Comparison of the morphological and biomechanical characteristics of keratoconus, forme fruste keratoconus, and normal corneas

A Comprehensive Survey on Emerging Assistive Technologies for Visually Impaired Persons: Lighting the Path with Visible Light Communications and Artificial Intelligence Innovations

In the context in which severe visual impairment significantly affects human life, this article emphasizes the potential of Artificial Intelligence (AI) and Visible Light Communications (VLC) in developing future assistive technologies. Toward this path, the article summarizes the features of some commercial assistance solutions, and debates the characteristics of VLC and AI, emphasizing their compatibility with blind individuals' needs. Additionally, this work highlights the AI potential in the efficient early detection of eye diseases. This article also reviews the existing work oriented toward VLC integration in blind persons' assistive applications, showing the existing progress and emphasizing the high potential associated with VLC use. In the end, this work provides a roadmap toward the development of an integrated AI-based VLC assistance solution for visually impaired people, pointing out the high potential and some of the steps to follow. As far as we know, this is the first comprehensive work which focuses on the integration of AI and VLC technologies in visually impaired persons' assistance domain.

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.

Accuracy of an Air-Puff Dynamic Tonometry Biomarker to Discriminate the Corneal Biomechanical Response in Patients With Keratoconus

PURPOSE

The aim of this study was to assess accuracy of the mean corneal stiffness ( kc , N/m) parameter to discriminate between patients with keratoconus and age-matched healthy subjects.

METHODS

Dynamic Scheimpflug imaging tonometry was performed with Corvis ST (Oculus Optikgeräte GmbH, Germany) in patients with keratoconus (n = 24; study group) and age-matched healthy subjects (n = 32; control). An image processing algorithm was developed to analyze the video sequence of the Corvis ST air-puff event and to determine the geometric and temporal parameters that correlated with the corneal tissue biomechanical properties. A modified 3-element viscoelastic model was used to derive the kc parameter, which represented the corneal tissue resistance to deformation under load. Receiver operating characteristic curves were used to assess the overall diagnostic performance for determining the area under the curve, sensitivity, and specificity of the kc in assessing the corneal tissue deformation to the Corvis ST air-puff event in keratoconus and control eyes. The Corvis Biomechanical Index ( CBI ) was analyzed for external validation.

RESULTS

The kc parameter was significantly different between keratoconus and controls ( P < 0.001), ranging from 24.9 ±3.0 to 34.2 ±3.5 N/m, respectively. It was highly correlated with CBI (r = -0.69; P < 0.001); however, the kc parameter had greater specificity (94%) than CBI (75%), whereas the 2 biomarkers had similar area under the curve (0.98 vs. 0.94) and sensitivity (96% vs. 92%) in predicting the occurrence of keratoconus.

CONCLUSIONS

The kc parameter extracted by video processing analysis of dynamic Scheimpflug tonometry data was highly accurate in discriminating patients with clinically manifest keratoconus compared with controls.

Performance of Corvis ST Parameters Including Updated Stress-Strain Index in Differentiating Between Normal, Forme-Fruste, Subclinical, and Clinical Keratoconic Eyes

PURPOSE

This study seeks to evaluate the ability of the updated stress strain index (SSIv2) and other Corvis ST biomechanical parameters in distinguishing between keratoconus at different disease stages and normal eyes.

DESIGN

Diagnostic accuracy analysis to distinguish disease stages.

METHODS

1084 eyes were included and divided into groups of normal (199 eyes), forme fruste keratoconus (FFKC, 194 eyes), subclinical keratoconus (SKC, 113 eyes), mild clinical keratoconus (CKC-Ⅰ, 175 eyes), moderate clinical keratoconus (CKC-Ⅱ, 204 eyes), and severe clinical keratoconus (CKC-Ⅲ, 199 eyes). Each eye was subjected to a Corvis ST examination to determine the central corneal thickness (CCT), biomechanically corrected intraocular pressure (bIOP), SSIv2 (updated stress-strain index), and other 8 Corvis parameters including the stress-strain index (SSIv1), stiffness parameter at first applanation (SP-A1), first applanation time (A1T), Ambrósio relational thickness to the horizontal profile (ARTh), integrated inverse radius (IIR), maximum deformation amplitude (DAM), ratio between deformation amplitude at the apex and at 2 mm nasal and temporal (DARatio2), and Corvis biomechanical index (CBI). The sensitivity and specificity of these parameters in diagnosing keratoconus were analyzed through receiver operating characteristic curves.

RESULTS

Before and after correction for CCT and bIOP, SSIv2 and ARTh were significantly higher and IIR and CBI were significantly lower in the normal group than in the FFKC group, SKC group and the 3 CKC groups (all P < .05). There were also significant correlations between the values of SSIv2, ARTh, IIR, CBI, and the CKC severity (all P < .05). AUC of SSIv2 was significantly higher than all other Corvis parameters in distinguishing normal eyes from FFKC, followed by IIR, ARTh and CBI.

CONCLUSION

Corvis ST's updated stress-strain index, SSIv2, demonstrated superior performance in differentiating between normal and keratoconic corneas, and between corneas with different keratoconus stages. Similar, but less pronounced, performance was demonstrated by the IIR, ARTh and CBI.

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.

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.

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.

Detection of Keratoconus With a New Corvis Biomechanical Index Optimized for Chinese Populations

PURPOSE

The aim of this study was to introduce an optimized version of the Corvis Biomechanical Index for Chinese populations (cCBI).

DESIGN

Retrospective, multicenter clinical validity enhancement study.

METHODS

Patients were included from 7 clinics in Beijing, Shenyang, Guangzhou, Shanghai, Wenzhou, Chongqing, and Tianjin, China. Logistic regression was used to optimize the values of the constants of the CBI, based on database 1 as the development dataset (6 of 7 clinics), to create a new version of the index named cCBI. The factors of the CBI (A1Velocity, ARTh, Stiffness Parameter-A, DARatio2mm, and Inverse Integrated Radius) and the cutoff value were kept the same (0.5). With the formation of cCBI determined, it was validated on database 2 (1 of the 7 clinics).

RESULTS

Two thousand four hundred seventy-three patients (healthy and keratoconus) were included. In database 2, the area under the curve of the cCBI was 0.985 with 93.4% specificity and 95.5% sensitivity. In the same dataset, the original CBI produced an area under the curve of 0.978 with 68.1% specificity and 97.7% sensitivity. There was a statistically significant difference between the receiver operating characteristic curve of cCBI and CBI (De Long P = .0009) CONCLUSION: The new cCBI for Chinese patients was shown to be statistically significantly better when compared with CBI to separate healthy from keratoconic eyes. The presence of an external validation dataset confirms this finding and suggests the use of cCBI in everyday clinical practice to aid in the diagnosis of keratoconus in patients who are of Chinese ethnicity.

Detection ability of corneal biomechanical parameters for early diagnosis of ectasia

PURPOSE

To assess the detection ability of corneal biomechanical parameters for early diagnosis of ectasia.

METHODS

This retrospective descriptive-analytical study included 134 normal eyes (control group) from 134 healthy subjects and 128 eyes with asymmetric contralateral corneal ectasia with normal topography (ACE-NT, study group) from 128 subjects with definite keratoconus in the opposite eye. Placido-disk-based corneal topography with TMS-4, Scheimpflug corneal tomography with Pentacam HR, and corneal biomechanical assessment with Corvis ST and ocular response analyzer (ORA) were performed. A general linear model was used to compare Corvis ST and ORA biomechanical parameters between groups, while central corneal thickness (CCT) and biomechanically corrected intraocular pressure (bIOP) were considered covariates. Receiving operator sensitivity curve (ROC) analysis was used to determine the cut-off point with the highest sensitivity and specificity along with the area under the curve (AUC) for each parameter.

RESULT

All parameters of Corvis ST and ORA showed a statistically significant difference between the two groups except for the first (P = 0.865) and second (P = 0.226) applanation lengths, and deformation amplitude (P = 0.936). The discriminative analysis of corneal biomechanical showed that the highest accuracy for the classic, new, and combined parameters of Corvis ST was related to HCR (AUC: 0.766), IR & DAR (0.846), and TBI (0.966), respectively. Using ORA, the corneal resistance factor (0.866) had a higher detection ability than corneal hysteresis (0.826).

CONCLUSIONS

TBI has the best accuracy and the highest effect size for differential diagnosis of normal from ACE-NT eyes with a cut-off point of 0.24.

Refractive and Topographic Parameters of the Belin/Ambrósio Module in Patients with Refractive Defects in Cuenca, Ecuador

Objective:

This study aimed to describe the refractive and topographic parameters of the Belin/Ambrósio module in patients with refractive defects at the Latino clinic in Cuenca, Ecuador, between 2017 to 2021.

Methods:

A descriptive, cross-sectional study was carried out. A database included anonymous cases of patients with refractive defects treated at the ophthalmological consultation of a Latino clinic from January, 2017 to June, 2021 was searched. Data was collected using a form containing study variables. Microsoft Excel and SPSS were used for data collection and analysis using frequencies, percentages, and measures of central tendency.

Results:

The sample consisted of 120 patients; 61.7% were women, and 38.3% were men. Moreover, 70.8% of patients were young adults. The pachymetry mean of the center of the pupil, apex, and position of lowest pachymetry was 521 µm, 520 µm, and 513 µm, respectively. The means of the flattest keratometry, curviest keratometry, and maximum keratometry were 43.30 D, 46.32 D, and 48.01 D, respectively.

Conclusion:

Cases distribution according to anterior and posterior elevation showed pathological values ​​in more than 50% of the studied corneas. According to the average progression index, pathological elevation was found in 18.8% of the cases, and according to the average deviations, 25.4% presented corneal ectasia in different stages.

Keratoconus: A Biomechanical Perspective

PURPOSE

The relevance of corneal biomechanics and the importance of including it in the clinical assessment of corneal ectasias are being increasingly recognized. The connection between corneal ultrastructure, biomechanical properties, and optical function is exemplified by a condition like keratoconus. Biomechanical instability is seen as the underlying basis for the secondary morphological changes in the cornea. Asymmetric biomechanical weakening is believed to drive progressive corneal steepening and thinning. Biomechanical strengthening is the principle of collagen crosslinking that has been shown to effectively arrest progression of the keratoconus. Corneal biomechanics has therefore ignited the interest of researchers and clinicians alike and has given us new insights into the cause and course of the disease. This article is an overview of the extensive work published, predominantly in the last two decades, on the biomechanical aspect of keratoconus.

METHODS

Published articles on corneal biomechanics in the specific context of keratoconus were reviewed, based on an electronic search using PubMed, Elsevier, and Science Direct. The search terms used included "Corneal Biomechanics," "Mechanical properties of the cornea," "Corneal ultrastructure," "Corneal Collagen," and "Keratoconus". Articles pertaining to refractive surgery, keratoplasty, collagen crosslinking, or intrastromal rings were excluded.

RESULTS

The electronic search revealed more than 500 articles, from which 80 were chosen for this article.

CONCLUSIONS

The structural and organizational pattern of the corneal stroma determines its mechanical properties and are responsible for the maintenance of the normal shape and function of the cornea. Changes in the ultrastructure are responsible for the biomechanical instability that leads to corneal ectasia. As non-invasive methods for evaluating corneal biomechanics in vivo evolve, our ability to diagnose subclinical keratoconus will improve, allowing identification of patients at risk to develop ectasia and to allow early treatment to arrest progression of the disease.

Analysis of the diagnostic accuracy of Belin/Ambrósio Enhanced Ectasia and Corvis ST parameters for subclinical keratoconus

OBJECTIVE

To investigate the diagnostic accuracy of the parameters in the Belin/Ambrósio Enhanced Ectasia Display built in Pentacam, which is designed for the screening of subclinical keratoconus (SKC) built in Pentacam, and the parameters in Corneal visualization Scheimpflug technology (Corvis ST).

METHODS

A retrospective study: The fellow eyes of unilateral keratoconus cases were diagnosed with SKC. Patients presented to Shanxi Eye Hospital with SKC from October 2020 to November 2021 were included as the SKC group, and myopic patients undergoing corneal refractive surgery at the Refractive Surgery Department in our hospital within the same period were included as the control group. The Belin/Ambrósio and Corvis ST parameters were extracted from the system and analyzed using independent samples t test. Receiver operating curves (ROCs) were also created to test the diagnostic accuracy of each parameter.

RESULTS

There were 70 patients (70 eyes) in the SKC group and 137 patients (137 eyes) in the control group. For Corvis ST parameters, Radius (P = 0.021), PachySlope (P = 0.040), SP-A1 (P = 0.002), A2 Deformation Amp. (P = 0.028), A2 Deflection Length (P < 0.001), Max ICR (P = 0.005), DA Ratio Max (1 mm) (P = 0.023), IR (P = 0.016), CBI (P = 0.003) and TBI (P < 0.001) were statistically different between the two groups. For Belin/Ambrósio parameters, PPI min. Axis, ART min, ART max, ART avg, Pachy min, Front K2, Astig, BAD-Df, BAD-Db, BAD-Dp, BAD-Dt, BAD-Da, BAD-D, PPI min, PPI max, PPI max. Axis, PPI avg and Dist.Apex-Thin.Loc. were significantly different between the two groups (all p < 0.001). TBI and BAD-D showed the best diagnostic accuracy, with AUCs of 0.944 and 0.965, respectively.

CONCLUSIONS

Some Belin/Ambrósio and Corvis ST parameters differed between SKC eyes and eyes with normal cornea. TBI and BAD-D showed the ideal diagnostic performance for SKC. In clinical practice, conventional corneal topography could not be replaced by Corvis ST.

In Vivo Corneal Biomechanical Properties in a Selected Chinese Population, Measured Using the Corneal Visualization Scheimpflug Technology

Purpose: To evaluate the repeatability and reproducibility of recalculated dynamic corneal response (DCR) parameters and the biomechanical-compensated intraocular pressure (bIOP) derived from the Corneal Visualization Scheimpflug Technology (Corvis ST), as well as to study the variations of DCR parameters and their relationship with demographic, and ocular characteristics.

Methods: A total of 544 healthy subjects were recruited in this study and a series of ophthalmological examinations were performed on their right eyes. Three repeated measurements were obtained at 3-min intervals for 291 of the participants to ensure repeatability. A sum of 100 participants was examined twice within 2-h intervals using two different Corvis ST in the reproducibility study. The repeatability and reproducibility of 37 parameters, including 36 DCR parameters and bIOP, were assessed by the coefficient of repeatability (CR), coefficient of variation (CV), intraclass correlation coefficient (ICC), and within-subject standard deviation (sw). Pearson’s correlation coefficients and stepwise multivariate linear regression models were performed to investigate whether the DCR parameters were related to demographic and ocular characteristics.

Results: Of all the 37 parameters, 34 showed excellent (ICC ≥0.90) or good (ICC ≥0.75) repeatability while 27 of the 37 parameters showed excellent (ICC ≥0.90) or good (ICC ≥0.75) reproducibility. In particular, a CV of less than 20% was found for all DCR parameters and bIOP. A fraction of 14 out of 36 DCR parameters was selected for correlation analysis, based on measurement reliability and clinical relevance in referring to previous literature. Age was negatively associated with the Highest concavity delta arc length (HCdArcL) and peak distance (PD) but it positively correlated with the Whole Eye Movement Max Length (WEMML). Intraocular pressure (IOP) and central corneal thickness (CCT) were negatively associated with the deformation amplitude ratio (DARM) [1 mm], A1 Velocity (A1V), and PD, while positively related to the stiffness parameter at applanation 1 (SP-A1). The bIOP was negatively associated with A1V but positively associated with A2 Velocity (A2V). The anterior chamber volume (ACV) was negatively associated with the pachy slope (PS), WEMML, and SP-A1.

Conclusion. The Corvis ST showed good precision for the repeatability and reproducibility of 36 DCR parameters and bIOP parameters in healthy eyes. The IOP, CCT, bIOP, Km, and ACV significantly influenced the DCR parameters of the eyes.

Visual Corneal Photomechanical Analysis Is Combined with the Pentacam Correlation Index for the Diagnosis of Cone Corneas at Different Stages of Progression

Cone-shaped corneas are blinding eye diseases characterised by dilated and thinning corneal tissue and forward conical protrusions, most often in adolescents. Early detection and intervention can prevent further dilatation of the cornea. The prevailing examination methods and techniques are not difficult to diagnose clinical cone corneas, but there are limitations in the diagnosis of early cone corneas (static cone corneas and subclinical cone corneas). In this study, we investigated the diagnostic value of the combination of these two instruments in the diagnosis of clinical cone corneas and subclinical cone corneas by performing the Pentacam and Corvis ST examinations in healthy eyes and dystrophic cone corneas. This study provides a theoretical basis for early cone cornea screening and diagnosis. The analysis revealed that only TP, SPA1, ARTh, and bIOP were normally distributed among all included parameters, and only bIOP was normally distributed with equal variance. TBI and CBI indices have a certain sensitivity and specificity for the diagnosis of subclinical cone corneas, with a strong diagnostic ability, and can be used for screening and early diagnosis of cone corneas.

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.].

Alteration of corneal biomechanical properties in patients with dry eye disease

Purpose

To evaluate the association between symptoms and signs of dry eye diseases (DED) with corneal biomechanical parameters.

Methods

This cross-sectional study enrolled 81 participants without history of ocular hypertension, glaucoma, keratoconus, corneal edema, contact lens use, diabetes, and ocular surgery. All participants were evaluated for symptoms and signs of DED using OSDI questionnaire, tear film break-up time (TBUT), conjunctival and corneal staining (NEI grading) and Schirmer test. Corneal biomechanical parameters were obtained using Corvis ST. Mixed-effects linear regression analysis was used to determine the association between symptoms and signs of DED with corneal biomechanical parameters. Difference in corneal biomechanical parameter between participants with low (Schirmer value ≤10 mm; LT group) and normal (Schirmer value >10mm; NT group) tear production was analyzed using ANCOVA test.

Results

The median OSDI scores, TBUT, conjunctival and corneal staining scores as well as Schirmer test were 13±16.5 (range; 0–77), 5.3±4.2 seconds (range; 1.3–11), 0±1 (range; 0–4), 0±2 (ranges; 0–9) and 16±14 mm (range; 0–45) respectively. Regression analysis adjusted with participants’ refraction, intraocular pressure, and central corneal thickness showed that OSDI had a negative association with highest concavity radius (P = 0.02). The association between DED signs and corneal biomechanical parameters were found between conjunctival staining scores with second applanation velocity (A2V, P = 0.04), corneal staining scores with second applanation length (A2L, P = 0.01), Schirmer test with first applanation time (A1T, P = 0.04) and first applanation velocity (P = 0.01). In subgroup analysis, there was no difference in corneal biomechanical parameters between participants with low and normal tear production (P>0.05). The associations were found between OSDI with time to highest concavity (P<0.01) and highest displacement of corneal apex (HC-DA, P = 0.04), conjunctival staining scores with A2L (P = 0.01) and A2V (P<0.01) in LT group, and Schirmer test with A1T (P = 0.02) and HC-DA (P = 0.03), corneal staining scores with A2L (P<0.01) in NT group.

Conclusions

According to in vivo observation with Corvis ST, patients with DED showed more compliant corneas. The increase in dry eye severity was associated with the worsening of corneal biomechanics in both patients with low and normal tear production.