DOI: 10.1101/518506Jan 12, 2019Paper

Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study

BioRxiv : the Preprint Server for Biology
Johnny WangGennady Roshchupkin

Abstract

Importance: The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as biomarker for early-stage neurodegeneration and potentially as a risk indicator for dementia. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. Objective: We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia in a general Dutch population, using a deep learning approach for predicting brain age based on MRI-derived grey matter maps. Design: Data was collected from participants of the cohort-based Rotterdam Study who underwent brain magnetic resonance imaging between 2006 and 2015. This study was performed in a longitudinal setting and all participant were followed up for incident dementia until 2016. Setting: The Rotterdam Study is a prospective population-based study, initiated in 1990 in the suburb Ommoord of in Rotterdam, the Netherlands. Participants: At baseline, 5496 dementia- and stroke-free participants (mean age 64.67+-9.82, 54.73% women) were scanned and screened for incident dementia. During 6.66+-2.46 years of follow-up, 159 people developed dementia. Main outcomes and measures: We built a convolutional n...Continue Reading

Related Concepts

Amygdaloid Structure
Attention
Biological Markers
Brain
Clinical Research
Cox Proportional Hazards Models
Dutch Population
Gray Matter
Learning
Longitudinal Studies

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