Literature DB >> 36043139

Deep-learning retinal vessel calibre measurements and risk of cognitive decline and dementia.

Carol Y Cheung1, Win Lee Edwin Wong2,3, Saima Hilal2,3,4, Cheuk Ni Kan2,3, Bibek Gyanwali2,3,5, Yih Chung Tham6,7, Leopold Schmetterer6,8,9,10,11, Dejiang Xu12, Mong Li Lee12, Wynne Hsu12, Narayanaswamy Venketasubramanian13, Boon Yeow Tan14, Tien Yin Wong6,7, Christopher P L H Chen2,3,15.   

Abstract

Previous studies have explored the associations of retinal vessel calibre, measured from retinal photographs or fundus images using semi-automated computer programs, with cognitive impairment and dementia, supporting the concept that retinal blood vessels reflect microvascular changes in the brain. Recently, artificial intelligence deep-learning algorithms have been developed for the fully automated assessment of retinal vessel calibres. Therefore, we aimed to determine whether deep-learning-based retinal vessel calibre measurements are predictive of risk of cognitive decline and dementia. We conducted a prospective study recruiting participants from memory clinics at the National University Hospital and St. Luke's Hospital in Singapore; all participants had comprehensive clinical and neuropsychological examinations at baseline and annually for up to 5 years. Fully automated measurements of retinal arteriolar and venular calibres from retinal fundus images were estimated using a deep-learning system. Cox regression models were then used to assess the relationship between baseline retinal vessel calibre and the risk of cognitive decline and developing dementia, adjusting for age, gender, ethnicity, education, cerebrovascular disease status, hypertension, hyperlipidemia, diabetes, and smoking. A total of 491 participants were included in this study, of whom 254 developed cognitive decline over 5 years. In multivariable models, narrower retinal arteriolar calibre (hazard ratio per standard deviation decrease = 1.258, P = 0.008) and wider retinal venular calibre (hazard ratio per standard deviation increase = 1.204, P = 0.037) were associated with increased risk of cognitive decline. Among participants with cognitive impairment but no dementia at baseline (n = 212), 44 progressed to have incident dementia; narrower retinal arteriolar calibre was also associated with incident dementia (hazard ratio per standard deviation decrease = 1.624, P = 0.021). In summary, deep-learning-based measurement of retinal vessel calibre was associated with risk of cognitive decline and dementia. © Crown copyright 2022.

Entities:  

Keywords:  cognitive decline; deep-learning system; dementia; retinal imaging; retinal vessel calibre

Year:  2022        PMID: 36043139      PMCID: PMC9416061          DOI: 10.1093/braincomms/fcac212

Source DB:  PubMed          Journal:  Brain Commun        ISSN: 2632-1297


  58 in total

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2.  Microvascular network alterations in retina of subjects with cerebral small vessel disease.

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Journal:  Neurosci Lett       Date:  2014-06-14       Impact factor: 3.046

Review 3.  The impact of inflammation on cognitive function in older adults: implications for healthcare practice and research.

Authors:  Andrea C Sartori; David E Vance; Larry Z Slater; Michael Crowe
Journal:  J Neurosci Nurs       Date:  2012-08       Impact factor: 1.230

4.  Retinal Microvascular Calibers Are Associated With Enlarged Perivascular Spaces in the Brain.

Authors:  Unal Mutlu; Hieab H H Adams; Albert Hofman; Aad van der Lugt; Caroline C W Klaver; Meike W Vernooij; M Kamran Ikram; M Arfan Ikram
Journal:  Stroke       Date:  2016-03-15       Impact factor: 7.914

5.  Clinical dementia rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type.

Authors:  J C Morris
Journal:  Int Psychogeriatr       Date:  1997       Impact factor: 3.878

6.  Cerebral microbleeds and cognition: the epidemiology of dementia in Singapore study.

Authors:  Saima Hilal; Monica Saini; Chuen Seng Tan; Joseree A Catindig; Way Inn Koay; Wiro J Niessen; Henri A Vrooman; Tien Yin Wong; Christopher Chen; Mohammad K Ikram; Narayanaswamy Venketasubramanian
Journal:  Alzheimer Dis Assoc Disord       Date:  2014 Apr-Jun       Impact factor: 2.703

7.  Retinal microvascular abnormalities predict progression of brain microvascular disease: an atherosclerosis risk in communities magnetic resonance imaging study.

Authors:  Thomas C Hanff; A Richey Sharrett; Thomas H Mosley; Dean Shibata; David S Knopman; Ronald Klein; Barbara E K Klein; Rebecca F Gottesman
Journal:  Stroke       Date:  2014-02-18       Impact factor: 7.914

8.  Retinal vascular fractals and cognitive impairment.

Authors:  Yi-Ting Ong; Saima Hilal; Carol Yim-Lui Cheung; Xin Xu; Christopher Chen; Narayanaswamy Venketasubramanian; Tien Yin Wong; Mohammad Kamran Ikram
Journal:  Dement Geriatr Cogn Dis Extra       Date:  2014-08-27

9.  Markers of cardiac dysfunction in cognitive impairment and dementia.

Authors:  Saima Hilal; Yuek Ling Chai; Mohammad Kamran Ikram; Sakktivel Elangovan; Tan Boon Yeow; Xu Xin; Jun Yi Chong; Narayanaswamy Venketasubramanian; Arthur Mark Richards; Jenny P C Chong; Mitchell Kim Peng Lai; Christopher Chen
Journal:  Medicine (Baltimore)       Date:  2015-01       Impact factor: 1.889

10.  Towards Standardization of Quantitative Retinal Vascular Parameters: Comparison of SIVA and VAMPIRE Measurements in the Lothian Birth Cohort 1936.

Authors:  Sarah McGrory; Adele M Taylor; Enrico Pellegrini; Lucia Ballerini; Mirna Kirin; Fergus N Doubal; Joanna M Wardlaw; Alex S F Doney; Baljean Dhillon; John M Starr; Emanuele Trucco; Ian J Deary; Thomas J MacGillivray
Journal:  Transl Vis Sci Technol       Date:  2018-03-23       Impact factor: 3.283

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