Topometric and Tomographic Parameters for Diagnosis of Ectatic Disease

Monday, April 20, 2015: 2:05 PM
Room 4 (San Diego Convention Center)
Marcella Salomão, MD
Bernardo T. Lopes, MD
Isaac C. Ramos, MD
Frederico P. Guerra, MD
Allan Luz, MD
Renato Ambrósio Jr, MD, PhD

To investigate topometric (front surface curvature) and tomographic (3D elevation and thickness distribution) parameters for detecting ectatic corneal disease.

Topometric and tomographic indices were obtained using the Pentacam HR  from 266 normals (N),  282 keratoconus (KC) cases, and 211 cases of forme fruste keratoconus (FFKC) and retrospectively reviewed. The N group comprised from preoperative data of cases that had LASIK with no ectasia development after one year. The KC group comprised from one eye randomly selected from patients with bilateral keratoconus. FFKC criteria was the eye with no clinical or topographic keratoconus, from patients with keratoconus  in the fellow eye.  ANOVA with post-hoc t-tests or Kruskal– Wallis with post-hoc Dunn’s test were used for assessing differences among the groups. The ability of the parameters to distinguish KC and FFKC from N was assessed by receiver operating characteristic (ROC) curve analysis.

All variables had significantly different distributions among the groups.  Only tomographic parameters had AUC higher than 0.81 for detecting FFKC from N. The best parameter was Ambrósio Relational Thickness  with AUC of 0.992 for detecting KC (95%) and 0.877 for FFKC.  IHD was the best topometric parameter with AUC of 0.992 for detecting KC (95% CI: 0.970 to 0.994) and 0.781 for FFKC (95% CI: 0.741 to 0.817).  BAD-D version 3 had AUC of 0.995 for detecting KC (95% CI: 0.982 to 0.998) and 0.892 for  FFKC (95% CI: 0.861 to 0.919). A new  a new function was calculated, which enhanced the AUC to 0.998 for detecting KC (95% CI: 0.99 to 1.00) and 0.951 for detecting FFKC (95% CI: 0.923 to 0.97).

Topometric and tomographic indices  successfully detect keratoconus, but the integration parameters from curvature and 3- D analysis is necessary to enhance accuracy in identifying milder forms of ectasia. The integration of age, a surrogate of biomechanical properties of the cornea significantly improved the ability to identify ectatic diseases.