Keratoconus Screening Indices and Their Diagnostic Ability to Distinguish Normal From Ectatic Corneas

Multi-modal imaging for the detection of early keratoconus: a narrative review

Keratoconus is a common progressive corneal disorder that can be associated with significant ocular morbidity. Various corneal imaging techniques have been used for the diagnosis of established cases. However, in the early stages of the disease, which include subclinical keratoconus and forme fruste keratoconus, detection of such cases can be challenging. The importance of detecting such cases is very important because early intervention can halt disease progression, improve visual outcomes and prevent postrefractive surgery ectasia associated with performing corneal refractive procedures in such patients. This narrative review aimed to examine several established and evolving imaging techniques for the detection of early cases of keratoconus. The utilization of combinations of these techniques may further increase their diagnostic ability.

Diagnosis of Forme Fruste Keratoconus Using Corvis ST Sequences with Digital Image Correlation and Machine Learning

PURPOSE

This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas.

METHODS

100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters.

RESULTS

The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age (p = 0.26) and gender (p = 0.36) at baseline, but they had significantly lower bIOP (p < 0.001) and thinner central cornea thickness (CCT) (p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation.

CONCLUSION

This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus.

Longitudinal Analysis of Corneal Biomechanics of Suspect Keratoconus: A Prospective Case-Control Study

BACKGROUND

To evaluate the corneal biomechanics of stable keratoconus suspects (Stable-KCS) at 1-year follow-up and compare them with those of subclinical keratoconus (SKC).

METHODS

This prospective case-control study included the eyes of 144 patients. Biomechanical and tomographic parameters were recorded (Corvis ST and Pentacam). Patients without clinical signs of keratoconus in both eyes but suspicious tomography findings were included in the Stable-KCS group (n = 72). Longitudinal follow-up was used to evaluate Stable-KCS changes. Unilateral keratoconus contralateral eyes with suspicious tomography were included in the SKC group (n = 72). T-tests and non-parametric tests were used for comparison. Multivariate general linear models were used to adjust for confounding factors for further analysis. Receiver operating characteristic (ROC) curves were used to analyze the distinguishability.

RESULTS

The biomechanical and tomographic parameters of Stable-KCS showed no progression during the follow-up time (13.19 ± 2.41 months, p > 0.05). Fifteen biomechanical parameters and the Stress-Strain Index (SSI) differed between the two groups (p < 0.016). The A1 dArc length showed the strongest distinguishing ability (area under the ROC = 0.888) between Stable-KCS and SKC, with 90.28% sensitivity and 77.78% specificity at the cut-off value of -0.0175.

CONCLUSIONS

The A1 dArc length could distinguish between Stable-KCS and SKC, indicating the need to focus on changes in the A1 dArc length for keratoconus suspects during the follow-up period. Although both have abnormalities on tomography, the corneal biomechanics and SSI of Stable-KCS were stronger than those of SKC, which may explain the lack of progression of Stable-KCS.

Corneal biomechanics in early diagnosis of keratoconus using artificial intelligence

Keratoconus is a blinding eye disease that affects activities of daily living; therefore, early diagnosis is crucial. Great efforts have been made toward an early diagnosis of keratoconus. Recent studies have shown that corneal biomechanics is associated with the occurrence and progression of keratoconus. Hence, detecting changes in corneal biomechanics may provide a novel strategy for early diagnosis. However, an early keratoconus diagnosis remains challenging due to the subtle and localized nature of its lesions. Artificial intelligence has been used to help address this problem. Herein, we reviewed the literature regarding three aspects of keratoconus (keratoconus, early keratoconus, and keratoconus grading) based on corneal biomechanical properties using artificial intelligence. Furthermore, we summarized the current research progress, limitations, and possible prospects.

Corneal Biomechanical Properties to Predict Prognosis of Abnormal Tomographic Corneas: A Prospective Cohort Study

PURPOSE

To analyze the corneal biomechanical properties in patients with abnormal corneal tomography (ACT) and predict their stability using the biomechanical stability index (BSI).

DESIGN

Prospective cohort study.

METHODS

Setting: Multicenter study.

STUDY POPULATION

This study included 385 eyes of 278 patients with stable ACT (n = 70), subclinical keratoconus (SKC, n = 65), keratoconus (n = 65), normal controls (NL, n = 142). Forty-three eyes with first-visit ACT were included in a separate cohort (follow-up ACT group).

OBSERVATION PROCEDURE

Tomographical and biomechanical parameters (Pentacam and Corvis ST) were recorded.

MAIN OUTCOME MEASURES

Nonparametric tests were used for comparison. Logistic regression was employed to introduce BSI to separate stable ACT and SKC accurately. An independent dataset of 43 first-visit ACT eyes was followed up for 1 year to validate BSI's accuracy and positive and negative predictive values (PPV, NPV).

RESULTS

The tomographical and biomechanical parameters in patients with Stable ACT remained stable over the follow-up period (12.73 ± 2.57 months, P > .05). Stable ACT had 12/14 biomechanical parameters different (P < .05) from SKC but not different from NL (P > .05). With a cut-off value of 0.585, BSI demonstrated the strongest ability to distinguish between stable ACT and SKC (area under the receiver operating characteristic curve = 0.991), with 93.85% sensitivity and 97.14% specificity. During the 1-year follow-up of 43 eyes (follow-up ACT group), 30 remained stable. The accuracy, PPV, and NPV of the BSI were 95.35%, 100%, and 93.75%, respectively.

CONCLUSIONS

Biomechanical properties of patients with stable abnormal tomography corneas were stronger than SKC and close to normal corneas, which may explain the reason for tomographic stability. The BSI may be useful for predicting disease progression in patients with ACT and the possible management of corneal cross-linking at the first visit.

Prevalence of Keratoconus Among High School Students in Southern Brazil: A Community-Based Study

OBJECTIVES

This study aimed to determine the prevalence of keratoconus (KC) in teenagers who live in Southern Brazil and detect any possible associated factors.

METHODS

This prospective, observational, mobile clinic-based cross-sectional study collected data from students between 14 and 21 years from seven high schools who were living in the Greater Porto Alegre metropolitan region in Southern Brazil. Subjects were clinically surveyed and examined using a slitlamp and rotational Scheimpflug corneal tomography system. All data were collected at the mobile clinic during a single visit.

RESULTS

Eight-hundred twenty-six students were evaluated (357 boys and 469 girls) with an average age of 16.7±1.2 years. Six subjects were classified as having KC (four girls), yielding a prevalence rate of 0.73% (95% confidence interval, 0.27%-1.57%) or one per 137 teenagers in Southern Brazil. Logistic regression showed an association between KC and positive history of eye rubbing ( P =0.02).

CONCLUSION

According to our investigation, this is the first KC prevalence study in South America using the latest technologies (Scheimpflug imaging). The prevalence of KC among teenagers in Southern Brazil is within the highest reported worldwide. We also found an association between KC and history of eye rubbing. Keratoconus is not an uncommon disorder in our population, and the efforts to identify the disease and reduce its risk factors in an earlier phase are justified.

Analysis of Scheimpflug Tomography Parameters for Detecting Subclinical Keratoconus in the Fellow Eyes of Patients with Unilateral Keratoconus in the Eastern Province of Saudi Arabia

Purpose

We compared the characteristics of subtle morphological changes in subclinical keratoconus (KC) and normal corneas using Scheimpflug tomography (Pentacam®) and assessed the efficacy of these parameters for distinguishing KC or subclinical KC from normal eyes.

Patients and Methods

In this multicenter comparative study at Dhahran Eye Specialist Hospital and Al Kahhal Medical Complex in the Eastern Province of Saudi Arabia, we analyzed the Scheimpflug tomography charts of patients with topographically normal eyes and those with unilateral KC. Patients were divided into the normal (NL: patients considered for refractive surgery and with normal topographic/tomographic features, 129 eyes), KC (30 patients with manifest KC in one eye based on biomicroscopy and topographical findings), and forme fruste KC (FFKC: fellow eyes of patients in the KC group that met the NL group criteria) groups. Corneal morphological parameters were analyzed using the area under the receiver operating characteristic (ROC) curves (AUCs).

Results

For distinguishing NL and KC groups, all measured corneal morphological parameters, except for flat keratometry, maximum Ambrósio relational thickness index, and minimum sagittal curvature, had AUCs >0.75. The surface variance index yielded the largest AUC (0.999). For distinguishing NL and FFKC groups, all corneal morphological parameters had AUCs <0.8. Total higher-order aberrations (RMS HOA) yielded the highest AUC, followed by Belin/Ambrỏsio Enhanced Ectasia total deviation (BAD-D), back elevation at the thinnest location, average pachymetric progression index (PPIave), and deviation of Ambrỏsio relational thickness (Da) (AUC 0.74-0.78).

Conclusion

The diagnostic performance of all tested topographic and tomographic parameters measured using Scheimpflug tomography for discriminating subclinical KC was fair at best, with the top parameters being RMS HOA, BAD-D, back elevation at the thinnest location, PPIave, and Da. Distinguishing between subclinical KC and healthy eyes remains challenging. Multimodal imaging techniques may be required for optimal early detection of subtle morphological changes.

Advanced Corneal Imaging in Keratoconus: A Report by the American Academy of Ophthalmology

PURPOSE

To review the published literature on the diagnostic capabilities of the newest generation of corneal imaging devices for the identification of keratoconus.

METHODS

Corneal imaging devices studied included tomographic platforms (Scheimpflug photography, OCT) and functional biomechanical devices (imaging an air impulse on the cornea). A literature search in the PubMed database for English language studies was last conducted in February 2023. The search yielded 469 citations, which were reviewed in abstract form. Of these, 147 were relevant to the assessment objectives and underwent full-text review. Forty-five articles met the criteria for inclusion and were assigned a level of evidence rating by the panel methodologist. Twenty-six articles were rated level II, and 19 articles were rated level III. There were no level I evidence studies of corneal imaging for the diagnosis of keratoconus found in the literature. To provide a common cross-study outcome measure, diagnostic sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were extracted. (A perfect diagnostic test that identifies all cases properly has an AUC of 1.0.) RESULTS: For the detection of keratoconus, sensitivities for all devices and parameters (e.g., anterior or posterior corneal curvature, corneal thickness) ranged from 65% to 100%. The majority of studies and parameters had sensitivities greater than 90%. The AUCs ranged from 0.82 to 1.00, with the majority greater than 0.90. Combined indices that integrated multiple parameters had an AUC in the mid-0.90 range. Keratoconus suspect detection performance was lower with AUCs ranging from 0.66 to 0.99, but most devices and parameters had sensitivities less than 90%.

CONCLUSIONS

Modern corneal imaging devices provide improved characterization of the cornea and are accurate in detecting keratoconus with high AUCs ranging from 0.82 to 1.00. The detection of keratoconus suspects is less accurate with AUCs ranging from 0.66 to 0.99. Parameters based on single anatomic locations had a wide range of AUCs. Studies with combined indices using more data and parameters consistently reported high AUCs.

FINANCIAL DISCLOSURE(S)

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

Early, Forme Fruste keratoconus and normal thin cornea, evaluation of sensitive parameters by combined Placido Scheimpflug topography

PURPOSE

To determine the sensitive indices distinguishing forme-fruste keratoconus (FFKC) and early keratoconus (early KC) from thin normal corneas, and their cutoff values using Sirius topography.

METHODS

156 eyes with normal thin corneas < 500 um (group 1), 99 eyes with early KC (group 2) and 41 eyes with FFKC (group 3), were assessed retrospectively for: corneal keratometric indices, pachymetry indices, corneal aberrations, elevation indices; thinnest corneal point elevation, Q value, root mean square (RMS) withRMS/ area (RMS/A); and KC summary indices of front and back surfaces; surface asymmetry index (SIf, SIb), elevation at KC vertex (KVf, KVb), Baiocchi-Calossi-Versaci index (BCVf, BCVb) and summation of its vector (BCV). Cutoff values were calculated.

RESULTS

Keratometry indices were significantly different between early KC and thin normal cases (apex front curvature had the highest area-under-the-ROC-curve (AUROC) (0.926) in early KC, while only apex curvature and coordinates were significant in FFKC cases. Pachymetry indices did not show any significance in differentiating either early KC or FFKC from normal thin corneas. KC summary indices were highly significant among the 3 groups. The highest AUROC was observed with KVb in early KC (0.987) and with KVf in FFKC (0.831). Vertical coma and vertical trefoil showed the highest significance of all aberration parameters differentiating the 3 groups. Thinnest point elevation, RMS and RMS/A showed the highest AUROC in differentiating early KC and FFKC cases from thin normal corneas.

CONCLUSION

Comparing early KC and FFKC to thin normal corneas, Sirius provided high precision in prediction.

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.

Structure-Function Relationship in Keratoconus: Spatial and Depth Vision

Purpose

The purpose of this study was to determine changes in spatial and depth vision with increasing severity of keratoconus and to model the structure-function relationship to identify distinct phases of loss in visual function with disease severity.

Methods

Best-spectacle corrected, monocular high-contrast visual acuity, contrast sensitivity function (CSF) and stereoacuity of 155 cases (16-31 years) with mild to advanced bilateral keratoconus was determined using standard psychophysical tests. Disease severity was quantified using the multimetric D-index. The structure-function relationship was modeled using linear, positive exponential, negative exponential, and logistic nonlinear regression equations.

Results

The logistic regression model explained the highest proportion of variance for spatial vision, without bias in the residual plots (R2 ≥ 66%, P < 0.001). Visual acuity showed a distinct ceiling phase and a steeper loss rate with increasing D-index (1.8 units/D-index) in this model. The area under the CSF lacked this ceiling phase and had a shallower loss rate (0.28 units/D-index). Stereoacuity loss with D-index was poorly explained by all models tested (P ≤ 0.2). Cases with lower and bilaterally symmetric D-index had better stereoacuity (181.6-376 arc seconds) than those with higher D-index (>400 arc second); both were significantly poorer than controls (approximately 30 arc second).

Conclusions

Vision loss in keratoconus varies with the visual function parameter tested. Contrast sensitivity may be an earlier indicator of spatial vision loss than visual acuity. Depth perception is significantly deteriorated from very early stages of the disease.

Translational Relevance

The study outcomes may be used to forecast longitudinal vision loss in keratoconus and to apply appropriate interventions for timely preservation/enhancement of vulnerable visual functions.

Anterior Scleral Thickness Profile in Keratoconus

PURPOSE

Considering that peripheral corneal thinning occurs in keratoconus (KC), the anterior scleral thickness (AST) profile was measured to compare thickness variations in healthy and KC eyes across several meridians.

METHODS

This cross-sectional case-control study comprised 111 eyes of 111 patients: 61 KC eyes and 50 age- and axial-length-matched healthy eyes. The AST was explored at three scleral eccentricities (1, 2, and 3 mm from the scleral spur) across four scleral zones (nasal, temporal, superior, and inferior) by using swept-source optical coherence tomography. The AST variations among eccentricities and scleral regions within and between groups were investigated.

RESULTS

The AST significantly varied with scleral eccentricity in healthy eyes over the temporal meridian (p = 0.009), whereas in KC eyes, this variation was observed over the nasal (p = 0.001), temporal (p = 0.029) and inferior (p = 0.006) meridians. The thinnest point in both groups was 2 mm posterior to the scleral spur (p < 0.001). The sclera was thickest over the inferior region (control 581 ± 52 μm, KC 577 ± 67 μm) and thinnest over the superior region (control 448 ± 48 μm, KC 468 ± 58 μm) in both populations (p < 0.001 for all eccentricities). The AST profiles were not significantly different between groups (p > 0.05). The inferior-superior thickness asymmetry was statistically different 2 mm posterior to the scleral spur between groups (p = 0.009), specifically with subclinical KC (p = 0.03). There is a trend where the asymmetry increases, although not significantly, with the KC degree (p > 0.05).

CONCLUSIONS

KC eyes presented significant thickness variations among eccentricities over the paracentral sclera. Although AST profiles did not differ between groups, the inferior-superior asymmetry differences demonstrated scleral changes over the vertical meridian in KC that need further investigation.

Corneal biomechanics in normal and subclinical keratoconus eyes

BACKGROUND

The diagnosis of keratoconus, as the most prevalent corneal ectatic disorder, at the subclinical stage gained great attention due to the increased acceptance of refractive surgeries. This study aimed to assess the pattern of the corneal biomechanical properties derived from Corneal Visualization Scheimpflug Technology (Corvis ST) and evaluate the diagnostic value of these parameters in distinguishing subclinical keratoconus (SKC) from normal eyes.

METHODS

This prospective study was conducted on 73 SKC and 69 normal eyes. Subclinical keratoconus eyes were defined as corneas with no clinical evidence of keratoconus and suspicious topographic and tomographic features. Following a complete ophthalmic examination, topographic and tomographic corneal assessment via Pentacam HR, and corneal biomechanical evaluation utilizing Corvis ST were done.

RESULTS

Subclinical keratoconus eyes presented significantly higher Deformation Amplitude (DA) ratio, Tomographic Biomechanical Index (TBI), and Corvis Biomechanical Index (CBI) rates than the control group. Conversely, Ambrósio Relational Thickness to the Horizontal profile (ARTh), and Stiffness Parameter at the first Applanation (SPA1) showed significantly lower rates in SKC eyes. In diagnosing SKC from normal eyes, TBI (AUC: 0.858, Cut-off value: > 0.33, Youden index: 0.55), ARTh (AUC: 0.813, Cut-off value: ≤ 488.1, Youden index: 0.58), and CBI (AUC: 0.804, Cut-off value: > 0.47, Youden index: 0.49) appeared as good indicators.

CONCLUSIONS

TBI, CBI, and ARTh parameters could be valuable in distinguishing SKC eyes from normal ones.

Keratoconus tomographic indices in osteogenesis imperfecta

PURPOSE

Osteogenesis imperfecta (OI) is a rare inherited disease affecting collagen-rich tissues. Ocular complications have been reported such as thin corneas, low ocular rigidity, keratoconus, among others. The purpose of this study is to characterize corneal tomographic features in OI patients compared to unaffected patients, with particular focus on commonly studied keratoconus indices.

METHODS

Cross-sectional case-control study including 37 OI patients and 37 age-matched controls. Patients and controls underwent comprehensive ophthalmological examination including corneal Scheimpflug tomography with a Pentacam HR device (Oculus Optikgeräte GmbH, Wetzlar, Germany) to analyse and compare topometric, tomographic, pachymetric and Belin-Ambrósio Enhanced Ectasia Display III (BAD-D) data of both eyes of each patient.

RESULTS

Most OI patients had type I disease (n = 24; 65%) but type III-VII patients were also included. Two patients had clinically overt bilateral keratoconus. OI patients had significantly higher maximum keratometry (45.2 ± 2.1 vs. 43.7 ± 1.2; p = 0.0416), front and back elevation (3.0 ± 3.3 vs. 2.1 ± 1.3, p = 0.0201; 11.1 ± 8.2 vs. 5.0 ± 3.7, p < 0.0001), index of surface variance (25.5 ± 13 vs. 17.4 ± 8.3; p = 0.0016), index of vertical asymmetry (0.21 ± 0.14 vs. 0.15 ± 0.06; p = 0.0215), index of height asymmetry (9.2 ± 14 vs. 6.0 ± 4.5; p = 0.0421), index of height decentration (0.02 ± 0.01 vs. 0.01 ± 0.01; p < 0.0001) and average pachymetric progression (1.01 ± 0.19 vs. 0.88 ± 0.14; p < 0.0001) readings. Thinnest corneal thickness and maximum Ambrósio relational thickness were significantly lower (477 ± 52 vs. 543 ± 26; 387 ± 95 vs. 509 ± 49; p < 0.0001). Two-thirds of OI patients had corneas with a minimum thickness < 500 µm. BAD-D value was significantly higher in OI patients (2.1 ± 1.4 vs. 0.9 ± 0.2; p < 0.0001).

CONCLUSION

OI patients showed significant changes in corneal profiles compared with healthy subjects. A high proportion of patients had tomographically suspect corneas when using keratoconus diagnostic indices. Further studies are warranted to assess the true risk of corneal ectasia in OI patients.

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

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

Biomechanical Analysis of Tomographically Regular Keratoconus Fellow Eyes Using Corvis ST

BACKGROUND

Keratoconus is a bilateral, yet asymmetric disease. In rare cases, the second eye may show no signs of tomographic changes. The purpose of this study was to analyze the biomechanical characteristics in tomographically regular keratoconus fellow eyes.

MATERIALS AND METHODS

This retrospective, consecutive case series analyzed 916 eyes of 458 patients who presented to our keratoconus clinic between November 2020 and October 2022. Primary outcome measures included best-corrected visual acuity (BCVA), tomographic Scheimpflug analysis using Pentacam AXL (Oculus, Wetzlar, Germany), and biomechanical assessment using Corvis ST (Oculus, Wetzlar, Germany). Tomographic changes were assessed via analysis of the anterior and posterior curvature, K-max, thinnest corneal thickness (TCT), the Belin/Ambrosio Deviation Display (BAD-D), and the ABCD-Grading. Biomechanical changes were analyzed using Corvis Biomechanical Index (CBI) and Tomographic Biomechanical Index (TBI).

RESULTS

Of 916 eyes, 34 tomographically regular fellow eyes (7.4%) were identified and included in the analysis. Overall, the mean BCVA was - 0.02 ± 0.13 logMAR. Tomographic analysis showed mean K-max of 43.87 ± 1.21 D, mean TCT of 532 ± 23 µm, and mean BAD-D of 1.02 ± 0.43. Biomechanical analysis demonstrated mean CBI of 0.28 ± 0.26 and mean TBI of 0.34 ± 0.30. While normal CBI-values were observed in 16 (47%) of 34 eyes, only 13 eyes (38%) showed a regular TBI and only 7 eyes (21%) showed regular TBI and CBI. The sensitivity of CBI and TBI to detect a tomographically normal keratoconus fellow eye was 53% and 62%, respectively.

CONCLUSION

A highly asymmetric corneal ectasia with regular tomographic finding in a fellow eye is rare among keratoconus patients. In such cases, a biomechanical analysis may be useful in detecting early signs of corneal ectasia. In our analysis, the TBI showed high sensitivity for detecting a biomechanical abnormality in tomographically regular fellow eyes.

Corneal topographic changes in patients with thyroid eye disease: A retrospective cross-sectional study

PURPOSE

This study aimed to evaluate corneal topographic findings in patients with thyroid eye disease (TED) using a Galilei camera and compare their corneal topographic parameters with those of control patients.

METHODS

This retrospective cross-sectional study included 52 eyes of 26 patients with TED (study group) and 40 eyes of 20 controls treated at a tertiary medical center in Taiwan between January and December 2021. All participants underwent basic ophthalmological examinations, corneal topography examination using a Galilei dual Scheimpflug camera, thyroid function examination, and orbital computed tomography. The corneal topographic parameters and cross-sectional area of the extraocular muscles were compared between the TED and control groups.

RESULTS

Several corneal topographic parameters, including the Inferior-Superior Index, Keratoconus Prediction Index, Surface Asymmetry Index, Surface Regularity Index, simulated keratometry astigmatism, and anterior instantaneous astigmatism axis, differed significantly between the groups (P ≤ 0.05). The anterior instantaneous astigmatism axis was more oblique in the TED group than in the control group. A scatter plot revealed a more scattered distribution in the anterior instantaneous astigmatism axis in the TED group than in the control group. However, the corneal topographic parameters did not differ significantly among the different thyroid dysfunction groups.

CONCLUSIONS

The corneas of patients with TED are suspicious and keratoconus-like, and TED can increase anterior corneal astigmatism in the oblique axis, albeit with large variations in the extent of change. These TED-related corneal changes may aid in the early diagnosis of TED, especially "silent" TED.

Progress of corneal morphological examination combined with biomechanical examination in preoperative screening for keratorefractive surgery

Although corneal refractive surgery has been proven to be excellent in terms of safety and effectiveness, the reduction of postoperative corneal ectasia remains one of the most concerned topics for surgeons. Forme fruste keratoconus (FFKC) is the most important factor that leads to postoperative corneal ectasia, and common preoperative screenings of the condition include corneal morphology examination and corneal biomechanical examination. However, there are limitations to the single morphological examination or biomechanical examination, and the advantages of the combination of the two have been gradually emerging. The combined examination is more accurate in the diagnosis of FFKC and can provide a basis for determining suspected keratoconus. It allows one to measure the true intraocular pressure (IOP) before and after surgery and is recommended for older patients and those with allergic conjunctivitis. This article aims to discuss the application, advantages, and disadvantages of single examination and combined examination in the preoperative screening of refractive surgery, so as to provide a certain reference value for choosing suitable patients for surgery, improving surgical safety, and reducing the risk of postoperative ectasia.

Quantifying Corneal Topographic Astigmatism (CorT Total) in Keratoconic Eyes

PURPOSE

To determine optimal corneal regions from which to derive corneal topographic astigmatism (CorT) in kerato-conic eyes.

METHODS

In this retrospective study, potential measures of corneal astigmatism are calculated from raw total corneal power data (179 eyes from 124 patients) from a corneal tomographer. The measures are derived from annular corneal regions varying in both extent and center position, and evaluated according to the variability of the ocular residual astigmatism (ORA) in the cohort. This variability is quantified by the ORArms, which is the root-mean-squared distance of the ORAs from their summated vector mean in double angle space. The lower the ORArms, the better the corneal astigmatism measure corresponds to manifest refractive cylinder.

RESULTS

Corneal astigmatism measures derived from regions centered on corneal vertex had ORArms values (mild: 1.07 diopters [D], moderate: 1.61 D, severe: 2.65 D) as low or lower than other measures derived from regions centered on thinnest point, corneal apex (front or back), or pupil center. Corneal astigmatism measures derived from a region centered 30% of the way toward thinnest point from corneal vertex appeared to have even lower ORArms values (mild: 1.05 D, moderate: 1.45 D, severe: 2.56 D). None of the corneal astigmatism measures corresponded closely with manifest refractive cylinder for severe keratoconus (ORArms > 2.50 D).

CONCLUSIONS

For keratoconic eyes, the CorT should be derived from an annular region centered 30% of the way toward thinnest point from corneal vertex, although when the keratoconus is mild, a standard corneal-vertex-centered CorT performs just as well. [J Refract Surg. 2023;39(3):206-213.].

The Characteristics of Quick Contrast Sensitivity Function in Keratoconus and Its Correlation with Corneal Topography

INTRODUCTION

To characterize quick contrast sensitivity function (qCSF) in keratoconus and its correlation with corneal topographic parameters.

METHODS

Patients with keratoconus (n = 120) who visited the Fudan Eye and ENT Hospital between April and June 2021 were enrolled in our study. A total of 215 eyes were subdivided into three groups according to maximum keratometry (K_max): Group 1 (K_max ≤ 48 D, 74 eyes), Group 2 (48 D < K_max ≤ 55 D, 64 eyes), and Group 3 (K_max > 55 D, 77 eyes). Manifest refraction, best corrected distance visual acuity (BCVA), corneal topography, and the qCSF test were examined. Intergroup comparisons and correlations among various corneal topographic parameters and qCSF were analyzed.

RESULTS

Significant differences in the area under the log CSF (AULCSF) and CSF Acuity among the three groups were found, which decreased with an increase in K_max. Contrast sensitivity (CS) between spatial frequencies of 3.0 to 18.0 cpd was significantly different (all P < 0.05) between Groups 1 and 2. The CS at all spatial frequencies was significantly different (all P < 0.05) between Group 3 and other two groups. At 3.0-18.0 cpd, CS decreased significantly (all P < 0.05) in Groups 1-3. Manifest refraction and topographic indices correlated significantly with qCSF parameters (all P < 0.05). Multivariable linear regression analysis showed that cylindrical refraction, logMAR BCVA, and index of surface variance had good predictive values for AULCSF and CSF Acuity.

CONCLUSIONS

The use of qCSF test can serve as a feasible tool to evaluate visual quality and severity of keratoconus, since changes in CS significantly correlated with keratoconus severity.

Comparison of Two Scheimpflug Systems in the Measurements of Eyes with Corneal Diameter Smaller than 11.1 mm

INTRODUCTION

This article aimed to evaluate the measurements of ectasia parameters by two Scheimpflug-based tomography devices, Pentacam and Sirius, for eyes with different corneal diameters (CDs).

METHODS

This cross-sectional research included subjects from the Fudan University EENT Hospital Refractive Center Database that were followed once a year for at least 3 years with unremarkable slit-lamp examination and normal topography. Pentacam and Sirius examinations were performed on these subjects and the ectasia indices were compared between different CD groups.

RESULTS

The right eyes of 153 subjects were included (CD ≤ 11.1 mm, n = 50; 11.2-12 mm, n = 52; > 12.0 mm, n = 51). For the ectasia parameters from Pentacam, CD had the greatest influence on the deviation of normality of back elevation (Db, R² = 0.371, β = - 1.119, P < 0.001), overall deviation of normality (BAD-D, R² = 0.305, β = - 0.589, P < 0.001), and minimum pachymetric progression index (PPImin, R² = 0.282, β = - 0.131, P < 0.001). For parameters derived from Sirius, CD had the greatest influence on Baiocchi-Calossi-Versaci index of the back surface (BCVb, R² = 0.138, β = - 0.179, P < 0.001), keratoconus vertex of the back surface (KVb, R² = 0.099, β = - 2.273, P < 0.001), and BCV (R² = 0.071, β = - 0.078, P = 0.001). CD had little influence on surface asymmetry index of the front (SIf) and back surface (SIb), keratoconus vertex of the front surface (KVf), Baiocchi-Calossi-Versaci index of the front surface (BCVf), and Sirius classifier (P > 0.05).

CONCLUSIONS

For Pentacam, CD mainly influenced indices related to back elevation (BE) and pachymetry progression, whereas for Sirius, CD mainly influenced indices related to BE and corneal aberration.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Use of Corneal Topography in Pediatric Ophthalmology

AIM

To introduce the topic of pediatric keratoconus, highlighting the importance of routine corneal topography and tomography in children and adolescents from predisposed groups. To attempt to ensure the early detection of keratoconus and its subclinical form, enabling early treatment, which brings better expected postoperative results.  Material and methods: Using the corneal tomograph Pentacam AXL we examined children and adolescents with astigmatism equal or greater than  2 diopters (in at least one eye) and patients with at least one risk factor such as eye rubbing in the case of allergic pathologies, positive family history of keratoconus or certain forms of retinal dystrophy. In total, we included 231 eyes (116 patients), of which 54 were girls and 62 were boys.

RESULTS

The Belin-Ambrósio deviation index parameter was evaluated, in which we classified a total of 41 eyes as subclinical keratoconus and 12 eyes as clinical keratoconus. Next, the corneal maps were evaluated individually, in which we included a total of 15 eyes as subclinical keratoconus and 6 eyes as clinical keratoconus. In our group, compared to the control group, subclinical and clinical keratoconus occurred most often in the group of patients with astigmatism and in the group of so-called "eye rubbers". After individual evaluation, keratoconus occurred more frequently in boys than in girls in our cohort.

CONCLUSION

Most patients with keratoconus are diagnosed when there is a deterioration of visual acuity and changes on the anterior surface of  the cornea. Corneal topography and tomography allows us to monitor the initial changes on the posterior surface of the cornea, and helps us to detect the subclinical form of keratoconus and the possibility of its early treatment. Therefore, it is important to determine which groups are at risk and groups in which corneal topography and tomography should be performed routinely.

Systematic detection of keratoconus in OCT: corneal and epithelial thickness maps

PURPOSE

To detect keratoconus (KC) only by analyzing the corneal and epithelial map parameters and patterns in optical coherence tomography (OCT).

SETTING

Tertiary care refractive surgery center.

DESIGN

Retrospective data collection.

METHODS

Corneal and epithelial thickness maps of normal, manifest, and subclinical keratoconic eyes (according to the Belin-Ambrosio display, Pentacam) were evaluated using spectral-domain OCT (Zeiss Cirrus 5000 HD). A new 2-step decision tree was developed based on previous studies with another OCT device. In the first step, if at least 1 of the 4 independent parameters (pachymetry minimum, pachymetry minimum-median, pachymetry superonasal-inferotemporal, and epithelial superonasal-inferotemporal) overruns the cutoff values, the eye was suspicious for KC. In the second step, if the epithelial map showed concentric thinning and the thinnest point of the cornea and epithelium is coincident, the eye was classified as keratoconic.

RESULTS

172 manifest keratoconic eyes (108 patients), 21 subclinical keratoconic eyes (20 patients), and 172 normal eyes (90 age-matched participants) were included in this study. Step 1 captured 100% of manifest and subclinical keratoconic eyes. Step 2 ruled out all suspicious but normal cases and, falsely, 2 subclinical keratoconic eyes. Our 2-step decision tree reached 100% specificity, 100% sensitivity in manifest KC, and 90.4% sensitivity in subclinical KC.

CONCLUSIONS

Pachymetric and epithelial map parameters and patterns in OCT can be used in the diagnosis of KC, including subclinical cases, yielding a high level of agreement with the commonly used diagnostic reference, the Belin-Ambrosio display. Further improvements by refining our algorithm and including an automated evaluation in the software are desirable.

Biomechanical properties analysis of forme fruste keratoconus and subclinical keratoconus

PURPOSE

To analyze the biomechanical properties of the eye in patients with unilateral keratoconus with normal (forme fruste keratoconus [FFKC]) or abnormal topography (subclinical keratoconus [SKC]).

METHODS

This study included 153 eyes of 153 participants, including 95 eyes of patients with unilateral keratoconus, and 58 eyes of 58 healthy controls. Contralateral eyes with unilateral keratoconus were divided into two groups according to clinical manifestations and global consensus: FFKC (n = 30) and SKC (n = 65). The biomechanical characteristics were analyzed using non-parametric tests; further analysis thereof was performed after adjusting for confounding factors (i.e., intraocular pressure, age, and corneal thickness). Receiver operating characteristic curve (ROC) was used to analyze the ability of the biomechanical parameters to distinguish FFKC from SKC.

RESULTS

Statistically significant differences between the FFKC and SKC groups were found in 9 of the 18 corneal biomechanical parameters analyzed using non-parametric tests. After adjusting for confounding factors, the multivariate analysis still revealed significant statistical differences in A1-time (P = 0.017), integrated radius (IR) (P = 0.024), and tomographic and biomechanical index (TBI, P < 0.001) between the FFKC and SKC groups. Stiffness parameter at first applanation (SP-A1) (Area under ROC [AUROC] = 0.765) demonstrated the strongest distinguishing ability, except for TBI (AUROC = 0.858) and Corvis Biomechanical Index (AUROC = 0.849), however, there was no statistically significant difference in SP-A1 (P = 0.366) between FFKC and SKC.

CONCLUSIONS

Biomechanical parameters A1-time and IR have a high diversity between FFKC and SKC, besides TBI, and may reflect more subtle changes in corneal biomechanical properties (BPs) preceding SP-A1. The BPs of SKC are weaker than FFKC, which might be a basic and clue for the classification and diagnosis of the severity of early keratoconus in terms of biomechanics.

Best indices of dual Scheimpflug/Placido tomographer for keratoconus detection

PURPOSE

To evaluate the accuracy of different corneal parameters in detecting keratoconus using a dual Scheimpflug/Placido system (Sirius, CSO, Italy).

METHODS

Sixty-eight eyes of 68 keratoconus patients and 77 eyes of 77 normal subjects were prospectively assessed in a diagnostic test study. The mean differences of the corneal parameters were compared using the independent t-test. The accuracy of curvature, elevation, pachymetry, and aberrometry indices, aqueous depth, and corneal volume in 10 mm was evaluated using the area under the curve (AUC), and the DeLong method was used for the comparison of AUCs. Multiple tests in a parallel manner and multiple logistic regression analysis were applied to determine the best predictor indices.

RESULTS

All indices except aqueous depth and corneal volume were significantly different between the two groups (P < 0.001). Back keratoconus vertex (KVb) and front Baiocchi-Calossi-Versaci index (BCVf) had the highest sensitivity (for both 98.53%) followed by front symmetry index (SIf) (96.12%) and thinnest point of the cornea (88.24%) in elevation, aberrometry, curvature, and pachymetry parameters, respectively. The highest diagnostic ability was observed in KVb (AUC 0.993) and BCVf index (AUC 0.992) (DeLong > 0.05). Multiple test analysis showed a combination of indices with the highest accuracy that was similar to the performance of each one individually, and keratoconus was diagnosed correctly in 98.5% of the cases (R² = 93%).

CONCLUSION

The parameters extracted from Sirius can differentiate keratoconus from normal corneas with high accuracy without the need for complex computational algorithms. Elevation-based and combined aberrometry indices had the highest diagnostic power.

Predictive accuracy of the ABCD progression display among patients with keratoconus: A historic cohort analysis

OBJECTIVE

To evaluate the accuracy of the ABCD Progression Display and the ABCD grading system in a population of adult patients with keratoconus.

METHODS

A retrospective cohort analysis of all adult patients with keratoconus followed at the Shamir Medical Center between 2012 and 2017. A recommendation by the cornea specialist to undergo corneal crosslinking (CXL) was used as a surrogate of ectasia progression. The ABCD grading was not available to the treating physician and was computed post-hoc. Sensitivity and specificity of the ABCD Progression Display was calculated, and multivariate regression was used to estimate the risk to undergo CXL when the ABCD Progression Display indicated progression. The ABCD grading was compared between patients who required CXL to those who did not. A single eye of each patient was included. Sensitivity and specificity of the ABCD Progression Display were 82% and 73%, respectively. A multivariable model adjusted for possible confounders, found that ABCD Progression was associated with a 7-fold risk of undergoing CXL compared to a patient in whom progression was not recorded in the ABCD Progression Display (OR = 7.55; 95% CI = 3.82-14.93, p < 0.001).

RESULTS

293 eyes of 293 patients were analysed. Mean age at presentation was 26.92 ± 6.12 years. In 68 eyes, progression of keratoconus was recorded and CXL was performed (CXL-group).

CONCLUSION

The ABCD Progression Display demonstrated adequate sensitivity and specificity and high predictive capabilities of keratoconus progression. It can be effectively utilized as an initial screening test in adults with keratoconus.

Patient selection for corneal topographic evaluation of keratoconus: A screening approach using artificial intelligence

Background

Corneal topography is a clinically validated examination method for keratoconus. However, there is no clear guideline regarding patient selection for corneal topography. We developed and validated a novel artificial intelligence (AI) model to identify patients who would benefit from corneal topography based on basic ophthalmologic examinations, including a survey of visual impairment, best-corrected visual acuity (BCVA) measurement, intraocular pressure (IOP) measurement, and autokeratometry.

Methods

A total of five AI models (three individual models with fully connected neural network including the XGBoost, and the TabNet models, and two ensemble models with hard and soft voting methods) were trained and validated. We used three datasets collected from the records of 2,613 patients' basic ophthalmologic examinations from two institutions to train and validate the AI models. We trained the AI models using a dataset from a third medical institution to determine whether corneal topography was needed to detect keratoconus. Finally, prospective intra-validation dataset (internal test dataset) and extra-validation dataset from a different medical institution (external test dataset) were used to assess the performance of the AI models.

Results

The ensemble model with soft voting method outperformed all other AI models in sensitivity when predicting which patients needed corneal topography (90.5% in internal test dataset and 96.4% in external test dataset). In the error analysis, most of the predicting error occurred within the range of the subclinical keratoconus and the suspicious D-score in the Belin-Ambrósio enhanced ectasia display. In the feature importance analysis, out of 18 features, IOP was the highest ranked feature when comparing the average value of the relative attributions of three individual AI models, followed by the difference in the value of mean corneal power.

Conclusion

An AI model using the results of basic ophthalmologic examination has the potential to recommend corneal topography for keratoconus. In this AI algorithm, IOP and the difference between the two eyes, which may be undervalued clinical information, were important factors in the success of the AI model, and may be worth further reviewing in research and clinical practice for keratoconus screening.

Visual Outcomes of Small-Incision Lenticule Extraction (SMILE) in Thin Corneas

We aimed to find out whether thin (≤500 μm) or normal (>500 μm, control) corneal thickness would impact efficacy and safety outcomes of small-incision lenticule extraction (SMILE). We retrospectively analyzed medical records of adult patients who had undergone SMILE. A total of 57 eyes were included in the “thin corneas” group and 180 eyes in the “control” group. At one month after surgery, rates of patients with uncorrected distance visual activity (UDVA) ≥ 0.8 were significantly higher in patients from the control group compared to the “thin corneas” group (87 vs. 71%, respectively p < 0.01), though rates were comparable at 3 months (87 vs. 76%, respectively, p > 0.05). SMILE had comparable safety in patients with thin and normal corneas. Procedure result predictability was comparable between groups. Regression analysis demonstrated that cap thickness impacted posterior corneal biomechanics, and the volume of removed tissue had a higher influence in patients with thin corneas. Moreover, an increase in cap thickness was associated with better final BCVA. Further study is needed for the evaluation of the impact of thin corneas on SMILE outcomes and planning. Our study also indicates that patients with thin corneas might require a different approach to nomogram calculation.

Understanding Corneal Epithelial Thickness Mapping

Corneal epithelial thickness (CET) and the regional variations in response to changes in corneal architecture and biomechanics have recently drawn the interest of corneal surgeons. Corneal epithelium possesses the tremendous capability of remodeling and changing its thickness. This remodeling of corneal epithelium takes place in response to underlying stromal irregularities which can result from a variety of corneal disorders including corneal ectasia. Measurement of CET can reveal the underlying stromal abnormalities and supplement in early diagnosis of corneal disorders especially corneal ectasia which has been one of the leading challenges in planning corneal refractive surgery. A significant number of patients ends up in ectasia after refractive surgery and the most common cause of this complication is the presence of preoperative subclinical keratoconus. Furthermore, postoperative complications of corneal refractive surgery are partly masked by epithelial remodeling and make the diagnosis and management difficult and extremely challenging. This leads not only to unpredictable visual and refractive outcome but also the need of multiple interventions to treat these complications. Although corneal tomography is considered as gold standard in the detection and diagnosis of corneal ectasia, a small number of subclinical cases may still go undetected. In this review, we have highlighted the underlying mechanism of epithelial remodeling, the devices and imaging modalities used to measure CET, and application of epithelial mapping in the diagnosis and management of various corneal disorders.

Performances of Corneal Topography and Tomography in the Diagnosis of Subclinical and Clinical Keratoconus

Aim

The purpose of the study was to assess the efficacy of topographical and tomographical indices given by the Pentacam (pachymetric, tomopetric, and aberometric) in clinical and subclinical keratoconus (KCN) diagnosis.

Material and Methods

In this observational analytic retrospective study, patients with abnormal findings in topography and tomography maps but with no signs on clinical examination (subclinical KCN group, sKCN), patients with clinical keratoconus (KCN group), and healthy subjects (Control group) were evaluated.

Results

The KCN group proved significantly different (p < 0.001) values of the investigated parameters than the Control group. Eleven out of 28 investigated parameters proved significantly different in the sKCN group compared to controls (p < 0.001). Two topographic measurements, namely I-S (cut-off = 1.435, a large value indicates the presence of KCN) and CCT (cut-off = 537, a small value indicates the presence of KCN), showed AUCs equal to 1 [0.999 to 1]. Six other Pentacam measurements, including Back maximum keratometry (Back Kmax) proved to be excellent parameters for case-finding and screening. In distinguishing sKCN from normal eyes, Pentacam index of vertical asymmetry (IVA), inferior-superior difference (I-S) value, thinnest point (TP), Belin Ambrosio Enhanced Ectasia Display (BAD_D) and root mean square total (RMS total) performed best.

Conclusions

In distinguishing sKCN from normal eyes, Back Kmax, IVA, I-S, and RMS total values demonstrated higher accuracy and utility. Six indices, namely ISV, IVA, KISA, PRC, RMS-HOA, and Back Kmax demonstrate excellent utility in case-finding and screening for clinical KCN.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Diagnostic accuracy of different keratoconus detection indices of pentacam in paediatric eyes

OBJECTIVE

No diagnostic gold standard for keratoconus in children and adolescents exists. Our objective was investigating the diagnostic accuracy of various indices for keratoconus (KC) detection in paediatric eyes.

METHODS

All retrievable data of significance from 432 normal right paediatric eyes and 48 eyes of paediatric KC and forme fruste KC (FFKC), imaged by use of a rotating Scheimpflug camera (Oculyzer II, Pentacam HR) between December 2013 and October 2018 at Watany Eye Hospitals, Cairo, Egypt, including Scheimpflug images data, were collected. The area under the receiver operating characteristic curve (AUROC) was calculated for different indices in this retrospective descriptive study.

RESULTS

All 36 tested indices showed discriminative power differentiating KC and FFKC from normal corneas (AUROC P-value <0.05), except AC volume, AC angle, and horizontal decentrations of the steepest and thinnest points. The 32 indices showed variable degrees of diagnostic accuracy. The highest AUROC was that of the corneal assessment index from the relational thickness and other OCULUS values (CAIRO 8). Only 8 indices showed non-inferiority to it, namely, Ambrosio's relational thickness maximum (ART max) and avg, the pachymetric progression index maximum (PPI max) and avg, the back elevation from the best-fit toric ellipsoid (BE BFTE), the KC index (KI), the topographic KC indices (TKC), and the index of height decentration (IHD) (P > 0.05).

CONCLUSIONS

The 8 most useful rotating Scheimpflug imaging indices for KC detection in paediatric eyes are CAIRO 8 followed by ART max and avg, PPI max and avg, BE BFTE, KI, TKC, and IHD.

Detection of subclinical keratoconus using a novel combined tomographic and biomechanical model based on an automated decision tree

Early detection of keratoconus is a crucial factor in monitoring its progression and making the decision to perform refractive surgery. The aim of this study was to use the decision tree technique in the classification and prediction of subclinical keratoconus (SKC). A total of 194 eyes (including 105 normal eyes and 89 with SKC) were included in the double-center retrospective study. Data were separately used for training and validation databases. The baseline variables were derived from tomography and biomechanical imaging. The decision tree models were generated using Chi-square automatic interaction detection (CHAID) and classification and regression tree (CART) algorithms based on the training database. The discriminating rules of the CART model selected metrics of the Belin/Ambrósio deviation (BAD-D), stiffness parameter at first applanation (SPA1), back eccentricity (Becc), and maximum pachymetric progression index in that order; On the other hand, the CHAID model selected BAD-D, deformation amplitude ratio, SPA1, and Becc. Further, the CART model allowed for discrimination between normal and SKC eyes with 92.2% accuracy, which was higher than that of the CHAID model (88.3%), BAD-D (82.0%), Corvis biomechanical index (CBI, 77.3%), and tomographic and biomechanical index (TBI, 78.1%). The discriminating performance of the CART model was validated with 92.4% accuracy, while the CHAID model was validated with 86.4% accuracy in the validation database. Thus, the CART model using tomography and biomechanical imaging was an excellent model for SKC screening and provided easy-to-understand discriminating rules.

The false positive rates for detecting keratoconus and potential ectatic corneal conditions when evaluating astigmatic eyes with Scheimpflug Technology

PURPOSE

To quantify the false positive rates for keratoconus (KC) and potential ectatic corneal conditions in highly astigmatism eyes when using published parameters/indices obtained from the Pentacam and Galilei units.

SETTING

Oftalmosalud Instituto de Ojos, Lima, Peru.

DESIGN

Prospective cohort study.

METHODS

67 consecutive eyes with corneal astigmatism > 1.5 D, with a minimum follow ups of 36 months after an uneventful LASIK procedure were included. Indices for KC and other potential ectatic corneal conditions (subclinical KC, forme fruste KC, suspect KC) were obtained using the Pentacam and Galilei Scheimpflug cameras.

MAIN OUTCOME MEASURES

The false positive rates for KC and potential ectatic corneal conditions were measured. Cut off values provided by previous studies and company-based parameters were used to assess the rate of false positivity.

RESULTS

The range of false positive rates for a KC diagnosis depending on the lowest and highest cutoff values were: index of height decentration (61% - 1%), index of surface variance (76% - 0%), Posterior elevation (55% - 0%), maximum Ambrosio Relational thickness (100% - 13%), Belin Ambrosio enhanced ectasia display total deviation value (100% - 4%), Average pachymetric progression index (69% - 3%), Pachymetry at the thinnest point (58% - 1%), CSI Center Surround Index (100%), Differential sector index (51%).

CONCLUSION

The false positive rates for KC and ectatic corneal conditions vary dramatically depending on the cut-off values used. Some indexes used for diagnosis of potential ectatic corneal conditions are inaccurate in normal, highly astigmatic eyes.

Evaluating the association between MPDZ-NF1B rs1324183 and keratoconus in an independent northwestern Chinese population

Background

Keratoconus (KC) is a complex, non-inflammatory corneal degenerative disease. Although numerous studies have analyzed the correlation of SNP rs1324183, which located in MPDZ-NF1B gene, and KC in different populations, only few findings were repeated. In this study, to evaluate the association between rs1324183 and KC in a new independent Chinese population, we performed a replication study of the significantly associated rs1324183.

Methods

In total of 114 unrelated KC patients and 88 unrelated controls were recruited from Ningxia, China. We detected the genotypes and alleles of rs1324183 using PCR technology and Sanger sequencing and also analyzed the association between this locus and KC, its clinical parameters by statistical methods.

Results

The frequency of genotype AA (11, 9.6%) and genotypes containing allele A (47, 41.2%) of rs1324183 in KC were both higher than those of the control group. And genotype AA of rs1324183 conferred a higher risk of KC (OR > 1). Moreover, corneal parameter Belin/Ambrósio enhanced ectasia display final D value (BAD-D) had significant correlation (p = 0.002) with AA genotype of rs1324183 in KC.

Conclusions

Our replication study indicates that the results of rs1324183 associated with KC in our population is robust and further better illustrates the significance of BAD-D as a diagnostic indicator for KC. rs1324183 should be considered as the first genetic mark of KC risk in its future diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-022-02359-1.

[Prospects for early detection of keratoconus based on systems built for computer-assisted diagnostics of structural changes in the cornea]

The article is devoted to the problem of diagnosing subclinical keratoconus (KK). The need to identify early signs of KK is primarily associated with the potential for the development of iatrogenic keratoectasia in cases of underdiagnosis of the disease when determining the conditions for laser keratorefractive surgery involving a decrease in the thickness of the cornea. Today generally accepted algorithms for early computer-assisted diagnosis of KK are mainly based on the analysis of various morphometric parameters of the cornea, reflecting changes in its shape and thickness induced by structural abnormalities. Direct detection of structural changes in the cornea characteristic of early KK requires the use of high-tech imaging methods that are not always applicable in everyday clinical practice. The promising approach proposed in this study is based on the fact that a digital image of a corneal «slice» obtained using serial analyzers such as the Scheimpflug camera widely used in clinical practice provides indirect information about the structure of the epithelial layer, the local thickening of which takes place in the initial stages KK. It is this criterion that underlies the proposed system of computer-assisted diagnosis of KK. The carried out studies have shown the high sensitivity of this algorithm, and its specificity can be increased by involving the known diagnostic indicators of KK.

Evaluation of corneal topography, pachymetry and higher order aberrations for detecting subclinical keratoconus

PURPOSE

To compare corneal topography, pachymetry and higher order aberrations in keratoconic and normal eyes; to investigate their association in keratoconic eyes; and to determine their diagnostic ability for detecting subclinical keratoconus in a Nepalese population.

METHODS

Ninety-six eyes of 48 keratoconus patients and 50 normal eyes of 50 control subjects were included in this study. The eyes of keratoconus patients were classified into four different study groups: subclinical, stage 1, stage 2 and advanced stage keratoconus. In each eye, corneal topography, pachymetry and corneal aberrometry indices were measured using a Sirius corneal tomographer. The study parameters of keratoconic eyes were compared with normal eyes, and the possible association of corneal aberrometry with topography and pachymetry indices was investigated. The area under curve (AUC) of receiver operating characteristic (ROC) curves along with optimal cutoff values with best sensitivity and specificity were also determined for each index to detect subclinical keratoconus.

RESULTS

All the indices except average keratometry measurements (K_avg and mm_avg ) and spherical aberration (SA) were found to be significantly different in subclinical keratoconus compared to the control group (p < 0.05). In keratoconic eyes, all corneal aberrations were significantly correlated with the topography and pachymetry indices (range of ρ: -0.25 to 0.96; all p < 0.05) except for trefoil and minimum corneal thickness (Thk_min ). All the indices except K_avg , mm_avg and SA showed excellent diagnostic ability (AUC > 0.90) in detecting subclinical keratoconus. The cutoff values proposed for the asymmetry index of the corneal back surface (SI_b ), Strehl ratio of point spread function (PSF), coma and Baiocchi-Calossi-Versaci index of corneal back surface (BCV_b ) each showed excellent sensitivity (100%) and specificity (≥97%).

CONCLUSIONS

Corneal higher order aberrations were found to be significantly elevated in subclinical keratoconus compared to healthy controls. SI_b , PSF, coma and BCV_b were identified as the most powerful Sirius indices for the detection of subclinical keratoconus.

Comparison of Artificial Intelligence-Based Machine Learning Classifiers for Early Detection of Keratoconus

Purpose

To compare the agreement between artificial intelligence (AI)-based classifiers and clinical experts in categorizing normal cornea from ectatic conditions.

Methods

Prospective diagnostic test study at Noor Eye Hospital. Two hundred twelve eyes of 212 patients were categorized into three groups of 92 normal, 52 subclinical keratoconus (SKCN), and 68 KCN eyes based on clinical findings by 3 independent expert examiners. All cases were then categorized using four different classifiers: Pentacam Belin/Ambrosio enhanced ectasia total deviation value (BADD) and Topographic Keratoconus Classification (TKC), Sirius Phoenix, and OPD-Scan III Corneal Navigator. The performance of classifiers and their agreement with expert opinion were investigated using the sensitivity, specificity, and Kappa index (κ).

Results

For detecting SKCN, Phoenix had the highest agreement with the clinical diagnosis (sensitivity, specificity, and κ of 84.62%, 90.0%, and 0.70, respectively) followed by BADD (55.56%, 86.08%, 0.42), TKC (26.92%, 97.50%, 0.30), and Corneal Navigator (30.77%, 93.75%, 0.29). For KCN diagnosis, the highest agreement with expert opinion was seen for Phoenix (80.02%, 96.60%, 0.79), BADD (95.59%, 85.42%, 0.75), TKC (95.59%, 84.03%, 0.73), and Corneal Navigator (67.65%, 96.45%, 0.68). Analysis of different classifiers showed that Phoenix had the highest accuracy for differentiating KCN (91.24%) and SKCN (88.68%) compared to other classifiers.

Conclusions

Although AI-based classifiers, especially Sirius Phoenix, can be very helpful in detecting early keratoconus, they cannot replace clinical experts’ opinions, particularly for decision-making before refractive surgery. Albeit, there may be concerns about the accuracy of clinical experts as well.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Keratoconus: An updated review

Keratoconus is a bilateral and asymmetric disease which results in progressive thinning and steeping of the cornea leading to irregular astigmatism and decreased visual acuity. Traditionally, the condition has been described as a noninflammatory disease; however, more recently it has been associated with ocular inflammation. Keratoconus normally develops in the second and third decades of life and progresses until the fourth decade. The condition affects all ethnicities and both sexes. The prevalence and incidence rates of keratoconus have been estimated to be between 0.2 and 4,790 per 100,000 persons and 1.5 and 25 cases per 100,000 persons/year, respectively, with highest rates typically occurring in 20- to 30-year-olds and Middle Eastern and Asian ethnicities. Progressive stromal thinning, rupture of the anterior limiting membrane, and subsequent ectasia of the central/paracentral cornea are the most commonly observed histopathological findings. A family history of keratoconus, eye rubbing, eczema, asthma, and allergy are risk factors for developing keratoconus. Detecting keratoconus in its earliest stages remains a challenge. Corneal topography is the primary diagnostic tool for keratoconus detection. In incipient cases, however, the use of a single parameter to diagnose keratoconus is insufficient, and in addition to corneal topography, corneal pachymetry and higher order aberration data are now commonly used. Keratoconus severity and progression may be classified based on morphological features and disease evolution, ocular signs, and index-based systems. Keratoconus treatment varies depending on disease severity and progression. Mild cases are typically treated with spectacles, moderate cases with contact lenses, while severe cases that cannot be managed with scleral contact lenses may require corneal surgery. Mild to moderate cases of progressive keratoconus may also be treated surgically, most commonly with corneal cross-linking. This article provides an updated review on the definition, epidemiology, histopathology, aetiology and pathogenesis, clinical features, detection, classification, and management and treatment strategies for keratoconus.

Corneal Scheimpflug topography values to distinguish between normal eyes, ocular allergy, and keratoconus in children

To identify and compare keratometric, corneal thickness, and elevation parameters and indices among healthy children, ocular allergy, and keratoconus using the OCULUS Pentacam Scheimpflug topography system. This study included healthy children, children with ocular allergy (OA) without keratoconus, and children with keratoconus (KC). The study design consisted of a prospective evaluation and review of medical records from a Brazilian ophthalmology department. The exclusion criteria were inability to undergo the ocular exam, other ocular diseases, contact lens wear, and topographic corneal ectasia. The effect of each corneal parameter was evaluated using univariate and multivariate logistic regression models adjusted for sex and age, and ROC curves were used to assess the ability each variable to discriminate among groups. A total of 182 subjects were included: healthy children (n = 99), children with OA (n = 32), and children with KC (n = 51). Groups differed in terms of sex, with more males in the OA group (73.2%) and the KC group (67.7%) than in the control group (40.9%). All corneal parameters studied differed significantly between the control and KC groups, and between the OA and KC groups; they also differed significantly between the three groups in terms of astigmatism, q-value, CCT, TP, BAD-D, and ARTmax values. We present the first study to describe and compare corneal tomographic parameters in healthy children, OA, and KC. Keratometry indices, ACD, ARTmax, AETP, and PETP were found to be the most useful for differentiating between healthy and KC children.IBR registry number: CAAE 54921916.9.0000.5404.

Accuracy of the indices of MS-39 anterior segment optical coherence tomography in the diagnosis of keratoconic corneas

PURPOSE

To determine the normative and the cut-off values of various indices available in the MS 39 Anterior Segment Optical Coherence Tomography (MS-39 AS-OCT) for keratoconus (KC) diagnosis, and to detect the accuracy of the variable available parameters.

METHODS

This cross sectional observational study was conducted at Dr Rifay Ophthalmology Center, Rabat, Morocco, on 172 eyes with KC (group 1) and 248 eyes of healthy controls (group 2). Participants were screened using MS-39 AS-OCT (CSO, Firenze, Italy). The investigated indices included: keratometric indices, pachymetric indices, elevation indices, Keratoconus Summary Indices (KSI), aberration indices, and epithelial mapping evaluation.

RESULTS

Most of the studied indices were significantly different between both groups (P value <0.001). Twenty two indices had Area Under the Receiver Operating Curve (AUROC) values >0.950, eight of which were from the KSI. The indices with the highest AUROC values were: Root Mean Square (RMS) for the front corneal surface at 6 mm circle (AUROC = 0.996, and best cut-off >1.69 with sensitivity of 97.67% and specificity of 97.98%) and RMS per unit of area for the front surface at 6 mm circle (AUROC = 0.996, and best cut-off >0.06 with sensitivity of 97.67% and specificity of 97.98%). Epithelial thickness-derived metrics were not among the parameters with the highest accuracy.

CONCLUSIONS

This study presented the mean and the cut-off values for a plethora of parameters available in the MS-39 AS-OCT. The results of this study show that MS-39 AS-OCT is a valuable equipment for diagnosing keratoconic corneas, with a high accuracy detected for many parameters.

Detecting subclinical keratoconus by biomechanical analysis in tomographically regular keratoconus fellow eyes

PURPOSE

To analyze the tomographically non-affected second eyes of keratoconus patients using the Corvis ST to detect any biomechanical abnormalities or subclinical keratoconus.

METHODS

In this retrospective, single-center, consecutive case series 244 eyes of 122 keratoconus patients were analyzed between November 2020 and February 2021. Fourteen fellow eyes fulfilled the inclusion criteria and showed no clinical or tomographic signs of keratoconus. Main outcome measures included best-corrected visual acuity, tomographic and biomechanical analyses using Scheimpflug imaging: Pentacam and Corvis ST (Oculus, Wetzlar, Germany). Tomographic analyses included anterior and posterior simulated keratometry, K-Max, central corneal thickness, thinnest corneal thickness, Belin/Ambrosio Ectasia Display, and the ABCD grading system. For biomechanical analyses, the corneal biomechanical index (CBI) and tomographic biomechanical index were used.

RESULTS

The mean best-corrected visual acuity was 0.01 ± 0.10 logMAR. Mean K-Max was 43.79 ± 1.12 D, mean central corneal thickness 529 ± 25 µm, mean thinnest corneal thickness 524 ± 23 µm, and mean Belin/Ambrosio Ectasia Display 1.0 ± 0.32. The mean CBI was 0.30 ± 0.21. Regular CBI values were found in six of 14 patients. The mean tomographic biomechanical index was 0.47 ± 0.22 with regular values observed in only two of 14 patients. No signs of tomographic or biomechanical abnormalities were shown in only one of 14 keratoconus fellow eyes, with regular ABCD, Belin/Ambrosio Ectasia Display, CBI and tomographic biomechanical index values.

CONCLUSIONS

Tomographically normal fellow eyes of keratoconus patients are rare. In these cases, a biomechanical analysis of the cornea may help detect a subclinical keratoconus. The tomographic biomechanical index was the most sensitive index to verify a mild ectasia.

Sensitivity and specificity of Sirius indices in diagnosis of keratoconus and suspect keratoconus

AIM

To estimate the sensitivity and specificity of topographic and tomographic corneal parameters as determined by Sirius (CSO, Florence, Italy) in discriminating keratoconus (KC) and suspect keratoconus from normal cornea.

METHOD

In this retrospective case-series study, keratoconus screening indices were measured using Sirius tomographer. Receiver operating characteristics (ROC) curves were used to determine the test's overall predictive accuracy (area under the curve) and to identify optimal cut-off points to maximize sensitivity and specificity in differentiating keratoconus and suspect keratoconus from normal corneas.

RESULTS

Receiver operating characteristics (ROC) curve analyses showed high predictive accuracy for Symmetry Index back (SIb), Keratoconus Vertex front (KVf), Symmetry Index front (SIf), Keratoconus Vertex back (KVb), Apex Keratometry (Curve-Apex) and Minimum corneal Thickness (ThkMin) to distinguish keratoconus from normal (area under the curve > 0.9, all). Symmetry Index back was identified as the best diagnostic parameter for detecting suspect keratoconus with AUC of 0.86. Highest specificity to detect keratoconus and suspect keratoconus was seen for SIb, 99.87% and 84.66%, respectively. These values were associated with optimal cut-off points of 0.46 D for keratoconus and 0.12 D for suspect keratoconus.

CONCLUSION

Sirius parameters evaluated in the study were effective to differentiate keratoconus from normal corneas. However, Symmetry Index back was the index with the highest ability to detect suspect keratoconus.

Agreement of Anterior Segment Parameters Between Schiempflug Topography and Swept-Source Optic Coherence Based Optic Biometry in Keratoconus and Healthy Subjects

PURPOSE

The aim of this study is to compare anterior segment parameters, including corneal thickness (CCT), keratometry and anterior chamber depth (ACD), and white to white corneal diameter (WTW), obtained by Pentacam Schiempflug imaging and intraocular lens (IOL) Master 700 swept-source optic coherence tomography biometry in keratoconus patients and healthy subjects.

METHODS

This prospective cross-sectional instrument agreement analysis includes 88 eyes of 50 keratoconus patients and 87 eyes of 50 healthy subjects. Biometry was performed using IOL Master 700, and topography was performed using Pentacam. The keratometry values (Kf, Ks, Km, and Kmax), ACD, WTW, CCT, axial length (AL), anterior chamber angle (ACA), and lens thickness (LT) were evaluated. Levels of agreement between devices were evaluated by Bland-Altman plots with 95% limits of agreement.

RESULTS

Intraocular lens Master 700 showed higher WTW, ACD, pupil diameter, and CCT values than Pentacam in both the keratoconus and control groups. However, there were no statistically significant differences in flat keratometry (Kf) and steep keratometry (Ks) values between the groups.

CONCLUSION

Pentacam and IOL Master 700 may be used interchangeably in normal eyes and keratoconus eyes for the measurement of keratometry values and axis; however, these two devices should not be considered interchangeable for WTW, ACD, pupil diameter, and CCT measurements in both keratoconus patients and healthy subjects.

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

PURPOSE

To evaluate the ABCD grading system in pediatric keratoconus.

METHODS

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

RESULTS

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

CONCLUSIONS

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

Application of a scheimpflug-based biomechanical analyser and tomography in the early detection of subclinical keratoconus in chinese patients

Background

In vivo corneal biomechanics evaluation has been used to help screen early keratoconus in recent years. This study is to evaluate the value of a Scheimpflug-based biomechanical analyser combined with tomography in detecting subclinical keratoconus by distinguishing normal eyes from frank keratoconus (KC) and forme frusta keratoconus (FFKC) eyes in Chinese patients.

Methods

Study design: diagnostic test. This study included 31 bilateral frank keratoconus patients, 27 unilateral clinically manifesting keratoconus patients with very asymmetric eyes, and 79 control subjects with normal corneas. Corneal morphological and biomechanical parameters were measured using a Pentacam HR and a Corvis ST (OCULUS, Wetzlar, Germany). The diagnostic ability of computed parameters reflecting corneal biomechanical and morphological traits [including the Belin-Ambrósio deviation index (BAD_D), the Corvis biomechanical index (CBI) and the tomographic and biomechanical index (TBI)] was determined using receiver operating characteristic (ROC) curve analysis and compared by the DeLong test. Additionally, the area under the curve (AUC), the best cut-off values, and the Youden index for each parameter were reported. A novel corneal stiffness parameter, the stress-strain index (SSI), was also compared between KC, FFKC and normal eyes.

Results

Every morphological and biomechanical index analysed in this study was significantly different among KC, FFKC and normal eyes (P = 0.000). The TBI was most valuable in detecting subclinical keratoconus (FFKC eyes), with an AUC of 0.928 (P = 0.000), and both forms of corneal ectasia (FFKC and frank KC eyes), with an AUC of 0.966 (P = 0.000). The sensitivity and specificity of the TBI was 97.5 and 77.8 % in detecting FFKC and 97.5 and 89.7 % in detecting any KC, respectively, with a cut-off value of 0.375. The morphological index BAD_D and the biomechanical index CBI were also very useful in distinguishing eyes with any KC from normal eyes, with AUCs of 0.965 and 0.934, respectively. The SSI was significantly different between KC, FFKC and normal eyes (P = 0.000), indicating an independent decrease in corneal stiffness in KC eyes.

Conclusions

The combination of a Scheimpflug-based biomechanical analyser and tomography could increase the accuracy in detecting subclinical keratoconus in Chinese patients. The TBI was the most valuable index for detecting subclinical keratoconus, with a high sensitivity and specificity. Evaluation of corneal biomechanical properties in refractive surgery candidates could be helpful for recognizing potential keratoconic eyes and increasing surgical safety.

Evaluation of CorvisST biomechanical parameters and anterior segment optical coherence tomography for diagnosing forme fruste keratoconus

PURPOSE

To investigate the utility of biomechanical property measurements using a Scheimpflug-based tonometer (SBT) and/or anterior segment optical coherence tomography (AS-OCT) for diagnosing forme fruste keratoconus (FFK).

METHODS

In this retrospective interventional case series, 23 eyes with FFK of 23 consecutive patients and 52 eyes of 52 healthy volunteers who visited our keratoconus outpatient clinic were enrolled. Logistic regression analysis was conducted to determine the causal relationship between FFK diagnosis and each parameter.

RESULTS

When only SBT was used, the corneal stiffness parameter, stiffness parameter A1 (SP-A1) and the corneal velocity at first applanation were selected as explanatory variables, and sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) were 82.9%, 86.9% and 0.938, respectively. When only AS-OCT parameters were used, the posterior corneal asymmetric component and central corneal thickness were selected, and the sensitivity, specificity and AUROC were 82.6%, 94.2% and 0.893, respectively. When parameters from both methods were used, SP-A1 and the posterior corneal asymmetry component derived from Fourier analysis were selected as explanatory variables, and sensitivity, specificity and AUROC were 91.30%, 90.38% and 0.947, respectively. No significant differences in AUROC were observed between diagnoses using each device and the combination of both devices (AS-OCT versus SBT, p = 0.314; integrated parameters versus AS-OCT, p = 0.081; integrated parameters versus SBT, p = 0.234).

CONCLUSION

Optimization of SBT and AS-OCT parameters allowed for the diagnosis of FFK at a clinically usable level. Forme fruste keratoconus (FFK) diagnosis integrating biomechanical properties with AS-OCT showed no superiority compared to diagnosis based on a single device.