CorvisST biomechanical indices in the diagnosis of corneal stromal and endothelial disorders: an artificial intelligence-based comparative study.

AIMS To analyse the value of the CorvisST indices in diagnosing corneal stromal and endothelial disorders (CSEDs). METHODS This institutional retrospective case-control study included 903 eyes with a CSED and 597 normal eyes (controls), assessed with CorvisST and MS39. MAIN OUTCOME MEASURES CorvisST indices. The collected data were divided into a training set (70%) and a test set (30%). Artificial intelligence frameworks were used to distinguish each disorder from controls and to classify corneas into seven groups: keratoconus, high-risk corneas for keratoconus, laser corneal refractive surgery (LCRS), endothelial disorders, stromal opacities, glaucoma corneas and normal corneas. RESULTS Stress-strain index (SSI) significantly increased with age in the control group. Compared with controls matched for age/sex, keratoconus was associated with Corvis Biomechanical Index (CBI) >0.51 (area under the curve, 0.99), Ambrósio's relational thickness horizontal (ARTh) <425.5 (0.97), deflection amplitude at the time of the first applanation (SPA-A1) <96.3 (0.97) and Pachy<522.4 µm (0.91); high-risk corneas with a difference in CBI between fellow eyes (CBI SYM) >0.14 (0.98), (L2) <1.95 (0.83) and Pachy<549.7 µm (0.71); LCRS with ARTh<455.1 (0.93) and CBI>0.35 (0.83); corneal endothelial disorders with Pachy SYM>19.7 µm (0.83), Pachy>569.1 µm (0.82) and CBI SYM>0.14 (0.77); stromal opacities with SPA-A1 SYM>11.8 (0.92), ARTh<569.9 (0.89), SSI SYM>0.14 (0.89) and CBI>0.22 (0.86). A logistic regression function using all indices reached an area under the receiver operating characteristic curve of 0.81 for glaucoma diagnosis. The TabPFN model provided the best accuracy (88.7%) for diagnosing the seven corneal conditions. SSI, SPA-A1, CBI and Pachy correlated with keratoconus grade. Keratoplasty for keratoconus improved but failed to restore normal corneal biomechanics. CONCLUSIONS CorvisST indices are relevant for diagnosing CESDs and distinguishing various disorders from each other.