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

Abstract：

: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 life span. 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 R2 of 0.21) than in the CBF data (average R2 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.

journal_name

Neurobiol Aging

journal_title

Neurobiology of aging

authors

MacDonald ME,Williams RJ,Rajashekar D,Stafford RB,Hanganu A,Sun H,Berman AJL,McCreary CR,Frayne R,Forkert ND,Pike GB

doi

10.1016/j.neurobiolaging.2020.06.019

subject

Has Abstract

pub_date

2020-11-01 00:00:00

pages

131-142

eissn

0197-4580

issn

1558-1497

pii

S0197-4580(20)30212-8

journal_volume

95

pub_type

杂志文章

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