Journal Article

DZNE-2020-02770

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Automated measurement of local white matter lesion volume.

van der Lijn, F. (Corresponding author) ; Verhaaren, B. F. J. ; Ikram, M. A. ; Klein, S. ; de Bruijne, M. ; Vrooman, H. A. ; Vernooij, M. W. ; Hammers, A. ; Rueckert, D. ; van der Lugt, A. ; Breteler, M. M. B.DZNE* ; Niessen, W. J.

2012
Academic Press Orlando, Fla.

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Please use a persistent id in citations: doi:10.1016/j.neuroimage.2011.11.021

Abstract: 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.

Keyword(s): Aged (MeSH) ; Aged, 80 and over (MeSH) ; Automation (MeSH) ; Brain Diseases: pathology (MeSH) ; Female (MeSH) ; Humans (MeSH) ; Magnetic Resonance Imaging: methods (MeSH) ; Male (MeSH) ; Middle Aged (MeSH)

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Contributing Institute(s):

1. Population Health Sciences (AG Breteler)

Research Program(s):

1. 345 - Population Studies and Genetics (POF3-345) (POF3-345)

Appears in the scientific report 2012

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Database coverage:
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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