Transferability of an Artificial Intelligence Algorithm Predicting Rebubblings After Descemet Membrane Endothelial Keratoplasty.
Cornea
; 42(5): 544-548, 2023 May 01.
Article
in En
| MEDLINE
| ID: mdl-35543586
ABSTRACT
PURPOSE:
To develop an artificial intelligence (AI) algorithm enabling corneal surgeons to predict the probability of rebubbling after Descemet membrane endothelial keratoplasty (DMEK) from images obtained using optical coherence tomography (OCT).METHODS:
Anterior segment OCT data of patients undergoing DMEK by 2 different DMEK surgeons (C.C. and B.B.; University of Cologne, Cologne, Germany) were extracted from the prospective Cologne DMEK database. An AI algorithm was trained by using a data set of C.C. to detect graft detachments and predict the probability of a rebubbling. The architecture of the AI model used in this study was called EfficientNet. This algorithm was applied to OCT scans of patients, which were operated by B.B. The transferability of this algorithm was analyzed to predict a rebubbling after DMEK.RESULTS:
The algorithm reached an area under the curve of 0.875 (95% confidence interval 0.880-0.929). The cutoff value based on the Youden index was 0.214, and the sensitivity and specificity for this value were 78.9% (67.6%-87.7%) and 78.6% (69.5%-86.1%).CONCLUSIONS:
The development of AI algorithms allows good transferability to other surgeons reaching a high accuracy in predicting rebubbling after DMEK based on OCT image data.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Fuchs' Endothelial Dystrophy
/
Descemet Stripping Endothelial Keratoplasty
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Cornea
Year:
2023
Document type:
Article
Affiliation country:
Japan