Combining Placido and Corneal Wavefront Data for the Detection of Forme Fruste Keratoconus

To evaluate the accuracy of a new objective method based on Placido disk-derived data for the detection of eyes at risk of ectasia.

One hundred nineteen eyes of 176 patients were included and separated into two groups, normal and forme fruste keratoconus (FFKC), using automated corneal classification software. Normal eyes (n = 114) were classified as negative for keratoconus and keratoconus suspect and had undergone LASIK with unremarkable follow-up for 4 years. The FFKC group was composed of 62 topographically normal eyes of patients with keratoconus in the fellow eye. Anterior topographic parameters, obtained from specular topography using Placido-based indices and corneal wavefront Zernike coefficients, were compared between groups. Receiver operating characteristic (ROC) curves were used to identify cut-off points in discriminating between keratoconic and normal eyes. Validation was performed on an external group of eyes.

A discriminant function was built combining four corneal wavefront variables and four Placido variables. The area under the receiver operating characteristic was 0.970 with this eight-variable model. The validation of this function had 63% sensitivity for detecting FFKC and 100% sensitivity for detecting keratoconus, with a specificity of 82%.

Indices generated from corneal wavefront and Placido measurements can assist in identifying early or mild forms of keratoconus undetected by a Placido-based neural network program. [J Refract Surg. 2016;32(8):510-516.].