Age-related differences in cerebral blood flow and cortical thickness with an application to age prediction

Author(s)
MacDonald, M Ethan
Williams, Rebecca J
Rajashekar, Deepthi
Stafford, Randall B
Hanganu, Alexandru
Sun, Hongfu
Berman, Avery J L
McCreary, Cheryl R
Frayne, Richard
Forkert, Nils D
Pike, G Bruce
Publication Date
2020-11
Abstract
<p>Cerebral cortex thinning and cerebral blood flow (CBF) reduction are typically observed during normal healthy aging. However, imaging-based age prediction models have primarily used morphological features of the brain. Complementary physiological CBF information might result in an improvement in age estimation. In this study, T1-weighted structural magnetic resonance imaging and arterial spin labeling CBF images were acquired in 146 healthy participants across the adult lifespan. Sixty-eight cerebral cortex regions were segmented, and the cortical thickness and mean CBF were computed for each region. Linear regression with age was computed for each region and data type, and laterality and correlation matrices were computed. Sixteen predictive models were trained with the cortical thickness and CBF data alone as well as a combination of both data types. The age explained more variance in the cortical thickness data (average <i>R<sup>2</sup></i> of 0.21) than in the CBF data (average <i>R<sup>2</sup></i> of 0.09). All 16 models performed significantly better when combining both measurement types and using feature selection, and thus, we conclude that the inclusion of CBF data marginally improves age estimation.</p>
Citation
Neurobiology of Aging, v.95, p. 131-142
ISSN
1558-1497
0197-4580
Link
Publisher
Elsevier Inc
Title
Age-related differences in cerebral blood flow and cortical thickness with an application to age prediction
Type of document
Journal Article
Entity Type
Publication

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