A new, pachymetry-based approach for diagnostic cutoffs for normal, suspect and keratoconic cornea

Corneal topometric indices and proclivity toward corneal ectasia in vernal keratoconjunctivitis

PURPOSE

To investigate changes in topometric corneal indices and proclivity toward corneal ectasia, as well as keratometric indices and anterior chamber dimensions in palpebral vernal keratoconjunctivitis (VKC).

METHODS

This study included 80 patients with clinically established symptoms of grade 0 or grade 1 palpebral VKC (group 1) and 66 healthy participants (group 2). After a comprehensive ophthalmic examination including best-corrected visual acuity, intraocular pressure measurements and slit-lamp biomicroscopy, pachymetric indices and anterior chamber dimensions were measured using the Pentacam HR rotating Scheimpflug device. Topometric indices, which are particularly useful for determining proclivity toward corneal ectasia, were extracted from a topometric map.

RESULTS

In groups 1 and 2, the mean ages were 13.11±5.22 and 16.45±5.09 years, respectively. The mean age at disease onset in group 1 was 10.09±5.03 years, and the mean disease duration was 36.23±8.43 months. Group 1 had significantly higher mean topometric indices than group 2, particularly the index of surface variance (P=0.001), index of vertical asymmetry (P=0.007), center keratoconus index (P=0.050), and Belin/Ambrosio enhanced ectasia total deviation value (P=0.032). Mean posterior corneal astigmatism differed significantly between groups 1 and 2 (P=0.003).

CONCLUSIONS

Significantly higher mean topometric indices in VKC indicate a proclivity for corneal ectasia, which could be attributed to general changes in the corneal ultrastructure caused by persistent itching-induced eye rubbing.

Detection of Corneal Ectasia Using OCT Maps of Pachymetry and Posterior Surface Mean Curvature

PURPOSE

To quantify the abnormal corneal thinning and posterior surface steepening that is observed in keratoconus with an Ectasia Index.

METHODS

Optical coherence tomography (OCT) was used to image the corneas of normal individuals and patients with varying stages of keratoconus (manifest, subclinical, and forme fruste). Maps of corneal pachymetry and posterior surface mean curvature were generated, and an Ectasia Index was calculated by multiplying Gaussian fits obtained from the two types of maps. Repeated five-fold cross-validation was used to evaluate the ability of the Ectasia Index to differentiate between normal and keratoconic eyes. The classification performance of the Ectasia Index was compared to minimum pachymetry and maximum posterior mean curvature.

RESULTS

Thirty-two eyes from 16 normal individuals, 89 eyes from 63 patients with manifest keratoconus, 16 eyes from 15 patients with subclinical keratoconus, and 26 eyes from 26 patients with forme fruste keratoconus were included in the study. During cross-validation, 100% of the eyes with manifest (89 of 89) and subclinical (16 of 16) keratoconus were correctly classified by the Ectasia Index. The average classification accuracy for the forme fruste keratoconus group was 63 ± 21% (16.4 of 26). The specificity for the normal group was 91 ± 10% (29.1 of 32). The Ectasia Index had a higher sensitivity for keratoconus detection and similar specificity in comparison to minimum pachymetry and maximum posterior mean curvature.

CONCLUSIONS

The Ectasia Index could be a valuable additional metric for clinicians to consider when screening for keratoconus. [J Refract Surg. 2022;38(8):502-510.].

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

Objective

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

Design

Multicentre retrospective study.

Methods and analysis

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

Results

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

Conclusion

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

Morphogeometric analysis for characterization of keratoconus considering the spatial localization and projection of apex and minimum corneal thickness point

This work evaluates changes in new morphogeometric indices developed considering the position of anterior and posterior corneal apex and minimum corneal thickness (MCT) point in keratoconus. This prospective comparative study included 440 eyes of 440 patients (age, 7-99 years): control (124 eyes) and keratoconus (KC) groups (316 eyes). Tomographic information (Sirius®, Costruzione Strumenti Oftalmici, Italy) was treated with SolidWorks v2013, creating the following morphogeometric parameters: geometric axis-apex line angle (GA-AP), geometric axis-MCT line angle (GA-MCT, apex line-MCT line angle (AP-MCT), and distances between apex and MCT points on the anterior (anterior AP-MCTd) and posterior corneal surface (posterior AP-MCTd). Statistically significant higher values of GA-AP, GA-MCT, AP-MCT and anterior AP-MCTd were found in the keratoconus group (p ≤ 0.001). Moderate significant correlations of corneal aberrations (r ≥ 0.587, p < 0.001) and corneal thickness parameters (r ≤ -0.414, p < 0.001) with GA-AP and AP-MCT were found. Anterior asphericity was found to be significantly correlated with anterior and posterior AP-MCTd (r ≥ 0.430, p < 0.001). Likewise, GA-AP and AP-MCT showed a good diagnostic ability for the detection of keratoconus, with optimal cutoff values of 9.61° (sensitivity 85.5%, specificity 80.3%) and 18.08° (sensitivity 80.5%, specificity 78.7%), respectively. These new morphogeometric indices allow a clinical characterization of the 3-D structural alteration occurring in keratoconus, with less coincidence in the spatial projection of the apex and MCT points of both corneal surfaces. Future studies should confirm the potential impact on the precision of these indices of the variability of posterior corneal surface measurements obtained with Scheimpflug imaging technology.

Comparison of corneal elevation and pachymetry measurements made by two state of the art corneal tomographers with different measurement principles

PURPOSE

To compare corneal tomography measurements (elevation and pachymetry) as made by two corneal tomographers: Pentacam AXL and CASIA 2.

MATERIAL AND METHODS

The devices were used in a standard measuring mode. 77 normal eyes were measured five times with both devices. The data maps for anterior and posterior corneal elevation and pachymetry were exported and analyzed. Repeatability and average values were calculated for each valid data point on the exported data maps. We also calculated a corrected repeatability of the elevation data maps by removing rotation, tilt, and decentration through realignment of the elevation measurement of each eye prior to analyzing the variations in the measurement usingthe same method as for the repeatability.

RESULTS

Pentacam AXL offered the better (corrected) repeatability for anterior corneal elevation measurements. CASIA 2 offered better repeatability for the pachymetry measurements. The tomographers could not be used interchangeably. The central corneal thickness was measured 9 μm ± 3 μm larger when measured with Pentacam AXL compared to CASIA 2.

Optical coherence tomography imaging in keratoconus

Optical coherence tomography (OCT) is being increasingly used as a tool in the diagnosis and management of keratoconus. While elevation-based topography remains essential, there is an expanding role for cross-sectional OCT imaging in the diagnosis of the disease. Images and measurements of corneal thickness, and in particular, epithelial thickness, may be important in diagnosing early cases, and following procedures such as intrastromal corneal ring segments, corneal transplants and corneal collagen cross-linking.

Comparison of Corneal Tomography: Repeatability, Precision, Misalignment, Mean Elevation, and Mean Pachymetry

PURPOSE

To compare corneal tomography and its statistical uncertainty for measurements obtained by three clinically used corneal tomographers: A Scheimpflug camera (Pentacam HR), a swept source optical coherence tomography system (CASIA SS-1000), and Placido ring imaging (TMS-5).

MATERIAL AND METHODS

Repeated measurements with all three devices on 34 normal eyes were used to estimate the repeatability, precision, and mean values of corneal elevation and pachymetry within 8 mm diameter. The repeatability (standard deviation) was calculated for each data point of the corneal elevation data-maps of anterior and posterior cornea as well as for the pachymetry data-maps. Uncertainty on the position of the eye at each measurement might contribute to the differences between elevation data-maps. To take this into account, we defined the precision as the standard deviation for the elevation data-maps of anterior and posterior cornea after correction of misalignment-effects (rotation, translation). The mean elevation and pachymetry data-maps were fitted with Zernike polynomials for interdevice-comparison.

RESULTS

Pentacam HR offered the best repeatability and precision for the anterior corneal elevation (<3 and <1.6 μm, respectively). CASIA SS-1000 offered good repeatability and precision with high resolution for posterior corneal elevation, and the best repeatability for pachymetry (<3 μm). TMS-5 measured anterior elevation with similar repeatability to CASIA SS-1000 (<6 μm). The data-maps of the three tomographers could not be used interchangeably. The largest differences were observed for pachymetry and posterior corneal elevation data-maps.

CONCLUSIONS

Misalignment limited the repeatability of TMS-5 and Pentacam HR, but had little influence on the repeatability of CASIA SS-1000.

A new approach to keratoconus detection based on corneal morphogeometric analysis

Purpose

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

Methods

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

Results

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

Conclusions

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

Differences in central and non-central keratoconus, and their effect on the objective screening thresholds for keratoconus

PURPOSE

To evaluate the differences in central and non-central keratoconus (based on cone location), and their effect on the objective screening thresholds for keratoconus.

METHODS

This comparative case series was performed at tertiary care cornea and refractive surgery service. Three groups were made: KC apex within central 2 mm (central keratoconus, n = 50), apex outside central 2mm (non-central keratoconus, n = 50) and normal controls (n = 100, with 50 cases each with apex within and outside central 2 mm). All cases underwent clinical evaluation and corneal topography (CSO, Sirius, Italy). Apex keratometry (ApexK), simulated keratometry at 3 mm (SimK), central corneal thickness (CCT) and minimum corneal thickness (MCT), anterior corneal higher-order aberrations root mean square (HOARMS), and Zernike's coefficients up to fourth order at different zones were measured.

RESULTS

In spite of the keratoconic groups having comparable ApexK (p > 0.05), central keratoconus had higher SimK and thinner CCT and MCT (p < 0.001). HOARMS was significantly more for central keratoconus at 3 mm zones. These findings had moderate to large effect size (Cohen's d). Receiver operating curve analysis was carried out to compare central keratoconus and non-central keratoconus with control group. ApexK and HOARMS had best discriminative parameters. Using single parametric suspicion cut-offs of 'either SimK steep >47.2 D or CCT < 491.6 μ' had a good sensitivity (0.98) for central keratoconus, but not for non-central keratoconus (0.80). Changing this cut-off to 'either SimK steep K ≥ 45.8 D or CCT ≤ 503 μ' gave a sensitivity and specificity of 0.95 and 0.87 for non-central keratoconus and 0.99 and 0.87 for central keratoconus.

CONCLUSION

Non-central keratoconus has lesser effect on SimK, pachymetry and smaller-aperture HOARMS. Using 'SimK steep >47.2 D or CCT < 491.6 μ' may miss timely referral for topography in many of these cases. Using more stringent criteria of SimK steep K ≥ 45.8 D or CCT ≤ 503 μ to get a corneal topography done to rule out keratoconus is recommended, especially in cohorts with higher risk.

Correlation of basic indicators with stages of keratoconus assessed by Pentacam tomography

AIM

To evaluate the diagnostic efficiency of basic indicators and find characteristic indicators for keratoconus (KC) at adjacent stages, and to assess the progression pattern of KC.

METHODS

One hundred and eight (41 subclinical, 40 moderate, and 27 severe) keratoconic patients (108 eyes) and 105 myopic patients (105 eyes) as controls were recruited in this prospective, comparative case series study. Pentacam topography was performed. Receiver-operating-characteristic curves were used to get the characteristic indicators.

RESULTS

The most efficient distinguishing index between the subclinical KC and the controls was posterior elevation value (PEV, AUC=0.882), with the highest specificity being 93.8%. Corneal thickness (AUC=0.852) and posterior inferior-superior value (I-S) ranked second and third (AUC=0.776). When KC became moderate, PEV remained to be of the highest diagnostic efficiency (AUC=0.988), followed by the anterior elevation value (AUC=0.986) and other parameters of anterior surface. The diagnostic value increased significantly in the anterior curvature indices (all AUC>0.900) and appeared in the anterior best fitting sphere radius (AUC=0.919) when KC developed into the severe stage.

CONCLUSION

In the subclinical stage of KC, PEV, thickness, and posterior I-S had important diagnostic values, and elevation values remained most efficient when KC developed to the moderate stage. The anterior curvature indices were most characteristic when KC became severe. KC first appeared in the inferior cornea of posterior surface, but the feature of protrusion formed at the moderate stage.

A combination of topographic and pachymetric parameters in keratoconus diagnosis

PURPOSE

To evaluate the utility of topographic and pachymetric parameters of Scheimpflug system in keratoconus diagnosis.

METHODS

This study included 183 eyes of 183 patients with keratoconus (keratoconus group) and 131 eyes of 131 age and sex-matched healthy subjects (control group). Mean keratometry (K, front), topographic astigmatism, pupil-center pachymetry, apical pachymetry, thinnest pachymetry (TP), corneal volume and maximum K (Kmax) were obtained from the Scheimpflug imaging system. A receiver operating characteristic (ROC) analysis was performed and area under the curve (AUC) was calculated to determine the diagnostic ability of each parameter in eyes with ≤ stage 3, ≤ stage 2 and stage 1 keratoconus based on the Amsler-Krumeich grading system.

RESULTS

The Kmax and TP showed the highest individual performance (with sensitivity-specificity of 92.9-92.4% and 89.6-93.3%, respectively) in diagnosis of keratoconus. The AUCs and sensitivity-specificity values for the Kmax/TP and Kmax(2)/TP were calculated to improve the diagnostic performance. As expected, sensitivity-specificity values significantly increased by using Kmax/TP (97.3-94.7% at the level ≥0.08) and Kmax(2)/TP (99.5-95.7% at the level ≥4.1) in discrimination of keratoconic eyes from normals. Moreover, Kmax(2)/TP had very high sensitivity (>99%) and specificity (>94%) in diagnosis of stage 1 and stage 2 keratoconus.

CONCLUSIONS

Although Kmax and TP appear to have high diagnostic ability in keratoconus, the use of either single parameter in isolation might be unsatisfactory in differential diagnosis. Therefore, the Kmax(2)/TP ratio has been introduced, which reflects major characteristics of keratoconus and might be used as an important criterion in keratoconus diagnosis.

Predictive Analysis Between Topographic, Pachymetric and Wavefront Parameters in Keratoconus, Suspects and Normal Eyes: Creating Unified Equations to Evaluate Keratoconus

PURPOSE

To perform prediction analysis between topographic, pachymetric and wavefront parameters in keratoconus, suspects, and normal cases and to look at the possibility of a unified equation to evaluate keratoconus.

METHODS

This cross-sectional, observational study was done in cornea services of a specialty hospital. Fifty eyes of 50 candidates with a diagnosis of normal, keratoconus suspect, and keratoconus were included in each group (total 150 eyes). All eyes underwent detailed analysis on Scheimplug + Placido device (Sirius, CSO, Italy). Main parameters evaluated were topographic [maximum keratometry (Max Km), average keratometry and astigmatism at 3, 5, and 7 mm], pachymetric [central and minimum corneal thickness (MCT) and their difference, corneal volume] and corneal aberrations [higher order aberrations root-mean-square (HOARMS), coma, spherical, residual].Central tendency, predictive fits and regression models, were computed.

RESULTS

The measured variables had a significant difference in mean between the three groups (Kruskal-Wallis, p < 0.001). Max Km, MCT, and HOARMS had significant fits with other topographic, pachymetric and wavefront parameters, respectively. Inter-relations between these three (Max Km, MCT, and HOARMS) were also stronger for keratoconus (R(2) from 0.75 to 0.33) compared to suspect/normal eyes (R(2) from 0.15 to 0.003). These three variables (Max Km, MCT and HOARMS) were used as representative variables to create the unified equations. The equation for the pooled data was (Kmax = 59.5 + 2.3 × HOARMS-0.03 × MCT; R(2)= 0.7, p < 0.001).

CONCLUSIONS

Major variables used for grading keratoconus (MaxKm, MCT, HOARMS) can be linked by linear regression equations to predict the pathology's behavior.

Evaluation of intereye corneal asymmetry in patients with keratoconus. A scheimpflug imaging study

Purpose

To assess the correlation between keratoconus severity and intereye asymmetry of pachymetric data and posterior elevation values and to evaluate their combined accuracy in discriminating normal corneas from those with keratoconus.

Methods

This study included 97 patients: 65 subjects with bilateral normal corneas (NC) and 32 with keratoconus (KC). Central corneal thickness (CCT), thinnest corneal thickness (ThCT) and posterior elevation (PE) at the thinnest point of the cornea were measured in both eyes using Scheimpflug imaging. Intereye asymmetry and its correlation with keratoconus severity were calculated for each variable. The area under the receiver operating characteristic curve (AUROC) was used to compare predictive accuracy of different variables for keratoconus.

Results

In normal eyes, intereye differences were significantly lower compared with the keratoconus eyes (p<0.001, for CCT, ThCT and PE). There was a significant exponential correlation between disease severity and intereye asymmetry of steep keratometry (r² = 0.55, p<0.001), CCT (r² = 0.39, p<0.001), ThCT (r² = 0.48, p<0.001) and PE (r² = 0.64, p<0.001). After adjustment for keratoconus severity, asymmetry in thinnest pachymetry proved to be the best parameter to characterize intereye corneal asymmetry in keratoconus. This variable had high accuracy and significantly better discriminating ability (AUROC: 0.99) for KC than posterior elevation (AUROC: 0.96), ThCT (AUROC: 0.94) or CCT (AUROC: 0.92) alone.

Conclusions

There is an increased intereye asymmetry in keratometry, pachymetry and posterior corneal elevation values in keratoconic patients compared to subjects with normal corneas. Keratoconus patients with more severe disease are also more asymmetric in their disease status which should be taken into account during clinical care.

Screening subclinical keratoconus with placido-based corneal indices

PURPOSE

To assess in a sample of normal, keratoconic, and keratoconus (KC) suspect eyes the performance of a set of new topographic indices computed directly from the digitized images of the Placido rings.

METHODS

This comparative study was composed of a total of 124 eyes of 106 patients from the ophthalmic clinics Vissum Alicante and Vissum Almería (Spain) divided into three groups: control group (50 eyes), KC group (50 eyes), and KC suspect group (24 eyes). In all cases, a comprehensive examination was performed, including the corneal topography with a Placido-based CSO topography system. Clinical outcomes were compared among groups, along with the discriminating performance of the proposed irregularity indices.

RESULTS

Significant differences at level 0.05 were found on the values of the indices among groups by means of Mann-Whitney-Wilcoxon nonparametric test and Fisher exact test. Additional statistical methods, such as receiver operating characteristic analysis and K-fold cross validation, confirmed the capability of the indices to discriminate between the three groups.

CONCLUSIONS

Direct analysis of the digitized images of the Placido mires projected on the cornea is a valid and effective tool for detection of corneal irregularities. Although based only on the data from the anterior surface of the cornea, the new indices performed well even when applied to the KC suspect eyes. They have the advantage of simplicity of calculation combined with high sensitivity in corneal irregularity detection and thus can be used as supplementary criteria for diagnosing and grading KC that can be added to the current keratometric classifications.

Topographic and Tomographic Indices for Detecting Keratoconus and Subclinical Keratoconus: A Systematic Review

Purpose

To provide an overview of the topographic and tomographic indices developed for detecting keratoconus (KC) and subclinical keratoconus.

Methods

Literature review of studies describing and testing KC indices as well as indices developed for improving the sensitivity of subclinical KC detection.

Results

Several indices, based on anterior and posterior curvature measurements, corneal spatial distribution or posterior corneal elevation have been developed for improving the detection of KC and subclinical KC. However, to date, none of them could reach, alone, sufficient discriminating power for differentiating the mildest forms of the disease from normal corneas. New detection programs, based on a combination of corneal indices, and generated using artificial intelligence emerged recently and helped to significantly improve the subclinical KC detection.

Conclusion

The combination of topographic and tomographic corneal indices has helped to significantly improve the sensitivity of subclinical KC detection. However, combining these morphological indices to wavefront and biomechanical analyses of the cornea will certainly further improve the sensitivity of the future screening tests.

How to cite this article

Smadja D. Topographic and Tomographic Indices for Detecting Keratoconus and Subclinical Keratoconus: A Systematic Review. Int J Kerat Ect Cor Dis 2013;2(2):60-64.