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Non-invasive in vivo hyperspectral imaging of the retina for potential biomarker use in Alzheimer’s disease

Author

Listed:
  • Xavier Hadoux

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne)

  • Flora Hui

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne)

  • Jeremiah K. H. Lim

    (University of Melbourne)

  • Colin L. Masters

    (The University of Melbourne)

  • Alice Pébay

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne)

  • Sophie Chevalier

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne)

  • Jason Ha

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne
    Monash University)

  • Samantha Loi

    (Neuropsychiatry Unit, North Western Mental Health, Melbourne Health, Royal Melbourne Hospital
    University of Melbourne, Department of Psychiatry)

  • Christopher J. Fowler

    (The University of Melbourne)

  • Christopher Rowe

    (Austin Health)

  • Victor L. Villemagne

    (Austin Health)

  • Edward N. Taylor

    (Swinburne University of Technology)

  • Christopher Fluke

    (Swinburne University of Technology
    Swinburne University of Technology)

  • Jean-Paul Soucy

    (McGill University
    Concordia University)

  • Frédéric Lesage

    (Département de Génie électrique
    Research Center, Montreal Heart Institute)

  • Jean-Philippe Sylvestre

    (Optina Diagnostics)

  • Pedro Rosa-Neto

    (McGill University
    Douglas Mental Health University Institute
    The McGill University Research Centre for Studies in Aging, McGill University)

  • Sulantha Mathotaarachchi

    (McGill University
    Douglas Mental Health University Institute)

  • Serge Gauthier

    (The McGill University Research Centre for Studies in Aging, McGill University)

  • Ziad S. Nasreddine

    (MoCA Clinic and Institute)

  • Jean Daniel Arbour

    (Clinique ophtalmologique 2121)

  • Marc-André Rhéaume

    (Clinique ophtalmologique 2121)

  • Sylvain Beaulieu

    (Hôpital Maisonneuve-Rosemont)

  • Mohamed Dirani

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne
    Singapore National Eye Centre)

  • Christine T. O. Nguyen

    (University of Melbourne)

  • Bang V. Bui

    (University of Melbourne)

  • Robert Williamson

    (University of Melbourne)

  • Jonathan G. Crowston

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne)

  • Peter Wijngaarden

    (Royal Victorian Eye and Ear Hospital
    University of Melbourne)

Abstract

Studies of rodent models of Alzheimer’s disease (AD) and of human tissues suggest that the retinal changes that occur in AD, including the accumulation of amyloid beta (Aβ), may serve as surrogate markers of brain Aβ levels. As Aβ has a wavelength-dependent effect on light scatter, we investigate the potential for in vivo retinal hyperspectral imaging to serve as a biomarker of brain Aβ. Significant differences in the retinal reflectance spectra are found between individuals with high Aβ burden on brain PET imaging and mild cognitive impairment (n = 15), and age-matched PET-negative controls (n = 20). Retinal imaging scores are correlated with brain Aβ loads. The findings are validated in an independent cohort, using a second hyperspectral camera. A similar spectral difference is found between control and 5xFAD transgenic mice that accumulate Aβ in the brain and retina. These findings indicate that retinal hyperspectral imaging may predict brain Aβ load.

Suggested Citation

  • Xavier Hadoux & Flora Hui & Jeremiah K. H. Lim & Colin L. Masters & Alice Pébay & Sophie Chevalier & Jason Ha & Samantha Loi & Christopher J. Fowler & Christopher Rowe & Victor L. Villemagne & Edward , 2019. "Non-invasive in vivo hyperspectral imaging of the retina for potential biomarker use in Alzheimer’s disease," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12242-1
    DOI: 10.1038/s41467-019-12242-1
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    Cited by:

    1. Chia-Hsiang Lin & Shih-Hsiu Huang & Ting-Hsuan Lin & Pin Chieh Wu, 2023. "Metasurface-empowered snapshot hyperspectral imaging with convex/deep (CODE) small-data learning theory," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

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