A Potential Screening Index of Corneal Biomechanics in Healthy Subjects, Forme Fruste Keratoconus Patients and Clinical Keratoconus Patients - Tian, Lei; Qin, Xiao; Zhang, Hui; Zhang, Di; Guo, Li-Li; Zhang, Hai-Xia; Wu, Ying; Jie, Ying; Li, Lin (Frontiers in Bioengineering and Biotechnology, 2021)
Purpose: This study aims to evaluate the validity of corneal elastic modulus (E) calculated from corneal visualization Scheimpflug technology (Corvis ST) in diagnosing Keratoconus (KC) and forme fruste keratoconus (FFKC). Methods: Fifty KC patients (50 eyes), 36 FFKC patients (36 eyes, the eyes without morphological abnormality while the contralateral eye was diagnosed as clinical keratoconus), and 50 healthy patients (50 eyes) were enrolled and underwent Corvis measurements. We calculated E according to the relation between air-puff force and corneal apical displacement. One-way analysis of variance (ANOVA) and receiver operating characteristic (ROC) curve analysis were used to identify the predictive accuracy of the E and other dynamic corneal response (DCR) parameters. Besides, we used back propagation (BP) neural network to establish the keratoconus diagnosis model. Results: (1) There was significant difference between KC and healthy subjects in the following DCR parameters: the first/second applanation time (A1T/A2T), velocity at first/second applanation (A1V/A2V), the highest concavity time (HCT), peak distance (PD), deformation amplitude (DA), Ambrsio relational thickness to the horizontal profile (ARTh). (2) A1T and E were smaller in FFKC and KC compared to healthy subjects. (3) ROC analysis showed E (AUC=0.746) was more accurate than other DCR parameters in detecting FFKC (AUC of these DCR parameters was not more than 0.719). (4) Keratoconus diagnosis model by BP neural network showed a more accurate diagnostic efficiency of 92.5%. The ROC analysis showed the predicted value (AUC=0.877) of BP neural network model was more sensitive in detection FFKC than the Corvis built-in parameters CBI (AUC=0.610, p=0.041) and TBI (AUC=0.659, p=0.034). Conclusions: Corneal elastic modulus was found to have improved predictability in detecting FFKC patients from healthy subjects and may be used as an additional parameter for the diagnosis of keratoconus.