Expanding the cone location and magnitude index to include corneal thickness and posterior surface information for the detection of keratoconus

Corneal Stress Distribution Evolves from Thickness-Driven in Normal Corneas to Curvature-Driven with Progression in Keratoconus

Purpose

To introduce the novel parameter of Corneal Contribution to Stress (CCS) and compare stress distribution patterns between keratoconus (KCN) and normal corneas.

Design

Prospective, observational, cross-sectional study.

Participants

The study included 66 eyes of 40 subjects diagnosed with KCN and 155 left eyes from 155 normal control (NRL) subjects.

Methods

Tomography was obtained to calculate the newly proposed CCS, defined according to the hoop stress formula without intraocular pressure, R/2t, where R is the radius of curvature and t is the thickness. CCS maps were calculated from pachymetry and tangential curvature maps. Custom software identified the 2-mm-diameter zones of greatest curvature (Cspot-max), thinnest pachymetry (Pach-min), greatest stress (CCSmax), and lowest stress (CCSmin). Stress difference (CCSdiff) was calculated as CCSmax - CCSmin. Distances between Cspot-max vs. Pach-min, vs. CCSmax, and vs. CCSmin, as well as between Pach-min vs. CCSmax and vs. CCSmin, were calculated. t tests were performed between cohorts, and paired t tests were performed within cohorts. Univariate linear regression analyses were performed between parameters and distances. The significance threshold was P < 0.05.

Main Outcome Measures

Corneal stress parameters, corneal features of maximum curvature, minimum thickness, and distances between corneal stress parameters and corneal features.

Results

CCSmax was significantly closer to Pach-min (0.79 ± 0.92) and Cspot-max (2.04 ± 0.85) than CCSmin (3.17 ± 0.38, 2.73 ± 1.53, respectively) in NRL, P < 0.0001, whereas CCSmin was significantly closer to Cspot-max (1.35 ± 1.43) than CCSmax (2.52 ± 0.72) in KCN, P < 0.0001. Cspot-max (severity) was significantly related to CCSdiff in KCN (P < 0.0001; R2 = 0.5882) with a weak relationship in NRL (P < 0.0080, R2 = 0.0451). Cspot-max was significantly related to the distance from Pach-min to CCSmax (P < 0.0001; R2 = 0.3737) without significance in NRL (P = 0.8011).

Conclusions

Corneal stress is driven by thickness in NRL, with greatest stress at thinnest pachymetry and greatest curvature. However, maximum stress moves away from thinnest pachymetry with progression in KCN, and minimum stress is associated with maximum curvature. Severity in KCN is significantly related to greater difference between maximum and minimum stress, consistent with the biomechanical cycle of decompensation.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Artificial intelligence for detecting keratoconus

BACKGROUND

Keratoconus remains difficult to diagnose, especially in the early stages. It is a progressive disorder of the cornea that starts at a young age. Diagnosis is based on clinical examination and corneal imaging; though in the early stages, when there are no clinical signs, diagnosis depends on the interpretation of corneal imaging (e.g. topography and tomography) by trained cornea specialists. Using artificial intelligence (AI) to analyse the corneal images and detect cases of keratoconus could help prevent visual acuity loss and even corneal transplantation. However, a missed diagnosis in people seeking refractive surgery could lead to weakening of the cornea and keratoconus-like ectasia. There is a need for a reliable overview of the accuracy of AI for detecting keratoconus and the applicability of this automated method to the clinical setting.

OBJECTIVES

To assess the diagnostic accuracy of artificial intelligence (AI) algorithms for detecting keratoconus in people presenting with refractive errors, especially those whose vision can no longer be fully corrected with glasses, those seeking corneal refractive surgery, and those suspected of having keratoconus. AI could help ophthalmologists, optometrists, and other eye care professionals to make decisions on referral to cornea specialists. Secondary objectives To assess the following potential causes of heterogeneity in diagnostic performance across studies. • Different AI algorithms (e.g. neural networks, decision trees, support vector machines) • Index test methodology (preprocessing techniques, core AI method, and postprocessing techniques) • Sources of input to train algorithms (topography and tomography images from Placido disc system, Scheimpflug system, slit-scanning system, or optical coherence tomography (OCT); number of training and testing cases/images; label/endpoint variable used for training) • Study setting • Study design • Ethnicity, or geographic area as its proxy • Different index test positivity criteria provided by the topography or tomography device • Reference standard, topography or tomography, one or two cornea specialists • Definition of keratoconus • Mean age of participants • Recruitment of participants • Severity of keratoconus (clinically manifest or subclinical) SEARCH METHODS: We searched CENTRAL (which contains the Cochrane Eyes and Vision Trials Register), Ovid MEDLINE, Ovid Embase, OpenGrey, the ISRCTN registry, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP). There were no date or language restrictions in the electronic searches for trials. We last searched the electronic databases on 29 November 2022.

SELECTION CRITERIA

We included cross-sectional and diagnostic case-control studies that investigated AI for the diagnosis of keratoconus using topography, tomography, or both. We included studies that diagnosed manifest keratoconus, subclinical keratoconus, or both. The reference standard was the interpretation of topography or tomography images by at least two cornea specialists.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted the study data and assessed the quality of studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. When an article contained multiple AI algorithms, we selected the algorithm with the highest Youden's index. We assessed the certainty of evidence using the GRADE approach.

MAIN RESULTS

We included 63 studies, published between 1994 and 2022, that developed and investigated the accuracy of AI for the diagnosis of keratoconus. There were three different units of analysis in the studies: eyes, participants, and images. Forty-four studies analysed 23,771 eyes, four studies analysed 3843 participants, and 15 studies analysed 38,832 images. Fifty-four articles evaluated the detection of manifest keratoconus, defined as a cornea that showed any clinical sign of keratoconus. The accuracy of AI seems almost perfect, with a summary sensitivity of 98.6% (95% confidence interval (CI) 97.6% to 99.1%) and a summary specificity of 98.3% (95% CI 97.4% to 98.9%). However, accuracy varied across studies and the certainty of the evidence was low. Twenty-eight articles evaluated the detection of subclinical keratoconus, although the definition of subclinical varied. We grouped subclinical keratoconus, forme fruste, and very asymmetrical eyes together. The tests showed good accuracy, with a summary sensitivity of 90.0% (95% CI 84.5% to 93.8%) and a summary specificity of 95.5% (95% CI 91.9% to 97.5%). However, the certainty of the evidence was very low for sensitivity and low for specificity. In both groups, we graded most studies at high risk of bias, with high applicability concerns, in the domain of patient selection, since most were case-control studies. Moreover, we graded the certainty of evidence as low to very low due to selection bias, inconsistency, and imprecision. We could not explain the heterogeneity between the studies. The sensitivity analyses based on study design, AI algorithm, imaging technique (topography versus tomography), and data source (parameters versus images) showed no differences in the results.

AUTHORS' CONCLUSIONS

AI appears to be a promising triage tool in ophthalmologic practice for diagnosing keratoconus. Test accuracy was very high for manifest keratoconus and slightly lower for subclinical keratoconus, indicating a higher chance of missing a diagnosis in people without clinical signs. This could lead to progression of keratoconus or an erroneous indication for refractive surgery, which would worsen the disease. We are unable to draw clear and reliable conclusions due to the high risk of bias, the unexplained heterogeneity of the results, and high applicability concerns, all of which reduced our confidence in the evidence. Greater standardization in future research would increase the quality of studies and improve comparability between studies.

Corneal Allogenic Intrastromal Ring Segments (CAIRS) for Corneal Ectasia: A Comprehensive Segmental Tomography Evaluation

PURPOSE

To evaluate the visual, refractive, and tomographic results of patients with corneal ectasia treated with corneal allogenic intrastromal ring segments (CAIRS) insertion without concomitant corneal cross-linking.

METHODS

Fifty-two eyes from 39 patients with stable corneal ectasia and unsatisfactory visual acuity with contact lenses were included. All patients underwent CAIRS insertion with no concomitant corneal procedure at the American University of Beirut Medical Center between September 2019 and July 2022. Visual, refractive, topographic, aberrometric, epithelial, stromal, and segment thickness data were measured relative to baseline at 1 week, 1 month, and at least 3 months postoperatively. Evaluations included slit-lamp examination, manifest refraction, uncorrected (UDVA) and corrected (CDVA) distance visual acuity, and tomography using anterior segment optical coherence tomography.

RESULTS

Mean follow-up time was 6.9 ± 5.2 months. UDVA and CDVA improved from 0.97 ± 0.47 and 0.56 ± 0.19 preoperatively to 0.52 ± 0.21 (P < .001) and 0.23 ± 0.19 (P < .001) 3 months postoperatively. Manifest refraction spherical equivalent and cylinder improved from -6.71 ± 6.51 and -4.02 ± 2.24 diopters (D) preoperatively to -3.78 ± 4.07 D (P < .001) and -2.35 ± 1.98 D (P < .001) 3 months postoperatively, respectively. Maximum anterior keratometry and vertical coma decreased from 58.09 ± 7.92 D and 1.56 ± 1.09 µm to 52.48 ± 6.69 D (P < .001) and 0.43 ± 0.77 µm, respectively (P < .001). Corneal epithelium thickened proximal to the allogenic segment by 7.25 µm (P < .001), whereas stromal elevation at the cone decreased from 38.61 ± 18.5 to 23.82 ± 13.4 µm, respectively (P < .001). No major complications were observed and only 1 eye lost one line of CDVA.

CONCLUSIONS

Treatment of corneal ectasia with CAIRS improved visual, refractive, topographic, and tomographic parameters. Epithelial thickening central to CAIRS, along with anterior stromal flattening is postulated to contribute to tomographic flattening and regularization. [J Refract Surg. 2023;39(11):767-776.].

Variability of CLMI-X parameters, zonal Kmax, and single-point Kmax in keratoconus progression

OBJECTIVES

To compare the repeatability of Cone Location and Magnitude Index expanded (CLMI.X) parameters of 2 mm diameter zone of greatest corneal curvature (Cspot-Axi) and 1 mm diameter zone of thinnest pachmymetry (Spot-Pach) with the maximum single point keratometry (Kmax), 3 mm Zonal Kmax (Z-Kmax3), and thinnest single point pachymetry (TP) in keratoconus (KC).

METHODS

In this Comparative repeatability study, data from 36 eyes of 36 normal individuals and 72 eyes of 72 KC patients (28 eyes with ≤50.0D and 44 eyes with >50.0D Z-Kmax3) were analyzed. For each enrolled eye, imaging was done 6 times (3 consecutive acquisitions with a half hour break). For each parameter, the within-subject standard deviation (Sw) was calculated from the data of the six exams.

RESULTS

In the normal group, Cspot-Axi-Sw was different from Kmax-Sw (p = 0.0004). Also, Z-Kmax3-Sw was different from Kmax-Sw (p = 0.0297). The difference between Cspot-Axi-Sw and Z-Kmax3-Sw was statistically significant (p = 0.0482). In the KC group, Sw were significantly different between Cspot-Axi and Kmax (p < 0.0001), and between Z-Kmax3 and Kmax (p < 0.0001). In the Z-Kmax3 ≤ 50.0D subgroup, Sw were different between Cspot-Axi and Kmax (p = 0.0002). In the Z-Kmax3 > 50.0D subgroup, Sw were different between Cspot-Axi and Kmax (p < 0.0001), and between Z-Kmax3 and Kmax (p < 0.0001). Sw differences between Spot-Pach and TP were not significant in any of the study groups (all P > 0.05).

CONCLUSIONS

In the diagnosis and follow up of KC, the zonal averages of Cspot-Axi and Z-Kmax3 are more reliable than the single point Kmax. The repeatability of Spot-Pach is similar to TP and both variables should suit the purpose equally.

Keratoconus Diagnosis: From Fundamentals to Artificial Intelligence: A Systematic Narrative Review

The remarkable recent advances in managing keratoconus, the most common corneal ectasia, encouraged researchers to conduct further studies on the disease. Despite the abundance of information about keratoconus, debates persist regarding the detection of mild cases. Early detection plays a crucial role in facilitating less invasive treatments. This review encompasses corneal data ranging from the basic sciences to the application of artificial intelligence in keratoconus patients. Diagnostic systems utilize automated decision trees, support vector machines, and various types of neural networks, incorporating input from various corneal imaging equipment. Although the integration of artificial intelligence techniques into corneal imaging devices may take time, their popularity in clinical practice is increasing. Most of the studies reviewed herein demonstrate a high discriminatory power between normal and keratoconus cases, with a relatively lower discriminatory power for subclinical keratoconus.

The Keratectasia Volume (KEV) in Corneal Topography to Evaluate the Effect of Corneal Collagen Cross-linking in Pediatric Keratoconus

The study aimed to evaluate the keratectasia volume (KEV) before and after corneal cross-linking (CXL) in pediatric patients. This study included 40 eyes of 25 pediatric patients (10-19 years) undergoing standard CXL. The support vector machine (SVM) algorithm was applied to transform mass pixels in corneal topography into a three-dimensioned model to calculate the KEV. The KEV, Kmax, K1, K2, Kave, keratectasia area (KEA), and thinnest corneal thickness (TCT) were determined before CXL and at 3, 6, and 12 months after surgery. The correlation between KEV and other parameters (Kmax, TCT, max decentration, eccentricity, and so on) was calculated. The KEV was 4.75 ± 0.74 preoperatively and 4.43 ± 1.22 postoperatively at last follow-up (p < 0.002). There was strong positive correlation between the KEV and Kmax (r = 0.806, p < 0.0005). The preoperat ive KEV was 4.32 ± 0.69 in mild to moderate keratoconus (Kmax < 58D) and 5.27 ± 0.37 in advanced keratoconus (Kmax > 58D) (p < 0.0005, t-test). Postoperative KEV and K readings remained stable at the early stage, and the KEV showed a more drastic decreasing trend than Kmax at sixth month. Statistical significance was found in the KEV between preoperative and 6 months after surgery (p < 0.0005), but not in Kmax and other parameters. In 83.3% (15 eyes out of 18 eyes) of the eyes, the preoperative KEV was greater than 4.6 in patients with significant flattening after CXL. Compared with K readings, the KEV can be regarded as a more sensitive index to evaluate the postoperative morphological changes after CXL in pediatric patients.

The ABCD grading system in assessment of corneal cross-linking effect in keratoconus with different cone locations

PURPOSE

The aim of this study was to analyse the postoperative corneal cross-linking results of corneal parameters and the ABCD grading system, depending on the cone location.

METHODS

Thirty eyes of 25 patients with keratoconus (KC), who received the corneal cross-linking (CXL) treatment, were included in this study. The exclusion criteria were: patients under 18 years of age, corneal pachymetry less than 400 μm, corneal scarring, history of ocular trauma, history of ocular surgery, and corneal pathology other than KC. Patients were examined at the baseline visit, and followed-up at three, six, and twelve months after the CXL. All patients underwent visual acuity and Scheimpflug tomography at all visits. Progression parameters, keratometries, and ABCD grading were compared between the visits. Patients were classified into two groups: central and paracentral cones group (within the central 5 mm corneal zone) and peripheral cones group (outside the central 5 mm corneal zone), based on X-Y coordinates of maximal keratometry (Kmax).

RESULTS

Parameter A remained relatively stable throughout the follow-up period in both groups. Parameter B and parameter C showed a significant increase in both groups postoperatively. Parameter D showed stability at the 6-month post-CXL visit in the peripheral KC group, while the central and paracentral KC group showed improvement at the 12-month post-CXL visit.

CONCLUSION

There was no significant difference in the postoperative response between different cone locations in the ABCD grading system, when classifying according to the Kmax, except an earlier recovery of the parameter D in peripherally located cones.

Best Fit Sphere Back and Adjusted Maximum Elevation of Corneal Back Surface as Novel Predictors of Keratoconus Progression

Purpose

We evaluated the Maximum Elevation of Corneal Back Surface adjusted to the same Best Fit Sphere Back (BFSB) between timeline measurements (AdjEleBmax) and the BFSB radius (BFSBR) itself as new tomographic parameters for documentation of ectasia progression and compare them with the most recent and reliable parameters used on keratoconus (KC) progression.

Results

We evaluated the performance and the ideal cutoff point of Kmax, D-index, posterior radius of curvature from the 3.0 mm centered on the thinnest point (PRC), EleBmax, BFSBR, and AdjEleBmax as isolated parameters to document KC progression (defined as a significant change in two or more variables), we found a sensitivity of 70%, 82%, 79%, 65%, 51%, and 63% and a specificity of 91%, 98%, 80%, 73%, 80%, and 84% to detect KC progression. The area under the curve (AUC) for each variable was 0.822, 0.927, 0.844, 0.690, 0.695, 0.754, respectively.

Conclusion

AdjEleBmax presented a greater specificity, larger AUC, and better performance compared to EleBmax without any adjustment, with similar sensitivity. Although AdjEleBmax and BFSB demonstrated smaller AUC and specificities comparing with Kmax and D-Index, AdjEleBmax still presented a good performance with a reasonable AUC. Since the shape of the posterior surface, more aspheric and curved than the anterior, may facilitate detection of change, we suggest the inclusion of AdjEleBmax in the evaluation of KC progression in conjunction with other variables to increase the reliability of our clinical evaluation and early detection of progression.

Biomechanical Evaluation of Topographically and Tomographically Normal Fellow Eyes of Patients With Keratoconus

PURPOSE

To determine the effectiveness of parameters and indices based on biomechanical measures at discriminating fellow eyes with topographically and tomographically normal corneas in patients with keratoconus from normal control corneas.

METHODS

The study included 47 keratoconus suspect eyes, defined as the topographically and tomographically normal fellow eyes of patients with frank keratoconus in the other eye. Eyes were imaged using the Pentacam HR and Corvis ST (both Oculus Optikgeräte GmbH). Fellow eyes were then categorized as topographically/tomographically normal fellow eyes (TNF) and topographically/tomographically borderline fellow eyes (TBF). The ability of each of the Corvis Biomechanical Index (CBI), Tomographic and Biomechanical Index (TBI), stiffness parameter at applanation 1 (SP-A1), and stress-strain index (SSI) at discriminating between normal controls and keratoconus suspects was assessed.

RESULTS

The TBI had the best discriminative ability with the greatest area under the receiver operating characteristic (AUROC) curve value of 0.946 for normal controls versus TBF eyes, and 0.824 for normal controls versus TNF eyes. Compared to the TBI AUROC curves, SP-A1 and CBI had AUROC curve values of 0.833 (P = .09) and 0.822 (P = .01) for normal controls versus TBF eyes, respectively, and AUROC curve values of 0.822 (P = .96) and 0.550 (P = .0002) for normal controls versus TNF eyes, respectively. The TBI had the best positive predictive value for TNF and TBF eyes, followed by CBI and SP-A1.

CONCLUSIONS

The TBI and the purely biomechanical parameter SP-A1 were of moderate utility in distinguishing between normal and keratoconus suspect eyes. In the absence of topographic/tomographic evidence of keratectasia, an independently abnormal biomechanical parameter may suggest an increased risk of ectasia. [J Refract Surg. 2022;38(5):318-325.].

Accuracy of Machine Learning Assisted Detection of Keratoconus: A Systematic Review and Meta-Analysis

(1) Background: The objective of this review was to synthesize available data on the use of machine learning to evaluate its accuracy (as determined by pooled sensitivity and specificity) in detecting keratoconus (KC), and measure reporting completeness of machine learning models in KC based on TRIPOD (the transparent reporting of multivariable prediction models for individual prognosis or diagnosis) statement. (2) Methods: Two independent reviewers searched the electronic databases for all potential articles on machine learning and KC published prior to 2021. The TRIPOD 29-item checklist was used to evaluate the adherence to reporting guidelines of the studies, and the adherence rate to each item was computed. We conducted a meta-analysis to determine the pooled sensitivity and specificity of machine learning models for detecting KC. (3) Results: Thirty-five studies were included in this review. Thirty studies evaluated machine learning models for detecting KC eyes from controls and 14 studies evaluated machine learning models for detecting early KC eyes from controls. The pooled sensitivity for detecting KC was 0.970 (95% CI 0.949–0.982), with a pooled specificity of 0.985 (95% CI 0.971–0.993), whereas the pooled sensitivity of detecting early KC was 0.882 (95% CI 0.822–0.923), with a pooled specificity of 0.947 (95% CI 0.914–0.967). Between 3% and 48% of TRIPOD items were adhered to in studies, and the average (median) adherence rate for a single TRIPOD item was 23% across all studies. (4) Conclusions: Application of machine learning model has the potential to make the diagnosis and monitoring of KC more efficient, resulting in reduced vision loss to the patients. This review provides current information on the machine learning models that have been developed for detecting KC and early KC. Presently, the machine learning models performed poorly in identifying early KC from control eyes and many of these research studies did not follow established reporting standards, thus resulting in the failure of these clinical translation of these machine learning models. We present possible approaches for future studies for improvement in studies related to both KC and early KC models to more efficiently and widely utilize machine learning models for diagnostic process.

The Location Consistency Index Helps to Distinguish Eyes With Subclinical Keratoconus From Normal Eyes

PURPOSE

To develop a novel index that combines the locations and magnitudes of corneal alterations to improve discrimination of eyes with subclinical keratoconus from normal eyes.

METHODS

A Scheimpflug-based tomography system was used to image 252 eyes (normal: 78 eyes, subclinical keratoconus: 71 eyes, and keratoconus: 103 eyes) of 252 patients from two clinical centers. Coordinates and magnitudes of the maximum corneal protrusion alterations were extracted from curvature, elevation, and pachymetry maps. A location consistency index (LCI) was calculated from the Euclidean distances among these locations. A logistic regression model, named the location consistency enhanced score (LCES), which combined the LCI and the magnitudes of these maximum alterations, was trained and tested in two different datasets.

RESULTS

The LCI in eyes with subclinical keratoconus was 7.8 ± 2.6 µm, which was significantly different from that in normal eyes (11.8 ± 3.9 µm) and eyes with keratoconus (5.8 ± 2.4 µm) (all P < .001). The LCI could differentiate eyes with subclinical keratoconus from normal eyes with a sensitivity of 67.6%, specificity of 83.3%, and area under the receiver operating characteristic curve (AUC) of 0.81. Combining the magnitudes of these maximum alterations with the LCI for the LCES yielded a sensitivity of 90.0% and a specificity of 74.4% for differentiating eyes with subclinical keratoconus from normal eyes (AUC: 0.91).

CONCLUSIONS

The LCI can assist in differentiating eyes with subclinical keratoconus from normal eyes. The LCES is a potential new index to assist in a confirmatory test of eyes with subclinical keratoconus. [J Refract Surg. 2022;38(1):35-42.].

Keratoconus enlargement as a predictor of keratoconus progression

Numerous approaches have been designated to document progression in keratoconus, nevertheless there is no consistent or clear definition of ectasia progression. In this present study, we aim to evaluate Keratoconus Enlargement (KCE) as a parameter to document ectasia progression. We define KCE as an increase of more than 1D in the anterior curvature of non-apical corneal areas. We have designed a longitudinal study in 113 keratoconic eyes to assess keratoconus progression. KCE was compared with variables commonly used for detection of keratoconus progression like Kmax, Km, K2, PachyMin, D-Index, Corneal Astigmatism and PRC of 3.0 mm centered on the thinnest point. The variations of keratometric readings, D-index and ELEBmax showed positive associations with KCE. Evaluating the performance of Kmax, D-index and KCE as isolated parameters to document keratoconus progression we found a sensitivity of 49%, 82% and 77% and a specificity of 100%, 95% and 66% to detect keratoconus progression (p < 0.001 for all). This difference in sensitivity can be explained by the changes in keratoconus outside the small area represented by Kmax. The inclusion of KCE should be considered in the evaluation of keratoconus progression in conjunction with other variables to increase the reliability of our clinical evaluation.

Superiority of Baseline Biomechanical Properties over Corneal Tomography in Predicting Keratoconus Progression

Objectives:

To determine corneal biomechanical and tomographic factors associated with keratoconus (KC) progression.

Materials and Methods:

This study included 111 eyes of 111 KC patients who were followed-up for at least 1 year. Progression was defined as the presence of progressive change between the first two consecutive baseline visits in any single parameter (A, B, or C) ≥95% confidence interval or two parameters ≥80% confidence interval for the KC population evaluated by the Belin ABCD progression display. The eye with better initial tomographic findings was chosen as the study eye. Analyzed Pentacam parameters were maximum keratometry (Kmax), minimum pachymetry (Kmin), central corneal thickness, thinnest corneal thickness, 90° vertical anterior and posterior coma data in Zernike analysis, and Belin Ambrosio Enhanced Ectasia Display Final D value. Corneal hysteresis (CH) and corneal resistance factor (CRF) were analyzed together with the waveform parameters obtained with Ocular Response Analyzer (ORA). Factors related to KC progression were evaluated using t-tests and logistic regression tests. Statistical significance was accepted as p<0.05.

Results:

There were 44 (mean age: 27.1±8.5 years, female: 25) and 67 (mean age: 31.1±9.1 years, female: 36) patients in the progressive and non-progressive groups, respectively. Although Pentacam parameters along with CH and CRF were similar between the two groups, ORA waveform parameter derived from the second applanation signal p2area was statistically significantly lower in the progressive group (p=0.02). Each 100-unit decrease in p2area increased the likelihood of keratoconus progression by approximately 30% in the logistic regression analysis (β=0.707, p=0.001, model r2=0.27).

Conclusion:

Parameters derived from the second applanation signal of ORA may be superior to conventional ORA parameters and corneal tomography in predicting KC progression.

The ABCD Keratoconus Grading System-A Useful Tool to Estimate Keratoconus Progression in the Pediatric Population

PURPOSE

To evaluate the ABCD grading system in pediatric keratoconus.

METHODS

A retrospective cohort analysis of all children with keratoconus followed up at the Shamir medical center between 2010 and 2017. A recommendation by the treating physician to undergo corneal crosslinking (CXL) was used as an estimate for clinically significant disease progression. The ABCD grading was not available to the treating physician and was computed post hoc. The ABCD grading was compared between patients who required CXL with those who did not. A single eye of each patient was included.

RESULTS

Fifty eyes of 50 children were analyzed. The mean age at presentation was 15.56 ± 1.36 years. In 23 eyes, progression of keratoconus was recorded and CXL was performed (CXL-group). On presentation, the stable and CXL groups did not differ significantly in their clinical parameters. In the CXL-group, a statistically significant increase was seen in the ABCD staging (P < 0.001). In the stable group, the ABCD staging did not change significantly in parallel visits (P = 0.87). An increase of 1 point in the sum of the ABCD staging showed a 5-fold risk for undergoing CXL (odds ratio = 5.28; 95% CI, 1.82-15.34). There was no significant change in the Amsler-Krumeich classification in the CXL group.

CONCLUSIONS

Among a cohort of pediatric patients with keratoconus, worsening in the ABCD grading was associated with disease progression, whereas no significant change was demonstrated in the Amsler-Krumeich classification The ABCD grading system is a useful tool for initial assessment of disease progression in the pediatric population, in which early recognition is of paramount importance.

Keratoconus detection of changes using deep learning of colour-coded maps

Objective

To evaluate the accuracy of convolutional neural networks technique (CNN) in detecting keratoconus using colour-coded corneal maps obtained by a Scheimpflug camera.

Design

Multicentre retrospective study.

Methods and analysis

We included the images of keratoconic and healthy volunteers’ eyes provided by three centres: Royal Liverpool University Hospital (Liverpool, UK), Sedaghat Eye Clinic (Mashhad, Iran) and The New Zealand National Eye Center (New Zealand). Corneal tomography scans were used to train and test CNN models, which included healthy controls. Keratoconic scans were classified according to the Amsler-Krumeich classification. Keratoconic scans from Iran were used as an independent testing set. Four maps were considered for each scan: axial map, anterior and posterior elevation map, and pachymetry map.

Results

A CNN model detected keratoconus versus health eyes with an accuracy of 0.9785 on the testing set, considering all four maps concatenated. Considering each map independently, the accuracy was 0.9283 for axial map, 0.9642 for thickness map, 0.9642 for the front elevation map and 0.9749 for the back elevation map. The accuracy of models in recognising between healthy controls and stage 1 was 0.90, between stages 1 and 2 was 0.9032, and between stages 2 and 3 was 0.8537 using the concatenated map.

Conclusion

CNN provides excellent detection performance for keratoconus and accurately grades different severities of disease using the colour-coded maps obtained by the Scheimpflug camera. CNN has the potential to be further developed, validated and adopted for screening and management of keratoconus.

Differentiating highly asymmetric keratoconus eyes using a combined Scheimpflug/Placido device

PURPOSE

To determine the ability to differentiate between normal eyes and clinically unaffected eyes of patients with highly asymmetric keratoconus (AKC) using a Scheimpflug/Placido device.

SETTING

Tel Aviv Sourasky Medical Center and Enaim Medical Center, Israel.

DESIGN

Retrospective case-control.

METHODS

Imaging from a combined Scheimpflug/Placido device (Sirius, C.S.O.) was obtained from 26 clinically unaffected eyes of patients with frank keratoconus in the fellow eye, and 166 eyes from 166 patients with bilaterally normal corneal examinations that underwent uneventful corneal refractive surgery with at least 1 year of follow-up. Receiver operating characteristic curves were produced to calculate the area under the curve, sensitivity, and specificity of 60 metrics, and finally a logistic regression modeling was used to determine optimal variables to differentiate populations.

RESULTS

The most predictive individual metric able to differentiate between 26 eyes in the case group to 166 eye in the control group was the posterior wall inferior-superior (I-S) ratio, with an receiver operating characteristics (ROC) of 0.862. A combination model of 4 metrics (posterior wall I-S ratio in the central 3 mm, thinnest pachymetry coordinate on the x horizontal axis, posterior asymmetry and asphericity index, corneal volume) yielded an ROC of 0.936, with a sensitivity/specificity pair of 92.3%/87%. Variables related to elevation were not found significant.

CONCLUSIONS

Using a combination of metrics from a combined Scheimpflug/Placido device, a practical model for discrimination between clinically normal eyes of patients with highly AKC and normal eyes was constructed. Variables related to pachymetry and posterior cornea asymmetry were the most impactful.

Agreement and repeatability of corneal tomography in healthy eyes using a novel Swept-Source optical coherence tomographer, a rotating Scheimpflug camera and a dual Scheimpflug-Placido system

PURPOSE

To investigate the accordance and repeatability of tomographic parameters measured by a novel Swept-Source optical coherence tomographer (SS-OCT, ANTERION), a rotating Scheimpflug camera (RSC, Pentacam) and a dual Scheimpflug-Placido system (DSP, Galilei G6).

SETTING

Department of Ophthalmology of Univ. Hospital Carl Gustav Carus, Dresden, Germany.

DESIGN

Prospective reliability analysis.

METHODS

Thirty randomly selected eyes of 30 healthy participants were enrolled in this study. Normal tomography were ensured by bilaterally evaluating appropriated parameters using RSC. All subjects received three consecutive measurements on each device by the same operator and in the uniform order RSC, SS-OCT and DSP. Anterior (ACP) and posterior (PCP) corneal parameters such as flat and steep keratometry and corneal thickness were analyzed. Repeatability was assessed by using a coefficient of repeatability (CR) and a coefficient of variation (CV). Agreement between RSC and SS-OCT as well as RSC and DSP were shown by Bland-Altman plots (BA).

RESULTS

CR of ACP did not exceed 0.5 D. There were no statistical differences in repeatability of ACP obtained from the three devices (P>0.05). For PCP and corneal thickness there was statistically significant higher repeatability mostly found for SS-OCT as opposed to RSC and DSP (P<0.05). For a wide range of analyzed parameters there were large limits of agreement (95%-LoA) found between the devices.

CONCLUSION

The SS-OCT showed highly repeatable measurements in healthy subjects regarding anterior, posterior and corneal thickness parameters. Repeatability of ACP did not differ between the devices. A mostly wide range of 95%-LoA prevents interchangeability between the devices.

Clinical Validation of the Automated Characterization of Cone Size and Center in Keratoconic Corneas

PURPOSE

To evaluate an automated method for detecting the cone shape characteristics and to assess the cornea specialists' subjective variability of these measures using different maps.

METHODS

Topographic images of the anterior and posterior surface of each eye were presented to 12 clinicians in two different types of map: tangential curvature and relative elevation to the best-fit sphere. They were asked to mark the cone center and its boundaries in the two maps without knowing that they belonged to the same patient. The results between the maps were compared to assess the subjective variability dependent on the map type and the automated method was compared against both estimations to assess its accuracy.

RESULTS

Considering the results of anterior and posterior surfaces, there was low agreement between the cone center estimations using different types of maps for 10 of the 12 cases (P < .05), whereas the comparison between the automated method and the two map estimations did not show differences in 11 of the 12 cases (P > .05). There was high variability, up to 55%, among clinicians' estimations of the cone area. The results of the automated method were within the range of the expert's estimations.

CONCLUSIONS

An objective, mathematically derived method of determining morphological dimensions of the cone was consistent with clinicians' evaluations. Although there was high variability among the experts' subjective estimates, which were highly influenced by the type of map, the objective method provided a reliable evaluation of the keratoconus shape independent of maps or color scale. [J Refract Surg. 2021;37(6):414-421.].

Long-term Outcomes of Collagen Crosslinking for Early Keratoconus

Purpose

To evaluate the long-term outcomes of collagen crosslinking in early keratoconus.

Methods

Thirty eyes of twenty patients with early keratoconus were enrolled. Uncorrected visual acuity (UCVA), best spectacle corrected visual acuity (BSCVA), objective refraction, subjective refraction, corneal topography and pachymetry were assessed before and 3, 6, 12 months and 9 years after performing collagen crosslinking surgery.

Results

The patients' mean age was 31.2 ± 5.59 years at nine-year follow-up (range, 25–44 years). The means of preoperative UCVA and BSCVA were 0.57 ± 0.34 and 0.15 ± 0.12 logMAR, respectively, and these values remained stable at the final follow-up (P = 0.990 and P = 0.227, respectively). The mean objective spherical equivalent decreased considerably from –6.00 ± 4.05 D preoperatively to –5.22 ± 3.71 D at the final follow-up (P< 0.05). The mean subjective spherical equivalent was –4.25 ± 2.87 D preoperatively and this value was stable at the last follow-up (P = 0.92). No considerable difference was found between the post- and preoperative mean objective cylinder values (P = 0.34). The mean subjective cylinder value changed significantly from –4.05 ± 1.85 D preoperatively to –3.1 ± 1.42 D at the final follow-up (P< 0.05). The mean central corneal thickness was 496.97 ± 45.95 µm preoperatively and this value was stable at nine-year follow-up (P = 0.183). No significant difference was found between the pre- and postoperative mean maximum and mean minimum corneal curvature values (P = 0.429 and P = 0.248, respectively). There were no significant postoperative complications.

Conclusion

Corneal crosslinking in early keratoconus seems to be a safe procedure that can effectively stabilize UCVA, BSCVA, subjective SE and CCT, while improving objective spherical equivalent.

Topographic, elevation, and keratoconus indices for diagnosis of keratoconus by a combined Placido and Scheimpflug topography system

PURPOSE

To determine the accuracy of various corneal parameters in keratoconus diagnosis using Scheimpflug camera combined with Placido disk corneal topography (Sirius, CSO).

METHODS

One hundred and fifteen keratoconic eyes (group1) and a 111 normal eyes (group2) were assessed prospectively between March 2018 and July 2019 for: corneal keratometric indices (K1, K2, sim K, apex curvature) at different corneal rings of both corneal surfaces, central corneal thickness (CCT), thinnest corneal thickness (TL), corneal asphericity (Q), elevation at thinnest point, root mean square (RMS), and root mean square per area (RMS/A) in spherical, aspheric and aspherotoric reference for both corneal surfaces and keratoconus summary parameters; surface asymmetry index of front and back (SIf, SIb respectively), elevation at keratoconus vertex front and back (KVf, KVb respectively), Baiocchi Calossi Versaci front and back index (BCVf, BCVb) and its vector summation (BCV) and convergence radius and cutoff value for each was calculated.

RESULTS

All studied indices were significantly different between the two groups. The highest predictive accuracy "Area under receiver operating characteristic curve (AUROC)" of 0.999 was observed for BCVf, KVb, RMS and RMS/A at 6 mm aspherotoric reference posterior surface. Keratoconus summary indices had high AUROC (0.986, 0.984, 0.948, 0.999, 0.999, 0.998 respectively). Curvature indices had lower AUROC than elevation indices, except for curvature of corneal apex at anterior (0.98) and posterior surface (0.99). Higher AUROC was noted with elevation at thinnest point especially at aspherotoric reference surface.

CONCLUSION

Sirius topography showed high predictive accuracy in detection of keratoconus. Elevation indices and keratoconus summary parameters have the highest diagnostic ability.

Repeatability of Zone Averages Compared to Single-Point Measurements of Maximal Curvature in Keratoconus

PURPOSE

To evaluate the repeatability of curvature zone averages centered on the point of maximum curvature (Kmax) compared to that of the single-point Kmax.

DESIGN

Comparative reliability analysis.

METHODS

Setting: American University of Beirut Medical Center, Beirut, Lebanon.

STUDY POPULATION

Sixty-five eyes of 65 adult keratoconus patients. Patients with other ocular disease, history of ocular surgery or trauma, and contact lens wear within 2 weeks of image acquisition were excluded.

OBSERVATION PROCEDURES

Eyes were evaluated with 3 consecutive scans using the Galilei dual Scheimpflug-Placido system.

MAIN OUTCOME MEASURES

Repeatability of axial and instantaneous Kmax single points, and zone averages with radii of 0.1-2.0 mm, centered on them. Repeatability was assessed by within-subject standard deviations, repeatability limits (r), and intraclass correlation coefficients.

RESULTS

Axial curvature zone averaging yielded clinically acceptable repeatability only in eyes with Kmax ≤50 diopters (D), for radii of 1.5 mm and 2.0 mm (r = 0.87 D and r = 0.76, respectively, vs r = 0.91 for the single-point axial Kmax). Compared to instantaneous Kmax, clinically acceptable repeatability was achieved with instantaneous zone averages of at least 1.5 mm radius in eyes with Kmax ≤50 D (r = 0.99 D and r = 0.70 D, respectively) and 2.0 mm radius in eyes with Kmax >50 D (r = 2.28 D and r = 0.87 D, respectively). For all eyes, the repeatability limit of the location of Kmax was 0.82 mm and 0.80 mm for axial and instantaneous curvature, respectively.

CONCLUSIONS

Instantaneous curvature zone averages centered on Kmax yielded a greater improvement in repeatability than axial zone averages and reached clinical adequacy with radii of at least 1.5 mm, for eyes with Kmax ≤50 D, and with a 2.0 mm radius for eyes with Kmax >50 D.

Determining Progression in Ectatic Corneal Disease

Before the advent of modern tomographic imaging and corneal cross-linking (CXL), diagnosis and treatment of ectatic disease were limited to disease severity where changes on the anterior corneal surface lead to visual complaints. Rigid contact lenses and/or penetrating keratoplasty addressed late stage disease, as identifying early or subclinical disease was not possible, or its need appreciated. The emergence of CXL as a viable treatment to alter the natural progression of keratoconus heightened the need for improved diagnostics.Several methods have been described in the literature to evaluate and document progression in keratoconus, but there has been no consistent definition of ectasia progression. Newer imaging techniques (ie, tomography) allowed the detection of earlier ectatic disease, before visual loss and subjective complaints. The Belin ABCD classification/staging system was introduced on a Scheimpflug imaging system [Pentacam, (Oculus GmbH, Wetzlar, Germany)] to address previous shortcomings. The ABCD system utilizes 4 parameters: Anterior ("A") and posterior ("B" for Back) radius of curvature taken from a 3.0 mm optical zone centered on the thinnest point, "C" is minimal Corneal thickness, and "D" best spectacle Distance visual acuity. The first 3 parameters (A, B, C) are machine-generated objective measurements that can be used to determine progressive change.The staging system is not limited to a specific commercial entity and can be incorporated in any tomographic imaging system. The ABCD Progression Display graphically displays each parameter and shows when statistical change above measurement noise is reached. This should allow the clinician the ability to diagnose progressive disease at a much earlier stage than was previously possible, with the confidence that earlier intervention could prevent visual loss.

Long-Term Visual, Refractive and Topographic Outcomes of "Epi-off" Corneal Collagen Cross-Linking in Pediatric Keratoconus: Standard versus Accelerated Protocol

PURPOSE

To compare the visual, refractive and topographic outcomes of standard and accelerated corneal collagen cross-linking (CXL) in pediatric keratoconus patients.

METHODS

Prospective, comparative observational study on 68 eyes of 35 pediatric keratoconus patients (<18 years). Patients were classified into two groups, group (I) included 34 eyes and received standard "Epi-Off" CXL (3 mW/cm², 30 min.) and group (II) included 34 eyes and received accelerated "Epi-Off" CXL (9 mW/cm², 10 min.). Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), spherical equivalent (SE), simulated keratometry (Sim K-1, Sim K-2, K-max, K-mean), cylindrical (CYL), pachymetry and Q-value were evaluated preoperatively and for 3 years postoperatively.

RESULTS

Postoperative UDVA and CDVA did not significantly change in both groups after 3 years. Postoperative SE was increased significantly in accelerated CXL (p=0.012) with no significant change in the postoperative cylinder in both procedures. Standard CXL had greater "significant" effect in decreasing Sim K-1, K-max and K-mean. The mean reduction in postoperative corneal pachymetry (at thinnest location) was significant in standard CXL (18.4 μm) (p=0.001). No significant change was noticed in postoperative Q-value.

CONCLUSION

Standard and accelerated CXL protocols are efficient in pediatric keratoconus management with better outcomes in the standard procedure.

Characterization of cone size and centre in keratoconic corneas

A novel method to locate the centre of keratoconus (KC) and the transition zone between the pathological area and the rest of the corneal tissue is proposed in this study. A spherical coordinate system was used to generate a spherical height map measured relative to the centre of the optimal sphere fit, and normal to the surface. The cone centre was defined as the point with the maximum height. Second derivatives of spherical height were then used to estimate the area of pathology in an iterative process. There was mirror symmetry between cone centre locations in both eyes. The mean distance between cone centre and corneal apex was 1.45 ± 0.25 mm (0.07-2.00), the mean cone height normal to the surface was 37 ± 23 µm (2-129) and 75 ± 45 µm (5-243) in the anterior and posterior surfaces, respectively. There was a significant negative correlation between the cone height and the radius of the sphere of optimal fit (p < 0.05 for both anterior and posterior surfaces). On average, posterior cone height was larger than the corresponding anterior cone height by 37 ± 24 µm (0-158). The novel method proposed can be used to estimate the cone centre and area, and explore the changes in anterior and posterior corneal surfaces that take place with KC progression. It can help improve understanding of keratoconic corneal morphology and assist in developing customized treatments.

Classification of Keratoconus Based on Anterior Corneal High-order Aberrations: A Cross-validation Study

SIGNIFICANCE

Placido disc-based videokeratography is one of the most extensively used methods for corneal topographic assessments in keratoconus. Anterior corneal wavefront analysis has been demonstrated to be an effective tool to manage keratoconus eyes. However, currently, there is no clinically adequate classification system for keratoconus.

PURPOSE

The aim of this study was to analyze the usefulness of anterior corneal high-order aberrations in keratoconus classification provided by Placido disc-based videokeratography conducting a cross-validation analysis.

METHODS

Corneal topography of 70 normal and 77 keratoconic eyes (divided according to the Amsler-Krumeich classification [n = 21, stage 1; n = 30, stage 2; and n = 26, stage 3]) was assessed using Placido disc-based videokeratography (Oculus Keratograph [Oculus Optikgeräte GmbH, Wetzlar, Germany]). Receiver operating characteristic curve analysis was used to compare the mean values of coma, trefoil, tetrafoil, secondary astigmatism, spherical aberration, and coma-like, third-, and fourth-order root mean square (RMS) to calculate cutoff values, sensitivity, and specificity to discriminate between normal and stage 1 keratoconus eyes and between each keratoconus stage after cross-validation analysis.

RESULTS

All wavefront aberrations were significantly different between the normal and keratoconus groups (P ≤ .01). The coma and third-order RMS values (cutoff values, 0.367 and 0.359 μm, respectively) provide better sensitivity (99 and 100%, respectively) and specificity (100%) to discriminate keratoconus (stage 1) from healthy eyes compared with trefoil, tetrafoil, secondary astigmatism, spherical aberration, and coma-like and fourth-order RMS values (sensitivity >84% and specificity >57%). The coma and third-order RMS values showed the highest specificity (100%) and great sensitivity (90 and 87%, respectively) to differentiate between stages 1 and 2 and good sensitivity (97 and 100%) and specificity (81 and 88%) to differentiate between stages 2 and 3.

CONCLUSIONS

Anterior corneal high-order aberrations, specifically coma and third-order RMS, could be useful in keratoconus diagnosis and topographical classification. These new cutoff values could improve different stages of keratoconus eyes discrimination.

Keratoconus after 40 years of age: a longitudinal comparative population-based study

PURPOSE

To determine 5-year changes in keratoconus indices and corrected distance visual acuity in 40-64-year-old keratoconus compared with normal subjects.

METHODS

In this prospective population-based cohort study, 5-year changes in Belin grading system indices including the average radii of curvature in the 3 mm zone surrounding the thinnest point in the anterior (ARC-3 mm) and posterior (PRC-3 mm) cornea, corrected distance visual acuity, minimum corneal thickness, maximum Ambrosio's relational thickness (ART-max), and maximum anterior keratometry indices centered on steepest point in the central 3 mm (Kmax-3 mm), 4 mm (Kmax-4 mm), and 5 mm (Kmax-5 mm) zones were compared between keratoconus and normal participants. In the analysis, comparisons were made between all keratoconus eyes and the right eyes of normal participants.

RESULTS

The mean age in the keratoconus (n = 16 eyes) and normal (n = 1986 eyes) groups (48.31 ± 4.78, 49.37 ± 5.79 years, respectively) was not statistically different (P = 0.327). The two groups differed in terms of changes in PRC-3 mm (- 0.07 ± 0.15 vs. + 0.001 ± 0.14 mm, respectively, P = 0.042) and ART-max (- 6.28 ± 25.19 vs. + 15.8 ± 72.7 μm, respectively, P = 0.003). There were significant correlations between the reduction in PRC-3 mm and its baseline value (β = - 0.20, P < 0.001) and keratoconus (β = - 0.26, P < 0.001). The reduction in ART-max significantly correlated with its baseline value (β = - 0.43, P < 0.001) and keratoconus (β = - 111.74, P < 0.001).

CONCLUSION

According to these findings, posterior corneal steepening and thinning in keratoconus patients continue after the age of 40 years, but it is clinically negligible. The changes are independent of normal age-related changes and appear to be slower in cases with steeper and thinner corneas.

Corneal Ectasia Risk And Percentage Tissue Altered In Myopic Patients Presenting For Refractive Surgery

Purpose

A percentage tissue altered (PTA) score of ≥40% has been advocated as an independent indicator of post-operative ectasia risk following laser in-situ keratomileusis (LASIK). This study was performed to test the hypothesis that refractive procedures, such as laser-assisted sub-epithelial keratectomy (LASEK) or small incision lenticule extraction (SMILE), may alter the range of PTA, within which refractive corneal surgery can be safely performed.

Setting

Refractive department, tertiary ophthalmic hospital.

Design

Retrospective observational study.

Methods

Review of case notes was performed for patients who presented for refractive surgeries, other than LASIK. To determine the risk of corneal ectasia for each patient prior to refractive surgery, we estimated what each patient’s PTA would have been if they had undergone LASIK. The Randleman Ectasia Risk Score System (ERSS) was also calculated.

Results

114 eyes (66 patients) were included. 94 eyes underwent SMILE. 20 eyes underwent LASEK. A significant proportion of eyes had PTA ≥40% – SMILE eyes: up to 31.9%, LASEK eyes: up to 60.0% (at presumed LASIK flap of 120 μm). The maximum calculated PTA was up to 47.9% in the SMILE group and up to 51.5% in the LASEK group. Using ERSS, 12.8–16% of SMILE eyes and 15.0–80.0% of LASEK eyes would have been considered to have moderate-to-high ectasia risk. No post-surgical ectasia was observed at 3 years.

Conclusion

SMILE and LASEK alter the range of PTA, within which corneal refractive surgery may be performed with a lower risk of developing post-operative corneal ectasia; a safe PTA threshold needs to be determined for these procedures before recommendations for clinical practice can be made.

Longitudinal corneal tomographical changes in eyes of patients with unilateral and bilateral non-progressive keratoconus

AIM

To evaluate the tomographic indices changes in keratoconic eyes which were classified as unilateral and bilateral non-progressive keratoconus according to the definition of Global Consensus on keratoconus and ectatic disease.

METHODS

Fifty non-progressive fellow eyes of 50 keratoconus patients who underwent corneal cross-linking treatment for the other progressive eyes (group 1), 50 eyes of 50 keratoconus patients who were followed up as bilateral non-progressive keratoconus (group 2), and 50 eyes of 50 control subjects (group 3) were included in this retrospective study. Topographic, topometric, and Belin-Ambrósio Enhanced Ectasia Display-III indices were recorded at baseline and after six months.

RESULTS

Groups were similar in terms of age and gender. The changes in topographic parameters and topometric indices were similar among the three groups (p > 0.05 for all values). The maximum pachymetric progression index (PPI_max), maximum Ambrósio relational thickness (ART_max), and final D significantly increased at sixth-months in group 1 (p < 0.001, p = 0.004, and p = 0.02 respectively) but did not change in groups 2 and 3 (p > 0.05 for all values). ART_max, PPI_max, and final D value changes indicated a statistically significant difference among the groups using the one-way ANOVA test (p = 0.03, p = 0.007, and p = 0.03 respectively). The Bonferroni posttest revealed that these values increased at a higher rate in group 1 than in group 2 (p = 0.03, p = 0.01, and p = 0.04 respectively) and group 3 (p = 0.04, p = 0.03, and p = 0.04, respectively).

CONCLUSIONS

Fellow eyes of keratoconus patients who have underwent CXL for their progressive eyes may be more prone to progress than the patients who have no progression in both eyes. Screening unilateral non-progressive patients more closely than those with bilateral non-progressive patients and evaluating the changes in final D, ART_max, and PPI_max values may be helpful in the follow up of non-progressive keratoconus.

Genetic Aspects of Keratoconus: A Literature Review Exploring Potential Genetic Contributions and Possible Genetic Relationships with Comorbidities

Introduction

Keratoconus (KC) is a complex, genetically heterogeneous, multifactorial degenerative disorder that is accompanied by corneal ectasia which usually progresses asymmetrically. With an incidence of approximately 1 per 2000 and 2 cases per 100,000 population presenting annually, KC follows an autosomal recessive or dominant pattern of inheritance and is, apparently, associated with genes that interact with environmental, genetic, and/or other factors. This is an important consideration in refractive surgery in the case of familial KC, given the association of KC with other genetic disorders and the imbalance between dizygotic twins. The present review attempts to identify the genetic loci contributing to the different KC clinical presentations and relate them to the common genetically determined comorbidities associated with KC.

Methods

The PubMed, MEDLINE, Google Scholar, and GeneCards databases were screened for KC-related articles published in English between January 2006 and November 2017. Keyword combinations of “keratoconus,” “risk factor(s),” “genetics,” “genes,” “genetic association(s),” and “cornea” were used. In total, 217 articles were retrieved and analyzed, with greater weight placed on the more recent literature. Further bibliographic research based on the 217 articles revealed another 124 relevant articles that were included in this review. Using the reviewed literature, an attempt was made to correlate genes and genetic risk factors with KC characteristics and genetically related comorbidities associated with KC based on genome-wide association studies, family-based linkage analysis, and candidate-gene approaches.

Results

An association matrix between known KC-related genes and KC symptoms and/or clinical signs together with an association matrix between identified KC genes and genetically related KC comorbidities/syndromes were constructed.

Conclusion

Twenty-four genes were identified as potential contributors to KC and 49 KC-related comorbidities/syndromes were found. More than 85% of the known KC-related genes are involved in glaucoma, Down syndrome, connective tissue disorders, endothelial dystrophy, posterior polymorphous corneal dystrophy, and cataract.

Modified wavelength scanning interferometry for simultaneous tomography and topography of the cornea with Fourier domain optical coherence tomography

Visual acuity is dependent on corneal shape and size. A minor variation in surface geometry can cause a deformation of corneal geometry, which affects its optical performance. In this work we demonstrate an algorithm for the simultaneous measurement of corneal tomography and topography with a traditional point-scanning Fourier domain optical coherence tomography (FD-OCT) system. A modified wavelength scanning interferometry (mWSI) algorithm enabled topographical evaluation of the surface with nanometer-scale resolution, which is superior to the micrometer-scale resolution of traditional OCT structural imaging. We validated the technique with an optically flat mirror, standard roughness gauges, and atomic force microscopy (AFM). The mirror results show nanometer-scale sensitivity (~3.5 nm), and the mWSI measurements were in good agreement (error ~5%) with the specifications of the roughness comparator and AFM, demonstrating the accuracy of the technique. Following validation, the measurements were made on pig corneas in situ at various artificially controlled intraocular pressures (IOP) and before and after cross-linking (CXL). The results show that the mean surface roughness increased by ~65% after removal of the epithelium in preparation for CXL but did not change as a function of IOP. The demonstrated method could be used for simultaneous measurement of tissue tomography with micrometer-precision and topography with nanometer-precision.

Quantifying the effects of hydration on corneal stiffness with noncontact optical coherence elastography

PURPOSE

To quantify the effects of the hydration state on the Young's modulus of the cornea.

SETTING

Biomedical Optics Laboratory, University of Houston, Houston, Texas, USA.

DESIGN

Experimental study.

METHODS

Noncontact, dynamic optical coherence elastography (OCE) measurements were taken of in situ rabbit corneas in the whole eye-globe configuration (n = 10) and at an artificially controlled intraocular pressure of 15 mm Hg. Baseline OCE measurements were taken by topically hydrating the corneas with saline for 1 hour. The corneas were then dehydrated topically with a 20% dextran solution for another hour, and the OCE measurements were repeated. A finite element method was used to quantify the Young's modulus of the corneas based on the OCE measurements.

RESULTS

The thickness of the corneas shrank considerably after topical addition of the 20% dextran solution (∼680 μm to ∼370 μm), and the OCE-measured elastic-wave speed correspondingly decreased (∼3.2 m/s to ∼2.6 m/s). The finite element method results showed an increase in Young's modulus (500 kPa to 800 kPa) resulting from dehydration and subsequent thinning.

CONCLUSION

Young's modulus increased significantly as the corneas dehydrated and thinned, showing that corneal geometry and hydration state are critical factors for accurately quantifying corneal biomechanical properties.

Repeatability of a Commercially Available Adaptive Optics Visual Simulator and Aberrometer in Normal and Keratoconic Eyes

PURPOSE

To evaluate the repeatability of aberration measurement obtained by a Hartmann-Shack aberrometer combined with a visual adaptive optics simulator in normal and keratoconic eyes.

METHODS

One hundred fifteen normal eyes and 92 eyes with grade I and II keratoconus, as per the Amsler-Krumeich classification, were included in the study. To evaluate the repeatability, three consecutive measurements of ocular aberrations were obtained by a single operator. Zernike analyses up to the 5th order for a pupil size of 4.5 mm were performed. Statistical analyses included the intraclass correlation coefficient (ICC) and within-subject standard deviation (SD).

RESULTS

For intrasession repeatability, the ICC value for sphere and cylinder was 0.94 and 0.93 in normal eyes and 0.98 and 0.97 in keratoconic eyes, respectively. The ICC for root mean square of higher order aberrations (HOA_RMS) was 0.82 in normal and 0.98 in keratoconic eyes. For 3rd order aberrations (trefoil and coma), the ICC values were greater than 0.87 for normal eyes and greater than 0.92 for keratoconic eyes. The ICC for spherical aberration was 0.92 and 0.90 in normal and keratoconic eyes, respectively.

CONCLUSIONS

Visual adaptive optics provided repeatable aberrometry data in both normal and keratoconic eyes. For most of the parameters, the repeatability in eyes with early keratoconus was somewhat better than that for normal eyes. The repeatability of the Zernike terms was acceptable for 3rd order (trefoil and coma) and spherical aberrations. Therefore, visual adaptive optics was a suitable tool to perform repeatable aberrometric measurements. [J Refract Surg. 2017;33(11):769-772.].

Validation of an Objective Keratoconus Detection System Implemented in a Scheimpflug Tomographer and Comparison With Other Methods

PURPOSE

To validate a recently developed program for automatic and objective keratoconus detection (Keratoconus Assistant [KA]) by applying it to a new population and comparing it with other methods described in the literature.

METHODS

KA uses machine learning and 25 Pentacam-derived parameters to classify eyes into subgroups, such as keratoconus, keratoconus suspect, postrefractive surgery, and normal eyes. To validate this program, it was applied to 131 eyes diagnosed separately by experienced corneal specialists from 2 different centers (Fondation Rothschild, Paris, and Antwerp University Hospital [UZA]). The agreement of the KA classification with 7 other indices from the literature was assessed using interrater reliability and confusion matrices. The agreement of the 2 clinical classifications was also assessed.

RESULTS

For keratoconus, KA agreed in 92.6% of cases with the clinical diagnosis by UZA and in 98.0% of cases with the diagnosis by Rothschild. In keratoconus suspect and forme fruste detection, KA agreed in 65.2% (UZA) and 100% (Rothschild) of cases with the clinical assessments. This corresponds with a moderate agreement with a clinical assessment (κ = 0.594 and κ = 0.563 for Rothschild and UZA, respectively). The agreement with the other classification methods ranged from moderate (κ = 0.432; Score) to low (κ = 0.158; KISA%). Both clinical assessments agreed substantially (κ = 0.759) with each other.

CONCLUSIONS

KA is effective at detecting early keratoconus and agrees with trained clinical judgment. As keratoconus detection depends on the method used, we recommend using multiple methods side by side.

Characteristic of entire corneal topography and tomography for the detection of sub-clinical keratoconus with Zernike polynomials using Pentacam

The study aimed to characterize the entire corneal topography and tomography for the detection of sub-clinical keratoconus (KC) with a Zernike application method. Normal subjects (n = 147; 147 eyes), sub-clinical KC patients (n = 77; 77 eyes), and KC patients (n = 139; 139 eyes) were imaged with the Pentacam HR system. The entire corneal data of pachymetry and elevation of both the anterior and posterior surfaces were exported from the Pentacam HR software. Zernike polynomials fitting was used to quantify the 3D distribution of the corneal thickness and surface elevation. The root mean square (RMS) values for each order and the total high-order irregularity were calculated. Multimeric discriminant functions combined with individual indices were built using linear step discriminant analysis. Receiver operating characteristic curves determined the diagnostic accuracy (area under the curve, AUC). The 3rd-order RMS of the posterior surface (AUC: 0.928) obtained the highest discriminating capability in sub-clinical KC eyes. The multimeric function, which consisted of the Zernike fitting indices of corneal posterior elevation, showed the highest discriminant ability (AUC: 0.951). Indices generated from the elevation of posterior surface and thickness measurements over the entire cornea using the Zernike method based on the Pentacam HR system were able to identify very early KC.

Keratoconus Detection Based on a New Corneal Volumetric Analysis

There are numerous tomographic indices for the detection of keratoconus risk. When the indexes based on corneal volume are analyzed, two problems are presented: on the one hand, they are not very sensitive to the detection of incipient cases of keratoconus because they are not locally defined in the primary developmental region of the structural abnormalities; and on the other hand, they do not register the geometric decompensation driven by the asymmetry present during the disease progression. This work performed a morphogeometric modeling of the cornea by the aid of CAD tools and using raw topographic data (Sirius system, CSO, Firenze). For this method, four singular points present on the corneal surfaces were located and the following parameters based on corneal volume were calculated: VOL_mct, defined by the points of minimal thickness; VOL_aap, defined by the anterior corneal apex, and VOL_pap, defined by the posterior corneal apex. The results demonstrate that a further reduction of corneal volume in keratoconus happens and significantly progresses along the disease severity level. The combination of optical and volumetric data, that collect the sensitivity of the asymmetry generated by the disease, allows an accurate detection of incipient cases and follow up of the disease progression.

A new approach to keratoconus detection based on corneal morphogeometric analysis

Purpose

To characterize corneal structural changes in keratoconus using a new morphogeometric approach and to evaluate its potential diagnostic ability.

Methods

Comparative study including 464 eyes of 464 patients (age, 16 and 72 years) divided into two groups: control group (143 healthy eyes) and keratoconus group (321 keratoconus eyes). Topographic information (Sirius, CSO, Italy) was processed with SolidWorks v2012 and a solid model representing the geometry of each cornea was generated. The following parameters were defined: anterior (A_ant) and posterior (A_post) corneal surface areas, area of the cornea within the sagittal plane passing through the Z axis and the apex (A_apexant, A_apexpost) and minimum thickness points (A_mctant, A_mctpost) of the anterior and posterior corneal surfaces, and average distance from the Z axis to the apex (D_apexant, D_apexpost) and minimum thickness points (D_mctant, D_mctpost) of both corneal surfaces.

Results

Significant differences among control and keratoconus group were found in A_apexant, A_apexpost, A_mctant, A_mctpost, D_apexant, D_apexpost (all p<0.001), A_post (p = 0.014), and D_mctpost (p = 0.035). Significant correlations in keratoconus group were found between A_ant and A_post (r = 0.836), A_mctant and A_mctpost (r = 0.983), and D_mctant and D_mctpost (r = 0.954, all p<0.001). A logistic regression analysis revealed that the detection of keratoconus grade I (Amsler Krumeich) was related to A_post, A_tot, A_apexant, A_mctant, A_mctpost, D_apexpost, D_mctant and D_mctpost (Hosmer-Lemeshow: p>0.05, R² Nagelkerke: 0.926). The overall percentage of cases correctly classified by the model was 97.30%.

Conclusions

Our morphogeometric approach based on the analysis of the cornea as a solid is useful for the characterization and detection of keratoconus.

Assessing Progression of Keratoconus and Cross-linking Efficacy: The Belin ABCD Progression Display

Several methods have been described to both evaluate and document progression in keratoconus and to show efficacy of cross-linking, however, there are no consistent generally accepted parameters. Modern corneal tomography, including both anterior and posterior elevation and pachymetric data can be used to screen for ectatic progression, be employed to detect earlier change and additionally to show efficacy of new treatment modalities, such as crosslinking.

To describe specific quantitative values that can be used as progression and efficacy determinants, the normal noise measurements of the three parameters used in the ABCD keratoconus classification (corneal thickness at the thinnest point, anterior and posterior radius of curvature taken from the 3.0 mm optical zone centered on the thinnest point), were determined. Values were obtained from both a normal population and a known keratoconic population. The 80 and 95% one-sided confidence intervals for all three parameters were surprisingly small, suggesting that they may perform well as progression and efficacy determinants.

How to cite this article

Belin MW, Meyer JJ, Duncan JK, Gelman R, Borgstrom M, Ambrósio Jr R. Assessing Progression of Keratoconus and Cross-linking Efficacy: The Belin ABCD Progression Display. Int J Kerat Ect Cor Dis 2017;6(1):1-10.

A review of keratoconus: Diagnosis, pathophysiology, and genetics

We discuss new approaches to the early detection of keratoconus and recent investigations regarding the nature of its pathophysiology. We review the current evidence for its complex genetics and evaluate the presently identified genes/loci and potential candidate gene/loci. In addition, we highlight current research methodologies that may be used to further elucidate the pathogenesis of keratoconus.

Application of high resolution OCT to evaluate irregularity of Bowman's layer in asymmetric keratoconus

Irregularity of the Bowman's layer (BL) in keratoconus (KC, sample size (n) = 28) and forme fruste keratoconus (FFKC, n = 18) eyes was evaluated. Subjects underwent high resolution OCT imaging (Bioptigen Inc., USA) and corneal tomography (Pentacam v1.20r41, OCULUS Optikgeräte GmbH, Germany). Anterior edge of the BL was segmented. A Bowman's roughness index (BRI) was defined as the sum of the enclosed areas between segmented edge and a smooth 3^rd order polynomial fit to the edge. BRI was compared with corneal aberrations, Keratoconus percentage index (KISA), Cone location magnitude index (CLMI) and Belin-Ambrosio enhanced ectasia display overall deviation index (BAD-D). Area under the curve (AUC) was determined with logistic regression (LR). Mean BRI (×10^-3 ) was 2.12 mm² , 1.81 mm² and 1.7 mm² in normal (n = 26), FFKC and KC eyes, respectively (p < 0.001). BAD-D (0.79) and BRI (0.74) had the best AUC for FFKC. By combining BAD-D and BRI, the AUC improved to 0.85 (p = 0.01). For KC eyes, KISA (0.94), CLMI (0.88), BAD-D (0.96) and aberrations had comparable AUC (p > 0.05). However, LR with BRI and other indices didn't improve the AUC in KC eyes (p > 0.05). BRI was significantly reduced in FFKC and KC eyes. It improved the detection of FFKC but not KC eyes.

Accelerated corneal collagen cross-linking in pediatric keratoconus: One year study

PURPOSE

To evaluate the safety and effectiveness of accelerated corneal collagen crosslinking (CXL) in pediatric keratoconus.

DESIGN

Prospective non-randomized observational study.

METHODS

33 eyes of 25 children with keratoconus were included. The corneal epithelium was mechanically removed. Next, riboflavin/hydroxypropyl methylcellulose solution) was applied for 10 min. Accelerated CXL (10 mW/cm2 for 9 min), was accomplished. Visual acuity, slit lamp examination, refraction, keratometry readings, pachymetry, anterior and posterior elevations, average progression indices, and Q values were recorded. The follow-up visits were scheduled on one day, 3 days, 7 days, one month and then on 3, 6, 12 months after the procedure.

RESULTS

It was statistically significant improvement of the mean UAVA, AVA, and the mean corneal astigmatism (P < .0001). The mean corneal thickness showed a significant reduction. The preoperative mean K max reading was reduced from 49.12 ± 3.7 D preoperatively to 47.9 ± 3.7 D at 12 months. The mean max anterior elevation, average progression index and Q value showed statistically significant improvement. No significant impact on posterior elevation was recorded. Serious complications were not encountered in this study.

CONCLUSION

Accelerated CXL shows a stabilization and beneficial clinical outcomes in pediatric keratoconus. It seems an effective and safe procedure in this age group. Effects of accelerated CXL on the posterior corneal surface will need further evaluation.

Detection of Keratoconus in Clinically and Algorithmically Topographically Normal Fellow Eyes Using Epithelial Thickness Analysis

PURPOSE

To assess the effectiveness of a keratoconus-detection algorithm derived from Artemis very high-frequency (VHF) digital ultrasound (ArcScan Inc., Morrison, CO) epithelial thickness maps in the fellow eye from a series of patients with unilateral keratoconus.

METHODS

The study included 10 patients with moderate to advanced keratoconus in one eye but a clinically and algorithmically topographically normal fellow eye. VHF digital ultrasound epithelial thickness data were acquired and a previously developed classification model was applied for identification of keratoconus to the clinically normal fellow eyes. Pentacam (Oculus Optikgeräte, Wetzlar, Germany) Belin-Ambrósio Enhanced Ectasia Display "D" score (BAD-D) data (5 of 10 eyes), and Orbscan (Bausch & Lomb, Rochester, NY) SCORE data (9 of 10 eyes) were also evaluated.

RESULTS

Five of the 10 fellow eyes were classified as keratoconic by the VHF digital ultrasound epithelium model. Five of 9 fellow eyes were classified as keratoconic by the SCORE model. For the 5 fellow eyes with Pentacam and VHF digital ultrasound data, one was classified as keratoconic by the VHF digital ultrasound model, one (different) eye by a combined VHF digital ultrasound and Pentacam model, and none by BAD-D alone.

CONCLUSIONS

Under the assumption that keratoconus is a bilateral but asymmetric disease, half of the 'normal' fellow eyes could be found to have keratoconus using epithelial thickness maps. The Orbscan SCORE or the combination of topographic BAD-D criteria with epithelial maps did not perform better.

Assessing progression of keratoconus: novel tomographic determinants

Several methods have been described in the literature to both evaluate and document progression in keratoconus, but there is no consistent or clear definition of ectasia progression. The authors describe how modern corneal tomography, including both anterior and posterior elevation and pachymetric data can be used to screen for ectatic progression, and how software programs such as the Enhanced Reference Surface and the Belin-Ambrosio Enhanced Ectasia Display (BAD) can be employed to detect earlier changes. Additionally, in order to describe specific quantitative values that can be used as progression determinants, the normal noise measurement of the three parameters (corneal thickness at the thinnest point, anterior and posterior radius of curvature (ARC, PRC) taken from the 3.0 mm optical zone centered on the thinnest point), was assessed. These values were obtained by imaging five normal patients using three different technicians on three separate days. The 95 % and 80 % one-sided confidence intervals for all three parameters were surprisingly small (7.88/4.03 μm for corneal thickness, 0.024/0.012 mm for ARC, and 0.083/0.042 mm for PRC), suggesting that they may perform well as progression determinants.

A novel zernike application to differentiate between three-dimensional corneal thickness of normal corneas and corneas with keratoconus

PURPOSE

To evaluate a novel Zernike algorithm to differentiate 3-dimensional (3-D) corneal thickness distribution of corneas with keratoconus (KC) from normal corneas.

DESIGN

A retrospective development and evaluation of a diagnostic approach.

METHODS

Corneal tomography with Scheimpflug imaging was performed in normal (43 eyes) and KC (85 eyes) corneas. Axial and tangential cone location magnitude index (axial CLMI and tangential CLMI, respectively) of the anterior and posterior surface were calculated. The aberrations of the anterior corneal surface were analyzed with Zernike polynomials. Pachymetric Zernike analyses (PZA) were used to map the 3-D thickness distribution of the cornea. Logistic regression was performed to develop a diagnostic procedure for KC using CLMI, PZA, and aberrations. A receiver operating characteristic curve was constructed for each regression model. Corneal volume was also compared between normal and KC corneas. Only the central 5 mm zone was used for all analyses.

RESULTS

Among the PZA coefficients, second- and third-order root mean squares of PZA coefficients were the best predictors of KC corneas (P < .0001). Among the CLMI variables, axial CLMI of anterior and tangential CLMI of posterior surface were the best predictors of KC (P < .0001). Among the Zernike corneal aberration coefficients, second- and third-order root mean squares of coefficients were the best predictors of KC (P < .0001). Sensitivity and specificity of Zernike corneal aberrations, CLMI, and PZA logistic regression model were similar (P > .05).

CONCLUSIONS

The entire 3-D corneal thickness was mapped with Zernike. The PZA method was comparable to CLMI and anterior corneal wavefront aberrations in detecting KC.