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Change in multimodal MRI markers predicts dementia risk in cerebral small vessel disease.

Zeestraten, EA; Lawrence, AJ; Lambert, C; Benjamin, P; Brookes, RL; Mackinnon, AD; Morris, RG; Barrick, TR; Markus, HS (2017) Change in multimodal MRI markers predicts dementia risk in cerebral small vessel disease. Neurology, 89 (18). pp. 1869-1876. ISSN 1526-632X https://doi.org/10.1212/WNL.0000000000004594
SGUL Authors: Lambert, Christian Paul

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Abstract

OBJECTIVE: To determine whether MRI markers, including diffusion tensor imaging (DTI), can predict cognitive decline and dementia in patients with cerebral small vessel disease (SVD). METHODS: In the prospective St George's Cognition and Neuroimaging in Stroke study, multimodal MRI was performed annually for 3 years and cognitive assessments annually for 5 years in a cohort of 99 patients with SVD, defined as symptomatic lacunar stroke and confluent white matter hyperintensities (WMH). Progression to dementia was determined in all patients. Progression of WMH, brain volume, lacunes, cerebral microbleeds, and a DTI measure (the normalized peak height of the mean diffusivity histogram distribution) as a marker of white matter microstructural damage were determined. RESULTS: Over 5 years of follow-up, 18 patients (18.2%) progressed to dementia. A significant change in all MRI markers, representing deterioration, was observed. The presence of new lacunes, and rate of increase in white matter microstructural damage on DTI, correlated with both decline in executive function and global functioning. Growth of WMH and deterioration of white matter microstructure on DTI predicted progression to dementia. A model including change in MRI variables together with their baseline values correctly classified progression to dementia with a C statistic of 0.85. CONCLUSIONS: This longitudinal prospective study provides evidence that change in MRI measures including DTI, over time durations during which cognitive change is not detectable, predicts cognitive decline and progression to dementia. It supports the use of MRI measures, including DTI, as useful surrogate biomarkers to monitor disease and assess therapeutic interventions.

Item Type: Article
Additional Information: Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Neurology & Neurosurgery, 1103 Clinical Sciences, 1109 Neurosciences, 1702 Cognitive Science
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Academic Structure > Molecular and Clinical Sciences Research Institute (MCS) > Neuroscience (INCCNS)
Journal or Publication Title: Neurology
ISSN: 1526-632X
Language: eng
Dates:
DateEvent
31 October 2017Published
4 October 2017Published Online
16 August 2017Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
081589Wellcome Trusthttp://dx.doi.org/10.13039/100004440
UNSPECIFIEDNational Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
ARUK-EXT2015B-1Alzheimer’s Research UKhttp://dx.doi.org/10.13039/501100002283
PG/13/30/30005British Heart Foundationhttp://dx.doi.org/10.13039/501100000274
PubMed ID: 28978655
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/109220
Publisher's version: https://doi.org/10.1212/WNL.0000000000004594

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