Subclinical keratoconus detection with three-dimensional (3-D) morphogeometric and volumetric analysis.

PURPOSE: To assess the efficacy of morphogeometric and volumetric characterization of the cornea based on three-dimensional (3-D) modelling in diagnosis of subclinical keratoconus (KC). METHODS: Cross-sectional study. Ninety-three eyes with subclinical KC with a best spectacle-corrected distance visual acuity ≥20/20 (grade zero KC according to the RETICS classification) and 109 control eyes were included. Computer-based 3-D corneal morphogeometric model was generated using raw topographic data. Distance-, area- and volume-based parameters were used for statistical analysis. Distance parameters included deviation of anterior (D(apexant) )/posterior (D(apexpost) ) apices and minimum thickness points (D(mctant) , D(mctpost) ) from corneal vertex, and D(apexant) -D(apexpost) difference. Areal variables were derived from anterior (A(ant) ) and posterior (A(post) ) corneal surfaces, sagittal plane passing through corneal apices (A(apexant) , A(apexpost) ) and thinnest point (A(mctant) , A(mctpost) ). Total corneal volume (V(total) ) and volumetric distribution (with 0.1mm steps) centred to thinnest corneal point (VOL(mct) ) and anterior (VOL(aap) )/posterior (VOL(pap) ) apices comprised the volume-based parameters. RESULTS: In the subclinical KC group, all D values, D(apexant) -D(apexpost) difference, A(ant) , A(post) and A(apexant) values were higher (p < 0.001), while A(apexpost) , A(mctpost) , V(total) , VOL(mct) , VOL(aap) and VOL(pap) values were lower when compared to the control group (p < 0.001). Regression analysis-based formula correctly classified 96.8% of the eyes with subclinical KC and 94.5% of the normal ones (pÂ