Predictive Factors for Clinical Outcomes after Primary Descemet’s Membrane Endothelial Keratoplasty for Fuchs’ Endothelial Dystrophy

Aim. To evaluate visual outcome and endothelial cell density (ECD) after Descemet’s Membrane Endothelial Keratoplasty (DMEK) in comparison with Descemet’s Stripping Automated Endothelial Keratoplasty (DSAEK) in the fellow eye for Fuchs endothelial dystrophy (FED).Design. Single-centre, retrospective case series.Methods. 30 eyes of 30 patients undergoing DMEK, who completed a 1-year follow-up, were compared with 30 fellow eyes which underwent DSAEK for bilateral FED. Main outcome measures studied included Best Corrected Visual Acuity (BCVA) and ECD during a 1-year follow-up period.Results. BCVA improved from 0.78 ± 0.35 logMAR, and 0.73 ± 0.31 logMAR before surgery to 0.22 ± 0.1 logMAR and 0.35 ± 0.12 logMAR 6 months after DMEK and DSEK, respectively (P<0.001). At one year after surgery, the BCVA was maintained at 0.21 ± 0.12 logMAR and 0.34 ± 0.1 logMAR, respectively, after DMEK and DSAEK. A statistically better visual outcome was observed after DMEK compared to DSAEK (P<0.05) in fellow eyes.Conclusions. DMEK provided better visual rehabilitation when compared to DSAEK. Nevertheless, there were no significant differences with regard to the ECD within a 1-year follow-up.

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Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty

Scientific Reports ◽

10.1038/s41598-021-93186-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Friso G. Heslinga ◽

Ruben T. Lucassen ◽

Myrthe A. van den Berg ◽

Luuk van der Hoek ◽

Josien P. W. Pluim ◽

...

Keyword(s):

Deep Learning ◽

Endothelial Function ◽

Corneal Thickness ◽

Anterior Segment ◽

Anatomical Landmarks ◽

Endothelial Keratoplasty ◽

Descemet’S Membrane Endothelial Keratoplasty ◽

Descemet's Membrane ◽

Descemet’S Membrane ◽

Thickness Measurements

AbstractCorneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemet’s membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be challenging for corneas that are irregularly shaped due to pathology, or as a consequence of surgery, leading to incorrect thickness measurements. In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans. Three different deep learning strategies were developed based on 960 B-scans from 50 patients. On an independent test set of 320 B-scans, corneal thickness could be measured with an error of 13.98 to 15.50 μm for the central 9 mm range, which is less than 3% of the average corneal thickness. The accurate thickness measurements were used to construct detailed pachymetry maps. Moreover, follow-up scans could be registered based on anatomical landmarks to obtain differential pachymetry maps. These maps may enable a more comprehensive understanding of the restoration of the endothelial function after DMEK, where thickness often varies throughout different regions of the cornea, and subsequently contribute to a standardized postoperative regime.

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