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Arterial-spin-labeling (ASL) perfusion MRI predicts cognitive function in elderly individuals: A 4-year longitudinal study

Authors :
De Vis, Jill B
Peng, Shin-Lei
Chen, Xi
Li, Yang
Liu, Peiying
Sur, Sandeepa
Rodrigue, Karen M
Park, Denise C
Lu, Hanzhang
Source :
Journal of magnetic resonance imaging : JMRI, vol 48, iss 2
Publication Year :
2018
Publisher :
eScholarship, University of California, 2018.

Abstract

BackgroundWith the disappointing outcomes of clinical trials on patients with Alzheimer's disease or mild cognitive impairment (MCI), there is increasing attention to understanding cognitive decline in normal elderly individuals, with the goal of identifying subjects who are most susceptible to imminent cognitive impairment.Purpose/hypothesisTo evaluate the potential of cerebral blood flow (CBF) as a biomarker by investigating the relationship between CBF at baseline and cognition at follow-up.Study typeProspective longitudinal study with a 4-year time interval.Population309 healthy subjects aged 20-89 years old.Field strength/sequence3T pseudo-continuous-arterial-spin-labeling MRI.AssessmentCBF at baseline and cognitive assessment at both baseline and follow-up.Statistical testsLinear regression analyses with age, systolic blood pressure, physical activity, and baseline cognition as covariates.ResultsLinear regression analyses revealed that whole-brain CBF at baseline was predictive of general fluid cognition at follow-up. This effect was observed in the older group (age ≥54 years, β = 0.221, P = 0.004), but not in younger or entire sample (β = 0.018, P = 0.867 and β = 0.089, P = 0.098, respectively). Among major brain lobes, frontal CBF had the highest sensitivity in predicting future cognition, with a significant effect observed for fluid cognition (β = 0.244 P = 0.001), episodic memory (β = 0.294, P = 0.001), and reasoning (β = 0.186, P = 0.027). These associations remained significant after accounting for baseline cognition. Voxelwise analysis revealed that medial frontal cortex and anterior cingulate cortex, part of the default mode network (DMN), are among the most important regions in predicting fluid cognition.Data conclusionIn a healthy aging cohort, CBF can predict general cognitive ability as well as specific domains of cognitive function.Level of evidence1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2018;48:449-458.

Details

Database :
OpenAIRE
Journal :
Journal of magnetic resonance imaging : JMRI, vol 48, iss 2
Accession number :
edsair.od.......325..c7d6ca8c8dff2a03266fcd75b75cdc2d