Acta ophthalmologica · 2020
Subclinical keratoconus detection with three-dimensional (3-D) morphogeometric and volumetric analysis.
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Toprak Ibrahim, Cavas Francisco, Velázquez José S, Alio Del Barrio Jorge L, Alio Jorge L
Аннотация
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 (Dapexant )/posterior (Dapexpost ) apices and minimum thickness points (Dmctant , Dmctpost ) from corneal vertex, and Dapexant -Dapexpost difference. Areal variables were derived from anterior (Aant ) and posterior (Apost ) corneal surfaces, sagittal plane passing through corneal apices (Aapexant , Aapexpost ) and thinnest point (Amctant , Amctpost ). Total corneal volume (Vtotal ) and volumetric distribution (with 0.1mm steps) centred to thinnest corneal point (VOLmct ) and anterior (VOLaap )/posterior (VOLpap ) apices comprised the volume-based parameters.
RESULTS: In the subclinical KC group, all D values, Dapexant -Dapexpost difference, Aant , Apost and Aapexant values were higher (p < 0.001), while Aapexpost , Amctpost , Vtotal , VOLmct , VOLaap and VOLpap 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 (p < 0.0001).
CONCLUSIONS: Eyes with subclinical KC seem to represent asymmetrically displaced anterior and posterior corneal apex, corneal thinning and volume loss. 3-D morphogeometric and volumetric parameters and differentiation formula can be incorporated into topography software to detect subclinical KC with high sensitivity and specificity in clinical practice.
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 (Dapexant )/posterior (Dapexpost ) apices and minimum thickness points (Dmctant , Dmctpost ) from corneal vertex, and Dapexant -Dapexpost difference. Areal variables were derived from anterior (Aant ) and posterior (Apost ) corneal surfaces, sagittal plane passing through corneal apices (Aapexant , Aapexpost ) and thinnest point (Amctant , Amctpost ). Total corneal volume (Vtotal ) and volumetric distribution (with 0.1mm steps) centred to thinnest corneal point (VOLmct ) and anterior (VOLaap )/posterior (VOLpap ) apices comprised the volume-based parameters.
RESULTS: In the subclinical KC group, all D values, Dapexant -Dapexpost difference, Aant , Apost and Aapexant values were higher (p < 0.001), while Aapexpost , Amctpost , Vtotal , VOLmct , VOLaap and VOLpap 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 (p < 0.0001).
CONCLUSIONS: Eyes with subclinical KC seem to represent asymmetrically displaced anterior and posterior corneal apex, corneal thinning and volume loss. 3-D morphogeometric and volumetric parameters and differentiation formula can be incorporated into topography software to detect subclinical KC with high sensitivity and specificity in clinical practice.