Dataset Information

Corneal Subbasal Plexus in Eyes with Fuchs' Endothelial Corneal Dystrophy after Two Different Endothelial Surgeries.

ABSTRACT:

Purpose

To evaluate the morphological features and density of corneal subbasal plexus (SBP) using in vivo corneal confocal microscopy (IVCCM) in patients affected by Fuchs' endothelial corneal dystrophy (FECD) six months after Descemet membrane endothelial keratoplasty (DMEK) and Descemet-stripping automated endothelial keratoplasty (DSAEK).

Methods

We included patients affected by FECD, requiring corneal endothelial surgery due to corneal oedema occurred from 3 to 6 months. 7 eyes underwent DMEK and 7 eyes DSAEK. All patients performed IVCCM preoperative and in six months postoperative. We analyzed SBP parameters, using CS4 Nerves Tracking Tool, and we studied the differences between the two endothelial keratoplasties.

Results

Comparing the eyes treated with DMEK with those treated with DSAEK, preoperative corneal thickness, corrected distance visual acuity (CDVA), and age were similar in both groups. SBP was not detectable at preoperative IVCCM in any eye. Postoperatively, the nerve fibers length, the nerve fibers density, the tortuosity, and the number of fibers and of branching did not differ in the eyes that underwent DMEK compared to DSAEK. The corneal beadings density was higher after DMEK than DSAEK, and this difference was statistically significant (P = 0.004). The type of endothelial keratoplasty was not associated with the presence or absence of postoperative corneal SBP (Pearson' chi-square, 0.755).

Conclusions

Postoperative corneal reinnervation should be easily and noninvasively studied using IVCCM. Morphological postoperative features of SBP did not differ between two different types of endothelial keratoplasty, DMEK and DSAEK, despite the different sizes of the corneal incision. The lower beading density in the DSAEK group should be the consequence of a different distribution of mitochondria along the nerve fibers, as expression of a supposed higher metabolic distress in the DSAEK group.

SUBMITTER: Abicca I

PROVIDER: S-EPMC8505089 | 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.

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