Document Detail


Automated measurement of local white matter lesion volume.
MedLine Citation:
PMID:  22116036     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
It has been hypothesized that white matter lesions at different locations may have different etiology and clinical consequences. Several approaches for the quantification of local white matter lesion load have been proposed in the literature, most of which rely on a distinction between lesions in a periventricular region close to the ventricles and a subcortical zone further away. In this work we present a novel automated method for local white matter lesion volume quantification in magnetic resonance images. The method segments and measures the white matter lesion volume in 43 regions defined by orientation and distance to the ventricles, which allows a more spatially detailed study of lesion load. The potential of the method was demonstrated by analyzing the effect of blood pressure on the regional white matter lesion volume in 490 elderly subjects taken from a longitudinal population study. The method was also compared to two commonly used techniques to assess the periventricular and subcortical lesion load. The main finding was that high blood pressure was primarily associated with lesion load in the vascular watershed area that forms the border between the periventricular and subcortical regions. It explains the associations found for both the periventricular and subcortical load computed for the same data, and that were reported in the literature. But the proposed method can localize the region of association with greater precision than techniques that distinguish between periventricular and subcortical lesions only.
Authors:
Fedde van der Lijn; Benjamin F J Verhaaren; M Arfan Ikram; Stefan Klein; Marleen de Bruijne; Henri A Vrooman; Meike W Vernooij; Alexander Hammers; Daniel Rueckert; Aad van der Lugt; Monique M B Breteler; Wiro J Niessen
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-11-11
Journal Detail:
Title:  NeuroImage     Volume:  59     ISSN:  1095-9572     ISO Abbreviation:  Neuroimage     Publication Date:  2012 Feb 
Date Detail:
Created Date:  2012-02-20     Completed Date:  2012-07-03     Revised Date:  2014-02-20    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  United States    
Other Details:
Languages:  eng     Pagination:  3901-8     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 Elsevier Inc. All rights reserved.
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MeSH Terms
Descriptor/Qualifier:
Aged
Aged, 80 and over
Automation
Brain Diseases / pathology*
Female
Humans
Magnetic Resonance Imaging / methods*
Male
Middle Aged
Grant Support
ID/Acronym/Agency:
G108/585//Medical Research Council

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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