Enhancing The Diagnostic Precision Of Subclinical Keratoconus By Combining Indices From Scheimpflug Tomography, Corneal Biomechanics, And Anterior Segment Optical Coherence Tomography

To determine the diagnostic precision of multi-modal corneal imaging for detection of subclinical keratoconus (SKC).

Ophthalmology Clinic, Hospital Canselor Tunku Mukhriz, Kuala Lumpur, Malaysia.

All subjects in this prospective, cross-sectional study underwent Scheimpflug tomography (Pentacam HR), air-puff tonometry (Corvis ST), and spectral-domain optical coherence tomography (Cirrus HD SD-OCT). Combined diagnostic models were developed using stepwise logistic regression (SLR). The Kruskal–Walli’s test evaluated group differences. Diagnostic accuracy was assessed by calculating the area under the curve (AUC).

A total of 137 participants were assessed ( 48 KCN , 36 SKC, and 53 normal). Most examined tomography, biomechanical, and pachymetry indices showed significant differences between KCN, SKC, and normal eyes (p<0.05). Single Tomographic Biomechanical Index, (TBI) data was most effective in identifying SCKC, achieving an AUC of 0.978 (p<0.001) with 100% sensitivity and 84.91% specificity. Combining SD-OCT and Pentacam HR data, the SLR model yielded superior accuracy for SKC detection, with an AUC of 0.966 (91.67% sensitivity and 100% specificity). The highest accuracy for SCKC identification was attained by integrating data from all three devices, resulting in 0.990 accuracy (86.91% sensitivity; 96.13% specificity).

Integrating a Scheimpflug-based biomechanical and tomography analyser with SD-OCT improves the precision of SCKC detection. This combined approach supports more accurate SKC screening and assists clinicians in identifying early disease in patients with otherwise normal findings.