Objective: To examine associations between dementia severity and quantitative magnetic resonance imaging measures of cortical gray matter volume and abnormal white matter volume in 52 patients diagnosed with probable Alzheimer disease.
Design: Analysis of the relationship between magnetic resonance imaging volume measures and dementia severity using multiple regression and Pearson correlations.
Setting: Alzheimer's Disease Research Center, University of California, San Diego.
Participants: Twenty-three men and 29 women with probable Alzheimer disease (average age, 71.7 years; average education, 13.3 years).
Main Outcome Measures: The Mattis Dementia Rating Scale (MDRS) and the Mini-Mental State Examination.
Results: Using simultaneous multiple regression, magnetic resonance imaging volumetric measures of cortical gray matter and abnormal white matter were independently associated with dementia severity measured by either the MDRS or the Mini-Mental State Examination. Cortical gray matter volume and abnormal white matter volume also made independent contributions to performance in 4 of 5 cognitive domains assessed by the MDRS. Regional analysis indicated that limbic cortical gray matter volume and nonlimbic cortical gray matter volume were also correlated with the MDRS score; however, in the regression analysis the individual gray matter measures were not independently associated with MDRS performance. A similar analysis revealed statistically independent relationships of limbic gray matter volume and abnormal white matter volume, but not nonlimbic cortical gray matter volume, to Mini-Mental State Examination performance.
Conclusions: Quantitative magnetic resonance methods provided strong evidence that cortical gray matter volume, which may reflect atrophy, and abnormal white matter volume are independently related to dementia severity in probable Alzheimer disease: lower gray matter and higher abnormal white matter volumes are associated with more severe dementia.
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http://dx.doi.org/10.1001/archneur.1996.00550080056013 | DOI Listing |
Sci Rep
January 2025
Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi, China.
The conventional statistical approach for analyzing resting state functional MRI (rs-fMRI) data struggles to accurately distinguish between patients with multiple sclerosis (MS) and those with neuromyelitis optic spectrum disorders (NMOSD), highlighting the need for improved diagnostic efficacy. In this study, multilevel functional metrics including resting state functional connectivity, amplitude of low frequency fluctuation (ALFF), and regional homogeneity (ReHo) were calculated and extracted from 116 regions of interest in the anatomical automatic labeling atlas. Subsequently, classifiers were developed using different combinations of these selected features to distinguish between MS and NMOSD.
View Article and Find Full Text PDFProg Neuropsychopharmacol Biol Psychiatry
January 2025
MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410006, PR China; Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha 410006, PR China. Electronic address:
Aging of the human brain involves intricate biological processes, resulting in complex changes in structure and function. While the effects of aging on gray matter (GM) connectivity are extensively studied, white matter (WM) functional changes have received comparatively less attention. This study examines age-related WM functional dynamics using resting-state fMRI across the adult lifespan.
View Article and Find Full Text PDFNeuroimage
January 2025
Department of Radiology, Columbia University Irving Medical Center, New York, NY; Department of Biomedical Engineering, Columbia University, New York, NY. Electronic address:
Background: The cortical gray matter-white matter interface (GWI) is a natural transition zone where the composition of brain tissue abruptly changes and is a location for pathologic change in brain disorders. While diffusion magnetic resonance imaging (dMRI) is a reliable and well-established technique to characterize brain microstructure, the GWI is difficult to assess with dMRI due to partial volume effects and is normally excluded from such studies.
Methods: In this study, we introduce an approach to characterize the dMRI microstructural profile across the GWI and to assess the sharpness of the microstructural transition from cortical gray matter (GM) to white matter (WM).
PLoS One
January 2025
Department of Neurology, Weill Cornell Medicine, New York, NY, United States of America.
Testosterone, an essential sex steroid hormone, influences brain health by impacting neurophysiology and neuropathology throughout the lifespan in both genders. However, human research in this area is limited, particularly in women. This study examines the associations between testosterone levels, gray matter volume (GMV) and cerebral blood flow (CBF) in midlife individuals at risk for Alzheimer's disease (AD), according to sex and menopausal status.
View Article and Find Full Text PDFF-Florbetaben (FBB) uptake in the supratentorial cortex is indicative of amyloid positivity. Due to PET's low spatial resolution, image noise, and spill-over of signal from adjacent white-matter into gray-matter, there are inconsistencies in ratings among trained readers. A set of 264 F-Florbetaben (amyloid) PET/MRI exams were reconstructed using conventional ordered subset expectation maximization (OSEM) method and MR-guided block sequential regularized expectation maximization (MRgBSREM) method.
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