Bernardo Lopes

Corneal Densitometry in Keratoconus

Purpose: The aim of this study was to compare corneal densitometry measured by Scheimpflug tomography in normal and keratoconic eyes and to assess the differences in densitometry values among the stages of keratoconus. Methods: Keratoconic and normal corneas were examined using the Pentacam. Corneal densitometry was measured over a 12-mm diameter area, divided by annular concentric zones and depths. Keratoconus was classified according to the topographic keratoconus classification. Results: We enrolled 1 eye randomly selected from each of 172 patients with normal corneas (N) and 98 patients with bilateral keratoconus (KC). There were significant differences between the groups for densitometry measurements in 2 annuli: central 2.0 mm in diameter (N = 16.85 ± 2.42, KC = 18.93 ± 2.78, P = 0.0001) and annulus 2.0 to 6.0 mm in diameter (N = 15.18 ± 2.18, KC = 16.16 ± 1.71, P = 0.005), and total diameter (N = 24.89 ± 6.18, KC = 16.71 ± 2.3, P = 0.033). Divided by layers, the inner parts of anterior (120 &mgr;m), central (from 120 &mgr;m to the last 60 &mgr;m), and posterior (last 60 &mgr;m) layers were also higher in the KC group (P < 0.001). There were differences according to the stages of KC for corneal densitometry of the central annuli at total thickness, anterior and central layers. More advanced cases presented a higher backscatter (P < 0.05). The anterior layer presented the smallest overlap between groups and KC stages. Conclusions: The densitometry map reveals that light backscatter was higher in the central portion of the anterior keratoconic cornea than in the normal cornea. The densitometry level is higher in more advanced stages.

Detection of Keratoconus With a New Biomechanical Index.

PURPOSE 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. METHODS 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. RESULTS 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, Ambrósios 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. CONCLUSIONS 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.].

Comprehensive anterior segment normal values generated by rotating Scheimpflug tomography.

Purpose To identify normal values for tomographic parameters that are considered useful in screening patients for refractive surgery. Setting Private center, Albany, New York, USA. Design Database study. Methods A Pentacam HR Scheimpflug system was used to examine 1 randomly selected eye of patients to determine normal values of 21 parameters considered the most clinically applicable for surgical screening. Normality of data was evaluated using the Kolmogorov‐Smirnov test. Statistical analyses were performed using the Student t test to compare means and the 2‐paired sample Wilcoxon signed‐rank test. Results are displayed in 95.0% and 97.5% confidence intervals (CIs). Results The study evaluated 341 adults. High‐end outliers at the 97.5% CI were 46.1 diopters (D) for flat keratometry (K), 47.4 D for steep K, 3.4 D for astigmatism, 3.8 &mgr;m for anterior chamber depth, 4 &mgr;m for front apical elevation, 5 &mgr;m for front elevation at the thinnest point, and 12 &mgr;m for front elevation in the central 4.0 mm. Respective posterior elevation values were 7 &mgr;m, 13 &mgr;m, and 25 &mgr;m, with a progression index maximum of 1.53 and mean of 1.19, difference between apical and thinnest pachymetric reading of 7 &mgr;m, a maximum K of 48.2 D, and an inferior–superior ratio of 1.44 D. Low‐end outliers were a maximum Ambrósio relational thickness of 335 and a mean of 425, minimum pachymetry of 479 &mgr;m, thickness at the apex of 481 &mgr;m, and central 4.0 mm corneal volume of 6.31 mm3. Conclusion Scheimpflug‐derived corneal tomography identified key refractive surgery parameters that may be useful in screening refractive surgical patients. Financial Disclosure Drs. Ambrósio and Belin are consultants to Oculus Optikgeräte GmbH. No other author has a financial or proprietary interest in any material or method mentioned.

Influence of Pachymetry and Intraocular Pressure on Dynamic Corneal Response Parameters in Healthy Patients

PURPOSE To evaluate the influence of pachymetry, age, and intraocular pressure in normal patients and to provide normative values for all dynamic corneal response parameters (DCRs) provided by dynamic Scheimpflug analysis. METHODS Seven hundred five healthy patients were included in this multicenter retrospective study. The biomechanical response data were analyzed to obtain normative values with their dependence on corrected and clinically validated intraocular pressure estimates developed using the finite element method (bIOP), central corneal thickness (CCT), and age, and to evaluate the influence of bIOP, CCT, and age. RESULTS The results showed that all DCRs were correlated with bIOP except deflection amplitude (DefA) ratio, highest concavity (HC) radius, and inverse concave radius. The analysis of the relationship of DCRs with CCT indicated that HC radius, inverse concave radius, deformation amplitude (DA) ratio, and DefA ratio were correlated with CCT (rho values of 0.343, -0.407, -0.444, and -0.406, respectively). The age group subanalysis revealed that primarily whole eye movement followed by DA ratio and inverse concave radius were the parameters that were most influenced by age. Finally, custom software was created to compare normative values to imported examinations. CONCLUSIONS HC radius, inverse concave radius, DA ratio, and DefA ratio were shown to be suitable parameters to evaluate in vivo corneal biomechanics due to their independence from IOP and their correlation with pachymetry and age. The creation of normative values allows the interpretation of an abnormal examination without the need to match every case with another normal patient matched for CCT and IOP. [J Refract Surg. 2016;32(8):550-561.].

Assessing ectasia susceptibility prior to LASIK: the role of age and residual stromal bed (RSB) in conjunction to Belin-Ambrósio deviation index (BAD-D)

Purpose: To compare the ability to detect preoperative ectasia risk among LASIK candidates using classic ERSS (Ectasia Risk Score System) and Pentacam Belin-Ambrosio deviation index (BAD-D), and to test the benefit of a combined approach including BAD-D and clinical data. Methods: A retrospective nonrandomized study involved preoperative LASIK data from 23 post-LASIK ectasia cases and 266 stable-LASIK (follow up > 12 months). Preoperative clinical and Pentacam (Oculus; Wetzlar, Germany) data were obtained from all cases. Mann-Whitneys test was performed to assess differences between groups. Stepwise logistic regression was used for combining parameters.The areas under the Receiver Operating Characteristic (ROC) curves (AUC) were calculated for all parameters and combinations, with pairwise comparisons of AUC (DeLongs method). Results: Statistically significant differences were found for age, residual stromal bed (RSB), central corneal thickness and BAD-D (p 0.05). ERSS was 3 or more on 12/23 eyes from the ectasia group (sensitivity = 52.17%) and 48/266 eyes from the stable LASIK group (18% false positive). BAD-D had AUC of 0.931 (95% CI: 0.895 to 0.957), with cut-off of 1.29 (sensitivity = 87%; specificity = 92.1%). Formula combining BAD-D, age and RSB provided 100% sensitivity and 94% specificity, with better AUC (0.989; 95% CI: 0.969 to 0.998) than all individual parameters (p>0.001). Conclusion: BAD-D is more accurate than ERSS. Combining clinical data and BAD-D improved ectasia susceptibility screening. Further validation is necessary. Novel combined functions using other topometric and tomographic parameters should be tested to further enhance accuracy.

Enhanced ectasia screening: the need for advanced and objective data.

To the Editor: We read with interest the report from Drs. Abdulmassih-Gonçalves and Gonçalves.1 The authors should be commended for publishing a case of ectasia after LASIK, which was detected and addressed by collagen cross-linking. We also appreciate their willingness in sharing the preoperative raw data from rotatingScheimpflug tomography, which generated interesting information that we address in this letter. The tomography examination was taken by the Oculyzer (Wavelight, Inc., Erlangen, Germany), which has the same hardware characteristics as the Oculus Pentacam (Oculus Optikgeräte GmbH, Wetzlar, Germany). Although the Oculyzer software is designed for topography-guided ablations with the Wavelight excimer lasers, there are significant differences on diagnostic parameters when compared to Pentacam. Objective tomographic parameters, which go beyond curvature and central corneal thickness, are critical for clinical decisions when screening for ectasia risk after laser vision correction.2 Advanced analysis from the raw data generated by the Oculyzer allowed for the calculation of Ambrósio’s Relational Thickness3 and the deviation value from the Belin-Ambrósio Enhanced Ectasia Display (BAD-D), which demonstrates enhanced accuracy for detecting milder forms of ectasia, defined as the fellow eye with relatively normal curvature maps from patients with asymmetric keratoconus (considered as forme fruste keratoconus) (Figure 1).4 BAD-D in the right eye was higher than 1.22, the cut-off value for forme fruste keratoconus (93.62% sensitivity and 94.56% specificity).4 Ambrósio’s Relational Thickness average was lower than 521 μm in both eyes, the cut-off value for forme fruste keratoconus (91.94% sensitivity and 93.05 specificity).4 Ambrósio’s Relational Thickness maximum in the right eye was lower than 386 μm, the cut-off for keratoconus detection (99.17% sensitivity and 97.28% specificity).4 The patient was 21 years old at the time of the Oculyzer examination. Therefore, the Ectasia Risk Score System should be recalculated to 5 for the right eye and 4 for the left eye. Although the consideration of age may be an important factor for the lack of specificity of the Ectasia Risk Score System, there is compelling evidence that supports the younger age being related to lower biomechanical properties of the cornea.2 In a retrospective study involving preoperative clinical and Pentacam data from 23 cases that developed ectasia after LASIK and 266 stable LASIK cases (more than 12 months of follow-up), age was a strong predictor of ectasia risk, being combined in a stepwise logistic regression analysis with BAD-D and residual stromal bed to calculate the Ectasia Susceptibility Score-1. The Ectasia Susceptibility Score-1 represents the percentage of risk for developing ectasia, with a threshold of 6.45%. This allows for 100% sensitivity and 94% specificity, which is better than BAD-D, the best isolated parameter with a cut-off of 1.29 (87% sensitivity and 92.1% specificity).5 Considering the calculated residual stromal bed of 281 and 301 μm,1 the Ectasia Susceptibility Score-1 would be 96.75% and 79% for the right and left eye, respectively. Also, minimal re-

Integration of Scheimpflug-Based Corneal Tomography and Biomechanical Assessments for Enhancing Ectasia Detection

PURPOSE To present the Tomographic and Biomechanical Index (TBI), which combines Scheimpflugbased corneal tomography and biomechanics for enhancing ectasia detection. METHODS Patients from different continents were retrospectively studied. The normal group included 1 eye randomly selected from 480 patients with normal corneas and the keratoconus group included 1 eye randomly selected from 204 patients with keratoconus. There were two groups: 72 ectatic eyes with no surgery from 94 patients with very asymmetric ectasia (VAE-E group) and the fellow eyes of these patients with normal topography (VAE-NT group). Pentacam HR and Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany) parameters were analyzed and combined using different artificial intelligence methods. The accuracies for detecting ectasia of the Belin/Ambrósio Deviation (BAD-D) and Corvis Biomechanical Index (CBI) were compared to the TBI, considering the areas under receiver operating characteristic curves (AUROCs). RESULTS The random forest method with leave-one-out cross-validation (RF/LOOCV) provided the best artificial intelligence model. The AUROC for detecting ectasia (keratoconus, VAE-E, and VAE-NT groups) of the TBI was 0.996, which was statistically higher (DeLong et al., P < .001) than the BAD-D (0.956) and CBI (0.936). The TBI cut-off value of 0.79 provided 100% sensitivity for detecting clinical ectasia (keratoconus and VAE-E groups) with 100% specificity. The AUROCs for the TBI, BAD-D, and CBI were 0.985, 0.839, and 0.822 in the VAE-NT group (DeLong et al., P < .001). An optimized TBI cut-off value of 0.29 provided 90.4% sensitivity with 96% specificity in the VAE-NT group. CONCLUSIONS The TBI generated by the RF/LOOCV provided greater accuracy for detecting ectasia than other techniques. The TBI was sensitive for detecting subclinical (fruste) ectasia among eyes with normal topography in very asymmetric patients. The TBI may also confirm unilateral ectasia, potentially characterizing the inherent ectasia susceptibility of the cornea, which should be the subject of future studies. [J Refract Surg. 2017;33(7):434-443.].

Discriminant Value of Custom Ocular Response Analyzer Waveform Derivatives in Forme Fruste Keratoconus.

PURPOSE To evaluate the performance of corneal hysteresis (CH), corneal resistance factor (CRF), 37 Ocular Response Analyzer (ORA) waveform parameters, and 15 investigator-derived ORA variables in differentiating forme fruste keratoconus (KC) from normal corneas. DESIGN Case-control study. METHODS Seventy-eight eyes of 78 unaffected patients and 21 topographically normal eyes of 21 forme fruste KC patients with topographically manifest KC in the contralateral eye were matched for age, the thinnest point of the cornea, central corneal thickness, and maximum keratometry. Fifteen candidate variables were derived from exported ORA signals to characterize putative indicators of biomechanical behavior, and 37 waveform parameters were tested. Differences between groups were assessed by the Mann-Whitney test. The area under the receiver operating characteristic curve (AUROC) was used to compare the diagnostic performance. RESULTS Ten of 54 parameters reached significant differences between the groups (Mann-Whitney test, P < .05). Neither CRF nor CH differed significantly between the groups. Among the ORA waveform measurements, the best parameters were those related to the area under the first peak, p1area, and p1area1 (AUROC, 0.714 ± 0.064 and 0.721 ± 0.065, respectively). Among the investigator ORA variables, a measure incorporating the pressure-deformation relationship of the entire response cycle performed best (hysteresis loop area, AUROC, 0.694 ± 0.067). CONCLUSION Waveform-derived ORA parameters, including a custom measure incorporating the pressure-deformation relationship of the entire response cycle, performed better than traditional CH and CRF parameters in differentiating forme fruste KC from normal corneas.

Detection of ectatic corneal diseases based on pentacam.

Pentacam is a rotating Scheimpflug-based corneal and anterior segment tomographer that gives as comprehensive analysis of corneal 3D geometry. With this device the detection of mild keratoconus or ectasia susceptibility is possible. This is fundamental for screening ectasia risk prior to laser vision correction. The identification of susceptible cases at risk for developing progressive iatrogenic ectasia should go beyond (but not over) corneal front surface topography.

Enhanced combined tomography and biomechanics data for distinguishing forme fruste keratoconus

PURPOSE To evaluate the performance of the Ocular Response Analyzer (ORA) (Reichert Ophthalmic Instruments, Depew, NY) variables and Pentacam HR (Oculus Optikgeräte GmbH, Wetzlar, Germany) tomographic parameters in differentiating forme fruste keratoconus (FFKC) from normal corneas, and to assess a combined biomechanical and tomographic parameter to improve outcomes. METHODS Seventy-six eyes of 76 normal patients and 21 eyes of 21 patients with FFKC were included in the study. Fifteen variables were derived from exported ORA signals to characterize putative indicators of biomechanical behavior and 37 ORA waveform parameters were tested. Sixteen tomographic parameters from Pentacam HR were tested. Logistic regression was used to produce a combined biomechanical and tomography linear model. Differences between groups were assessed by the Mann-Whitney U test. The area under the receiver operating characteristics curve (AUROC) was used to compare diagnostic performance. RESULTS No statistically significant differences were found in age, thinnest point, central corneal thickness, and maximum keratometry between groups. Twenty-one parameters showed significant differences between the FFKC and control groups. Among the ORA waveform measurements, the best parameters were those related to the area under the first peak, p1area1 (AUROC, 0.717 ± 0.065). Among the investigator ORA variables, a measure incorporating the pressure-deformation relationship of the entire response cycle was the best predictor (hysteresis loop area, AUROC, 0.688 ± 0.068). Among tomographic parameters, Belin/Ambrósio display showed the highest predictive value (AUROC, 0.91 ± 0.057). A combination of parameters showed the best result (AUROC, 0.953 ± 0.024) outperforming individual parameters. CONCLUSIONS Tomographic and biomechanical parameters demonstrated the ability to differentiate FFKC from normal eyes. A combination of both types of information further improved predictive value. [J Refract Surg. 2016;32(7):479-485.].