A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre.

Journal: Nature biomedical engineering
Published Date: Jun 1, 2021

Abstract

Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using diverse multiethnic multicountry datasets that comprise more than 70,000 images. Retinal-vessel calibre measured by the models and by expert human graders showed high agreement, with overall intraclass correlation coefficients of between 0.82 and 0.95. The models performed comparably to or better than expert graders in associations between measurements of retinal-vessel calibre and CVD risk factors, including blood pressure, body-mass index, total cholesterol and glycated-haemoglobin levels. In retrospectively measured prospective datasets from a population-based study, baseline measurements performed by the deep-learning system were associated with incident CVD. Our findings motivate the development of clinically applicable explainable end-to-end deep-learning systems for the prediction of CVD on the basis of the features of retinal vessels in retinal photographs.

Authors

  • Carol Y Cheung
    Department of Ophthalmology and Visual Sciences, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China. Electronic address: carolcheung@cuhk.edu.hk.
  • Dejiang Xu
    School of Computing, National University of Singapore, Singapore.
  • Ching-Yu Cheng
    Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore.
  • Charumathi Sabanayagam
    Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore.
  • Yih-Chung Tham
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore.
  • Marco Yu
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Tyler Hyungtaek Rim
    Department of Ocular Epidemiology, Singapore Eye Research Institute, Singapore, Singapore.
  • Chew Yian Chai
    Emergency Medicine Department, National University Hospital, Singapore, Singapore.
  • Bamini Gopinath
    Centre for Vision Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia.
  • Paul Mitchell
    Centre for Vision Research, Department of Ophthalmology, The Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia.
  • Richie Poulton
    Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand.
  • Terrie E Moffitt
    Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
  • Avshalom Caspi
    Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
  • Jason C Yam
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China.
  • Clement C Tham
    Department of Ophthalmology and Visual Sciences, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China; Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
  • Jost B Jonas
    Department of Ophthalmology, Ruprecht-Karls University of Heidelberg, Heidelberg, Germany.
  • Ya Xing Wang
    Beijing Visual Science and Translational Eye Research Institute (BERI), Eye Center of Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
  • Su Jeong Song
    Department of Ophthalmology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Louise M Burrell
    Department of Medicine, Austin Health, Melbourne, VIC, Australia.
  • Omar Farouque
    Department of Cardiology, Austin Health, Austin Hospital, and Department of Medicine, University of Melbourne, Heidelberg, Victoria, Australia.
  • Ling Jun Li
    Division of Obstetrics and Gynaecology, KK Women's and Children's Hospital, Singapore, Singapore.
  • Gavin Tan
    Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore.
  • Daniel S W Ting
    Singapore National Eye Center, Duke-National University of Singapore Medical School, Singapore 168751, Singapore; National Institutes of Health Research Biomedical Research Centre Biomedical Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Electronic address: daniel.ting.s.w@singhealth.com.sg.
  • Wynne Hsu
    School of Computing, National University of Singapore.
  • Mong Li Lee
    School of Computing, National University of Singapore.
  • Tien Y Wong
    Singapore National Eye Center, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.

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