UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

A multi-centre prospective evaluation of THEIA™ to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) in the New Zealand screening program

Vaghefi, Ehsan; Yang, Song; Xie, Li; Han, David; Yap, Aaron; Schmeidel, Ole; Marshall, John; (2022) A multi-centre prospective evaluation of THEIA™ to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) in the New Zealand screening program. Eye 10.1038/s41433-022-02217-w. (In press). Green open access

[thumbnail of Marshall_A multi-centre prospective evaluation of THEIA_AOP.pdf] Text
Marshall_A multi-centre prospective evaluation of THEIA_AOP.pdf - Published Version

Download (657kB)

Abstract

Purpose To validate the potential application of THEIA™ as clinical decision making assistant in a national screening program. Methods A total of 900 patients were recruited from either an urban large eye hospital, or a semi-rural optometrist led screening provider, as they were attending their appointment as part of New Zealand Diabetic Eye Screening Programme. The de-identified images were independently graded by three senior specialists, and final results were aggregated using New Zealand grading scheme, which was then converted to referable/non-referable and Healthy/mild/more than mild/sight threatening categories. Results THEIA™ managed to grade all images obtained during the study. Comparing the adjudicated images from the specialist grading team, “ground truth”, with the grading by the AI platform in detecting “sight threatening” disease, at the patient level THEIA™ achieved 100% imageability, 100% [98.49–100.00%] sensitivity and [97.02–99.16%] specificity, and negative predictive value of 100%. In other words, THEIA™ did not miss any patients with “more than mild” or “sight threatening” disease. The level of agreement between the clinicians and the aggregated results was (k value: 0.9881, 0.9557, and 0.9175), and the level of agreement between THEIA™ and the aggregated labels was (k value: 0.9515). Conclusion This multi-centre prospective trial showed that THEIA™ did not miss referable disease when screening for diabetic retinopathy and maculopathy. It also had a very high level of granularity in reporting the disease level. As THEIA™ has been tested on a variety of cameras, operating in a range of clinics (rural/urban, ophthalmologist-led\optometrist-led), we believe that it will be a suitable addition to a public diabetic screening program.

Type: Article
Title: A multi-centre prospective evaluation of THEIA™ to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) in the New Zealand screening program
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41433-022-02217-w
Publisher version: https://doi.org/10.1038/s41433-022-02217-w
Language: English
Additional information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Outcomes research, Technology
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10155094
Downloads since deposit
5Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item