The Scheimpflug-derived shape and biomechanical parameters are able to accurately distinguish normal corneas from frank (clinical) keratoconic corneas. However, the combined parameters were more effective. Further studies should test milder ectasia cases.

ObjectiveTo evaluate the accuracy of convolutional neural networks technique (CNN) in detecting keratoconus using colour-coded corneal maps obtained by a Scheimpflug camera.DesignMulticentre retrospective study.Methods and analysisWe 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.ResultsA 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.ConclusionCNN 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.

Purpose: To investigate corneal biomechanical response parameters in varying degrees of myopia and their correlation with corneal geometrical parameters and axial length.Methods: In this prospective cross-sectional study, 172 eyes of 172 subjects, the severity degree of myopia was categorized into mild, moderate, severe, and extreme myopia. Cycloplegic refraction, corneal tomography using Pentacam HR, corneal biomechanical assessment using Corvis ST and Ocular Response Analyser (ORA), and ocular biometry using IOLMaster 700 were performed for all subjects. A general linear model was used to compare biomechanical parameters in various degrees of myopia, while central corneal thickness (CCT) and biomechanically corrected intraocular pressure (bIOP) were considered as covariates. Multiple linear regression was used to investigate the relationship between corneal biomechanical parameters with spherical equivalent (SE), axial length (AXL), bIOP, mean keratometry (Mean KR), and CCT.Results: Corneal biomechanical parameters assessed by Corvis ST that showed significant differences among the groups were second applanation length (AL2, p = 0.035), highest concavity radius (HCR, p < 0.001), deformation amplitude (DA, p < 0.001), peak distance (PD, p = 0.022), integrated inverse radius (IR, p < 0.001) and DA ratio (DAR, p = 0.004), while there were no significant differences in the means of pressure-derived parameters of ORA between groups. Multiple regression analysis showed all parameters of Corvis ST have significant relationships with level of myopia (SE, AXL, Mean KR), except AL1 and AL2. Significant biomechanical parameters showed progressive reduction in corneal stiffness with increasing myopia (either with greater negative SE or greater AXL), independent of IOP and CCT. Also, corneal hysteresis (CH) or ability to dissipate energy from the ORA decreased with increasing level of myopia.Conclusions: Dynamic corneal response assessed by Corvis ST shows evidence of biomechanical changes consistent with decreasing stiffness with increasing levels of myopia in multiple parameters. The strongest correlations were with highest concavity parameters where the sclera influence is maximal.

Purpose:To evaluate changes in corneal topography and biomechanical properties after collagen cross-linking (CXL) for progressive keratoconus.Patients and Methods:Collagen cross-linking was performed on 97 eyes. We assessed uncorrected visual acuity (UCVA) and best corrected visual acuity (BCVA). Corneal topography indices were evaluated using placido disc topography, scanning slit anterior topography (Orbscan II), and rotating Scheimpflug topography (Pentacam). Specular microscopy and corneal biomechanics were evaluated.Results:A 1-year-follow-up results revealed that UCVA improved from 0.31 to 0.45 and BCVA changed from 0.78 to 0.84 (P < 0.001). The mean of average keratometry value decreased from 49.62 to 47.95 D (P < 0.001). Astigmatism decreased from 4.84 to 4.24 D (P < 0.001). Apex corneal thickness decreased from 458.11 to 444.46 μm. Corneal volume decreased from 56.66 to 55.97 mm3 (P < 0.001). Posterior best fit sphere increased from 55.50 to 46.03 mm (P = 0.025). Posterior elevation increased from 99.2 to 112.22 μm (P < 0.001). Average progressive index increased from 2.26 to 2.56 (P < 0.001). A nonsignificant decrease was observed in mean endothelial count from 2996 to 2928 cell/mm2 (P = 0.190). Endothelial coefficient of variation (CV) increased nonsignificantly from 18.26 to 20.29 (P = 0.112). Corneal hysteresis changed from 8.18 to 8.36 (P = 0.552) and corneal resistance factor increased from 6.98 to 7.21 (P = 0.202), so these changes were not significant.Conclusion:Visual acuity and K values improved after CXL. In spite of the nonsignificant increase in endothelial cell count and increase in the CV, CLX seems to be a safe treatment for keratoconus. Further studies with larger sample sizes and longer follow-up periods are recommended.

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To compare the corneal cone location on different maps and instruments and their agreements with elevation maps. Methods:In 90 left eyes with bilateral keratoconus, the apex of cone location was determined based on the maximum simulated keratometry (Kmax) location on the anterior sagittal curvature map by Pentacam HR, the maximum curvature on the mean curvature map by ATLAS 9000, most elevated point of the island of positive elevation relative to the best fit sphere on the front and back corneal elevation maps by Pentacam HR, and thinnest point on the thickness map by Pentacam HR and Orbscan, and the thinnest points on pachymetry and epithelial thickness maps by RTVue OCT.Results: There was a significant difference among the location on different maps along the xand y-axes (p< 0.001). The lowest agreement with the cone apex on both front and back elevation maps was for the anterior sagittal curvature map and the highest agreement for the Pentacam thickness map. The majority of keratoconus cone apexes were displaced in the inferotemporal direction on the different maps except for the epithelial thickness maps.Conclusions: Despite the variability between different devices and methods; the thickness map on the Pentacam HR showed the highest correlation with the front and back elevation maps, while the RTVue epithelial thickness map showed the poorest correlation. Based on this study, epithelial thickness maps and anterior curvature maps should be utilized with caution to determine the location of the cone.

PurposeTo compare the biomechanically-corrected intraocular pressure (bIOP) measured by the Corvis ST (Oculus, Wetzlar, Germany) with IOP measurements made by other commonly used tonometers; and to test the correlations between IOP measures and central corneal thickness.MethodsOne randomly-selected eye from each of 94 healthy subjects was assessed. The bIOP was determined by the CorVis ST and compared with the IOP measurements made by standard Goldmann Applanation Tonometer (GAT: Haag-Streit AG, Bern, Switzerland), the Icare (Icare Finland Oy, Vantaa, Finland), and the Ocular Response Analyzer (ORA-IOPcc: Reichert, New York, USA). Corneal thickness was assessed by the Oculus Pentacam. The correlation between bIOP and the other devices and between CCT were assessed using the Pearson correlation test or Spearman’s rho test accordingly to the distribution of these values. The Bland-Altman method and intraclass correlation coefficients (ICC) were used to assess the agreement of bIOP results with IOP obtained with other techniques. The limits of agreement (LoA) were determined as the mean difference ±1.96 SD of the mean differences. In all tests, the significance level was considered to be 0.05.ResultsMean and SD of the bIOP were 16.11±1.66 mmHg. Significant differences were found between the bIOP and other IOP measurements (GAT, 3.02±2.60 mmHg, p<0.001, Icare, 1.51±2.95 mmHg, p<0.001, IOPcc, 1.09±1.96 mmHg, p<0.001). The lowest and highest mean differences in IOP were with the IOPcc and GAT, respectively. Interestingly, there were no significant differences in bIOP, GAT-IOP and ORA-IOPcc between the eyes with thin or thick corneal thicknesses, with Icare-IOP being the only exception (p<0.001).ConclusionThe Corvis bIOP has a higher correlation with the IOPcc by ORA, which are also compensated for the effects of corneal biomechanics and have less association with corneal thickness relative to the uncorrected GAT and Icare measurements.