Theoretical basis, laboratory evidence, and clinical research of chemical surgery of the cornea: cross-linking

The Role of Corneal Biomechanics for the Evaluation of Ectasia Patients

Purpose: To review the role of corneal biomechanics for the clinical evaluation of patients with ectatic corneal diseases. Methods: A total of 1295 eyes were included for analysis in this study. The normal healthy group (group N) included one eye randomly selected from 736 patients with healthy corneas, the keratoconus group (group KC) included one eye randomly selected from 321 patients with keratoconus. The 113 nonoperated ectatic eyes from 125 patients with very asymmetric ectasia (group VAE-E), whose fellow eyes presented relatively normal topography (group VAE-NT), were also included. The parameters from corneal tomography and biomechanics were obtained using the Pentacam HR and Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany). The accuracies of the tested variables for distinguishing all cases (KC, VAE-E, and VAE-NT), for detecting clinical ectasia (KC + VAE-E) and for identifying abnormalities among the VAE-NT, were investigated. A comparison was performed considering the areas under the receiver operating characteristic curve (AUC; DeLong’s method). Results: Considering all cases (KC, VAE-E, and VAE-NT), the AUC of the tomographic-biomechanical parameter (TBI) was 0.992, which was statistically higher than all individual parameters (DeLong’s; p < 0.05): PRFI- Pentacam Random Forest Index (0.982), BAD-D- Belin -Ambrosio D value (0.959), CBI -corneal biomechanical index (0.91), and IS Abs- Inferior-superior value (0.91). The AUC of the TBI for detecting clinical ectasia (KC + VAE-E) was 0.999, and this was again statistically higher than all parameters (DeLong’s; p < 0.05): PRFI (0.996), BAD-D (0.995), CBI (0.949), and IS Abs (0.977). Considering the VAE-NT group, the AUC of the TBI was 0.966, which was also statistically higher than all parameters (DeLong’s; p < 0.05): PRFI (0.934), BAD- D (0.834), CBI (0.774), and IS Abs (0.677). Conclusions: Corneal biomechanical data enhances the evaluation of patients with corneal ectasia and meaningfully adds to the multimodal diagnostic armamentarium. The integration of biomechanical data and corneal tomography with artificial intelligence data augments the sensitivity and specificity for screening and enhancing early diagnosis. Besides, corneal biomechanics may be relevant for determining the prognosis and staging the disease.

Patient selection for corneal collagen cross-linking: an updated review

Corneal cross-linking (CXL) is an option that in the last decade has demonstrated its efficacy and safety in halting the progression of keratoconus (KCN) and other corneal ectasias. Its indication has been extended beyond the classic definition that required evidence of KCN progression, especially in the presence of some risk factors for a possible progression (particularly the younger age). However, the results can be still somewhat variable today. There are several protocols, each with its own advantages and disadvantages. Some predictors of CXL outcome have been identified. We will review the current knowledge on patient selection for CXL, its indications, and options in special cases (such as thin corneas).

Corneal Deformation Response with Dynamic Ultra-high-speed Scheimpflug Imaging for Detecting Ectatic Corneas

Purpose

To test the ability of metrics derived from corneal response to noncontact tonometry (NCT) to distinguish between normal and ectatic cases.

Materials and methods

The prototype of CorVis ST (Oculus, Wetzlar, Germany) was used for assessing corneal biomechanical response using ultra-high-speed 8 mm horizontal Scheimpflug photography, taking 4,330 frames per second during NCT. Patients were stratified based on clinical data, including rotating Scheimpflug corneal tomography (Oculus Pentacam HR). Biomechanical data from one eye randomly selected of 177 patients with normal corneas (N) and from 79 patients with bilateral keratoconus (KC) were investigated. Group forme fruste keratoconus (FFKC) was composed of 20 eyes with normal topographic patterns from cases with ectasia detected in the fellow eye. Group keratoconus suspect (KCS) had 16 eyes from 16 patients with topographic patterns suspicious of KC but documented stability over 3 years and normal tomographic findings. A combination of deformation parameters using linear regression analysis (Prototype Factor 1, pF1) was created by the BrAIn (Brazilian Artificial Intelligence on Corneal Tomography and Biomechanics) study group in order to provide the best possible separation of KC and normals.

Results

Statistical significant differences were found for N × KC for several parameters, including first and second applanation times, deformation amplitude, and maximal concavity radius (Mann–Whitney, p < 0.001). However, the areas under the receiver operating characteristic curves (AUC) were lower than 0.90. The pF1 had AUC of 0.945 (IC 0.909–0.97; sensitivity = 87.3% and specificity = 89.3%). The pF1 had statistically significant differences between the ectatic (KC and FFKC) and nonectatic groups (N and KCS) (p < 0.05, Kruskall–Wallis Test with post hoc Dunn's test).

Conclusion

Corneal deformation response analysis by ultra- high-speed 8 mm horizontal Scheimpflug photography provides relevant data for distinguishing ectatic and nonectatic corneas but cannot be used independently to detect KC. This data may be integrated with corneal tomography data for enhancing sensitivity and specificity for screening ectasia.

How to cite this article

Salomão MQ, Correia FF, Ramos I, Luz A, Ambrósio R Jr. Corneal Deformation Response with Dynamic Ultra-high-speed Scheimpflug Imaging for Detecting Ectatic Corneas. Int J Kerat Ect Cor Dis 2016;5(1):1-5.