Abstract

Abstract

Spectral-domain optical coherence tomography (SDOCT) is the gold standard of imaging the eye in clinics. Penetration depth with such devices is, however, limited and visualization of the choroid, which is essential for diagnosing chorioretinal disease, remains limited. Whereas swept-source OCT (SSOCT) devices allow for visualization of the choroid these instruments are expensive and availability in praxis is limited. We present an artificial intelligence (AI)-based solution to enhance the visualization of the choroid in OCT scans and allow for quantitative measurements of choroidal metrics using generative deep learning (DL). Synthetically enhanced SDOCT B-scans with improved choroidal visibility were generated, leveraging matching images to learn deep anatomical features during the training. Using a single-center tertiary eye care institution cohort comprising a total of 362 SDOCT-SSOCT paired subjects, we trained our model with 150,784 images from 410 healthy, 192 glaucoma, and 133 diabetic retinopathy eyes. An independent external test dataset of 37,376 images from 146 eyes was deployed to assess the authenticity and quality of the synthetically enhanced SDOCT images. Experts’ ability to differentiate real versus synthetic images was poor (47.5% accuracy). Measurements of choroidal thickness, area, volume, and vascularity index, from the reference SSOCT and synthetically enhanced SDOCT, showed high Pearson’s correlations of 0.97 [95% CI: 0.96–0.98], 0.97 [0.95–0.98], 0.95 [0.92–0.98], and 0.87 [0.83–0.91], with intra-class correlation values of 0.99 [0.98–0.99], 0.98 [0.98–0.99], and 0.95 [0.96–0.98], 0.93 [0.91–0.95], respectively. Thus, our DL generative model successfully generated realistic enhanced SDOCT data that is indistinguishable from SSOCT images providing improved visualization of the choroid. This technology enabled accurate measurements of choroidal metrics previously limited by the imaging depth constraints of SDOCT. The findings open new possibilities for utilizing affordable SDOCT devices in studying the choroid in both healthy and pathological conditions.

Details

Title
Optical coherence tomography choroidal enhancement using generative deep learning
Author
Bellemo, Valentina 1 ; Kumar Das, Ankit 2 ; Sreng, Syna 3   VIAFID ORCID Logo  ; Chua, Jacqueline 4 ; Wong, Damon 5 ; Shah, Janika 6 ; Jonas, Rahul 7   VIAFID ORCID Logo  ; Tan, Bingyao 8 ; Liu, Xinyu 4   VIAFID ORCID Logo  ; Xu, Xinxing 2 ; Tan, Gavin Siew Wei 6 ; Agrawal, Rupesh 9 ; Ting, Daniel Shu Wei 6 ; Yong, Liu 10   VIAFID ORCID Logo  ; Schmetterer, Leopold 11   VIAFID ORCID Logo 

 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Nanyang Technological University, Lee Kong Chian School of Medicine, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); SERI-NTU Advanced Ocular Engineering (STANCE) Program, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670) 
 Technology and Research (A∗STAR), Institute of High Performance Computing, Agency for Science, Singapore, Singapore (GRID:grid.418742.c) (ISNI:0000 0004 0470 8006) 
 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); SERI-NTU Advanced Ocular Engineering (STANCE) Program, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670) 
 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); SERI-NTU Advanced Ocular Engineering (STANCE) Program, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Duke-NUS Medical School, Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Singapore, Singapore (GRID:grid.428397.3) (ISNI:0000 0004 0385 0924) 
 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); SERI-NTU Advanced Ocular Engineering (STANCE) Program, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Duke-NUS Medical School, Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Singapore, Singapore (GRID:grid.428397.3) (ISNI:0000 0004 0385 0924); Medical University of Vienna, Centre for Medical Physics and Biomedical Engineering, Vienna, Austria (GRID:grid.22937.3d) (ISNI:0000 0000 9259 8492) 
 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Duke-NUS Medical School, Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Singapore, Singapore (GRID:grid.428397.3) (ISNI:0000 0004 0385 0924) 
 Department Ophthalmology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany (GRID:grid.6190.e) (ISNI:0000 0000 8580 3777) 
 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); SERI-NTU Advanced Ocular Engineering (STANCE) Program, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Department Ophthalmology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany (GRID:grid.6190.e) (ISNI:0000 0000 8580 3777) 
 National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Nanyang Technological University, Lee Kong Chian School of Medicine, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); Nanyang Technological University (NTU), National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore School of Chemical and Biomedical Engineering, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361) 
10  National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Technology and Research (A∗STAR), Institute of High Performance Computing, Agency for Science, Singapore, Singapore (GRID:grid.418742.c) (ISNI:0000 0004 0470 8006) 
11  National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Nanyang Technological University, Lee Kong Chian School of Medicine, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); SERI-NTU Advanced Ocular Engineering (STANCE) Program, Singapore, Singapore (GRID:grid.272555.2) (ISNI:0000 0001 0706 4670); Duke-NUS Medical School, Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Singapore, Singapore (GRID:grid.428397.3) (ISNI:0000 0004 0385 0924); Medical University of Vienna, Centre for Medical Physics and Biomedical Engineering, Vienna, Austria (GRID:grid.22937.3d) (ISNI:0000 0000 9259 8492); Nanyang Technological University, School of Chemistry, Chemical Engineering and Biotechnology, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361); Medical University of Vienna, Department of Clinical Pharmacology, Vienna, Austria (GRID:grid.22937.3d) (ISNI:0000 0000 9259 8492); Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland (GRID:grid.508836.0) (ISNI:0000 0005 0369 7509) 
Pages
115
Publication year
2024
Publication date
Dec 2024
Publisher
Nature Publishing Group
e-ISSN
23986352
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3050584711
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.