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ToolsKeane, Pearse A., Grossi, Carlota M., Foster, Paul J., Yang, Qi, Reisman, Charles A., Chan, Kinpui, Peto, Tunde, Thomas, Dhanes and Patel, Praveen J. (2016) Optical coherence tomography in the UK Biobank study – Rapid automated analysis of retinal thickness for large population-based studies. PLoS One, 11 (10). ISSN 1932-6203
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Abstract
Purpose: To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. Methods: In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available “spectral domain” OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. Results: 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. Conclusions: We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging.
| Item Type: | Article |
|---|---|
| Additional Information: | © 2016 Keane et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Faculty \ School: | Faculty of Medicine and Health Sciences > School of Health Sciences |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Groups > Health Promotion |
| Related URLs: | |
| Depositing User: | Pure Connector |
| Date Deposited: | 13 Oct 2016 15:00 |
| Last Modified: | 28 Jan 2024 02:10 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/60923 |
| DOI: | 10.1371/journal.pone.0164095 |
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