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@ARTICLE{Baykara:138890,
author = {Baykara, Ebru and Gesierich, Benno and Adam, Ruth and
Tuladhar, Anil Man and Biesbroek, J Matthijs and Koek,
Huiberdina L and Ropele, Stefan and Jouvent, Eric and
Initiative, Alzheimer's Disease Neuroimaging and Chabriat,
Hugues and Ertl-Wagner, Birgit and Ewers, Michael and
Schmidt, Reinhold and de Leeuw, Frank-Erik and Biessels,
Geert Jan and Dichgans, Martin and Duering, Marco},
title = {{A} {N}ovel {I}maging {M}arker for {S}mall {V}essel
{D}isease {B}ased on {S}keletonization of {W}hite {M}atter
{T}racts and {D}iffusion {H}istograms.},
journal = {Annals of neurology},
volume = {80},
number = {4},
issn = {0364-5134},
address = {Hoboken, NJ},
publisher = {Wiley-Blackwell},
reportid = {DZNE-2020-05212},
pages = {581-592},
year = {2016},
abstract = {To establish a fully automated, robust imaging marker for
cerebral small vessel disease (SVD) and related cognitive
impairment that is easy to implement, reflects disease
burden, and is strongly associated with processing speed,
the predominantly affected cognitive domain in SVD.We
developed a novel magnetic resonance imaging marker based on
diffusion tensor imaging, skeletonization of white matter
tracts, and histogram analysis. The marker (peak width of
skeletonized mean diffusivity [PSMD]) was assessed along
with conventional SVD imaging markers. We first evaluated
associations with processing speed in patients with
genetically defined SVD (n = 113). Next, we validated our
findings in independent samples of inherited SVD (n = 57),
sporadic SVD (n = 444), and memory clinic patients with SVD
(n = 105). The new marker was further applied to healthy
controls (n = 241) and to patients with Alzheimer's disease
(n = 153). We further conducted a longitudinal analysis and
interscanner reproducibility study.PSMD was associated with
processing speed in all study samples with SVD (p-values
between 2.8 × 10(-3) and 1.8 × 10(-10) ). PSMD explained
most of the variance in processing speed (R(2) ranging from
$8.8\%$ to $46\%)$ and consistently outperformed
conventional imaging markers (white matter hyperintensity
volume, lacune volume, and brain volume) in multiple
regression analyses. Increases in PSMD were linked to
vascular but not to neurodegenerative disease. In
longitudinal analysis, PSMD captured SVD progression better
than other imaging markers.PSMD is a new, fully automated,
and robust imaging marker for SVD. PSMD can easily be
applied to large samples and may be of great utility for
both research studies and clinical use. Ann Neurol
2016;80:581-592.},
keywords = {Adult / Aged / Aged, 80 and over / Alzheimer Disease:
diagnostic imaging / Biomarkers / Cerebral Small Vessel
Diseases: complications / Cerebral Small Vessel Diseases:
diagnostic imaging / Cognitive Dysfunction: diagnostic
imaging / Cognitive Dysfunction: etiology / Cognitive
Dysfunction: physiopathology / Diffusion Tensor Imaging:
methods / Diffusion Tensor Imaging: standards / Female /
Humans / Male / Middle Aged / Reproducibility of Results /
White Matter: diagnostic imaging / Young Adult / Biomarkers
(NLM Chemicals)},
cin = {Clinical Dementia Research München},
ddc = {610},
cid = {I:(DE-2719)1111016},
pnm = {344 - Clinical and Health Care Research (POF3-344)},
pid = {G:(DE-HGF)POF3-344},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:27518166},
doi = {10.1002/ana.24758},
url = {https://pub.dzne.de/record/138890},
}