001     826796
005     20210129225711.0
024 7 _ |a 10.1007/s11682-016-9647-x
|2 doi
024 7 _ |a 1931-7557
|2 ISSN
024 7 _ |a 1931-7565
|2 ISSN
024 7 _ |a 2128/25628
|2 Handle
024 7 _ |a pmid:27796731
|2 pmid
024 7 _ |a WOS:000416555800014
|2 WOS
037 _ _ |a FZJ-2017-01013
082 _ _ |a 150
100 1 _ |a Lange, Catharina
|0 P:(DE-HGF)0
|b 0
245 _ _ |a Mental speed is associated with the shape irregularity of white matter MRI hyperintensity load
260 _ _ |a New York, NY [u.a.]
|c 2017
|b Springer
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1599659002_20795
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Brain MRI white matter hyperintensities (WMHs) are common in elderly subjects. Their impact on cognition, however, appears highly variable. Complementing conventional scoring of WMH load (volume and location) by quantitative characterization of the shape irregularity of WMHs might improve the understanding of the relationship between WMH load and cognitive performance. Here we propose the “confluency sum score” (COSU) as a marker of the total shape irregularity of WMHs in the brain. The study included two independent patient samples: 87 cognitively impaired geriatric inpatients from a prospective neuroimaging study (iDSS) and 198 subjects from the National Alzheimer’s Coordinating Center (NACC) database (132 with, 66 w/o cognitive impairment). After automatic segmentation and clustering of the WMHs on FLAIR (LST toolbox, SPM8), the confluency of the i-th contiguous WMH cluster was computed as confluencyi = [1/(36π)∙surfacei 3/volumei 2]1/3–1. The COSU was obtained by summing the confluency over all WMH clusters. COSU was tested for correlation with CERAD-plus subscores. Correlation analysis was restricted to subjects with at least moderate WMH load (≥ 13.5 ml; iDSS / NACC: n = 52 / 80). In the iDSS sample, among the 12 CERAD-plus subtests the trail making test A (TMT-A) was most strongly correlated with the COSU (Spearman rho = −0.345, p = 0.027). TMT-A performance was not associated with total WMH volume (rho = 0.147, p = 0.358). This finding was confirmed in the NACC sample (rho = −0.261, p = 0.023 versus rho = −0.040, p = 0.732). Cognitive performance in specific domains including mental speed and fluid abilities seems to be more strongly associated with the shape irregularity of white matter MRI hyperintensities than with their volume.
536 _ _ |a 573 - Neuroimaging (POF3-573)
|0 G:(DE-HGF)POF3-573
|c POF3-573
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Suppa, Per
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Mäurer, Anja
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Ritter, Kerstin
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Pietrzyk, Uwe
|0 P:(DE-Juel1)131667
|b 4
700 1 _ |a Steinhagen-Thiessen, Elisabeth
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Fiebach, Jochen B.
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Spies, Lothar
|0 P:(DE-HGF)0
|b 7
700 1 _ |a Buchert, Ralph
|0 P:(DE-HGF)0
|b 8
|e Corresponding author
773 _ _ |a 10.1007/s11682-016-9647-x
|0 PERI:(DE-600)2377165-3
|p 1720–1730
|t Brain imaging and behavior
|v 11
|y 2017
|x 1931-7565
856 4 _ |y Published on 2016-10-28. Available in OpenAccess from 2017-10-28.
|u https://juser.fz-juelich.de/record/826796/files/nihms840351.pdf
856 4 _ |y Published on 2016-10-28. Available in OpenAccess from 2017-10-28.
|x pdfa
|u https://juser.fz-juelich.de/record/826796/files/nihms840351.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:826796
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)131667
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-573
|2 G:(DE-HGF)POF3-500
|v Neuroimaging
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a Embargoed OpenAccess
|0 StatID:(DE-HGF)0530
|2 StatID
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b BRAIN IMAGING BEHAV : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
920 1 _ |0 I:(DE-Juel1)INM-4-20090406
|k INM-4
|l Physik der Medizinischen Bildgebung
|x 0
920 1 _ |0 I:(DE-82)080010_20140620
|k JARA-BRAIN
|l JARA-BRAIN
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-4-20090406
980 _ _ |a I:(DE-82)080010_20140620
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21