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      White matter and its relationship with cognition in subjective cognitive decline

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          Abstract

          Introduction

          Subjective cognitive decline (SCD) is the earliest stage on the continuum toward Alzheimer's disease. This study examined (1) differences in white matter integrity between individuals with SCD and healthy control subjects and (2) how white matter integrity related to memory and executive function.

          Methods

          Diffusion tensor imaging and neuropsychological assessment data were retrieved from the Alzheimer's Disease Neuroimaging Initiative database for 30 individuals with SCD and 44 control subjects.

          Results

          Results revealed significantly lower white matter integrity in individuals with SCD relative to control subjects in widespread regions, including the bilateral corticospinal tracts, superior and inferior longitudinal fasciculi, fronto-occipital fasciculi, corpus callosum, forceps major and minor, hippocampi, anterior thalamic radiations, and the cerebellum. There was a widespread relationship between diffusion tensor imaging metrics and executive function in SCD, but not healthy control subjects, and no relationship with memory for either group.

          Discussion

          Relatively lower white matter integrity in SCD may be a useful early biomarker for risk of future cognitive decline. Future research should better characterize the SCD group longitudinally and in individuals at risk for Alzheimer's disease.

          Highlights

          • Individuals with SCD had lower FA and higher MD relative to healthy controls.

          • Lower FA and higher mean MD were related to lower executive function in SCD only.

          • White matter integrity was unrelated to memory in SCD and healthy control subjects.

          • DTI metrics may be a sensitive biomarker for early Alzheimer's disease.

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          Most cited references25

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          Fast robust automated brain extraction.

          An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods. Copyright 2002 Wiley-Liss, Inc.
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              Diffusion tensor imaging and tract-based spatial statistics in Alzheimer's disease and mild cognitive impairment.

              We aimed to explore the changes in fractional anisotropy (FA) in subjects with mild cognitive impairment (MCI) and Alzheimer's disease (AD) by analyzing diffusion tensor imaging (DTI) data using the Tract-Based Spatial Statistics (TBSS). DTI data were collected from 17 AD patients, 27 MCI subjects and 19 healthy controls. Voxel-based analysis with TBSS was used to compare FA among the three groups. Additionally, guided by TBSS findings, a region of interest (ROI)-based analysis along the TBSS skeleton was performed on group-level and the accuracy of the method was assessed by the back-projection of ROIs to the native space FA. Neurofiber tracts with decreased FA included: the parahippocampal white matter, cingulum, uncinate fasciculus, inferior and superior longitudinal fasciculus, corpus callosum, fornix, tracts in brain stem, and cerebellar tracts. Quantitative ROI-analysis further demonstrated the significant decrease on FA values in AD patients relative to controls whereas FA values of MCI patients were found in between the controls and AD patients. We conclude that TBSS is a promising method in examining the degeneration of neurofiber tracts in MCI and AD patients. Copyright © 2009 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Alzheimers Dement (Amst)
                Alzheimers Dement (Amst)
                Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring
                Elsevier
                2352-8729
                14 December 2018
                December 2019
                14 December 2018
                : 11
                : 28-35
                Affiliations
                [1]Department of Psychology, University of Victoria, Victoria, British Columbia, Canada
                Author notes
                []Corresponding author. Tel.: +1-250-721-7549; Fax: +1-250-721-8929. gawryluk@ 123456uvic.ca
                [∗∗]

                Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database ( adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

                Article
                S2352-8729(18)30076-9
                10.1016/j.dadm.2018.10.008
                6297855
                30581973
                81e7ad60-ef4a-45cb-a6df-9c8e6585c206
                © 2018 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Categories
                Neuroimaging

                subjective cognitive decline,diffusion tensor imaging,executive function,memory,alzheimer's disease

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