Detection of Keratoconus With a New Biomechanical Index

• Published in: Journal of refractive surgery (1995) Vol. 32; no. 12; p. 803
• Main Authors: Vinciguerra, Riccardo, Ambrósio, Jr, Renato, Elsheikh, Ahmed, Roberts, Cynthia J, Lopes, Bernardo, Morenghi, Emanuela, Azzolini, Claudio, Vinciguerra, Paolo
• Format: Journal Article
• Language: English
• Published: United States 01-12-2016
• Subjects: Adult; Biomechanical Phenomena; Cornea - physiopathology; Corneal Pachymetry; Corneal Topography; Diagnostic Techniques, Ophthalmological; Elasticity - physiology; Female; Healthy Volunteers; Humans; Intraocular Pressure - physiology; Keratoconus - diagnosis; Keratoconus - physiopathology; Male; Middle Aged; Retrospective Studies; ROC Curve; Sensitivity and Specificity
• ISSN: 1081-597X
• DOI: 10.3928/1081597X-20160629-01

To evaluate the ability of a new combined biomechanical index called the Corvis Biomechanical Index (CBI) based on corneal thickness profile and deformation parameters to separate normal from keratoconic patients.
Six hundred fifty-eight patients (329 eyes in each database) were included in this multicenter retrospective study. Patients from two clinics located on different continents were selected to test the capability of the CBI to separate healthy and keratoconic eyes in more than one ethnic group using the Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany). Logistic regression was employed to determine, based on Database 1 as the development dataset, the optimal combination of parameters to accurately separate normal from keratoconic eyes. The CBI was subsequently independently validated on Database 2.
The CBI included several dynamic corneal response parameters: deformation amplitude ratio at 1 and 2 mm, applanation 1 velocity, standard deviation of deformation amplitude at highest concavity, Ambrósio's Relational Thickness to the horizontal profile, and a novel stiffness parameter. The receiver operating characteristic curve analysis of the training database showed an area under the curve of 0.983. With a cut-off value of 0.5, 98.2% of the cases were correctly classified with 100% specificity and 94.1% sensitivity. In the validation dataset, the same cut-off point correctly classified 98.8% of the cases with 98.4% specificity and 100% sensitivity.
The CBI was shown to be highly sensitive and specific to separate healthy from keratoconic eyes. The presence of an external validation dataset confirms this finding and suggests the possible use of the CBI in everyday clinical practice to aid in the diagnosis of keratoconus. [J Refract Surg. 2016;32(12):803-810.].