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Arterial‐spin‐labeling (ASL) perfusion MRI predicts cognitive function in elderly individuals: A 4‐year longitudinal study
Author(s) -
Vis Jill B.,
Peng ShinLei,
Chen Xi,
Li Yang,
Liu Peiying,
Sur Sandeepa,
Rodrigue Karen M.,
Park Denise C.,
Lu Hanzhang
Publication year - 2018
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.25938
Subject(s) - default mode network , cerebral blood flow , cognition , cognitive decline , medicine , cardiology , posterior cingulate , population , cerebral perfusion pressure , psychology , audiology , disease , psychiatry , dementia , environmental health
Background With 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/Hypothesis To 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 Type Prospective longitudinal study with a 4‐year time interval. Population 309 healthy subjects aged 20–89 years old. Field Strength/Sequence 3T pseudo‐continuous‐arterial‐spin‐labeling MRI. Assessment CBF at baseline and cognitive assessment at both baseline and follow‐up. Statistical Tests Linear regression analyses with age, systolic blood pressure, physical activity, and baseline cognition as covariates. Results Linear 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 Conclusion In a healthy aging cohort, CBF can predict general cognitive ability as well as specific domains of cognitive function. Level of Evidence : 1 Technical Efficacy : Stage 3 J. MAGN. RESON. IMAGING 2018;48:449–458.