Jill B De Vis1, Shin-Lei Peng1,2, Xi Chen3, Yang Li1, Peiying Liu1, Sandeepa Sur1, Karen M Rodrigue3, Denise C Park3, Hanzhang Lu1,4. 1. Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 2. Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan. 3. Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Texas, USA. 4. Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Abstract
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.
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.
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