Predicted Brain Age After Stroke

Natalia Egorova; Franziskus Liem; Vladimir Hachinski; Amy Brodtmann

doi:10.3389/fnagi.2019.00348

Predicted Brain Age After Stroke

Front Aging Neurosci. 2019 Dec 10:11:348. doi: 10.3389/fnagi.2019.00348. eCollection 2019.

Authors

Natalia Egorova^{1

2}, Franziskus Liem³, Vladimir Hachinski^{4

5}, Amy Brodtmann¹

Affiliations

¹ Division of Behavioural Neuroscience, The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia.
² Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia.
³ University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.
⁴ Department of Clinical Neurological Sciences, Western University, London, ON, Canada.
⁵ Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.

Abstract

Aging is a known non-modifiable risk factor for stroke. Usually, this refers to chronological rather than biological age. Biological brain age can be estimated based on cortical and subcortical brain measures. For stroke patients, it could serve as a more sensitive marker of brain health than chronological age. In this study, we investigated whether there is a difference in brain age between stroke survivors and control participants matched on chronological age. We estimated brain age at 3 months after stroke, and then followed the longitudinal trajectory over three time-points: within 6 weeks (baseline), at 3 and at 12 months following their clinical event. We found that brain age in stroke participants was higher compared to controls, with the mean difference between the groups varying between 3.9 and 8.7 years depending on the brain measure used for prediction. This difference in brain age was observed at 6 weeks after stroke and maintained at 3 and 12 months after stroke. The presence of group differences already at baseline suggests that stroke might be an ultimate manifestation of gradual cerebrovascular burden accumulation and brain degeneration. Brain age prediction, therefore, has the potential to be a useful biomarker for quantifying stroke risk.

Keywords: age prediction; brain age; chronological age; stroke; structural magnetic resonance imaging.