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Retinal Biomarker Discovery for Dementia in an Elderly Diabetic Population

  • Ahmed E. Fetit
  • Siyamalan Manivannan
  • Sarah McGrory
  • Lucia Ballerini
  • Alexander Doney
  • Thomas J. MacGillivray
  • Ian J. Deary
  • Joanna M. Wardlaw
  • Fergus Doubal
  • Gareth J. McKay
  • Stephen J. McKenna
  • Emanuele Trucco
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10554)

Abstract

Dementia is a devastating disease, and has severe implications on affected individuals, their family and wider society. A growing body of literature is studying the association of retinal microvasculature measurement with dementia. We present a pilot study testing the strength of groups of conventional (semantic) and texture-based (non-semantic) measurements extracted from retinal fundus camera images to classify patients with and without dementia. We performed a 500-trial bootstrap analysis with regularized logistic regression on a cohort of 1,742 elderly diabetic individuals (median age 72.2). Age was the strongest predictor for this elderly cohort. Semantic retinal measurements featured in up to 81% of the bootstrap trials, with arterial caliber and optic disk size chosen most often, suggesting that they do complement age when selected together in a classifier. Textural features were able to train classifiers that match the performance of age, suggesting they are potentially a rich source of information for dementia outcome classification.

Keywords

Retina Dementia Microvasculature Classification Biomarkers 

Notes

Acknowledgement

This work was supported by EPSRC grant EP/M005976/1 “Multi-modal retinal biomarkers for vascular dementia”.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ahmed E. Fetit
    • 1
  • Siyamalan Manivannan
    • 1
  • Sarah McGrory
    • 2
  • Lucia Ballerini
    • 3
    • 4
  • Alexander Doney
    • 1
  • Thomas J. MacGillivray
    • 3
  • Ian J. Deary
    • 2
  • Joanna M. Wardlaw
    • 4
  • Fergus Doubal
    • 4
  • Gareth J. McKay
    • 5
  • Stephen J. McKenna
    • 1
  • Emanuele Trucco
    • 1
  1. 1.VAMPIRE Project, CVIP, Computing (SSE)University of DundeeDundeeUK
  2. 2.Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
  3. 3.VAMPIRE Project, Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
  4. 4.Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
  5. 5.Centre for Public HealthQueen’s University BelfastBelfastUK

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