Staging of keratoconus indices regarding tomography, topography, and biomechanical measurements

Diagnostic ability of the corneal anterior and posterior surface area calculated by corneal modelling approach in early stage keratoconus patients

PURPOSE

To investigate the discrimination ability of the corneal anterior and posterior surface area between patients with keratoconus stage 1 and normal individuals.

METHODS

In this retrospective study, 116 eyes of 116 normal individuals and 366 eyes of 366 keratoconus patients were included. Keratoconus patients were divided into six groups according to the topographic keratoconus classification of Pentacam. Anterior and posterior surface data of sagittal (SM) and elevation maps (EM) were exported from Pentacam, and human corneal models were created employing the software utilizing the PyVista module of Python programming language. The anterior and posterior corneal surface area (a-CSA and p-CSA) of SM and EM were calculated by the software ranging from central 3 to 8mm diameter.

RESULTS

Anterior and posterior CSA values were higher in KC patients compared to normal individuals (p < 0.001). The p-CSA for SM and EM measured at the central 3mm was higher in patients with KC-1 compared to normal eyes (p = 0.002, p = 0.005, respectively), For both maps, a-CSA and p-CSA measured at the central 4 and 5mm were higher in KC-1 compared to normal individuals (p < 0.05). The highest area under the curve (AUC) values in the diagnosis patients with KC-1 were obtained from 3mm p-CSA for SM (AUC: 0.8338), 3mm p-CSA for EM (AUC: 0.7999), 4mm p-CSA for SM (AUC: 0.8531), 4mm p-CSA for EM (AUC:0.7948), 5mm p-CSA for SM (AUC: 0.8455), 5mm p-CSA for EM (AUC:0.7614).

CONCLUSION

The corneal surface area as a parameter, especially for central 3, 4, and 5mm, has a discrimination ability in diagnosing keratoconus disease and distinguishes normal eyes from KC-1 eyes.

Non-orthogonal spectacle correction for irregular astigmatism

PURPOSE

To investigate the potential improvement in visual acuity and subjective perception of image quality in patients with keratoconus using non-orthogonal correction (NOC) cylinder trial lenses where the steep and flat power meridians are set at angles less or greater than 90°.

METHODS

A set of NOC plano/cylindrical trial lenses, where the axes between the power meridians were set at a range of non-orthogonal angles, were used to refract 18 participants with keratoconus in whom 23 eyes were used for testing. Corneal elevation data were processed by bespoke MATLAB code from Pentacam Scheimpflug tomographer scans. Each participant first underwent subjective refraction using standard orthogonal cylinder trial lenses, and the monocular best-corrected visual acuity (BCVA, logMAR) was recorded for each eye. They then underwent a second subjective refraction using NOC cylinder trial lenses created for the study and completed a questionnaire to elicit their subjective appraisal of letter clarity and ghosting.

RESULTS

Fourteen (61%) eyes demonstrated an increase in objective BCVA with the NOC versus the orthogonal correction; seven (30%) eyes showed no change and in two (9%) eyes, the BCVA was slightly worse. Further, 87% and 79% experienced an increase in letter clarity and a reduction in ghosting, respectively, independent of changes in BCVA. The majority of non-orthogonal angles were in the range of 80°-85°, and it was possible to refine the cylinder and axis of the NOC further compared with the orthogonal correction. All but one of the participants said they would be interested in trying non-orthogonal spectacles if the opportunity arose.

CONCLUSIONS

Correcting irregular astigmatism in keratoconic individuals with non-orthogonal spectacle correction may provide benefit in terms of increased visual acuity, improvements in letter clarity and a reduction of ghosting effects. This type of correction has the potential to improve the overall quality of life for patients with keratoconus.

Smart decision support system for keratoconus severity staging using corneal curvature and thinnest pachymetry indices

BACKGROUND

This study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements.

METHODS

A clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience.

RESULTS

The performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality.

CONCLUSION

The developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting.

Keratectasia severity staging and progression assessment based on the biomechanical E-staging

Until recently, corneal topography has been the gold standard in detecting keratectasia and monitoring its progression. The recently introduced ABCD tomographic keratoconus staging system focuses on anterior ("A") and posterior ("B") radius of curvature, thinnest corneal thickness ("C"), best-corrected visual acuity with spectacles ("D") and is supplemented with the introduction of the biomechanical E-staging (BEST, "E"). The need for biomechanical staging arose from the fact of altered biomechanical characteristics of keratectasia in comparison to healthy corneas. Ectatic corneas usually exhibit a biomechanical weakening and greater deformation than healthy corneas when exposed to a biomechanical stressor such as a standardized air puff indentation as provided by the Corvis ST® (CST, Oculus, Wetzlar, Germany). The BEST is based on the linear term of the Corvis Biomechanical Index (CBI) and provides a biomechanical keratoconus severity staging and progression assessment within the CST software. This review traces the development of the BEST as an addition to the tomographic ABCD staging system and highlights its strengths and limitations when applied in daily practice for the detection, monitoring and progression assessment in keratectasia.

Scheimpflug-Derived Keratometric, Pachymetric and Pachymetric Progression Indices in the Diagnosis of Keratoconus: A Systematic Review and Meta-Analysis

Scheimpflug Pentacam Tomography is becoming crucial in the diagnosis and monitoring of keratoconus, as well as in pre- and post-corneal refractive care, but there are still some inconsistencies surrounding its evidence base diagnostic outcome. Therefore, this study aimed at employing meta-analysis to systematically evaluate the keratometric, pachymetric, and pachymetric progression indices used in the diagnosis of Keratoconus. The review protocol was registered with PROSPERO (Identifier: CRD4202310058) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. PubMed, MEDLINE, Web of Science, and EMBASE were used for data search, followed by a quality appraisal of the included studies using the revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2). Meta-analysis was conducted using the meta (6.5.0) and metafor (4.2.0) packages in R version 4.3.0, as well as Stata. A total of 32 studies were included in the analysis. All keratometry (K) readings (flattest meridian, K1; steepest meridian, K2, maximum, Kmax) were significantly steeper in keratoconic compared to normal eyes: [MD (95% CI)], K1 [2.67 (1.81; 3.52)], K1-back [-0.71 (-1.03; -0.39)], K1-front [4.06 (2.48; 5.63)], K2 [4.32 (2.89; 5.75)], K2-back [-1.25 (-1.68; -0.82)], K2-front [4.82 (1.88; 7.76)], Kmax [7.57 (4.80; 10.34)], and Kmean [2.80 (1.13; 4.47)]. Additionally, corneal thickness at the center, CCT [-61.19 (-73.79; -48.60)] and apex, pachy-apex [-41.86 (-72.64; -11.08)] were significantly thinner in keratoconic eyes compared to normal eyes. The pooled estimates for pachymetric progression index (PPI): PPImin [0.66 (0.43; 0.90)], PPImax [1.26 (0.87; 1.64)], PPIavg [0.90 (0.68; 1.12)], and Ambrosio relational thickness (ART): ARTmax [-242.77 (-288.86; -196.69)], and ARTavg [-251.08 (-308.76; -195.39)] revealed significantly more rapid pachymetric progression in keratoconic eyes than in normal eyes. The Pentacam Scheimpflug-derived keratometric, pachymetric, and pachymetric progression indices are good predictors in discriminating KC from normal eyes.

Comparing Repeatability and Agreement between Commonly Used Corneal Imaging Devices in Keratoconus

SIGNIFICANCE

Keratometry and pachymetry are important for diagnosis and monitoring of keratoconus. Many corneal imaging units exist, but comparison to determine repeatability and agreement is paramount for adequate keratoconus management in primary and secondary care.

PURPOSE

This study aimed to evaluate the repeatability and agreement of a Placido disc-based videokeratoscope (Melbourne, Victoria, Australia) used in primary care with spectral-domain optical coherence tomography (Optopol Technology, Zawiercie, Poland) and Scheimpflug corneal tomography (Oculus, Wetzlar, Germany) in secondary care.

METHODS

This was a prospective single-center study where one eye was randomized to have central corneal thickness;thinnest corneal thickness (TCT); and maximum, mean, steep, and flat keratometry (Kmax, Kmean, Ksteep, and Kflat, respectively), measured with all three devices. Three measurements were completed per device to assess intraobserver repeatability.

RESULTS

A total of 110 eyes from 110 patients with keratoconus were analyzed. Repeatability was best with the Pentacam for central corneal thickness, Kmax, Kmean, Ksteep, and Kflat parameters (precision, 9.21, 0.8, 0.38, 0.52, and 0.58). The Medmont had better repeatability than the Revo with Kmax, Kmean, Ksteep, and Kflat (precision, 1.41,1.35,1.43, and 1.59). Revo had the best repeatability with TCT (precision, 3.81). The intraclass correlation coefficient was >0.94 for all parameters in all devices. Agreement was generally poor between devices. However, there was good agreement between Pentacam and Medmont Kflat measurements ( P > .05).

CONCLUSIONS

Repeatability of keratometry parameters with the Pentacam and Medmont was greater than the Revo, suggesting a lower threshold for detecting change in anterior corneal parameters. The Revo had the greatest repeatability for TCT, suggesting a lower threshold for detecting thinning in disease progression and corneal-crosslinking safety. There was poor agreement between devices, and it is not recommended for them to be used interchangably.

Corneal thickness measurements with the RTVue, Casia-2, and Pentacam devices in patients with mild-to-moderate keratoconus: a comparative study

BACKGROUND

To compare the characteristics of corneal thickness measurements among the RTVue, Casia-2, and Pentacam in patients with mild-to-moderate keratoconus.

METHODS

We recruited 46 eyes of 46 patients diagnosed with mild-to-moderate keratoconus at our hospital between January and March 2022. The central corneal thickness (CCT) and thinnest corneal thickness (TCT) were measured using two optical coherence tomography (OCT) instruments (RTVue and Casia-2) and the more conventional Pentacam. Differences and correlations between the CCTs and TCTs, based on the device and influencing factors, were explored.

RESULTS

The CCTs were highly consistent among the groups (p = 0.434) and correlated with one another (p < 0.001). The TCTs measured by OCTs were thinner than those measured by the Pentacam (p < 0.001); however, all three devices were highly correlated (p < 0.001). The thinnest point location measurements with RTVue and Casia-2 differed significantly from the measurements with the Pentacam. Bland-Altman plots demonstrated a significant agreement between Pentacam and OCTs in TCT measurement (p < 0.001); the 95% limits of agreement were - 3.1 μm to + 33.1 μm for Pentacam and RTVue and - 8.6 μm to + 36.5 μm for Pentacam and Casia-2. RTVue and Casia-2 showed no difference in corneal thickness (p = 0.633) and thinnest point location measurement (p > 0.05). Multivariate analysis identified that the TCT measurement difference between the RTVue and Pentacam was related to the difference between the CCT and TCT (b = 0.490, 95% confidence interval [CI]: 0.033 to 0.948, p = 0.036), whereas the difference between the Casia-2 and Pentacam was related to the anterior radius for curvature (A) grade (b = 3.9, 95% CI: 1.753 to 6.074, p = 0.001), corneal pachymetry at the thinnest (C) grade (b = - 7.875, 95% CI: - 11.404 to - 4.346, p < 0.001), and the difference between the CCT and TCT (b = 0.425, 95% CI: 0.1 to 0.751, p = 0.012).

CONCLUSIONS

CCTs in patients with mild-to-moderate keratoconus were similar among all three devices, but the TCTs and the thinnest point locations were not. Furthermore, the TCT measurement differences between the OCT devices and the Pentacam were more pronounced in keratoconus cases with a steeper anterior surface, thicker TCTs, and a larger difference between the CCT and TCT.

TRIAL REGISTRATION

Number: 2021118-1. Retrospectively registered: September 01, 2021.

Analysis of Various Modalities for Intraocular Pressure Measurement in Relation to Keratoconus Severity in 246 Eyes of the Homburg Keratoconus Center

PURPOSE

Intraocular pressure (IOP) measurement may be difficult in keratoconus (KC) due to corneal protrusion and irregular astigmatism. This study aimed to assess which IOP measurement modality is least affected by KC severity.

METHODS

Data from 246 corneas of 246 patients with KC were retrospectively analyzed. KC stages were determined using the Topographic KC (TKC) and ABCD KC classifications derived from Pentacam (Oculus, Germany). IOP was measured using Goldmann applanation tonometry (GAT), Ocular Response Analyzer (ORA, Reichert Instruments, USA), and Corvis ST (CST, Oculus, Germany). Cronbach alpha (CA), analysis of variance with Bonferroni correction, Dunnett T3, and Pearson correlation were performed.

RESULTS

Using CA, the reliability of measurements using various modalities increased to 0.764 to 0.943 when excluding IOP Goldmann overall and in each KC stage (TKC and ABCD). Analysis of variance revealed significant differences between TKC and ABCD stages for almost all IOP modalities. The Bonferroni post hoc test showed significant differences between the measured IOP in earlier and advanced KC stages, except for the biomechanically CST-corrected IOP (bIOP). Pearson correlation analysis showed a significant correlation between IOP and thinnest corneal thickness (TCT) for all IOP modalities except bIOP.

CONCLUSIONS

CST-based bIOP seems to be best suited for IOP measurement in KC because it did not correlate with TCT in contrast to IOP measurements by ORA or GAT. The measurement results from GAT in patients with KC should be interpreted with care and always in view of corneal thickness. As a thumb rule, we suggest to add at least 2 mm Hg to the measured GAT value.

Fourier analysis on irregular corneal astigmatism using optical coherence tomography in various severity stages of keratoconus

PURPOSE

To investigate the diagnostic capability of Fourier indices in detecting clinical or subclinical keratoconus (KC).

DESIGN

Prospective cross-sectional study METHODS: : The study included 126 eyes with clinical KC (50 KC without any corneal scar, 50 KC with anterior corneal scar, and 26 KC with posterior scar having a history of acute corneal hydrops), 50 with topographic KC (without clinical signs), 50 with pre-topographic KC (normal topography without clinical signs), and 50 controls. Corneal tomographic data were obtained using anterior segment optical coherence tomography (OCT). Fourier analysis decomposed dioptric data from both anterior and posterior corneal surface into spherical, regular astigmatism, asymmetry, and higher-order irregularity components. The discriminating ability of the Fourier indices of pre-topographic KC, topographic KC, and clinical KC from controls were assessed after quantitative Fourier analysis of irregular corneal astigmatism.

RESULTS

Posterior asymmetry and higher-order irregularity components were significantly greater in pre-topographic KC eyes than those in controls (p<0.001 for both), with the highest area under the receiver operating characteristic curve (AUROC) of 0.778 and 0.709, respectively. The same was true for anterior asymmetry, posterior asymmetry, and posterior higher-order irregularity components in topographic KC (AUROC of 0.945, 0.941, and 0.893, respectively), whereas it was >0.948 for all Fourier components in clinical KC.

CONCLUSIONS

Fourier analysis using OCT can evaluate anterior and posterior corneal irregular astigmatism of various KC stages, from very mild to advanced, including severe cases with corneal scar. Irregular astigmatism indices from the posterior corneal surface showed the highest AUROC values in discriminating early KC stages.

Protocol for the diagnosis of keratoconus using convolutional neural networks

Keratoconus is the corneal disease with the highest reported incidence of 1:2000. The treatment's level of success highly depends on how early it was started. Subsequently, a fast and highly capable diagnostic tool is crucial. While there are many computer-based systems that are capable of the analysis of medical image data, they only provide parameters. These have advanced quite far, though full diagnosis does not exist. Machine learning has provided the capabilities for the parameters, and numerous similar scientific fields have developed full image diagnosis based on neural networks. The Homburg Keratoconus Center has been gathering almost 2000 patient datasets, over 1000 of them over the course of their disease. Backed by this databank, this work aims to develop a convolutional neural network to tackle diagnosis of keratoconus as the major corneal disease.

Reliability analysis of successive Corneal Visualization Scheimpflug Technology measurements in different keratoconus stages

BACKGROUND

This study assesses the reliability of successive corneal biomechanical response measurements by the Corneal Visualization Scheimpflug Technology (CST, Corvis ST^® , Oculus Optikgeräte, Wetzlar, Germany) in different keratoconus (KC) stages.

METHODS

A total of 173 eyes (15 controls: 15 eyes, and 112 KC patients: stages 1|1-2|2|2-3|3|3-4|4, n = 26|16|36|18|31|26|5 according to Topographical KC Classification, TKC) were repeatedly examined five times with the CST, each after repositioning the patient's head and re-adjusting the device. Tomographical analysis (Pentacam HR^® ; Oculus, Wetzlar, Germany) was performed once before and once after CST measurements. Outcome measures included (1) A1 velocity, (2) deformation amplitude (DA) ratio 2 mm, (3) integrated radius, (4) stiffness parameter A1 and (5) Ambrósio relational thickness to the horizontal profile (ARTh). The Corvis Biomechanical Index (CBI) is reported to be extracted out of these parameters. Mean values of the five measurements and Cronbach's α were calculated as a measure for reliability.

RESULTS

Ambrósio relational thickness to the horizontal profile and SPA1 were significantly higher in controls (534|123) compared to TKC1 (384|88), TKC2 (232|66), TKC3 (152|55) and TKC4 (71|27; p < 0.0001). The other parameters were similar in controls and TKC1 (A1 velocity: 0.148|0.151 m/s; integrated radius: 8.2|8.6 mm^-1 ), but significantly higher in TKC stages 2 to 4 (DA ratio 2 mm: 5.5|6.3|8.0; A1 velocity: 0.173|0.174|0.186 m/second; integrated radius: 10.9|12.8|19.0 mm^-1 ; p < 0.0001). All parameters proved to be highly reliable (Cronbach's α ≥ 0.834) and the corneal tomography remained unaffected.

CONCLUSIONS

The individual parameters included in the CBI (consisting of ARTh, SPA1, DA ratio 2 mm, A1 velocity and integrated radius) are highly reliable but differ KC stage-dependently.

Prospective one year study of corneal biomechanical changes following high intensity, accelerated cornea cross-linking in patients with keratoconus using a non-contact tonometer

PURPOSE

To characterize corneal biomechanical properties utilizing a dynamic ultra-high-speed Scheimpflug camera equipped with a non-contact tonometer (CorVis ST, CST) in keratoconic corneas following continuous high intensity, high irradiance corneal cross-linking.

DESIGN

Prospective longitudinal single-centre study at a tertiary referral center.

METHODS

Corneal biomechanical properties were measured in patients with progressive keratoconus undergoing high intensity (30 mW/cm2), high irradiance (5.4 J/cm2), accelerated corneal cross-linking with continuous exposure to ultraviolet-A for 4 min. CST was used to assess corneal biomechanical properties pre-operatively and at 1, 3, 6 and 12 months post-operatively. CST output videos were further analyzed using several previously reported algorithms.

RESULTS

A total of 25 eyes of 25 participants were examined. The mean age of participants was 20.9 ± 5.3 years; 56% were male and 80% were of Māori or Pacific Island origin. Energy absorbed area (mN mm), was the only significantly changed parameter compared to baseline at all time points measuring 3.61 ± 1.19 preoperatively, 2.81 ± 1.15 at 1 month (p = 0.037), 2.79 ± 0.81 (p = 0.033) at 3 months, 2.76 ± 0.95 (p = 0.028) at 6 months and 2.71 ± 1.18 (p = 0.016) at 12 months.

CONCLUSIONS

The significant difference between the pre and post-operative energy absorbed area appears to reflect changes in corneal viscous properties that occur following corneal cross-linking.

Optical Quality in Keratoconus Is Associated With Corneal Biomechanics

PURPOSE

To evaluate the correlations between corneal biomechanical indices from dynamic Scheimpflug assessment and optical quality assessed as higher-order aberrations (HOAs) using a Hartmann-Shack ocular wavefront sensor in patients with keratoconus (KC).

METHODS

In this prospective, observational case series, the eyes with KC or KC suspect (KCS) from Osaka University Hospital, Osaka, Japan, were analyzed. Corneal biomechanical assessment was performed using Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany), and ocular wavefront aberrations were measured using the KR-1W (Topcon Corp, Tokyo, Japan). Correlations between the biomechanical indices and ocular HOAs were assessed. Corneal biomechanical indices included the deformation amplitude ratio within 2 mm, integrated radius, stiffness parameter at the first applanation, and the linear Corvis Biomechanical Index. Wavefront data of the central 4-mm region were expanded up to the sixth order of Zernike polynomials. The magnitudes of trefoil, coma, tetrafoil, secondary astigmatism, and spherical aberration were calculated by Zernike vector analysis and then used as ocular HOA parameters along with total HOAs.

RESULTS

Thirty-four KC eyes and 37 KCS eyes were included. KC eyes showed significant correlations between ocular HOAs and biomechanics, whereas there were few significant correlations in KCS eyes. In KC eyes, deformation amplitude ratio within 2 mm, integrated radius, and Corvis Biomechanical Index beta showed stronger correlations with coma among the wavefront parameters.

CONCLUSIONS

Corneal biomechanical indices correlated with ocular HOAs in patients with KC. In particular, there was a strong association with the increase in coma caused by inferosuperior asymmetry of the shape of the cornea in patients with KC.

[Stage-appropriate treatment of keratoconus]

Keratoconus (KC) is a progressive cone-shaped corneal protrusion that causes paracentral thinning at the apex of the cone and typically occurs asymmetrically on both sides. After a careful anamnesis and classification of the degree of severity a targeted treatment appropriate to the stage of the disease is available. If the visual acuity is no longer sufficient, rigid gas-permeable contact lenses (CL) are fitted by a specialist. Riboflavin UVA cross-linking (CXL) is recommended in cases of progression and visual acuity that is still useful for the patient. Intracorneal ring segments (ICRS) are indicated for CL intolerance in cases of reduced visual acuity and a clear central cornea. If the stage is more advanced, deep anterior lamellar keratoplasty (DALK) or penetrating keratoplasty (PKP) is recommended. A PKP is contraindicated in acute KC but deep stromal sutures for readaptation of the Descemet tear with gas filling of the anterior chamber can considerably shorten the course. Almost no other eye disease is nowadays as easily accessible for an early instrument-based diagnosis and stage-appropriate treatment as KC.

Tomographic and aberrometric assessment of first-time diagnosed paediatric keratoconus based on age ranges: a multicentre study

PURPOSE

To describe paediatric keratoconus (KC) patients by tomographic and aberrometric characteristics at first diagnosis, in a multicentre study.

METHODS

We included 278 eyes from 139 paediatric patients, with a first tomographic diagnosis (Pentacam^® ) of KC prior to 18 years old. KC classification was based on the KC Index (≥ 1.07) and Topographic Keratoconus Classification (TKC ≥ 1). Patients were divided based on age ranges (14 and under and over 14 years) and gender. Statistical analysis was performed with SPSS statistics 25.0. ANOVA factor was carried out comparing to compare groups.

RESULTS

278 eyes were screened, and 230 eyes were diagnosed with paediatric KC. Mean age was 15.48 ± 2.33 (6 to 18) years. We found differences in terms of TKC (2.08 ± 0.89 and 2.38 ± 0.82, p < 0.05) and spherical aberration (-0.71 ± 0.97 and -1.07 ± 1.36, p < 0.05) among the 14 years old or under and above 14 years old groups, respectively. Overall, female paediatric KC patients presented a more severe TKC, Belin Ambrosio Display, maximum keratometry, asphericity and primary and secondary coma aberrations compared to male KC patients. We observed a correlation between CDVA and asphericity (r = 0.71, p < 0.01), as well as between CDVA and spherical aberration (r = 0.69, p < 0.01).

CONCLUSION

Our findings revealed that the debut of KC is usually in a moderate to advanced stage in the paediatric population at first diagnosis, particularly in female patients. Corneal tomography should be systematically performed in children with recent onset of corneal astigmatism.

Tomographically normal partner eye in very asymmetrical corneal ectasia: biomechanical analysis

PURPOSE

To point out the biomechanical changes of the topographically and tomographically normal partner eye (NPE) in patients with very asymmetrical corneal ectasia.

SETTING

Department of Ophthalmology, Saarland University Medical Center in Homburg/Saar, Germany.

DESIGN

Retrospective study.

METHODS

The topographical and tomographical results of the NPE were assessed using the Pentacam HR and the biomechanical corneal properties using the Ocular Response Analyzer (keratoconus match index [KMI], corneal hysteresis [CH], and corneal resistance factor [CRF]) and the Corvis ST (topographic biomechanical index [TBI] and Corvis biomechanical index) and compared those results with a normal control group (CG).

RESULTS

The clinical records of 26 patients recruited from the Homburg Keratoconus Center diagnosed with a very asymmetrical corneal ectasia were reviewed. The NPE (8.5 ± 1.5 mm Hg) showed a significantly more pathological CH (P < .001) compared with the CG. The CRF was also significantly more pathological (P = .04) for the NPE (8.3 ± 1.5 mm Hg) compared with the CG. The NPE (0.62 ± 0.32) showed a nonsignificant (P = .08) more pathological KMI compared with the CG. Nineteen (73.1%) of 26 NPE had a KMI less than 0.72 and were considered pathological. Compared with the CG, the TBI of the NPE (0.19 ± 0.25) did not differ significantly overall (P = .57). However, 5 (19.2%) of 26 eyes had a TBI more than 0.29 and were considered pathological.

CONCLUSIONS

Topographically and tomographically NPEs in very asymmetrical corneal ectasia frequently showed biomechanical changes. This should be considered before planning any type of refractive corneal surgery in such patients.

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.

[Keratoconus detection and classification from parameters of the Corvis®ST : A study based on algorithms of machine learning]

BACKGROUND AND OBJECTIVE

In the last decades increasingly more systems of artificial intelligence have been established in medicine, which identify diseases or pathologies or discriminate them from complimentary diseases. Up to now the Corvis®ST (Corneal Visualization Scheimpflug Technology, Corvis®ST, Oculus, Wetzlar, Germany) yielded a binary index for classifying keratoconus but did not enable staging. The purpose of this study was to develop a prediction model, which mimics the topographic keratoconus classification index (TKC) of the Pentacam high resolution (HR, Oculus) with measurement parameters extracted from the Corvis®ST.

PATIENTS AND METHODS

In this study 60 measurements from normal subjects (TKC 0) and 379 eyes with keratoconus (TKC 1-4) were recruited. After measurement with the Pentacam HR (target parameter TKC) a measurement with the Corvis®ST device was performed. From this device 6 dynamic response parameters were extracted, which were included in the Corvis biomechanical index (CBI) provided by the Corvis®ST (ARTh, SP-A1, DA ratio 1 mm, DA ratio 2 mm, A1 velocity, max. deformation amplitude). In addition to the TKC as the target, the binarized TKC (1: TKC 1-4, 0: TKC 0) was modelled. The performance of the model was validated with accuracy as an indicator for correct classification made by the algorithm. Misclassifications in the modelling were penalized by the number of stages of deviation between the modelled and measured TKC values.

RESULTS

A total of 24 different models of supervised machine learning from 6 different families were tested. For modelling of the TKC stages 0-4, the algorithm based on a support vector machine (SVM) with linear kernel showed the best performance with an accuracy of 65.1% correct classifications. For modelling of binarized TKC, a decision tree with a coarse resolution showed a superior performance with an accuracy of 95.2% correct classifications followed by the SVM with linear or quadratic kernel and a nearest neighborhood classifier with cubic kernel (94.5% each).

CONCLUSION

This study aimed to show the principle of supervised machine learning applied to a set-up for the modelled classification of keratoconus staging. Preprocessed measurement data extracted from the Corvis®ST device were used to mimic the TKC provided by the Pentacam device with a series of different algorithms of machine learning.

Repeatability of corneal and epithelial thickness measurements with anterior segment optical coherence tomography in keratoconus

PURPOSE

To investigate the repeatability in corneal thickness (CT) and epithelial thickness (ET) measurements using spectral domain anterior segment optical coherence tomography (AS-OCT, REVO NX, Optopol) in keratoconus, and examine the effect of corneal crosslinking (CXL) on repeatability.

METHODS

A cross-sectional study of 259 eyes of 212 patients with keratoconus attending the corneal disease clinic at a university hospital tertiary referral center were enrolled. Two groups were analysed: eyes with no prior history of CXL (Group A) and eyes with prior CXL (Group B). Repeatability of measurements was assessed using the intraclass correlation coefficient (ICC) and coefficient of variation (CV).

RESULTS

In Group A, central corneal thickness (CCT) was 472.18 ± 45.41μm, and the ET was found to be the thinnest in the inferior-temporal aspect at 51.79 ± 5.97μm and thickest at the superior-nasal aspect at 56.07 ± 5.70μm. In Group B, CCT was 465.11± 42.28μm, and the ET was the thinnest at the inferior-temporal aspect at 50.63 ± 5.52μm and thickest at the superior aspect at 56.80 ± 6.39μm. When evaluating CT measurements, ICC was above 0.86 and 0.83 for Group A and Group B respectively. When evaluating ET measurements, ICC was above 0.82 for both groups. CXL had no statistically significant impact on the repeatability of measurements.

CONCLUSIONS

AS-OCT provides repeatable CT and ET measurements in the central and peripheral cornea in patients with keratoconus. Repeatability is not affected by a history of CXL.

Corneal biomechanical parameters in keratoconus eyes with abnormal elevation on the back corneal surface only versus both back and front surfaces

Corneal biomechanical parameters were compared in 100 keratoconus eyes with abnormal elevation on the back corneal surface only (group 1), versus both the back and front surfaces (group 2). Scheimpflug tomography with Pentacam HR, corneal biomechanical assessments using Corvis ST and Ocular Response Analyzer (ORA) and corneal epithelium thickness maps using anterior segment optical coherence tomography were assessed. There were no significant differences in the IOP measured using Corvis ST and ORA, age or sex between the two groups. Statistically significant differences were found in all corneal shape parameters and all new parameters of Corvis ST: corneal stiffness parameter at first applanation (SP-A1), integrated inverse radius (IR) and deformation amplitude ratio (DAR)) between groups (p < 0.001). The classic parameters of ORA including corneal hysteresis (CH) and corneal resistance factor (CRF) were about 1.00 mmHg higher in group 1 (p < 0.001). In conclusion, keratoconus eyes with abnormal elevation limited to the back corneal surface have lower grade, stiffer corneal biomechanical parameters and less asymmetric shape. This is consistent with progressive biomechanical weakening from the first detectable back surface elevation to manifestation on the front surface as the severity overwhelms the ability of the epithelium to compensate.

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.].

Development of a classification system based on corneal biomechanical properties using artificial intelligence predicting keratoconus severity

Background

To investigate machine-learning (ML) algorithms to differentiate corneal biomechanical properties between different topographical stages of keratoconus (KC) by dynamic Scheimpflug tonometry (CST, Corvis ST, Oculus, Wetzlar, Germany). In the following, ML models were used to predict the severity in a training and validation dataset.

Methods

Three hundred and eighteen keratoconic and one hundred sixteen healthy eyes were included in this monocentric and cross-sectional pilot study. Dynamic corneal response (DCR) and corneal thickness related (pachymetric) parameters from CST were chosen by appropriated selection techniques to develop a ML algorithm. The stage of KC was determined by the topographical keratoconus classification system (TKC, Pentacam, Oculus). Patients who were classified as TKC 1, TKC 2 and TKC 3 were assigned to subgroup mild, moderate, and advanced KC. If patients were classified as TKC 1–2, TKC 2–3 or TKC 3–4, they were assigned to subgroups according to the normative range of further corneal indices (index of surface variance, keratoconus index and minimum radius). Patients classified as TKC 4 were not included in this study due to the limited amount of cases. Linear discriminant analysis (LDA) and random forest (RF) algorithms were used to develop the classification models. Data were divided into training (70% of cases) and validation (30% of cases) datasets.

Results

LDA model predicted healthy, mild, moderate, and advanced KC eyes with a sensitivity (S_n)/specificity (S_p) of 82%/97%, 73%/81%, 62%/83% and 68%/95% from a validation dataset, respectively. For the RF model, a S_n/S_p of 91%/94%, 80%/90%, 63%/87%, 72%/95% could be reached for predicting healthy, mild, moderate, and advanced KC eyes, respectively. The overall accuracy of LDA and RF was 71% and 78%, respectively. The accuracy for KC detection including all subgroups of KC severity was 93% in both models.

Conclusion

The RF model showed good accuracy in predicting healthy eyes and various stages of KC. The accuracy was superior with respect to the LDA model. The clinical importance of the models is that the standalone dynamic Scheimpflug tonometry is able to predict the severity of KC without having the keratometric data.

Trial registration

NCT04251143 at Clinicaltrials.gov, registered at 12 March 2018 (Retrospectively registered).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40662-021-00244-4.

Measurement of In Vivo Biomechanical Changes Attributable to Epithelial Removal in Keratoconus Using a Noncontact Tonometer

PURPOSE

To compare the biomechanical properties of the cornea after epithelial removal in eyes with keratoconus undergoing corneal cross-linking.

METHODS

Prospective interventional case series at a university hospital tertiary referral center. Corneal biomechanical properties were measured in patients with keratoconus undergoing corneal cross-linking, immediately before and after epithelial debridement by using a dynamic ultrahigh-speed Scheimpflug camera equipped with a noncontact tonometer.

RESULTS

The study comprised 45 eyes of 45 patients with a mean age of 19.6 ± 4.9 years (range 14-34). The cornea was found to be 23.7 ± 15.7 μm thinner after epithelial removal (P < 0.01). Corneal stiffness was reduced after epithelial removal as demonstrated by a significant decrease of parameters such as stiffness parameter A1 (12.31, P < 0.01), stiffness parameter-highest concavity (2.25, P < 0.01), A1 length (0.13 mm, P = 0.04), highest concavity radius of curvature (0.26 mm, P = 0.01), highest concavity time (0.22 ms, P = 0.04) and an increase in A1 velocity (-0.01 m/s, P = 0.01), A1 deformation amplitude (-0.03 mm, P ≤ 0.01), A1 deflection length (-0.32 mm, P < 0.01), A2 deformation amplitude (-0.03 mm, P = 0.01), and A2 deflection length (-1.00 mm, P < 0.01). There were no significant differences in biomechanical intraocular pressure (0.15 mm Hg, P = 0.78), deformation amplitude (0.03, P = 0.54), maximum inverse radius (-0.01 mm, P = 0.57), and whole eye movement length (-0.02 mm, P = 0.12).

CONCLUSIONS

Dynamic ultrahigh-speed Scheimpflug camera equipped with a noncontact tonometer offers an alternative method for in vivo measurements of the epithelial layer's contribution to corneal biomechanical properties. Our results suggest that corneal epithelium may play a more significant role in corneal biomechanical properties in patients with keratoconus than previously described.

Repeatability and agreement of biometric measurements using spectral domain anterior segment optical coherence tomography and Scheimpflug tomography in keratoconus

Purpose

To compare the repeatability and agreement in biometric measurements using Spectral Domain Anterior Segment OCT (AS-OCT, REVO-NX, Optopol) and Scheimpflug tomography (Pentacam-AXL, Oculus) in keratoconus.

Methods

Prospective case series at a university hospital tertiary center. Axial length (AL), anterior chamber depth (ACD), central corneal thickness (CCT), and thinnest corneal thickness (TCT) were measured using both devices in patients with keratoconus. Three groups were analyzed: eyes with no prior crosslinking or contact lens wear (Group A), eyes with prior crosslinking (Group B), and eyes with prior contact lens wear (Group C). Repeatability and agreement of measurements were analyzed.

Results

The study comprised of 214 eyes of 157 subjects. In Group A (n = 95 eyes), Group B (n = 86 eyes), and Group C (n = 33 eyes), intraclass correlation coefficient (ICC) was higher than 0.90 for all examined parameters, except for ACD readings in Group A with the REVO-NX (ICC = 0.83). Differences in ACD, TCT, and CCT were significantly different between the two devices for Groups A, B and C (p<0.05). AL measurements differed significantly in Groups A and B (p<0.05) but not in Group C (p = 0.18). Repeatability did not vary significantly between Groups A, B, or C in any parameter with both devices (p>0.05). There was poor agreement between the two devices across all parameters (p<0.05).

Conclusions

Both devices demonstrated good repeatability but poor agreement across AL, ACD, CCT and TCT measurements. There was no significant difference in repeatability in virgin eyes compared to eyes with prior crosslinking or contact lens wear, however, the interchangeable use of the two devices is not recommended.

Structural changes in the corneal subbasal nerve plexus in keratoconus

BACKGROUND

Corneal confocal microscopy (CCM) allows visualizing slightest alterations within the corneal subbasal nerve plexus (SNP). Recent CCM studies based on the analysis of three-five CCM images per eye assumed a reduced corneal nerve fibre length (CNFL) in keratoconus (KC).

METHODS

The SNP of KC patients (n = 23, 13 contact lens wearing, 10 noncontact lens wearing) and patients without KC (n = 16) was examined by 10 CCM images of one eye per patient. The CNFL per frame area was calculated, and the SNP tortuosity was quantified by measuring (a) the amplitude of the curves and (b) the area under the curve (AUC) formed by the SNP.

RESULTS

Analysing 390 non-overlapping confocal images revealed the CNFL (mm/mm² ) to be significantly lower in KC (16.4 ± 1.9 mm/mm² ) than in healthy corneae (23.8 ± 3.3 mm/mm² , p < 0.0001; mean ± SD; p-value calculated using the Mann-Whitney U-test), without a difference between contact lens wearing and noncontact lens wearing KC patients (p = 0.4). Amplitudes and AUCs analysed as median with 25th and 75th percentile were significantly increased in KC (amplitude 33/23/41 µm and AUC 2839/1545/3444 µm² ) compared to healthy corneae (amplitude 24/18/28 µm and AUC 1870/1193/2327 µm² , p < 0.0001).

CONCLUSIONS

Corneal confocal microscopy (CCM) visualizes slightest alterations within the SNP in KC including (a) a significantly lower CNFL and (b) an enhanced winding course of the SNP. The significantly lower CNFL observed in KC may support the hypothesis of a neurodegenerative aspect of the disease and might be a measure to be correlated with the severity and progression of the disease.

Correlation Between Corneal Biomechanical Indices and the Severity of Keratoconus

PURPOSE

To investigate the correlations between the biomechanical indices determined in Scheimpflug-based corneal biomechanical assessments and the severity of keratoconus (KC) based on corneal tomographic assessments in patients with different stages of KC.

METHODS

Fifty-three patients who presented with clinical KC in 1 eye and KC suspect in the fellow eye were included. Corneal tomographic and biomechanical assessments were performed using the Pentacam HR and Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany). Correlations between the tomographic indices and biomechanical indices were assessed, including the anterior radius of curvature (ARC) and posterior radius of curvature (PRC) at a 3.0-mm optical zone and the thinnest pachymetry (Tmin), deformation amplitude ratio max 2 mm (DAR2mm), integrated radius, stiffness parameter at the first applanation, and linear Corvis Biomechanical Index (beta).

RESULTS

DAR2mm correlated negatively with ARC (R = -0.722), PRC (R = -0.677), and Tmin (R= -0.650) (P < 0.001 for all). Integrated radius correlated negatively with ARC (R = -0.700), PRC (R = -0.668), and Tmin (R= -0.648) (P < 0.001 for all). Stiffness parameter at the first applanation correlated positively with ARC (R = 0.622), PRC (R = 0.601), and Tmin (R = 0.703) (P < 0.001 for all). The Corvis Biomechanical Index beta correlated negatively with ARC (R = -0.754), PRC (R = -0.755), and Tmin (R= -0.765) (P < 0.001 for all).

CONCLUSIONS

Corneal biomechanical indices correlated with corneal tomographic parameters in patients with KC. These findings support the possibility of developing biomechanical-based staging classification for KC in combination with topographic or tomographic indices.

Keratoconus staging by decades: a baseline ABCD classification of 1000 patients in the Homburg Keratoconus Center

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.

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.

Reproducibility, and repeatability of corneal topography measured by Revo NX, Galilei G6 and Casia 2 in normal eyes

PURPOSE

To test the repeatability and reproducibility of the topography module in posterior segment spectral domain optical coherence tomography with Revo NX (new device) and to compare keratometry values obtained by a Scheimpflug tomography (Galilei G6) and a swept source OCT (Casia 2).

METHODS

In this prospective study, healthy subjects with nonoperated eyes had their central corneal thickness (CCT), anterior and posterior K1/K2 corneal power measured with the new device. Two operators made 6 measurements on the new device to check intraobserver repeatability and reproducibility, and measurement on Casia 2 and Galilei G6. Bland-Altman plots were used to assess the agreement between the devices for each analyzed variable.

RESULTS

94 eyes (94 patients) were studied. All devices produced significantly different mean CCT, the highest for Galilei 569.13±37.58 μm followed by Casia 545.00 ±36.15 μm and Revo 537.39±35.92 μm. The mean anterior K1 was 43.21 ± 1.37 for Casia 2 43.21 ± 1.55 for Revo NX and 43.19 ± 1.39 for Galilei G6, and the differences were insignificant p = 0.617. The posterior K1 for Revo NX was -5.77 ± 0.25 whereas for Casia 2 it was -5.98±0.22 and for Galilei G6-6.09±0.28 D p< 0.0001. The Revo NX showed intraclass correlation coefficient ranging from 0.975 for the posterior K2 surface, and 0.994 for anterior K1 and 0.998 for CCT.

CONCLUSIONS

Revo NX is independent of the user and offers a high level of repeatability for the anterior and posterior cornea. The wide range of differences between the devices suggests they should not be used interchangeably.

Hypothyroidism is Not Associated with Keratoconus Disease: Analysis of 626 Subjects

Purpose

To analyze the association between hypothyroidism and keratoconus, we examined blood thyroid hormone levels and corneal tomographic parameters in healthy subjects and patients with keratoconus.

Methods

We included 626 subjects (304 left eyes, 49%; 431 males, 69%; age 38.4 ± 14.3 y). Patients with keratoconus were from our Homburg Keratoconus Center (HKC) (n = 463); patients with hypothyroidism were from the Department of Internal Medicine of Saarland Medical University, Homburg/Saar, Germany (n = 75); and healthy subjects were from the Department of Ophthalmology of Saarland University Medical Center (n = 88). We included only one randomly selected eye of each subject and the first examination data.

Exclusion criteria

Previous thyroid medication, previous ocular surgery, and patients with suspected keratoconus (topographic keratoconus classification, [TKC]: 0 < 1). Patient eyes were classified (TKC) with dedicated, instrument-based, keratoconus detection software provided with the Pentacam. TKC = 0 was considered “normal,” and TKCs ≥ 1 were considered keratoconus. Subjects were also classified as euthyroid or hypothyroid, based on blood thyroid hormone status (i.e., TSH, FT3, and FT4). A multiple logistic linear regression model was constructed to determine the effects of age (covariate), gender, and hypothyroidism (effect sizes) on “TKC-positive” disease.

Results

The significance levels for a constant parameter, sex, thyroid condition, and age were p < 0.0001, p < 0.0001, p < 0.0001, and p=0.003, respectively. The odds ratios for age, sex, and hypothyroidism were 0.98, 3.05, and 3.34, respectively. Male sex and a euthyroid condition had significantly positive, clinically relevant effects, and age had a significantly negative, but clinically irrelevant effect on the estimated TKC index.

Conclusions

Keratoconus appeared to occur more often in patients classified as euthyroid than in patients with hypothyroidism. Thus, hypothyroidism alone could not support the development of keratoconus. Based on these results, it should not be mandatory to screen patients with hypothyroidism for keratoconus or patients with keratoconus for hypothyroidism.

Assessment of corneal biomechanical parameters in healthy and keratoconic eyes using dynamic bidirectional applanation device and dynamic Scheimpflug analyzer

PURPOSE

To investigate corneal biomechanical parameters in healthy and keratoconic eyes using the Ocular Response Analyzer dynamic bidirectional applanation device (ORA) and the Corvis ST dynamic Scheimpflug analyzer (CST).

SETTING

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

DESIGN

Prospective, monocentric, case-control study.

METHODS

Corneal biomechanical parameters were obtained in 60 eyes of 60 healthy participants (Group I) and 60 eyes of 60 keratoconus patients (Group II) with different grades of severity using the ORA and the CST. Participants were matched by age (Group I: 38.3 years ± 12.8 [SD], Group II: 37.3 ± 11.2 years) and intraocular pressure (Group I: 13.7 ± 1.7 mm Hg, Group II: 13.6 ± 1.5 mm Hg).

RESULTS

For the ORA, the receiver operating characteristic curve analysis showed an area under the curve (AUC) of 0.950 for the keratoconus score, a sensitivity of 87% and a specificity of 93%. The AUC for the corneal resistant factor and corneal hysteresis was 0.930 and 0.868 with a sensitivity of 87% and a specificity of 87%, and sensitivity of 80% and a specificity of 80%, respectively. For the CST, the corneal biomechanical index showed the highest AUC (0.977) with a sensitivity of 97% and a specificity of 98%. The AUC of integrated radius (0.974; 90% sensitivity, 93% specificity) was followed by maximum inverse radius (0.962; 92% sensitivity, 93% specificity). Most parameters were able to discriminate healthy eyes from different keratoconus stages and early stages of keratoconus from moderate stages.

CONCLUSION

Both devices allowed for good differentiation between healthy eyes and keratoconic eyes and between different severity grades of keratoconus. Several parameters of ORA and CST revealed high sensitivity and specificity values for keratoconus detection.

Improving precision for detecting change in the shape of the cornea in patients with keratoconus

To investigate a method for precision analysis to discriminate true corneal change from measurement imprecision in keratoconus (KC). Thirty patients with KC and 30 healthy controls were included. Coefficients of repeatability and limits of agreement (LOA) were compared using multiple measurements for inter-observer and inter-device agreement with the Pentacam HR, Orbscan IIz, and Tomey Casia SS-1000. Correlation of repeated measurements was evaluated using a linear mixed effect model (also called random effect model). A formula was derived for the theoretical expected change in precision and compared with measured change. Correlation between measurements from the same eye was small (R = 0.13). The 99.73% LOA (3 SD) of the mean of three measurements, provided better precision than 95% LOA (2 SD) of single cut-off values as expected from statistical theory for uncorrelated measurements for evidence of a significant change in corneal shape in patients with keratoconus. This enabled the determination of cut-off values for the detection of true change in corneal shape. The mean of three repeated measurements will provide better precision when there is minimal correlation. Three (rather than two) standard deviations provides a precise estimate of the LOA within or between observers and can be used as a reliable measure for identifying stage-independent corneal shape changes (progression) in keratoconus.

Comparison of Corneal Deformation Parameters in Keratoconic and Normal Eyes Using a Non-contact Tonometer With a Dynamic Ultra-High-Speed Scheimpflug Camera

PURPOSE

To evaluate and compare biomechanical properties in normal and keratoconic eyes using a dynamic ultra-high-speed Scheimpflug camera equipped with a non-contact tonometer (Corvis ST; Oculus Optikgeräte GmbH, Wetzlar, Germany).

METHODS

This retrospective study evaluated 89 eyes (47 normal, 42 keratoconic) and a validation arm of 72 eyes (33 normal, 39 keratoconic) using the Corvis ST. A diagnosis of keratoconus was established by clinical findings confirmed by topography and tomography. Dynamic corneal response parameters collected by the Corvis ST (A1 velocity, deformation amplitude [DA], DA Ratio Max 1mm, and Max Inverse Radius) and a stiffness parameter at first applanation (SP-A1) were incorporated into a novel logistic regression equation (DCR index). Area under the receiver operating curve (AUC) was used to assess the sensitivity and specificity of the DCR index.

RESULTS

DA, DA Ratio Max 1mm, Max Inverse Radius, and SP-A1 were each found to be statistically significantly different between normal and keratoconic eyes (Mann-Whitney test [independent samples]; P = .0077, < .0001, < .0001, and < .0001, respectively; significance level: P < .05). DCR index demonstrated high sensitivity, specificity, and overall correct detection rate (92.9%, 95.7%, and 94.4%, respectively; AUC = 98.5). The sensitivity and overall correct detection rate improved when eyes with Topographical Keratoconus Classification grades (TKC) greater than 0 were reevaluated (from 92.9% to 96.6% and from 94.4% to 96.1%, respectively).

CONCLUSIONS

Combining multiple biomechanical parameters (A1 velocity, DA, DA Ratio Max 1mm, Max Inverse Radius, and SP-A1) into a logistic regression equation allows for high sensitivity and specificity for distinguishing keratoconic from normal eyes. [J Refract Surg. 2017;33(9):625-631.].

Asymmetry between Left and Right Eyes in Keratoconus Patients Increases with the Severity of the Worse Eye

PURPOSE

To evaluate whether the inter-eye asymmetry of keratoconus (KC) patients is different from a healthy control group and to investigate how asymmetry changes with increasing severity of the disease.

METHODS

In this retrospective study, we included both eyes of 350 patients with KC (age 35 ± 13 years) and 68 candidates planned for refractive surgery (control group, age 37 ± 11 years). Inclusion criteria for the KC group were keratoconus in at least one eye with Pentacam Topographical Keratoconus Classification (TKC) of at least 0.5. Patients eligible for refractive surgery in both eyes were included in the control group. Corneal tomography as well as Ocular Response Analyzer measurements were compared between both groups. Subgroup analysis was performed with respect to the TKC staging. Asymmetry was provided as worse eye (defined by higher TKC) minus fellow eye.

RESULTS

In the KC group, both eyes showed the same TKC staging in 30.6%, a difference of one stage in 34.0% and of two stages in 24.6% of the patients. The inter-eye asymmetry in the keratoconus group was significantly larger than that in the control group. Corneal power showed an asymmetry of 3.8 ± 4.0 D in keratoconus eyes versus 0.22 ± 0.17 D in the control group. Central corneal thickness (CCT) asymmetry was 34 ± 30 µm versus 6 ± 5 µm, respectively. The Keratoconus Match Index showed an asymmetry of 0.40 ± 0.35 versus 0.15 ± 0.14. The difference between both eyes increased with increasing TKC of the worse eye.

CONCLUSIONS

Inter-eye asymmetry is larger in keratoconus than in normal eyes, and it increases with keratoconus severity in the worse eye.

Endothelial alterations in 712 keratoconus patients

PURPOSE

To investigate the effect of the severity of keratoconus on the corneal endothelium using specular microscopy.

METHODS

Seven hundred and twelve eyes from the Homburg Keratoconus Center (HKC) database were included in this retrospective study. Corneal endothelium was evaluated using the Tomey EM-3000 specular microscope. Keratoconus-related topographic and tomographic data were obtained from Scheimpflug-based tomography (Oculus Pentacam^® HR). Eyes were classified into stages 0 (healthy) to 4 (severe keratoconus) according to the Topographic Keratoconus Classification (TKC). Subgroups were analysed based on contact lens (CL) type (none/rigid/soft).

RESULTS

The frequencies of keratoconus stages 0/1/2/3/4 according to TKC were 169/94/206/166/77. The endothelial cell density (ECD) for the endothelial cell area for TKC 0/1/2/3/4 was 2611/2624/2557/2487/2401 cells per mm² and the coefficient of variation (CV) was 40.9/40.0/41.6/46.2/49.0%, respectively. The more severe the keratoconus stage, the lower the endothelial cell count (p < 0.001) and the higher the CV (p < 0.001). No contact lens wearing was noted in 207 eyes (NoCL), rigid CL in 200 (RCL) and soft CL in 54 (SCL). CD for NoCL/RCL/SCL was 2523/2533/2644 per mm² and CV was 41.8/54.1/43.1%, respectively. A significant difference in CV was found between NoCL and RCL (p = 0.02), and no significant difference in CV was found between NoCL and SCL (p = 0.07). Endothelial cell density (ECD) did not differ significantly between NoCL and RCL or SCL.

CONCLUSION

Endothelial cell density (ECD) decreases and CV increases significantly with increasing tomographic severity of keratoconus. In patients with RCL compared to eyes without CL wear, we found a statistically significantly higher CV in the endothelial cell size.

Repeatability of corneal elevation maps in keratoconus patients using the tomography matching method

To assess repeatability of corneal tomography in successive measurements by Pentacam in keratoconus (KC) and normal eyes based on the Iterative Closest Point (ICP) algorithm. The study involved 143 keratoconic and 143 matched normal eyes. ICP algorithm was used to estimate six single and combined misalignment (CM) parameters, the root mean square (RMS) of the difference in elevation data pre (PreICP-RMS) and post (PosICP-RMS) tomography matching. Corneal keratometry, expressed in the form of M, J₀ and J₄₅ (power vector analysis parameters), was used to evaluate the effect of misalignment on corneal curvature measurements. The PreICP-RMS and PosICP-RMS were statistically higher (P < 0.01) in KC than normal eyes. CM increased significantly (p = 0.00), more in KC (16.76 ± 20.88 μm) than in normal eyes (5.43 ± 4.08 μm). PreICP-RMS, PosICP-RMS and CM were correlated with keratoconus grade (p < 0.05). Corneal astigmatism J₀ was different (p = 0.01) for the second tomography measurements with misalignment consideration (−1.11 ± 2.35 D) or not (−1.18 ± 2.35 D), while M and J₄₅ kept similar. KC corneas consistently show higher misalignments between successive tomography measurements and lower repeatability compared with healthy eyes. The influence of misalignment is evidently clearer in the estimation of astigmatism than spherical curvature. These higher errors appear correlated with KC progression.

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.

Detection of Keratoconus With a New Biomechanical Index

PURPOSE

To evaluate the ability of a new combined biomechanical index called the Corvis Biomechanical Index (CBI) based on corneal thickness profile and deformation parameters to separate normal from keratoconic patients.

METHODS

Six hundred fifty-eight patients (329 eyes in each database) were included in this multicenter retrospective study. Patients from two clinics located on different continents were selected to test the capability of the CBI to separate healthy and keratoconic eyes in more than one ethnic group using the Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany). Logistic regression was employed to determine, based on Database 1 as the development dataset, the optimal combination of parameters to accurately separate normal from keratoconic eyes. The CBI was subsequently independently validated on Database 2.

RESULTS

The CBI included several dynamic corneal response parameters: deformation amplitude ratio at 1 and 2 mm, applanation 1 velocity, standard deviation of deformation amplitude at highest concavity, Ambrósio's Relational Thickness to the horizontal profile, and a novel stiffness parameter. The receiver operating characteristic curve analysis of the training database showed an area under the curve of 0.983. With a cut-off value of 0.5, 98.2% of the cases were correctly classified with 100% specificity and 94.1% sensitivity. In the validation dataset, the same cut-off point correctly classified 98.8% of the cases with 98.4% specificity and 100% sensitivity.

CONCLUSIONS

The CBI was shown to be highly sensitive and specific to separate healthy from keratoconic eyes. The presence of an external validation dataset confirms this finding and suggests the possible use of the CBI in everyday clinical practice to aid in the diagnosis of keratoconus. [J Refract Surg. 2016;32(12):803-810.].

Corneal Biomechanics in Ectatic Diseases: Refractive Surgery Implications

BACKGROUND

Ectasia development occurs due to a chronic corneal biomechanical decompensation or weakness, resulting in stromal thinning and corneal protrusion. This leads to corneal steepening, increase in astigmatism, and irregularity. In corneal refractive surgery, the detection of mild forms of ectasia pre-operatively is essential to avoid post-operative progressive ectasia, which also depends on the impact of the procedure on the cornea.

METHOD

The advent of 3D tomography is proven as a significant advancement to further characterize corneal shape beyond front surface topography, which is still relevant. While screening tests for ectasia had been limited to corneal shape (geometry) assessment, clinical biomechanical assessment has been possible since the introduction of the Ocular Response Analyzer (Reichert Ophthalmic Instruments, Buffalo, USA) in 2005 and the Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany) in 2010. Direct clinical biomechanical evaluation is recognized as paramount, especially in detection of mild ectatic cases and characterization of the susceptibility for ectasia progression for any cornea.

CONCLUSIONS

The purpose of this review is to describe the current state of clinical evaluation of corneal biomechanics, focusing on the most recent advances of commercially available instruments and also on future developments, such as Brillouin microscopy.

Penetrating Keratoplasty for Keratoconus - Excimer Versus Femtosecond Laser Trephination

BACKGROUND

In case of keratoconus, rigid gas-permeable contact lenses as the correction method of first choice allow for a good visual acuity for quite some time. In a severe stage of the disease with major cone-shaped protrusion of the cornea, even specially designed keratoconus contact lenses are no more tolerated. In case of existing contraindications for intrastromal ring segments, corneal transplantation typically has a very good prognosis.

METHODS

In case of advanced keratoconus - especially after corneal hydrops due to rupture of Descemet's membrane - penetrating keratoplasty (PKP) still is the surgical method of first choice. Noncontact excimer laser trephination seems to be especially beneficial for eyes with iatrogenic keratectasia after LASIK and those with repeat grafts in case of "keratoconus recurrences" due to small grafts with thin host cornea. For donor trephination from the epithelial side, an artificial chamber is used. Wound closure is achieved with a double running cross-stitch suture according to Hoffmann. Graft size is adapted individually depending on corneal size ("as large as possible - as small as necessary"). Limbal centration will be preferred intraoperatively due to optical displacement of the pupil. During the last 10 years femtosecond laser trephination has been introduced from the USA as a potentially advantageous approach.

RESULTS

Prospective clinical studies have shown that the technique of non-contact excimer laser PKP improves donor and recipient centration, reduces "vertical tilt" and "horizontal torsion" of the graft in the recipient bed, thus resulting in significantly less "all-sutures-out" keratometric astigmatism (2.8 vs. 5.7 D), higher regularity of the topography (SRI 0.80 vs. 0.98) and better visual acuity (0.80 vs. 0.63) in contrast to the motor trephine. The stage of the disease does not influence functional outcome after excimer laser PKP. Refractive outcomes of femtosecond laser keratoplasty, however, resemble that of the motor trephine.

CONCLUSIONS

In contrast to the undisputed clinical advantages of excimer laser keratoplasty with orientation teeth/notches in keratoconus, the major disadvantage of femtosecond laser application is still the necessity of suction and applanation of the cone during trephination with intraoperative pitfalls and high postoperative astigmatism.

Comparison of corneal dynamic parameters and tomographic measurements using Scheimpflug imaging in keratoconus

AIM

To compare the diagnostic ability of corneal tomography and corneal dynamic response measurements in normal and keratoconus eyes.

METHODS

Consecutive patients with grade II-III keratoconus and age-matched normal subjects were recruited. Corneal imaging was performed using Pentacam (Oculus Optikgeräte, Wetzlar, Germany) and Corvis (Oculus Optikgeräte). A beta version of Corvis software was used with three additional parameters: maximal change of arc length, deformation amplitude (DA) ratio 1 and DA ratio 2. Diagnostic ability of both devices to differentiate normal and keratoconus eyes was evaluated using receiver-operating characteristic (ROC) curves. The areas under the ROC curve (AUC) and partial AUC (pAUC) for specificity ≥80% for each parameter of Corvis and final D value of Belin/Ambrosio Enhanced Ectasia Display (BAD) were compared.

RESULTS

Forty-two eyes of 42 patients (21 patients with keratoconus and 21 normal subjects) were included. Both groups were age matched (p=0.760). The ROC analysis showed that the final D value of BAD had the highest AUC (0.994) and pAUC (0.194). Maximum inverse radius had the highest AUC (0.954) but a relatively lower pAUC (0.158), while DA ratio 2 had the second highest AUC (0.946) together with the highest pAUC (0.177) among Corvis parameters. There was no significant difference between AUC and pAUC of BAD compared with those of DA ratio 1 (p≥0.162) and DA ratio 2 (p≥0.208).

CONCLUSIONS

The results of our study suggest that Corvis measurements have the potential to differentiate keratoconus and normal eyes. The diagnostic ability of novel parameters on Corvis was comparable to Pentacam.

Complementary Keratoconus Indices Based on Topographical Interpretation of Biomechanical Waveform Parameters: A Supplement to Established Keratoconus Indices

Purpose. To build new models with the Ocular Response Analyzer (ORA) waveform parameters to create new indices analogous to established topographic keratoconus indices. Method. Biomechanical, tomographic, and topographic measurements of 505 eyes from the Homburger Keratoconus Centre were included. Thirty-seven waveform parameters (WF) were derived from the biomechanical measurement with the ORA. Area under curve (ROC, receiver operating characteristic) was used to quantify the screening performance. A logistic regression analysis was used to create two new keratoconus prediction models based on these waveform parameters to resample the clinically established keratoconus indices from Pentacam and TMS-5. Results. ROC curves show the best results for the waveform parameters p1area, p2area, h1, h2, dive1, mslew1, aspect1, aplhf, and dslope1. The new keratoconus prediction model to resample the Pentacam topographic keratoconus index (TKC) was WF_TKC = -4.068 + 0.002 × p2area - 0.005 × dive1 - 0.01 × h1 - 2.501 × aplhf, which achieves a sensitivity of 90.3% and specificity of 89.4%; to resample the TMS-5 keratoconus classification index (KCI) it was WF_KCI = -3.606 + 0.002 × p2area, which achieves a sensitivity of 75.4% and a specificity of 81.8%. Conclusion. In addition to the biomechanically provided Keratoconus Index two new indices which were based on the topographic gold standards (either Pentacam or TMS-5) were created. Of course, these do not replace the original topographic measurement.

Characteristics of Corneal Astigmatism of Anterior and Posterior Surface in a Normal Control Group and Patients With Keratoconus

PURPOSE

To evaluate and compare power and axis orientation of anterior and posterior astigmatism in eyes with keratoconus with healthy eyes.

METHODS

In this retrospective cohort study, we examined 861 eyes of 494 patients diagnosed with keratoconus at the Department of Ophthalmology, University Hospital Frankfurt, and 256 eyes of 256 healthy individuals. Using a Scheimpflug device (Pentacam HR), we measured the magnitude and axis orientation of anterior and posterior corneal astigmatism, corneal thickness, and conus location. The results were compared between different stages of the disease according to the Amsler-Krumeich classification and the control group.

RESULTS

Magnitude of corneal astigmatism was 3.47 ± 2.10 diopters (D) on the anterior surface and 0.69  ± 0.40 D on the posterior surface in eyes across all keratoconus stages. We found a significant increase of anterior and posterior corneal astigmatism with progression of disease (P < 0.01, 1-way analysis of variance) and a significant correlation between anterior and posterior corneal astigmatism (r = 0.77, P < 0.01). In contrast to eyes of healthy individuals, in which posterior corneal axis alignment is vertical in most cases independent of anterior alignment, we found in eyes with keratoconus a match between anterior and posterior alignment when alignment was vertical in 97% of eyes, 46% when oblique and 61% when horizontal (Cohen kappa coefficient κ = 0.55, P < 0.01). With progression of disease, alignment of anterior and posterior corneal astigmatism became increasingly vertical.

CONCLUSIONS

In eyes with keratoconus, posterior axis alignment of corneal astigmatism is in line with alignment of the anterior surface in the majority of cases. Posterior astigmatism axis alignment could potentially be used in algorithms to support diagnosis and staging of keratoconus.

Astigmatic Vector Analysis of Posterior Corneal Surface: A Comparison Among Healthy, Forme Fruste, and Overt Keratoconic Corneas

PURPOSE

To determine novel diagnostic parameters for keratoconus, and to assess the correlation between anterior and posterior corneal surfaces based on vectorial astigmatism analyses.

DESIGN

Retrospective case-control study.

METHODS

Six hundred and ninety-eight eyes of 698 patients were enrolled in the study. Healthy corneas, or controls (C, n = 264), were compared to keratoconic corneas, further categorized as forme fruste (FFKc, n = 212) and overt keratoconus (Kc, n = 222). Corneal measurements were obtained from a Scheimpflug-based tomographer. Vectorial analyses were conducted in accordance with the method proposed by Thibos.

RESULTS

Posterior corneal astigmatic power vector (APV) >0.23 diopter (D) yielded a test for overt Kc with sensitivity and specificity rates of, respectively, 81% and 77%, indicating a positive likelihood ratio (LR+) of 3.5 and a negative likelihood ratio (LR-) of 0.25. Posterior corneal overall blur vector (Blur) >6.45 D yielded a test slightly less sensitive and specific, with rates of 75% and 72%, respectively, associated to LR+ of 2.7 and LR- of 0.35. The highest (Spearman ρ) correlation coefficients between anterior and posterior corneal astigmatisms were associated with Blur, being 0.93 for Kc, 0.87 for C, and 0.81 for FFKc. The astigmatism vectors along the 45-degree (J45) and 0-dregree meridians (J0) and APV most often presented higher coefficient values for Kc and FFKc than for C (P = .01).

CONCLUSIONS

Posterior corneal vectors APV and Blur constitute objective supplemental parameters for the diagnosis of Kc. Anterior and posterior corneal surfaces correlate in all groups, although it was not possible to accurately predict posterior astigmatism from anterior astigmatism.