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Abstract
The efficacy of deep learning in predicting successful big-bubble (SBB) formation during deep anterior lamellar keratoplasty (DALK) was evaluated. Medical records of patients undergoing DALK at the University of Cologne, Germany between March 2013 and July 2019 were retrospectively analyzed. Patients were divided into two groups: (1) SBB or (2) failed big-bubble (FBB). Preoperative images of anterior segment optical coherence tomography and corneal biometric values (corneal thickness, corneal curvature, and densitometry) were evaluated. A deep neural network model, Visual Geometry Group-16, was selected to test the validation data, evaluate the model, create a heat map image, and calculate the area under the curve (AUC). This pilot study included 46 patients overall (11 women, 35 men). SBBs were more common in keratoconus eyes (KC eyes) than in corneal opacifications of other etiologies (non KC eyes) (p = 0.006). The AUC was 0.746 (95% confidence interval [CI] 0.603–0.889). The determination success rate was 78.3% (18/23 eyes) (95% CI 56.3–92.5%) for SBB and 69.6% (16/23 eyes) (95% CI 47.1–86.8%) for FBB. This automated system demonstrates the potential of SBB prediction in DALK. Although KC eyes had a higher SBB rate, no other specific findings were found in the corneal biometric data.
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1 Nihon University School of Medicine, Division of Ophthalmology, Department of Visual Sciences, Tokyo, Japan (GRID:grid.260969.2) (ISNI:0000 0001 2149 8846); Hiroshima University, Department of Technology and Design Thinking for Medicine (DT2M), Hiroshima, Japan (GRID:grid.257022.0) (ISNI:0000 0000 8711 3200); Jichi Medical University, Department of Ophthalmology, Shimotsuke, Japan (GRID:grid.410804.9) (ISNI:0000000123090000)
2 Xeno-Hoc, Shinjyuku, Japan (GRID:grid.410804.9)
3 Hiroshima University, Department of Technology and Design Thinking for Medicine (DT2M), Hiroshima, Japan (GRID:grid.257022.0) (ISNI:0000 0000 8711 3200); Tsukazaki Hospital, Department of Ophthalmology, Himeji, Japan (GRID:grid.257022.0)
4 Tsukazaki Hospital, Department of Ophthalmology, Himeji, Japan (GRID:grid.257022.0)
5 University of Cologne, Department of Ophthalmology, Cologne, Germany (GRID:grid.6190.e) (ISNI:0000 0000 8580 3777)
6 University of Cologne, Department of Ophthalmology, Cologne, Germany (GRID:grid.6190.e) (ISNI:0000 0000 8580 3777); MVZ ADTC Mönchengladbach/Erkelenz, Erkelenz, Germany (GRID:grid.6190.e)