Dataset Information

Lower Corneal Haze and Aberrations in Descemet Membrane Endothelial Keratoplasty Versus Descemet Stripping Automated Endothelial Keratoplasty in Fellow Eyes for Fuchs Endothelial Corneal Dystrophy.

ABSTRACT:

Purpose

To investigate the long-term corneal changes in patients with Fuchs endothelial corneal dystrophy contributing to superior postoperative visual outcomes after Descemet membrane endothelial keratoplasty (DMEK) compared with Descemet stripping automated endothelial keratoplasty (DSAEK).

Methods

Using retrospective analysis, we evaluated 9 patients with Fuchs endothelial corneal dystrophy who underwent DSAEK in 1 eye and DMEK in the fellow eye. Patients were genotyped for the triplet repeat expansion in the TCF4 gene and imaged using optical coherence tomography, Scheimpflug imaging, and in vivo confocal microscopy through focusing.

Results

Eight of 9 subjects were genotyped, and all were found to harbor the triplet repeat expansion. The average time between endothelial keratoplasty and imaging was 76 ± 22 and 37 ± 9 months after DSAEK and DMEK, respectively. The mean best spectacle-corrected visual acuity (logMAR) was 0.04 ± 0.05 and 0.11 ± 0.03 in the DMEK eyes versus DSAEK eyes (P = 0.02), respectively. Posterior corneal higher order aberrations were less in the DMEK eyes compared with fellow DSAEK eyes (0.25 ± 0.06 and 0.66 ± 0.25, respectively, P ≤ 0.01). Using confocal microscopy through focusing, we found that the persistent anterior stromal haze was correlated between the right and left eyes (R = 0.73, P ≤ 0.05), but total stromal backscattering was higher for the DSAEK eyes (P ≤ 0.05).

Conclusions

DSAEK inherently results in higher total stromal backscattering (haze) compared with DMEK because of the addition of stromal tissue. Lower higher order aberrations of the posterior cornea and lower total stromal backscattering (haze) may both contribute to superior visual outcomes after DMEK compared with DSAEK.

SUBMITTER: Waldrop WH

PROVIDER: S-EPMC7510625 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Purpose To develop a model to predict corneal improvement after Descemet membrane endothelial keratoplasty (DMEK) for Fuchs endothelial corneal dystrophy (FECD) from Scheimpflug tomography. Design Cross-sectional study. Participants Forty-eight eyes (derivation group) and 45 eyes (validation group) with a range of severity of FECD undergoing DMEK. Methods Scheimpflug images were obtained before and after DMEK. Before DMEK, pachymetry map and posterior elevation map patterns were quantified by a special image analysis program measuring tomographic features of edema (loss of regular isopachs, displacement of the thinnest point of the cornea, posterior surface depression). Image-derived novel parameters were combined with instrument-derived parameters, and the relative influences of parameters associated with the change in central corneal thickness (CCT) after DMEK in the derivation group were determined by using a gradient boosting machine learning model. The parameters with highest relative influence were then fit in a linear regression model. The derived model was applied to the validation group. Correlations and agreement were assessed between predicted and observed changes in CCT. Main Outcome Measures Predictive power (R2) and mean difference between predicted and observed change in CCT. Results The gradient boosting machine model identified 4 novel parameters of isopach circularity and eccentricity and 1 instrument-derived parameter (posterior surface radius); preoperative CCT was a poor predictor. In the derivation group, the model strongly predicted the change in CCT after DMEK (R2 = 0.80; 95% confidence interval [CI], 0.71–0.89) and the mean difference between predicted and observed change was, by definition, 0 μm. When the same 5 parameters were fit to the validation group, the model performed very highly (R2 = 0.89; 95% CI, 0.84–0.94). When the coefficient estimates from the derivation model were used to predict the change in CCT in the validation group, the predictive power was also high (R2 = 0.78; 95% CI, 0.68–0.88), and the mean difference was 4 μm (predicted minus observed). Conclusions Scheimpflug tomography maps of corneas with FECD can predict the improvement in CCT after DMEK, independent of preoperative corneal thickness measurement. The model could be applied in clinical practice or for clinical research of FECD.