 eyes separated into three groups by the Sirius automated corneal classification software: normal (N) (n = 65), SKC (n = 43), and KC (n = 36). Corneal thickness (CT) and epithelial thickness (ET) in the central (0-2 mm) and paracentral (2-5 mm) zones were obtained with the Cirrus high-definition OCT. Areas under the curve (AUC) of receiver operator characteristic (ROC) curves were compared across groups to estimate their discrimination capacity. Results. ROC curve analysis revealed excellent predictive ability for ET variables: minimum (Min) ET (0_2), minimum-maximum (Min-Max) ET (0_2), superonasal-inferotemporal (SN-IT) ET (2_5), Min-Max ET (2_5), and Min ET (2_5) to detect keratoconus (AUC > 0.9, all). Min-Max CT (0_2) was the only CT parameter with excellent ability to discriminate between KC and N eyes (AUC = 0.94; cutoff = ≤-32 μm). However, both ET and CT variables were not strong enough (AUC < 0.8, all) to differentiate between SKC and N eyes, with the highest diagnostic power for Min-Max ET (2_5) (AUC = 0.71; cutoff = ≤-9 μm) and central corneal thickness (CCT) (AUC = 0.76; cutoff = ≤533 μm). Conclusion. These results demonstrate that OCT-derived CT and ET are able to differentiate between KC and N eyes, with a high level of certainty. However, Min-Max ET (2_5) was the parameter with the highest ability to detect suspect keratoconus.