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Early detection of keratoconus will provide more treatment choices, avoid heavy treatments, and help stop the rapid progression of the disease. This study presents a machine learning-based keratoconus classification approach, using transfer learning, applied on corneal topographic images. Classi- fication is performed considering the three corneal classes namely: normal, suspicious and keratoconus. Keratoconus classification is carried out using transfer learning, by the adoption of six different pretrained convolutional neural networks (CNN) VGG16, InceptionV3, MobileNet, DenseNet201, Xception and EfficientNetB0, which already have knowledge from solving previous specific problems. Each of these different classifiers is trained individually on five different datasets, generated from an original dataset of 2924 corneal topographic images. Original corneal topographic images have been subjected to a special preprocessing before their use by different models in the learning phase. Images of corneal maps are separated in five different datasets while removing noise and textual annotation from images. Most of models used in the classification allow good discrimination between normal cornea, suspicious and keratoconus one. Obtained results reached classification accuracy of 99.31% and 98.51% by DenseNet201 and VGG16 respectively. Obtained results indicate that transfer learning technique could well improve performance of keratoconus classification systems. [ABSTRACT FROM AUTHOR]

Purpose: To determine the misclassification rate of the keratoconus percentage (KISA%) index efficacy in eyes with progressive keratoconus., Methods: This was a retrospective case-control study of consecutive patients with confirmed progressive keratoconus and a contemporaneous normal control group with 1.00 diopters or greater regular astigmatism. Scheimpflug imaging (Pentacam HR) was obtained for all patients. KISA% index and inferior-superior (IS) values were obtained from the Pentacam topometric/keratoconus staging map. Receiver operating characteristic curves were generated to determine the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity values., Results: There were 160 eyes from 160 patients evaluated, including 80 eyes from 80 patients with progressive keratoconus and 80 eyes from 80 control patients. There were 20 eyes (25%) with progressive keratoconus misclassified by the KISA% index, with 16 eyes (20%) of the progressive keratoconus cohort classified as normal (ie, KISA% < 60). There were 4 eyes (5%) with progressive keratoconus that would classify as having "normal topography" using the published criteria for very asymmetric ectasia with normal topography of KISA% less than 60 and IS value less than 1.45. All controls had a KISA% index value of less than 15. The optimal cut-off value to distinguish cohorts was 15.31 (AUROC = 0.972, 93.75% sensitivity). KISA% index values of 60 and 100 achieved low sensitivity (80% and 73.75%, respectively)., Conclusions: The KISA% index misclassified a significant proportion of eyes with progressive keratoconus as normal. Although highly specific for clinical keratoconus, the KISA% index lacks sensitivity, does not effectively discriminate between normal and abnormal topography, and thus should not be used in large data analysis or artificial intelligence-based modeling. [ J Refract Surg . 2024;40(9):e614-e624.] .

Objective: Our objective is to develop a novel keratoconus image classification system that leverages multiple pretrained models and a transformer architecture to achieve state-of-the-art performance in detecting keratoconus., Methods and Analysis: Three pretrained models were used to extract features from the input images. These models have been trained on large datasets and have demonstrated strong performance in various computer vision tasks.The extracted features from the three pretrained models were fused using a feature fusion technique. This fusion aimed to combine the strengths of each model and capture a more comprehensive representation of the input images. The fused features were then used as input to a vision transformer, a powerful architecture that has shown excellent performance in image classification tasks. The vision transformer learnt to classify the input images as either indicative of keratoconus or not.The proposed method was applied to the Shahroud Cohort Eye collection and keratoconus detection dataset. The performance of the model was evaluated using standard evaluation metrics such as accuracy, precision, recall and F1 score., Results: The research results demonstrated that the proposed model achieved higher accuracy compared with using each model individually., Conclusion: The findings of this study suggest that the proposed approach can significantly improve the accuracy of image classification models for keratoconus detection. This approach can serve as an effective decision support system alongside physicians, aiding in the diagnosis of keratoconus and potentially reducing the need for invasive procedures such as corneal transplantation in severe cases., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the early stages of the disease because the patient does not feel any pain. Therefore, the development of a method for detecting this disease based on machine and deep learning methods is necessary for early detection in order to provide the appropriate treatment as early as possible to patients. Thus, the objective of this work is to determine the most relevant parameters with respect to the different classifiers used for keratoconus classification based on the keratoconus dataset of Harvard Dataverse. A total of 446 parameters are analyzed out of 3162 observations by 11 different feature selection algorithms. Obtained results showed that sequential forward selection (SFS) method provided a subset of 10 most relevant variables, thus, generating the highest classification performance by the application of random forest (RF) classifier, with an accuracy of 98% and 95% considering 2 and 4 keratoconus classes, respectively. Found classification accuracy applying RF classifier on the selected variables using SFS method achieves the accuracy obtained using all features of the original dataset., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2021 Mustapha Aatila et al.)

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., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Background: This retrospective cross-sectional study aims to analyse the keratoconus (KC) stage distribution at different ages within the Homburg Keratoconus Center (HKC)., Methods: 1917 corneae (1000 patients) were allocated to decades of age, classified according to Belin's ABCD KC grading system and the stage distribution was analysed., Results: 73 per cent (n=728) of the patients were males, 27% (n=272) were females. The highest KC prevalence occurred between 21 and 30 years (n=585 corneae, 294 patients). Regarding anterior (A) and posterior (B) curvature, the frequency of A was significantly higher than B in all age groups for stage 0, 1 and 2 (A0>B0; A1>B1; A2>B2; p<0.03, Wilcoxon matched-pairs test). There was no significant difference between the number of A3 and B3, but significantly more corneae were classified as B4 than A4 in all age groups (p<0.02). The most frequent A|B combinations were A4|B4 (n=451), A0|B0 (n=311), A2|B4 (n=242), A2|B2 (n=189) and A1|B2 (n=154). Concerning thinnest pachymetry (C), most corneae in all age groups were classified as C0>C1>C2>C3>C4 (p<0.04, Wilcoxon matched-pairs test). For the best distance visual acuity (D), a significantly higher number of corneae were classified as D1 compared to D0 (p<0.008; D1>D0>D2>D3>D4)., Conclusion: The stage distributions in all age groups were similar. Early KC rather becomes manifest in the posterior than the anterior corneal curvature whereas advanced stages of posterior corneal curvature coincide with early and advanced stages of anterior corneal curvature. Thus, this study emphasises the necessity of posterior corneal surface assessment in KC as enabled by the ABCD grading system., Competing Interests: Competing interests: KX, SCG, SR, EZ, LH, TJ, UK, AL and BS declare that they do not have any financial disclosures in medicine. EF has received a travel grant to the Second and Third Ophthalmology Cystinosis Forum (Orphan Europe, Ulm, Germany) and an invitation to a seminar on presentation training organised by the Santen GmbH (Munich, Germany). TE was a member of the Institute of Experimental Ophthalmology, Saarland University Medical Center (Homburg, Germany), at the time of data collection and is now an employee of the Amiplant GmbH (Schnaittach, Germany)., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: To present the baseline data for a large cohort of patients with keratoconus enrolled in the Retrospective Digital Computer Analysis of Keratoconus Evolution (REDCAKE) study., Methods: Eight centers contributed the Scheimpflug tomographical data for 906 patients with keratoconus, 743 measured with a Pentacam and 163 with a Galilei. The stage of keratoconus at baseline, the location of the reference points, minimum pachymetry (Pmin), and maximum keratometry (Kmax) were analyzed. The intereye asymmetry was evaluated for Kmax (anterior and posterior), Pmin, and keratoconus stage. Average maps and elevation profiles were calculated for each degree of keratoconus., Results: Keratoconus was more frequently diagnosed in men (73%) than in women (27%). At baseline, 500/1155 eyes (43%) presented with moderate to severe changes in the posterior surface, whereas moderate/severe changes were only found in 252 and 63 eyes when evaluating anterior surface and pachymetry, respectively. The location of Pmin was usually inferotemporal (94% OD and 94% OS), while the location of Kmax showed more variability and significantly higher distance from apex (P < 0.05). The keratoconus presentation was chiefly asymmetric for all the parameters studied. Clear differences between stages could be identified in the maps and elevation profiles., Conclusions: The staging map set presented can be used as a graphical guidance to classify keratoconus stage. Keratoconus presented asymmetrically, and generally the posterior surface was more affected than the anterior surface or the thickness. Asymmetry is playing a role in KC detection. Although Pmin was almost invariably located inferotemporally, Kmax location showed higher variability and distance from the apex., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: To report an observation made while performing Scheimpflug densitometry analysis on the corneal region affected in keratoconus (KC) that seems to delineate the base of the cone., Methods: Scheimpflug densitometries of 20 healthy subjects and 90 patients with KC were examined. Corneal densitometry was analyzed using both "1-layer" and "2-layer" approaches. The first considers the corneal transparency layer by layer at different depths, whereas the second averages densitometry between 2 corneal layers selected by the examiner. Fixed layers, 120 μm depth, and endothelium were selected. Repeated same-day scans and longitudinal series of scans were also evaluated to see whether the findings evolved over time., Results: Eighty-eight of 90 KC cases displayed a bright area on the densitometry map that corresponded to the cone location. The area's characteristics, such as its brightness, contrast, and the presence of a delimiting arc correlated with KC severity and was more noticeable in advanced cases. No similar marks were found in any of the normal subjects. The shape, location, and extent of the mark were consistent over consecutive measures taken on the same day. Changes over time were also seen in eyes with known clinical progression but was also seen in eyes considered clinically stable., Conclusions: The densitometry mark seems to correspond with the zone most affected by KC and could be a supplementary tool for documenting KC stage, alongside conventional parameters. Further studies are required to ascertain whether it could prove useful in KC detection, to determine progression, and to relate it to corneal biomechanical behavior., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: We investigated the efficiency of a convolutional neural network applied to corneal topography raw data to classify examinations of 3 categories: normal, keratoconus (KC), and history of refractive surgery (RS)., Design: Retrospective machine-learning experimental study., Methods: A total of 3,000 Orbscan examinations (1,000 of each class) of different patients of our institution were selected for model training and validation. One hundred examinations of each class were randomly assigned to the test set. For each examination, the raw numerical data from "elevation against the anterior best fit sphere (BFS)," "elevation against the posterior BFS" "axial anterior curvature," and "pachymetry" maps were used. Each map was a square matrix of 2,500 values. The 4 maps were stacked and used as if they were 4 channels of a single image.A convolutional neural network was built and trained on the training set. Classification accuracy and class wise sensitivity and specificity were calculated for the validation set., Results: Overall classification accuracy of the validation set (n = 300) was 99.3% (98.3%-100%). Sensitivity and specificity were, respectively, 100% and 100% for KC, 100% and 99% (94.9%-100%) for normal examinations, and 98% (97.4%-100%) and 100% for RS examinations., Conclusion: Using combined corneal topography raw data with a convolutional neural network is an effective way to classify examinations and probably the most thorough way to automatically analyze corneal topography. It should be considered for other routine tasks performed on corneal topography, such as refractive surgery screening., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: To evaluate the repeatability of an extensive number of relevant indices with the Pentacam HR in keratoconus of varying severity and normal eyes., Design: Reliability analysis., Methods: This study was performed at Antwerp University Hospital, Belgium, and enrolled 20 healthy volunteers (20 eyes) and 69 patients (69 eyes) with keratoconus. Three consecutive measurements were performed by the same operator with Pentacam HR in keratoconus and normal eyes. Exclusion criteria included past ocular surgery, recent rigid contact lens wear, and corneal scarring. The keratoconus group was subdivided according to the Belin/Ambrosio total deviation value: subclinical, mild, and moderate. The within-subject standard deviation and repeatability limit were computed for repeatability assessment. The tolerance index (TI) was calculated to compare across parameters with different measurement scales. For the sample size included, TI > 0.36 signified statistical significance at the 0.05 level., Results: Repeatability in subclinical keratoconus did not differ significantly from controls (P > .05), except for wavefront aberrations. In mild keratoconus, 11 of 18 (61.1%) anterior corneal, 7 of 14 (50%) posterior corneal, 2 of 5 (40%) pachymetry, 7 of 11 (63.6%) combined, and 1 of 6 (16.7%) densitometry parameters showed significantly worse repeatability compared to controls (TI > 0.36). Repeatability of most parameters worsened in moderate disease. In particular, maximal keratometry and anterior astigmatism showed significantly worse repeatability in moderate keratoconus., Conclusions: Measurement variability of Pentacam HR is of clinical relevance when assessing for progression of keratoconus. We provide reference repeatability values and scale independent analysis of relevant corneal parameters in keratoconus of varying degrees., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Importance: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machine learning methods based on specific corneal parameters. To date, a deep learning algorithm has not been used in combination with corneal tomographic scans., Objective: To examine the use of a deep learning model in the screening of candidates for refractive surgery., Design, Setting, and Participants: A diagnostic, cross-sectional study was conducted at the Zhongshan Ophthalmic Center, Guangzhou, China, with examination dates extending from July 18, 2016, to March 29, 2019. The investigation was performed from July 2, 2018, to June 28, 2019. Participants included 1385 patients; 6465 corneal tomographic images were used to generate the artificial intelligence (AI) model. The Pentacam HR system was used for data collection., Interventions: The deidentified images were analyzed by ophthalmologists and the AI model., Main Outcomes and Measures: The performance of the AI classification system., Results: A classification system centered on the AI model Pentacam InceptionResNetV2 Screening System (PIRSS) was developed for screening potential candidates for refractive surgery. The model achieved an overall detection accuracy of 94.7% (95% CI, 93.3%-95.8%) on the validation data set. Moreover, on the independent test data set, the PIRSS model achieved an overall detection accuracy of 95% (95% CI, 88.8%-97.8%), which was comparable with that of senior ophthalmologists who are refractive surgeons (92.8%; 95% CI, 91.2%-94.4%) (P = .72). In distinguishing corneas with contraindications for refractive surgery, the PIRSS model performed better than the classifiers (95% vs 81%; P < .001) in the Pentacam HR system on an Asian patient database., Conclusions and Relevance: PIRSS appears to be useful in classifying images to provide corneal information and preliminarily identify at-risk corneas. PIRSS may provide guidance to refractive surgeons in screening candidates for refractive surgery as well as for generalized clinical application for Asian patients, but its use needs to be confirmed in other populations.

Purpose: To compare the efficacy, safety and stability of standard epithelium-off cross-linking (SCXL) versus accelerated epithelium-off cross-linking (ACXL) and transepithelial epithelium-on cross-linking (TCXL) in the treatment of progressive keratoconus (KC) in children., Methods: This prospective multicentre controlled trial included 271 eyes (136 children) with grade 1-3 progressive KC who were randomized to undergo SCXL (n = 91, as a control group), ACXL (n = 92) or TCXL (n = 88). Uncorrected and corrected distance visual acuity, subjective refraction, pachymetry, keratometry and corneal topography measurements were recorded preoperatively and 6, 12 and 24 months postoperatively., Results: At 1 year, there was no significant difference in uncorrected distance visual acuity, refractive sphere, cylinder, spherical equivalent or Kmax between the ACXL and SCXL groups; however, during year 2, ACXL regressed while SCXL continued to improve. After 2 years, there were significant differences in all visual, refractive and keratometric components between SCXL and both ACXL and TCXL (p < 0.0001) and between ACXL and TCXL (p < 0.0001). KC progressed in 5.4% of patients who had ACXL and 28.4% of those who had TCXL but in none of those who had SCXL. Vernal keratoconjunctivitis was documented in 43.3% of eyes that progressed postoperatively., Conclusion: SCXL was more effective for paediatric KC and achieved greater stability than either ACXL or TCXL, and ACXL was superior to TCXL. SCXL also achieved marked improvement in both myopia and spherical equivalent; however, these refractive outcomes were unpredictable and uncontrollable. TCXL had a 28.4% failure rate within 2 years. SCXL is preferable for management of paediatric KC., (© 2019 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

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.

Objective: To evaluate the diagnostic accuracy of keratoconus using deep learning of the colour-coded maps measured with the swept-source anterior segment optical coherence tomography (AS-OCT)., Design: A diagnostic accuracy study., Setting: A single-centre study., Participants: A total of 304 keratoconic eyes (grade 1 (108 eyes), 2 (75 eyes), 3 (42 eyes) and 4 (79 eyes)) according to the Amsler-Krumeich classification, and 239 age-matched healthy eyes., Main Outcome Measures: The diagnostic accuracy of keratoconus using deep learning of six colour-coded maps (anterior elevation, anterior curvature, posterior elevation, posterior curvature, total refractive power and pachymetry map)., Results: Deep learning of the arithmetical mean output data of these six maps showed an accuracy of 0.991 in discriminating between normal and keratoconic eyes. For single map analysis, posterior elevation map (0.993) showed the highest accuracy, followed by posterior curvature map (0.991), anterior elevation map (0.983), corneal pachymetry map (0.982), total refractive power map (0.978) and anterior curvature map (0.976), in discriminating between normal and keratoconic eyes. This deep learning also showed an accuracy of 0.874 in classifying the stage of the disease. Posterior curvature map (0.869) showed the highest accuracy, followed by corneal pachymetry map (0.845), anterior curvature map (0.836), total refractive power map (0.836), posterior elevation map (0.829) and anterior elevation map (0.820), in classifying the stage., Conclusions: Deep learning using the colour-coded maps obtained by the AS-OCT effectively discriminates keratoconus from normal corneas, and furthermore classifies the grade of the disease. It is suggested that this will become an aid for improving the diagnostic accuracy of keratoconus in daily practice., Clinical Trial Registration Number: 000034587., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: To investigate the validity and reliability of retinoscopy in screening for keratoconus using the rotating Pentacam Scheimpflug camera as the gold standard comparison., Methods: Patients between the ages of 10 and 30 years who were referred to the outpatient clinic with keratoconus, keratoconus suspect, reduced vision, eye discomfort or frequent change of glasses, or for refraction or refractive surgery, were screened by two independent and masked retinoscopists for the presence of scissoring reflex. Patients then underwent vision testing, slit lamp examination, and Pentacam imaging. A diagnosis of keratoconus by Pentacam was made if the final D index in the Belin and Ambrósio Display was ≥2.69. The results of retinoscopy and Pentacam examinations were compared to assess the validity and reliability of the test., Results: A total of 123 patients (67 male patients and 45 female patients) with a mean age of 21 years ±5.6 (range 10-30 years) comprising 245 eyes were included. There were 87 eyes with keratoconus, and using the Amsler-Krumeich classification, 67.8%, 26.4%, 2.3%, and 3.4% of the eyes had stage I, II, III, and IV, respectively. Sensitivity, specificity, positive predictive value, and negative predictive value of retinoscopy were 97.7%, 79.9%, 70.8%, and 98.4%, respectively. The area under the curve was 0.88 (95% confidence interval, 0.83-0.92). There was excellent agreement between the 2 retinoscopists (Cohen's kappa value 0.84)., Conclusions: Retinoscopy appears to be a very sensitive and reliable test for detecting keratoconus including early disease. Such a test may be implemented in population-based screening programs for keratoconus.

Purpose: To evaluate and compare the topographic and topometric parameters, thickness profile data, and data from enhanced elevation maps of thin non-keratoconic, subclinical keratoconic, and mild keratoconic corneas with the Pentacam Scheimpflug corneal tomography and to study the usefulness of different parameters to differentiate keratoconus from topographically normal thin corneas., Methods: The study included 30 eyes with subclinical keratoconus, 30 eyes with mild-stage keratoconus, and 54 healthy eyes with minimal pachymetry ≤500 µm, with a mean age of 21.19 ± 2.97, 21.75 ± 1.93, and 21.5 ± 2.95 years, respectively. The area under the receiver operating characteristic curves was used to analyze the diagnostic significance of the Pentacam parameters., Results: The anterior and posterior corneal elevations, pachymetric progression, the percentage of thickness increase measurements, overall D value, and topometric indices were statistically significantly higher in subclinical and mild keratoconic corneas than in normal eyes with thin cornea (p < 0.05). All these parameters had sufficient strength (area under the receiver operating characteristic curves >0.90) to differentiate clinical keratoconus. Posterior elevation showed the excellent area under the receiver operating characteristic curves with 100% sensitivity and 100% specificity for this purpose. However, among all parameters studied, the anterior elevation (0.935) showed the excellent area under the receiver operating characteristic curves to differentiate subclinical keratoconus, followed by posterior elevation (0.897), index of height decentration (0.887), and D value (0.882)., Conclusion: The parameters derived from the Scheimpflug device, such as corneal elevations and overall D value, can effectively differentiate subclinical and clinical keratoconus from non-keratoconic thin cornea eyes. However, the specificity levels of these parameters were relatively limited in the diagnosis of subclinical keratoconus.

Purpose: To identify tomographic variables best suited for detecting keratoconus before manifestation of ectatic changes and showing disease progression in the early stage., Methods: Twenty-seven patients with diagnosed unilateral keratoconus were followed up for their fellow eye, which had not yet shown any ectatic changes, to determine initial change indicators toward keratoconus disease. Variables were compared to 50 normal eyes without any known disease. A following receiver operating characteristic (ROC) analysis was performed to reveal the variables best used to discriminate healthy eyes from early ectatic eyes., Results: The calculated mean difference of the cylinder for total corneal refractive power was only 0.07 ± 0.32 diopters (D) (anterior astigmatism = 0.12 ± 0.28 D and posterior astigmatism = 0.02 ± 0.10 D). ROC revealed the index of height decentration with an area under the curve of 0.788 ± 0.054 as the most suitable to differentiate between eyes of healthy patients and the non-ectatic eye of patients with asymmetrical keratoconus, followed by the index of vertical asymmetry of 0.772 ± 0.057 and a keratoconus index of 0.743 ± 0.062. However, with progression of the eyes into early ectactic stages, the ROC showed the highest area under the curve for D-index (0.876 ± 0.039), followed by index of height decentration (0.855 ± 0.046) and index of vertical asymmetry (0.842 ± 0.046)., Conclusions: Early stages of keratoconus are hard to diagnose and best results can be achieved by using index of height decentration and index of vertical asymmetry. As the disease progresses, D-index is better suited to diagnose an ectasia. Astigmatism, keratometry, and pachymetry barely change in the early stages, so these values are not as fitting as corneal elevation parameters for early diagnosis. [J Refract Surg. 2018;34(4):254-259.]., (Copyright 2018, SLACK Incorporated.)

Introduction Keratoconus is a typically bilateral, progressive-extending corneal disease. The aim of this work is to evaluate the intraindividual progression of keratoconus. Patients and Methods This single-center retrospective study of disease progression based on topographic data from non-operated keratoconus patients (n = 48) was examined over a period of two years. Seven topographical keratoconus indices derived from Scheimpflug tomography were used to compare both the initial findings, as well as the progression of the fellow eyes. Results The mean observation period was 3.3 ± 0.9 years. The initial findings illustrated that a pair of eyes did not correlate with each other (p > 0.05). When comparing baseline and the progression of the individual indices, a negative correlation was found for all indices (p < 0.05). Progression and age did correlate for index smallest radius (Rmin, (R = 0.376, p = 0.008) and index of height decentration (IHD, R = 0.291, p = 0.045). Regarding the intraindividual progression, we found a weak correlation to the index of surface variance (ISV, R = - 0.399, p = 0.005), index of vertical asymmetry (IVA, R = - 0.291, p = 0.045) and the keratoconus index (KI, R = 0.307, p = 0.038). Conclusions The intraindividual asymmetry, which is typical for keratoconus, could be verified. This study suggests that the progression of keratoconus in one eye is independent of the progression in the fellow eye. In this small group of patients, age relationship to keratoconus could not be demonstrated for all keratoconus indices., Competing Interests: Interessenkonflikt: Die Autoren geben an, dass kein Interessenkonflikt besteht., (Georg Thieme Verlag KG Stuttgart · New York.)

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.

Purpose: To measure retinal image quality using point spread function (PSF) analysis by double-pass retina point imaging in patients with keratoconus and to correlate visual quality with disease severity., Methods: Patients diagnosed as having keratoconus by clinical examination, topography, and tomography and normal eyes were included in this study. A commercially available double-pass retina point imaging instrument (OQAS 108 II AcuTarget HD; Visiometrics S.L., Terrassa, Spain) was used to collect Objective Scatter Index (OSI) values in 21 keratoconic and 22 normal eyes. Eyes were also subjected to corneal topography and tomography, and staged using the Keratoconus Severity Score (KSS) and Amsler-Krumeich (AK) scales., Results: The OSI was increased in keratoconic eyes (5.85 ± 0.98) versus control eyes (0.83 ± 0.12; mean ± SEM), in AK stages 1 to 4, and KSS stages 3 and 4. Receiver-operator characteristic analysis obtained an area under the curve (AUC) of 0.859 when evaluating the OSI as a unimodal diagnostic indicator for any KSS stage and 0.993 for KSS stages 3 and higher. An AUC of 0.949 was obtained in comparing eyes with lower severity topographic aberrations (KSS 1 and 2) versus mild to moderate keratoconus (KSS 3 and 4). Increasing corneal steepening patterns on tomography and topography were associated with PSF broadening and increased OSI., Conclusions: Double-pass retina point imaging is useful in correlating retinal image quality with keratoconus severity. The OSI may represent a clinically significant parameter for staging keratoconus with a unique ability to directly evaluate quality of vision in this population. [J Refract Surg. 2016;32(11):760-765.]., (Copyright 2016, SLACK Incorporated.)

Purpose: To evaluate the robustness of numerical indications of corneal cross-linking by evaluating the inter-session reliability of recently used parameters of progression in keratoconus., Methods: In this observational study, 100 eyes of 100 patients with keratoconus underwent analysis with the Sirius Scheimpflug Topography System (CSO, Firenze, Italy) by a single user. Two sessions (three scans per session) were performed 2 to 4 weeks apart. Cases having poor quality scans, recent visual deterioration, and ocular surgery were excluded. The corneal variables measured were thinnest point and apex characteristics (pachymetry, polar coordinates), volume, central simulated keratometry (flat, steep, average, astigmatism), central corneal thickness, maximum elevation (anterior, posterior), symmetry indices (front, back), and Baiocchi-Calossi-Versaci index. Intra-session (first session, all three measurements) and inter-session (one measurement from each session, selected randomly) statistics were computed., Results: There were no significant differences in the six measurements for all variables (P > .05, analysis of variance). The intra-session and inter-session intraclass correlations were high (0.937 to 0.997) and within-subject standard deviations (Sw) were satisfactory (< 5 µm for thickness, < 0.50 diopters [D] for curvature, and < 0.11 mm, < 5° for polar coordinates). Inter-session repeatability (2.77 × Sw) was found to be satisfactory when compared to previously used central keratometric (> 1.00 D increase) or pachymetric (> 2%/> 5% decrease) guidelines to define progression. Apex power repeatability (1.24 D) was found to be poorer than previously used recommendations (1.00 D change)., Conclusions: The criteria used to define keratoconus progression were satisfactory when compared to inter-session reliability of corneal parameters. Because higher variability was noted at apex, its curvature repeatability cut-off may be raised to 1.25 D for identifying progressive keratoconus. [J Refract Surg. 2016;32(7):465-472.]., (Copyright 2016, SLACK Incorporated.)

Purpose: To evaluate the performance of a support vector machine algorithm that automatically and objectively identifies corneal patterns based on a combination of 22 parameters obtained from Pentacam measurements and to compare this method with other known keratoconus (KC) classification methods., Methods: Pentacam data from 860 eyes were included in the study and divided into 5 groups: 454 KC, 67 forme fruste (FF), 28 astigmatic, 117 after refractive surgery (PR), and 194 normal eyes (N). Twenty-two parameters were used for classification using a support vector machine algorithm developed in Weka, a machine-learning computer software. The cross-validation accuracy for 3 different classification tasks (KC vs. N, FF vs. N and all 5 groups) was calculated and compared with other known classification methods., Results: The accuracy achieved in the KC versus N discrimination task was 98.9%, with 99.1% sensitivity and 98.5% specificity for KC detection. The accuracy in the FF versus N task was 93.1%, with 79.1% sensitivity and 97.9% specificity for the FF discrimination. Finally, for the 5-groups classification, the accuracy was 88.8%, with a weighted average sensitivity of 89.0% and specificity of 95.2%., Conclusions: Despite using the strictest definition for FF KC, the present study obtained comparable or better results than the single-parameter methods and indices reported in the literature. In some cases, direct comparisons with the literature were not possible because of differences in the compositions and definitions of the study groups, especially the FF KC.

Purpose: To propose a new keratoconus classification/staging system that utilises current tomographic data and better reflects the anatomical and functional changes seen in keratoconus., Method: A previously published normative database was reanalysed to generate both anterior and posterior average radii of curvature (ARC and PRC) taken from a 3.0 mm optical zone centred on the thinnest point of the cornea. Mean and standard deviations were recorded and anterior data were compared to the existing Amsler-Krumeich (AK) Classification. ARC, PRC, thinnest pachymetry and distance visual acuity were then used to construct a keratoconus classification., Results: 672 eyes of 336 patients were analysed. Anterior and posterior values were 7.65 ± 0.236 mm and 6.26 ± 0.214 mm, respectively, and thinnest pachymetry values were 534.2 ± 30.36 µm. The ARC values were 2.63, 5.47 and 6.44 standard deviations from the mean values of stages 1-3 in the AK classification, respectively. PRC staging uses the same standard deviation gates. The pachymetric values differed by 4.42 and 7.72 standard deviations for stages 2 and 3, respectively., Conclusion: A new keratoconus staging incorporates anterior and posterior curvature, thinnest pachymetric values, and distance visual acuity and consists of stages 0-4 (5 stages). The proposed system closely matches the existing AK classification stages 1-4 on anterior curvature. As it incorporates posterior curvature and thickness measurements based on the thinnest point, rather than apical measurements, the new staging system better reflects the anatomical changes seen in keratoconus., (Georg Thieme Verlag KG Stuttgart · New York.)

Purpose: To evaluate the long-term outcomes after femtosecond laser (FSL)-assisted mushroom-configuration keratoplasty in advanced keratoconus., Patients and Methods: Thirteen eyes with Amsler-Krumeich stage IV keratoconus underwent FSL-assisted mushroom-configuration penetrating keratoplasty (PKP) and deep anterior lamellar keratoplasty (DALK) at a tertiary referral centre. Preoperative risk factors included low orneal thickness, high keratometry measurements, previous hydrops, and central stromal scarring. Main outcome measures were visual acuity and refractive outcome., Results: The median follow-up was 33 months (range: 4-43). Preoperatively, the mean corrected distance visual acuity (CDVA) was 1.22±0.47 LogMAR (range: 0.5-1.9 LogMAR), mean minimum corneal thickness was 282±100.8 μm (range: 147-478 μm), and mean average keratometric (K) value was 63.4±7.63 dioptre (D; range: 57.0-75.7 D). Four patients underwent PKP and nine underwent DALK (two converted to PKP). Five patients subsequently underwent a modified arcuate mushroom interface dissection (AMID) procedure for astigmatic correction. At the final follow-up, the mean CDVA was 0.05±0.13 LogMAR (range: -0.10 to 0.20 LogMAR), mean spherical equivalent was -3.21±3.21D, mean cylindrical refractive error was 3.23±2.20 D, and mean average K was 43.1±1.53 D. Complications included early graft dehiscence, corneal vascularisation, stromal rejection, and sclerokeratitis. Sutures were completely removed at the mean 18.4 months for PKP and 9.1 months for DALK postoperatively., Conclusion: FSL-assisted mushroom-configuration keratoplasty is feasible and safe in patients with stage IV keratoconus. AMID could further enhance the refractive outcome safely.

Purpose: Keratoconus is characterized by bilateral asymmetrical corneal ectasia that leads to inferior stromal thinning and corneal protrusion. There is currently a lack of consensus regarding the most efficacious method for fitting contact lenses in patients with keratoconus, given the various topographical patterns and evolution grades observed in affected populations. The purpose of the present study was to evaluate the association between keratoconus evolution grade and topography pattern and the type and design of fitted contact lens., Methods: We performed a retrospective analysis of contact lenses fitted in a total of 185 patients with keratoconus (325 eyes). Keratoconus was classified as either grade I, II, III, or IV based on keratometry and cone morphology (nipple, oval, globus, or indeterminate) results., Results: A total of 325 eyes were evaluated in the present study. Of the 62 eyes classified as grade I, 66.1% were fitted with monocurve contact lenses. Of the 162 eyes classified as grade I and II, 51%, 30%, and 19% were fitted with adapted monocurve rigid gas-permeable contact lenses (RGPCL), bicurve lenses, and others lens types, respectively. Bicurve lenses were fitted in 52.1% and 62.2% of eyes classified as grade III and IV, respectively. Of the eyes classified as grade III and IV, monocurve and bicurve RGPCL were fitted in 26% and 55%, respectively. In eyes with oval keratoconus, 45%, 35%, and 20% were fitted with monocurve lenses, bicurve lenses, and other lens types, respectively. In eyes with round cones (nipple morphology), 55%, 30%, and 15% were fitted with bicurve lenses, monocurve lenses, and other lens types, respectively., Conclusion: Monocurve RGPCL were most frequently fitted in patients with mild to moderate keratoconus and oval cones morphology, while bicurve lenses were more frequently fitted in patients with severe and advanced keratoconus. This was probably because bicurve lenses are more appropriate for round cones due to increased corneal asphericity.

Aims: To compare intraocular pressure (IOP) measurements obtained with Goldmann applanation tonometery (GAT), dynamic contour tonometry (DCT), tonopen (TP), and ocular response analyzer (ORA), and to determine the influence of Amsler grade and central corneal thickness (CCT) on the IOP readings in eyes with keratoconus that are classified into four groups according to the Amsler-Krumeich classification., Methods: All eyes with keratoconus were separated into four groups using Amsler-Krumeich classification for keratoconus. IOP was measured in 202 eyes of 202 patients with keratoconus using GAT, DCT, TP, and ORA., Results: The IOP differences revealed no significant difference among the Amsler degree in the DCT and corneal-compensated IOP (IOPcc) measurements (P>0.05 for all). There was no statistically significant difference in terms of IOP differences between GAT and IOPcc (P>0.05), TP and Goldmann-correlated measure of IOP (IOPg; P>0.05) in the Amsler I, while the IOP measurements revealed significant difference among the measurements of the four different tonometers in the Amsler II, Amsler III, and Amsler IV (P<0.05 for all)., Conclusions: There was no significant association between DCT IOP or IOPcc and CCT in eyes with keratoconus; no statistically significant difference was found between keratoconus stages and the control group in terms of the IOP analyzed with these two techniques. These two techniques may be the most stable in the measurement of IOP in different keratoconus stages. However, no IOP technique can be used interchangeably with other techniques in the follow-up of keratoconus patients.

Purpose: To assess the repeatability of the corneal topography functions of Orbscan II (Bausch & Lomb, Rochester, NY), OPD-Scan III (Nidek, Gamagori, Japan), and iTrace (Tracey Technologies, Houston, TX) in keratoconic eyes and in a control group of normal patients., Methods: In this prospective cohort study, patients were recruited between November 2011 and May 2012. Measurements were performed with a combined Placido-scanning slit system (Orbscan II) and two combined Placido-aberrometer systems (OPD-Scan III and iTrace). Repeatability limit and intraclass correlation coefficients (ICCs) of keratometric readings were calculated., Results: Fifty-nine keratoconic eyes of 34 patients and 54 normal eyes of 27 patients were included. Three groups were evaluated: all stage I-IV keratoconic eyes (59 eyes), a subgroup consisting of stage I-II keratoconic eyes (41 eyes), and normal eyes (54 eyes). For almost all parameters studied, the repeatability limit was higher in the two groups of keratoconic eyes compared to normal eyes with all three topographers, indicating lower repeatability. For the maximum keratometry measurement, repeatability limit was 1.73, 1.49, and 1.41 diopters (D) in the stage I-IV keratoconic eyes group, 1.11, 1.02, and 0.98 D in the stage I-II keratoconic eyes group, and 0.61, 0.37, and 1.02 D in the normal eyes group with Orbscan II, OPD-Scan III, and iTrace, respectively., Conclusions: Topographies performed in keratoconic eyes are less repeatable than those performed in normal eyes. Threshold values of keratometric changes used to ascertain keratoconus progression should be carefully considered. Caution should be taken when interpreting the topographies of such patients. The higher variability should be taken into account before performing any treatment., (Copyright 2016, SLACK Incorporated.)

Purpose: To describe the topographic and tomographic characteristics of normal fellow eyes of unilateral keratoconus cases and to evaluate the accuracy of machine learning classifiers in discriminating healthy corneas from the normal fellow corneas., Setting: Department of Ophthalmology, Semmelweis University, Budapest, Hungary., Design: Retrospective case-control study., Methods: Patients with bilateral keratoconus (keratoconus group), clinically and according to the keratoconus indices of the Pentacam HR Scheimpflug camera; normal fellow eyes of patients with unilateral keratoconus (fellow-eye group); and eyes of refractive surgery candidates (control group) were compared. Tomographic data, topographic data, and keratoconus indices were measured in both eyes using the Scheimpflug camera. Receiver operating characteristic (ROC) analysis was used to assess the performance of automated classifiers trained on bilateral data as well as individual parameters to discriminate fellow eyes of patients with keratoconus from control eyes., Results: Keratometry, elevation, and keratoconus indices values were significantly higher and pachymetry values were significantly lower in keratoconus eyes than in fellow eyes of unilateral keratoconus cases (P < .001). These fellow eyes had significantly higher keratometry, elevation, and keratoconus index values and significantly lower pachymetry values than control eyes (P < .001). Automated classifiers trained on bilateral data of index of height decentration had higher accuracy than the unilateral single parameter in discriminating fellow eyes of patients with keratoconus from control eyes (area under ROC 0.96 versus 0.88)., Conclusion: Automatic classifiers trained on bilateral data were better than single parameters in discriminating fellow eyes of patients with unilateral keratoconus with preclinical signs of keratoconus from normal eyes., Financial Disclosure: No author has a financial or proprietary interest in any material or method mentioned., (Copyright © 2016 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate the utility of topographic and pachymetric parameters of Scheimpflug system in keratoconus diagnosis., Methods: This study included 183 eyes of 183 patients with keratoconus (keratoconus group) and 131 eyes of 131 age and sex-matched healthy subjects (control group). Mean keratometry (K, front), topographic astigmatism, pupil-center pachymetry, apical pachymetry, thinnest pachymetry (TP), corneal volume and maximum K (Kmax) were obtained from the Scheimpflug imaging system. A receiver operating characteristic (ROC) analysis was performed and area under the curve (AUC) was calculated to determine the diagnostic ability of each parameter in eyes with ≤ stage 3, ≤ stage 2 and stage 1 keratoconus based on the Amsler-Krumeich grading system., Results: The Kmax and TP showed the highest individual performance (with sensitivity-specificity of 92.9-92.4% and 89.6-93.3%, respectively) in diagnosis of keratoconus. The AUCs and sensitivity-specificity values for the Kmax/TP and Kmax(2)/TP were calculated to improve the diagnostic performance. As expected, sensitivity-specificity values significantly increased by using Kmax/TP (97.3-94.7% at the level ≥0.08) and Kmax(2)/TP (99.5-95.7% at the level ≥4.1) in discrimination of keratoconic eyes from normals. Moreover, Kmax(2)/TP had very high sensitivity (>99%) and specificity (>94%) in diagnosis of stage 1 and stage 2 keratoconus., Conclusions: Although Kmax and TP appear to have high diagnostic ability in keratoconus, the use of either single parameter in isolation might be unsatisfactory in differential diagnosis. Therefore, the Kmax(2)/TP ratio has been introduced, which reflects major characteristics of keratoconus and might be used as an important criterion in keratoconus diagnosis., (Copyright © 2015 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.)

Purpose: To evaluate the repeatability and agreement of the anterior segment measurements obtained using the Galilei dual Scheimpflug analyzer (Galilei DSA; Ziemer) and Nidek AL Scan (Nidek CO, Aichi, Japan) biometry in keratoconic and normal eyes., Methods: Three consecutive measurements were performed by the same examiner using both devices in 62 healthy and 88 keratoconic eyes. Central corneal thickness (CCT), anterior chamber depth, keratometry readings (K) [in flattest meridian (Kf), in steepest meridian (Ks), and mean (Km)], and white-to-white distance were evaluated. Repeatability was assessed by calculating the within-subject SD and coefficient of variation. The agreement between both devices was assessed using the Bland-Altman method., Results: Both devices achieved excellent repeatability for all parameters in each group. The 95% limits of agreement (LoA) between both devices were also very narrow and acceptable for all parameters in normal corneas. However, the 95% LoA for agreement was large for CCT and measurements related to K (Kf, Ks, and Km) using both 2.4 and 3.3 mm in keratoconic eyes. In addition, compared with the Galilei DSA, K values of the Nidek AL Scan using a diameter of 3.3 mm showed slightly closer 95% LoA than those obtained using a diameter of 2.4 mm., Conclusions: In normal eyes, the Galilei DSA and Nidek AL Scan can be used interchangeably for anterior segment measurements. In keratoconic eyes, both devices yielded interchangeable anterior chamber depth and white-to-white distance measurements, whereas CCT and keratometry measurements showed clinically significant differences.

Purpose: To demonstrate the topographic and keratometric findings in patients with keratoconus (KC), according to age, sex, and KC severity groups., Methods: A total of 2073 eyes of 1081 patients with KC were consecutively diagnosed and enrolled in this prospective cross-sectional study. All patients underwent ophthalmic examination and Pentacam (Oculus Optikgerate GmbH) measurements. The patients were divided into different groups according to their age, sex, Amsler-Krumeich classification, and keratoconus severity score classification. Keratometric (K) values (flattest, steepest, and mean), central and thinnest corneal thickness, and manifest refraction were recorded for each patient with KC and they were then compared according to the patient's age, sex, and KC severity groups., Results: The age (mean ± SD) of the population was 24 ± 7 years. The average central corneal thickness and mean K of all patients were 462 ± 45 μm and 48.8 ± 4.8 diopters, respectively. Female patients with KC were significantly younger and had significantly higher K values and lower anterior chamber depth than those of men. All parameters except for the pupil diameter and astigmatism were significantly associated with KC severity grades. The thinnest corneal thickness was the most important and also the most sensitive and specific parameter for distinguishing all stages of KC severity in all KC severity classifications. The Amsler-Krumeich classification had the most correlation with other severity classifications., Conclusions: The results of this study enable clinicians and researchers to understand better the differences between clinical characteristics between sex, age groups, and the changes in clinical characteristics during disease progression, which may lead to further advancement in KC management.

Purpose: To define the optical coherence tomography (OCT) corneal changes predisposing to acute corneal hydrops among patients with advanced keratoconus., Design: Retrospective cohort study., Participants: A total of 191 advanced keratoconic eyes from 191 patients with advanced keratoconus cases were studied., Methods: Data collected from patients with advanced keratoconus cases were studied during a minimum period of 24 months of follow-up. High-resolution Fourier-domain corneal OCT (5 μm of axial resolution) and corneal topography were performed every 4 months during the follow-up. Several anatomic features at the keratoconus cone were analyzed with OCT, including epithelial and stromal thicknesses, the aspect of Bowman's layer, the presence of Vogt's striae, and stromal opacities. A comparative analysis between anatomic corneal features in eyes that developed corneal hydrops and those that did not develop this complication during the follow-up was performed., Main Outcome Measures: Evaluation of anatomic corneal changes at risk of developing a corneal hydrops on the basis of OCT findings., Results: Eleven cases of corneal hydrops (5.8%) occurred in our series during a mean follow-up of 30 months (24-36 months). All of these patients were male and younger (23.7±5.9 years) than patients with no acute keratoconus (32.7±11.3 years). Increased epithelial thickening with stromal thinning at the conus and the presence of anterior hyperreflectives at the Bowman's layer level were significantly associated with corneal hydrops, whereas the presence of corneal scarring was a preventive factor. At the healing stage, a pan-stromal scar occurs, with a significant stromal thickening and cornea flattening., Conclusions: Increased epithelial thickening, stromal thinning at the keratoconus cone, anterior hyperreflectives at the Bowman's layer level, and the absence of stromal scarring are associated with a high risk of developing corneal hydrops. These aspects should be taken into account by the clinician in the evaluation of keratoconus eyes and in the planning of corneal keratoplasty., (Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate the clinical and topographic effects after accelerated corneal collagen cross-linking (CXL) in keratoconus., Methods: This was a prospective interventional study in 25 eyes of 24 Asian patients with keratoconus, where 10 eyes in group 1 had mild to moderate keratoconus with the steepest keratometry reading (Kmax) < 58 diopters (D), and 15 eyes in group 2 had advanced keratoconus with Kmax ≥ 58.0 D. The patients underwent accelerated CXL with 18 W/cm UV-A light for 5 minutes. Clinical and topographic parameters were obtained before and 1 year after treatment., Results: Overall, spectacle-corrected distance visual acuity, refraction, average keratometry readings, Kmax, anterior elevation at the apex, and corneal endothelial cell density remained stable (P < 0.102). Posterior elevation at the apex increased at 1 year (P = 0.002). The thinnest pachymetry readings also showed significant reduction (P < 0.001). Kmax in group 1 increased by 1.00 ± 1.63 D (range, -2.2 to 5.4 D; P = 0.012), whereas Kmax in group 2 reduced by 1.69 ± 2.61 D (range, -8.4 to 3.2 D; P = 0.013) at 1 year after accelerated CXL. The change in Kmax between the 2 groups was significantly different (P < 0.001). There was no intergroup difference for the change in other parameters. A significant correlation was found between the preoperative Kmax and postoperative change in Kmax at 1 year (r = -0.648; P < 0.001)., Conclusions: Accelerated CXL seems to be effective in preventing progression and causing topographic flattening in advanced cases of keratoconus but not as effective in the less progressed counterparts.

Purpose: To determine the repeatability of keratometry (K) measurements of a Scheimpflug pachymeter (Pentacam), Placido topographer (Eyesys), scanning-slit corneal topographer (Orbscan), partial coherence interferometry (PCI) device (IOLMaster), and Javal manual keratometer with different grades of keratoconus., Setting: Noor Eye Hospital, Tehran, Iran., Design: Retrospective case series., Methods: Keratometry was performed first with Scheimpflug pachymetry followed, in order, by Placido topography, scanning-slit corneal topography, PCI, and manual keratometry. Repeatability was examined in groups with a maximum K of less than 50.0 diopters (D), 50.0 to 55.0 D, and more than 55.0 D., Results: Seventy-eight eyes of 45 keratoconus patients were assessed. In Group 1, repeatability was highest with Scheimpflug pachymetry and lowest with scanning-slit corneal topography (0.36 to 1.24). In Group 2, the intraclass correlation coefficients (ICCs) for maximum K ranged from 0.823 with the scanning-slit corneal topography to 0.974 with Scheimpflug pachymetry. The repeatability index for minimum K (0.53 to 2.11) and maximum K (0.60 to 1.92) in this group was highest with Scheimpflug pachymetry and with for scanning-slit corneal topography. In Group 3, the ICCs for minimum K and maximum K ranged from 0.890 to 0.990, and the repeatability index for minimum K varied between 1.66 with Scheimpflug pachymetry to 2.98 with Placido topography; for maximum K, the index was from 2.15 with PCI to 2.81 with the manual keratometer., Conclusions: In mild keratoconus, the 5 devices had acceptable repeatability in K readings. In cases with a maximum K reading greater than 55.0 D, all devices had reduced repeatability as a result of measurement errors; thus, measurements might not be so reliable., (Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.)

Purpose: Are the classifications achieved by the Belin-Ambrósio (BA) enhanced ectasia module, the keratoconus indices of the Pentacam HR and the ectasia screening index (ESI) using CASIA anterior segment optical coherence tomography (OCT) comparable to the topographical keratoconus classification (TKC) of the Pentacam HR? Can the indices be used interchangeably to assist in the diagnosis of keratoconus?, Methods: This retrospective study examined 228 datasets (eyes) of patients with a mean age of 36.6 ± 13.6 years which were grouped into a non-keratoconus group (group I, n = 59) and a keratoconus group (group II, n = 169) according to the clinical assessment. From the data sets of these eyes the sensitivity and specificity of various ectasia and keratoconus indices (KI) were calculated with the help of receiver operating characteristics (ROC). Groups were compared using the Mann-Whitney and χ(2)-tests., Results: Groups I and II had a mean KI of 1.04 and 1.26 and a mean ESI of 3.0 and 66.6, respectively. The χ(2)-test showed no significant coincidence of the distance of the thinnest point from the apex with TKC (χ(2) > 2, p > 0.35). All other BA parameters as well as the ESI showed a significant coincidence with the keratoconus diagnosis and the classification of TKC (p < 0.001). The ESI and KI along with some BA parameters (Df, Db, Dp and D) showed a good separation between groups I and II with an area under the ROC curves of > 0.93., Conclusion: The enhanced indices and classifiers, such as the BA module or the ESI were comparable with the purely anterior corneal surface based TKC.

Purpose: To derive limits of metric keratoconus indices for classification into keratoconus stages., Design: Validity and reliability analysis of diagnostic tools., Methods: A total of 126 patients from the keratoconus center of Homburg/Saar were evaluated with respect to Amsler criteria, using Pentacam (Keratoconus Index [KI], Topographic Keratoconus Classification [TKC]), Topographic Modeling System (Smolek/Klyce, Klyce/Maeda), and Ocular Response Analyzer (Keratoconus Match Probability [KMP], Keratoconus Match Index [KMI]). Mean value, standard deviation, 90% confidence interval, and the Youden J index for definition of the thresholds were evaluated., Results: For separation of keratoconus stages 0/1/2/3/4 we derived the following optimum thresholds: for KI 1.05/1.15/1.31/1.49 and for KMI 0.77/0.32/-0.08/-0.3. For Smolek/Klyce and Klyce/Maeda high standard deviations and overlapping confidence intervals were found; therefore no discrete thresholds could be defined. Nevertheless, for them we still found a good sensitivity and specificity in discriminating between healthy (stage 0) and keratoconus (stages 2-4) eyes in comparison with the other indices., Conclusions: We derived thresholds for the metric keratoconus indices KI and KMI, which allow classification of keratoconus stages. These now need to be validated in clinical use. Smolek/Klyce and Klyce/Maeda were not sufficiently sensitive to allow classification into individual stages, but these indices did show a good specificity and sensitivity in discriminating between keratoconus and healthy eyes., (Copyright © 2015 Elsevier Inc. All rights reserved.)

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 μm), central (from 120 μm to the last 60 μm), and posterior (last 60 μm) 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.

Purpose: The aim of this study was to investigate the corneal thickness asymmetry indices in a large pool of patients with keratoconus derived using anterior segment optical coherence tomography (AS-OCT) in comparison with established Scheimpflug imaging-derived keratoconus classification indices., Methods: Six specific indices were comparatively investigated in this study encompassing 2 groups: keratoconic group A (175 eyes) and age- and gender-matched control group B (175 eyes). AS-OCT was used for corneal focal thinning and irregularity indices, namely the superior nasal minus inferior temporal (SN-IT), superior minus inferior (S-I), minimum minus median (Min-Med) focal thinning, and thickness range, defined as the minimum minus maximum (Min-Max). Scheimpflug imaging was used for keratoconus grading and for investigating anterior surface irregularity index of height decentration (IHD) and index of surface variance (ISV)., Results: In study group A, SN-IT was 74.6 ± 38.9 μm; S-I, 77.3 ± 42.3 μm; Min-Med, -60.1 ± 36.8 μm; and Min-Max, -117.7 ± 55.4 μm. In control group B, SN-IT was 23.32 ± 11.47 μm; S-I, 22.55 ± 12.56 μm; Min-Med, -19.69 ± 5.20 μm; and Min-Max, -55.24 ± 12.96 μm. In group A, IHD was 0.077 ± 0.055 and ISV was 84.24 ± 48.61. In group B, IHD was 0.031 ± 0.038 and ISV was 31.82 ± 29.72. A statistically significant relationship was identified between SN-IT, S-I, Min-Med, and Min-Max indices with IHD and ISV (P < 0.01 in all pairs; coefficients of determination 0.649, 0.663, 0.481 and 0.483 versus IHD, and 0.690, 0.722, 0.551, and 0.562 versus ISV, respectively)., Conclusions: This study presents a novel and comprehensive investigation of corneal asymmetry and focal thinning indices for keratoconus by AS-OCT. These indices correlate with established Scheimpflug-derived anterior surface irregularity indices, particularly in the early and milder stages. AS-OCT may hold promise as a helpful screening and diagnostic tool for suspect, early, and clinical keratoconus.

Purpose: The aim was to study the corneal endothelial count and morphology in patients with keratoconus by specular microscopy and to correlate them to the stage of keratoconus., Methods: Forty eyes of 29 patients with keratoconus were enrolled in this cross-sectional cohort study. Corneal endothelium was evaluated using specular microscopy, and corneal topography and thickness data were obtained from Scheimpflug-based corneal tomography. Eyes were classified into stages 1 through 4 of keratoconus according to Amsler classification, using keratometry and pachymetry readings obtained from corneal tomography., Results: Eleven eyes (27.5%) had stage 1, 17 eyes (42.5%) had stage 2, and 12 eyes (30%) had stage 3. Specular microscopy was not possible in stage 4. There was no statistically significant correlation between the stage of keratoconus and the endothelial cell density (ECD) (r = 0.018, P = 0.91), coefficient of variation (CV) (r = -0.011, P = 0.94), or percentage of hexagonality (6A) (r = -0.112, P = 0.51). When mild-to-moderate keratoconus (stages 1 and 2) was compared with severe keratoconus (stage 3), the difference was not significant regarding ECD (P = 0.1), CV (P = 0.3), or 6A (P = 0.4). However, there was a trend toward lower ECD and percentage of hexagonality, and a higher CV with advancing disease., Conclusions: Up to stage 3, keratoconus does not significantly affect the corneal endothelium, as measured by specular microscopy. Eyes with stage 4 could not be studied by specular microscopy and may require other imaging methods such as confocal microscopy.

Purpose: To evaluate Pentacam ectasia detection indices in topographically normal patients and in subclinical keratoconus cases., Design: Prospective, observational case series., Methods: setting: Institutional. patients: Group 1 comprised 1 eye from 189 patients with unremarkable topography and Groups 2 and 3 included the better and worse eyes, respectively, of 55 keratoconic patients. Group 2 eyes with normal topography (n = 37) were considered subclinical keratoconus cases. observation procedure: Pentacam Scheimpflug tomography. main outcome measures: Eleven Pentacam ectasia detection indices., Results: All Pentacam ectasia indices significantly differed between Groups 1 and 2 and were correlated with keratoconus grade. Only 99 eyes (52%) in Group 1 had normal values for every index, whereas 7 subclinical keratoconus eyes (19%) showed 2 or fewer abnormal indices. Standardized relational thickness and overall deviation indices had 73% and 89% sensitivity for subclinical keratoconus, respectively. Both average and maximum pachymetric progression indices offered 84% sensitivity while maximum relational thickness index showed 78% sensitivity for subclinical keratoconus. Optimized cutoff values for subclinical keratoconus increased the sensitivity of the standardized and maximum relational thickness indices., Conclusion: Pentacam Scheimpflug tomography can detect most subclinical keratoconus cases with unremarkable topography, but performance is not as good as reported and varies considerably for each index. The overall deviation, average and maximum pachymetric progression, and maximum relational thickness indices offer the highest sensitivity, which can be improved by using optimized cutoff values. Specificity constitutes an issue for some indices and up to 10% of subclinical keratoconus cases may go undetected by this technology., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Purpose: To assess anterior segment parameters of eyes with keratoconus (KC) at different clinical stages of disease., Methods: KC and non-KC patients were recruited from public and private clinics in Melbourne, Australia. Axial length (AL), mean front corneal curvature (Front Km), mean back corneal curvature (Back Km), central corneal thickness (CCT), corneal thickness at the apex (CTA), corneal thickness at the thinnest point (CTT), anterior chamber depth (ACD), and corneal volume were noted for all the eyes., Results: A total of 181 individuals comprising 44 (24.3%) subclinical KC, 118 (65.2%) clinical KC, and 19 (10.5%) control subjects were analyzed. Significant differences were noticed between the subclinical KC and control group for ACD and CTT, whereas between clinical and control groups, significant differences were obtained for AL, CCT, CTA, CTT, and ACD (p < 0.05). In the case of mild, moderate, and severe KC groups, Back Km, CCT, CTA, and CTT were significantly associated (p < 0.001) with increasing disease severity. We further did receiver operating characteristic analysis to confirm the importance of pachymetric parameters in differentiating between control and KC eyes. The area under the receiver operating characteristic curve value of CTT for subclinical and clinical KC was 0.68 and 0.82, which showed that it may be a potential marker for the early detection and prevention of KC., Conclusions: This study identified the anterior chamber parameters that differ between subclinical and clinical KC as well as the severity of KC. There is a significant reduction in CTT between control and subclinical eyes, although there are no significant alterations in Front and Back Km or AL between the two groups. Also, a progressive reduction in the pachymetric readings at the pupil center, apex, and thinnest corneal point was identified when comparing mild to severe KC groups. Thus, corneal thickness represents an important parameter that needs to be considered in monitoring KC disease severity.

Purpose: To evaluate the diagnostic capacity of the Ocular Response Analyzer's keratoconus match index (KMI) and keratoconus match probability (KMP) classification in keratoconus-suspect eyes., Setting: Department of Ophthalmology, University Clinics Saarland, Homburg, Germany., Design: Comparative case series., Methods: The KMI and KMP parameters in keratoconus-suspect eyes and normal eyes (control group) were compared. The quantitative keratoconus percentage index was calculated for all suspect eyes. According to the thinnest corneal thickness (TCT), keratoconus-suspect eyes were divided into 2 subgroups: subgroup 1 (TCT <520 μm) and subgroup 2 (TCT >520 μm). The KMI's overall predictive accuracy was assessed using receiver operating characteristic (ROC) curves. The relationship between KMI and a series of Scheimpflug-derived keratoconus-related indices was evaluated using Spearman analysis., Results: The mean KMI was 0.41 ± 0.29 (SD) in the keratoconus-suspect group (50 eyes) and 0.94 ± 0.29 in the control group (50 eyes) (P<.001). Nonsignificant KMI differences were detected between the keratoconus-suspect subgroups (subgroup 1, 27 eyes; subgroup 2, 23 eyes) (P=.059). Nonsignificant correlations were found between Scheimpflug indices and the KMI. The KMP identified 27.65% of control eyes as keratoconus suspect and 10.71%, 28.57%, and 3.57% of keratoconus-suspect eyes as being normal, having mild keratoconus, or having moderate keratoconus, respectively. The ROC analysis for the KMI indicated a predictive accuracy of 94% (cutoff point 0.72)., Conclusions: The KMI seems to be a valuable index in the early diagnosis of keratoconus-suspect eyes. The KMP identified a significant percentage of topographically defined keratoconus-suspect eyes as normal or keratoconic., Financial Disclosure: No author has a financial or proprietary interest in any material or method mentioned., (Copyright © 2014 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.)

Aim: To evaluate corneal elevation, pachymetry and keratometry in keratoconic eyes according to the clinical stage of the disease., Methods: This prospective comparative study was performed on one hundred and twenty-six eyes of 83 patients who had keratoconus, and 42 normal eyes of 42 age-matched subjects. Corneal elevation, pachymetry and keratometry were measured using a rotating Scheimpflug camera (Pentacam HR, Oculus) in these eyes. The area under the receiver operating characteristic (AUROC) curves was used to analyse the diagnostic significance of these parameters, with respect to each stage of Amsler-Krumeich classifications. AUROC was calculated to describe the predictive accuracy of the different indices and to determine the cut-off points where sensitivity and specificity were maximised., Results: Posterior (0.980) and anterior (0.977) elevation differences showed the highest AUROCs, followed by dioptres (D) value (0.941), percentage thickness increase (PTI) 2 mm (0.931), PTI 4 mm (0.927), progression index (0.927), minimal pachymetry (0.923), average keratometry (0.914), anterior elevation (0.909), PTI 6 mm (0.906), posterior elevation (0.898), central pachymetry (0.889), PTI 8 mm (0.870), PTI 10 mm (0.864), corneal thickness spatial profile 2 mm (0.835) and cylinder (0.796). The differences in AUROC curves between anterior and posterior elevation difference measurements and other diagnostic parameters tended to be larger at the earlier stages of keratoconus., Conclusions: Anterior and posterior corneal surface height data obtained by enhanced ectasia display, effectively discriminates keratoconus from normal corneas. Elevation difference measurements may provide useful information for improving the diagnostic accuracy of keratoconus, especially in the early stage of the disease.

Purpose: To develop parameters using a combination of optical coherence tomography (OCT) and videokeratography to detect early keratoconus., Methods: Videokeratography, wavefront analysis, and measured OCT indices were performed on 180 normal eyes, 46 eyes with moderate keratoconus, 54 eyes with early keratoconus, 7 eyes with forme fruste keratoconus, and 16 eyes with keratoconus "suspect" to determine the most sensitive parameters for separating these groups., Results: A combination of videokeratography and OCT indices (inferior-superior [I-S] value and minimum pachymetry) was statistically the most significant in separating the keratoconus groups from normal eyes (P < .001). Using a newly derived index, the minimum pachymetry divided by the I-S value (pachymetry/asymmetry [PA]/I-S index) with a cut-off of 100, 100% of early and forme fruste keratoconus could be identified as being abnormal with 7 normals misclassified (misclassification rate 2.7%). By adding keratoconus "suspect" to the analysis and an I-S value of 1.2 as a cut-off point, 5 "suspects" were classified as normal and 11 normals as abnormal (misclassification rate 7.8%). The PA/I-S index, with a cut-off point of 100, reduced this misclassification rate to 4.4%., Conclusions: These results suggest that OCT combined with videokeratography may be more useful for differentiating mild forms of keratoconus than videokeratography alone., (Copyright 2014, SLACK Incorporated.)

Objective: To study corneal morphologic changes in a large keratoconic population and to establish a structural optical coherence tomography (OCT) classification., Design: Cross-sectional, observational study., Participants: A total of 218 keratoconic eyes from 218 patients and 34 eyes from 34 normal subjects., Methods: A Fourier-domain OCT system with 5-μm axial resolution was used. For each patient, 3 high-resolution scans were made across the keratoconus cone. All scans were analyzed by keratoconus specialists who were not given access to patients' clinical and topographic data, and who established an OCT classification. The reproducibility of the classification and its correlation with clinical and paraclinical characteristics of patients with keratoconus were evaluated. The OCT examinations were performed every 4 months to follow up structural corneal changes., Main Outcome Measures: Evaluation of the structural corneal changes occurring in keratoconus cases with various stages of severity based on OCT findings., Results: Fourier-domain OCT classification containing 5 distinct keratoconus stages is proposed. Stage 1 demonstrates thinning of apparently normal epithelial and stromal layers at the conus. Stage 2 demonstrates hyperreflective anomalies occurring at the Bowman's layer level with epithelial thickening at the conus. Stage 3 demonstrates posterior displacement of the hyperreflective structures occurring at the Bowman's layer level with increased epithelial thickening and stromal thinning. Stage 4 demonstrates pan-stromal scar. Stage 5 demonstrates hydrops; 5a, acute onset: Descemet's membrane rupture and dilaceration of collagen lamellae with large fluid-filled intrastromal cysts; 5b, healing stage: pan-stromal scarring with a remaining aspect of Descemet's membrane rupture. The reproducibility of the classification was very high between the corneal specialist observers. Clinical and paraclinical characteristics of keratoconus, including visual acuity, corneal epithelium and stromal thickness changes, corneal topography, biomechanical corneal characteristics, and microstructural changes observed on confocal microscopy, were concordant with our OCT grading., Conclusions: Optical coherence tomography provides an accurate assessment of structural changes occurring in keratoconus eyes. These changes were correlated with clinical and paraclinical characteristics of patients. The established classification not only allows structural follow-up of patients with keratoconus but also provides insight into the pathogenesis of keratoconus and treatment strategies for future research., (Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: To develop a method for automatizing the detection of subclinical keratoconus based on a tree classification., Design: Retrospective case-control study., Methods: setting: University Hospital of Bordeaux. participants: A total of 372 eyes of 197 patients were enrolled: 177 normal eyes of 95 subjects, 47 eyes of 47 patients with forme fruste keratoconus, and 148 eyes of 102 patients with keratoconus. observation procedure: All eyes were imaged with a dual Scheimpflug analyzer. Fifty-five parameters derived from anterior and posterior corneal measurements were analyzed for each eye and a machine learning algorithm, the classification and regression tree, was used to classify the eyes into the 3 above-mentioned conditions. main outcome measures: The performance of the machine learning algorithm for classifying eye conditions was evaluated, and the curvature, elevation, pachymetric, and wavefront parameters were analyzed in each group and compared., Results: The discriminating rules generated with the automated decision tree classifier allowed for discrimination between normal and keratoconus with 100% sensitivity and 99.5% specificity, and between normal and forme fruste keratoconus with 93.6% sensitivity and 97.2% specificity. The algorithm selected as the most discriminant variables parameters related to posterior surface asymmetry and thickness spatial distribution., Conclusion: The machine learning classifier showed very good performance for discriminating between normal corneas and forme fruste keratoconus and provided a tool that is closer to an automated medical reasoning. This might help in the surgical decision before refractive surgery by providing a good sensitivity in detecting ectasia-susceptible corneas., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: To analyze and compare the relationship between anterior and posterior corneal shape evaluated by a tomographic system combining the Scheimpflug photography and Placido-disc in keratoconus and normal healthy eyes, as well as to evaluate its potential diagnostic value., Methods: Comparative case series including a sample of 161 eyes of 161 subjects with ages ranging from 7 to 66 years and divided into two groups: normal group including 100 healthy eyes of 100 subjects, and keratoconus group including 61 keratoconus eyes of 61 patients. All eyes received a comprehensive ophthalmologic examination including an anterior segment analysis with the Sirius system (CSO). Antero-posterior ratios for corneal curvature (k ratio) and shape factor (p ratio) were calculated. Logistic regression analysis was used to evaluate if some antero-posterior ratios combined with other clinical parameters were predictors of the presence of keratoconus., Results: No statistically significant differences between groups were found in the antero-posterior k ratios for 3-, 5- and 7-mm diameter corneal areas (p ≥ 0.09). The antero-posterior p ratio for 4.5- and 8-mm diameter corneal areas was significantly higher in the normal group than in the keratoconus group (p<0.01). The k ratio for 3, 5, and 7 mm was significantly higher in the keratoconus grade IV subgroup than in the normal group (p<0.01). Furthermore, significant differences were found in the p ratio between the normal group and the keratoconus grade II subgroup (p ≤ 0.01). Finally, the logistic regression analysis identified as significant independent predictors of the presence of keratoconus (p<0.01) the 8-mm anterior shape factor, the anterior chamber depth, and the minimal corneal thickness., Conclusions: The antero-posterior k and p ratios are parameters with poor prediction ability for keratoconus, in spite of the trend to the presence of more prolate posterior corneal surfaces compared to the anterior in keratoconus eyes.

Purpose: To analyze and compare the changes in visual function under mesopic and photopic conditions in different stages of keratoconus before and after Keraring intrastromal corneal ring segment (ICRS) implantation., Setting: Clinico San Carlos Hospital and Faculty of Optics and Optometry, Complutense University, Madrid, Spain., Design: Case series., Methods: Keratoconic eyes were evaluated under mesopic (0.1 to 0.2 candelas [cd]/m(2)) and photopic (85 cd/m(2)) conditions. LogMAR high-contrast corrected distance visual acuity (CDVA) and low-contrast CDVA were assessed using the Bailey-Lovie test and logarithmic contrast sensitivity, using the Pelli-Robson test., Results: The study evaluated 12 eyes with stage I keratoconus, 21 eyes with stage 2, and 14 eyes with stage 3. The mean change in photopic high-contrast CDVA was 0.16 logMAR ± 0.20 (SD) (P<.00001). Photopic low-contrast CDVA increased by a mean of 0.14 ± 0.26 logMAR (P=.0005), photopic contrast sensitivity by a mean of 0.09 ± 0.22 logMAR (P=.005), and mesopic high-contrast CDVA by a mean of 0.10 ± 0.26 logMAR (P=.03). There were no significant differences between stages. Surgery did not affect the mean changes in mesopic low-contrast CDVA or mesopic contrast sensitivity for any stage., Conclusions: Implantation of ICRS in keratoconic eyes increased photopic high-contrast CDVA, low-contrast CDVA, and contrast sensitivity. Under low luminance, the mean changes in high-contrast CDVA, low-contrast CDVA, and contrast sensitivity did not worsen after ICRS implantation performed 5.0 mm from the visual axis, despite the rings being partially superimposed on the mydriatic pupil., (Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.)

Up-to-date methods for diagnosis and monitoring of keratoconus are reviewed. Main advantages and drawbacks in early keratoconus diagnosis are analyzed for such methods as videokeratography, ultrasound corneal pachymetry, aberrometry, scanning projection corneal topography, confocal microscopy.