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      MRI and MRS predictors of mild cognitive impairment in a population-based sample.

      Neurology
      Aged, Aged, 80 and over, Aging, pathology, physiology, Female, Humans, Magnetic Resonance Imaging, methods, Magnetic Resonance Spectroscopy, Male, Mild Cognitive Impairment, metabolism, physiopathology, Predictive Value of Tests, Prodromal Symptoms, Proportional Hazards Models

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          Abstract

          To investigate MRI and proton magnetic resonance spectroscopy (MRS) predictors of mild cognitive impairment (MCI) in cognitively normal older adults. Subjects were cognitively normal older adults (n = 1,156) who participated in the population-based Mayo Clinic Study of Aging MRI/MRS study from August 2005 to December 2010 and had at least one annual clinical follow-up. Single-voxel MRS was performed from the posterior cingulate gyri, and hippocampal volumes and white matter hyperintensity volumes were quantified using automated methods. Brain infarcts were assessed on MRI. Cox proportional hazards regression, with age as the time scale, was used to assess the effect of MRI and MRS markers on the risk of progression from cognitively normal to MCI. Linear mixed-effects models were used to assess the effect of MRI and MRS markers on cognitive decline. After a median follow-up of 2.8 years, 214 participants had progressed to MCI or dementia (estimated incidence rate = 6.1% per year; 95% confidence interval = 5.3%-7.0%). In univariable modeling, hippocampal volume, white matter hyperintensity volume, and N-acetylaspartate/myo-inositol were significant predictors of MCI in cognitively normal older adults. In multivariable modeling, only decreased hippocampal volume and N-acetylaspartate/myo-inositol were independent predictors of MCI. These MRI/MRS predictors of MCI as well as infarcts were associated with cognitive decline (p < 0.05). Quantitative MRI and MRS markers predict progression to MCI and cognitive decline in cognitively normal older adults. MRS may contribute to the assessment of preclinical dementia pathologies by capturing neurodegenerative changes that are not detected by hippocampal volumetry.

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