Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy
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 grou...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-06-01
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| Series: | Ophthalmology Science |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666914522000173 |
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| author | Sanjay V. Patel, MD, FRCOphth Jon J. Camp, BSEE David O. Hodge, MS Keith H. Baratz, MD David R. Holmes, III, PhD |
| author_facet | Sanjay V. Patel, MD, FRCOphth Jon J. Camp, BSEE David O. Hodge, MS Keith H. Baratz, MD David R. Holmes, III, PhD |
| author_sort | Sanjay V. Patel, MD, FRCOphth |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-13T16:43:03Z |
| format | Article |
| id | doaj.art-9c0827f461c64fa583fe511f6ccecabe |
| institution | Directory Open Access Journal |
| issn | 2666-9145 |
| language | English |
| last_indexed | 2024-04-13T16:43:03Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ophthalmology Science |
| spelling | doaj.art-9c0827f461c64fa583fe511f6ccecabe2022-12-22T02:39:10ZengElsevierOphthalmology Science2666-91452022-06-0122100128Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal DystrophySanjay V. Patel, MD, FRCOphth0Jon J. Camp, BSEE1David O. Hodge, MS2Keith H. Baratz, MD3David R. Holmes, III, PhD4Department of Ophthalmology, Mayo Clinic, Rochester, Minnesota; Correspondence: Sanjay V. Patel, MD, FRCOphth, Department of Ophthalmology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.Biomedical Imaging Resource, Mayo Clinic, Rochester, MinnesotaDepartment of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FloridaDepartment of Ophthalmology, Mayo Clinic, Rochester, MinnesotaBiomedical Imaging Resource, Mayo Clinic, Rochester, MinnesotaPurpose: 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.http://www.sciencedirect.com/science/article/pii/S2666914522000173DMEKFuchs endothelial corneal dystrophyImage analysisPachymetryScheimpflug tomography |
| spellingShingle | Sanjay V. Patel, MD, FRCOphth Jon J. Camp, BSEE David O. Hodge, MS Keith H. Baratz, MD David R. Holmes, III, PhD Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy Ophthalmology Science DMEK Fuchs endothelial corneal dystrophy Image analysis Pachymetry Scheimpflug tomography |
| title | Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy |
| title_full | Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy |
| title_fullStr | Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy |
| title_full_unstemmed | Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy |
| title_short | Predicting Corneal Improvement after Descemet Membrane Endothelial Keratoplasty for Fuchs Endothelial Corneal Dystrophy |
| title_sort | predicting corneal improvement after descemet membrane endothelial keratoplasty for fuchs endothelial corneal dystrophy |
| topic | DMEK Fuchs endothelial corneal dystrophy Image analysis Pachymetry Scheimpflug tomography |
| url | http://www.sciencedirect.com/science/article/pii/S2666914522000173 |
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