Predicting the extent of corneal edema resolution after Descemet membrane endothelial keratoplasty (DMEK) may help in preoperative decision-making by identifying patients who may benefit from restoring endothelial function.OBJECTIVE To develop and validate a predictive model for edema resolution after DMEK using Scheimpflug tomographic imaging. DESIGN, SETTING, AND PARTICIPANTSTwo prospective studies recruited participants with advanced Fuchs dystrophy at a university-based tertiary referral center between July 1, 2017, and August 31, 2019. Analyses were designed in November 2019 and completed on June 30, 2020. Development of a predictive model using linear least absolute shrinkage and selection operator regression was conducted in a derivation cohort (100 eyes). Overall performance, discrimination, and calibration were tested in the separate validation cohort (32 eyes).EXPOSURES Preoperative Scheimpflug parameters and patient-reported visual disability were considered as potential predictors of edema resolution: (1) tomographic features (irregularity of lines of equal corneal thickness, displacement of the thinnest point of corneal thickness from the inferior-temporal quadrant, and absolute amount of focal posterior corneal depression), (2) standardized anterior and posterior corneal backscatter, (3) preoperative central corneal thickness, and (4) Fuchs dystrophy-specific visual disability. MAIN OUTCOMES AND MEASURES Decrease in central corneal thickness after DMEK indicative of edema resolution. RESULTSOf the 88 patients included in the analysis, 54 were women (61%); median age was 68 years (interquartile range [IQR], 59-76 years). A median of 13 months after DMEK (IQR, 9-16 months), median corneal thickness was 77 μm lower (IQR, 51-94 μm) in the derivation cohort and 75 μm lower in the validation cohort (IQR, 54-96 μm) than before surgery. Per 10-μm edema resolution, eyes gained 0.66 Early Treatment Diabetic Retinopathy Study letters (95% CI, 0.09-1.23) in best-corrected visual acuity. Three tomographic features were present in 68 of 100 eyes (68%) in the derivation cohort and in 18 of 32 eyes (56%) in the validation cohort before DMEK and in only 1 of 132 eyes (1%) after DMEK. To predict edema resolution after DMEK based on preoperative assessment, 5 variables were selected by the statistical learning algorithm: nonparallel isopachs, focal posterior depression, anterior and posterior corneal backscatter, and central corneal thickness. In the separate validation cohort, the model showed high overall performance, discrimination, and calibration.CONCLUSIONS AND RELEVANCE These post hoc analyses of prospective cohorts support a model for use in the prediction of edema resolution after DMEK using Scheimpflug measurement to identify patients benefitting most from DMEK.
To develop and apply a neural network for quantification of endothelial corneal graft detachment using anterior segment (AS) OCT.Design: Training and validation of a neural network and application within a prospective cohort.Participants: Patients two weeks after Descemet membrane endothelial keratoplasty. Methods: Investigators manually labeled the posterior cornea and the graft in cross-sectional images of rotational AS OCT scans. Neural networks for image segmentation were trained to identify the area of graft detachment on cross-sectional images. The best-performing neural network with the lowest misclassification (Youden index) and highest spatial overlap with the ground truth (Dice coefficient) was selected and evaluated in a separate dataset. Three-dimensional maps of the area and volume of graft detachment were calculated. For application, the neural network's rating on the detachment was compared with slit-lampebased ratings of cornea specialists on the same day as the AS OCT imaging took place.Main Outcome Measures: Youden index and Dice coefficient.Results: Neural networks were trained on 27 AS OCT scans with 6912 labeled images. Among 48 combinations of probability thresholds and epoch states, the best-performing neural network showed a Youden index of 0.99 and a Dice coefficient of 0.77, indicating low misclassification and good spatial overlap on individual image segmentation. In the validation set unknown to the neural network with 20 scans (5120 images), the Youden index was 0.85 and the Dice coefficient was 0.73, and a high overall performance compared with the manually labeled ground truth (R 2 ¼ 0.90). In the application set with 107 eyes, the neural network estimated the mean percent detachment larger than the cornea specialist (mean difference, 8.2 percentage points; 95% confidence interval, 6.2e10.2). Masked review of 42 AS OCTs with more than AE10 percentage points difference in ratings showed that clinicians underestimated the true detachment in cases with significant detachment requiring intervention.Conclusions: Deep learning-based segmentation of AS OCT images quantified the percent and the volume of DMEK graft detachment with high precision. Fully automated 3-dimensional quantification of graft detachment is highly sensitive, particularly in corneas with a significant amount of detachment, and may support decision making.
Purpose: To identify determinants of visual disability in patients with advanced Fuchs endothelial corneal dystrophy. Methods: This prospectively sampled cross-sectional study at a tertiary referral center included participants with clinically advanced Fuchs dystrophy requiring endothelial keratoplasty and no other vision-limiting pathologies. We quantified visual disability using the Fuchs dystrophy-specific Visual Function and Corneal Health Status (V-FUCHS) visual disability instrument. We calculated Fuchs dystrophy-specific glare and diurnal variation (Glare Factor) scores and visual acuity-related disability (Visual Acuity Factor) scores. To assess corneal morphology and optics, all participants underwent standardized Scheimpflug imaging and tests for disability glare and best-corrected visual acuity on Early Treatment Diabetic Retinopathy Study charts after subjective refraction. Associations of morphological and optical parameters with V-FUCHS scores were assessed adjusting for age, sex, and lenticular status. Results: Participants with more posterior corneal backscatter had more visual disability (higher scores), with participants in the highest quartile of backscatter (median, 1409 scatter units) having 0.57 higher Glare Factor scores (95% confidence interval, 0.14–1.00) and 0.61 higher Visual Acuity Factor scores (95% confidence interval, 0.15–1.06) compared with participants in the lowest quartile of backscatter (median, 812 scatter units). Other morphological and optical factors such as anterior corneal backscatter, higher-order aberrations, or edematous surface changes were not empirical contributors to visual disability, especially when accounting for posterior corneal backscatter. Conclusions: Corneal backscatter is a driver of characteristic visual disability in Fuchs dystrophy. Comprehensive assessments of morphology and direct quantification of disease-related disability may help identify the best candidates for endothelial keratoplasty.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.