000826796 001__ 826796
000826796 005__ 20210129225711.0
000826796 0247_ $$2doi$$a10.1007/s11682-016-9647-x
000826796 0247_ $$2ISSN$$a1931-7557
000826796 0247_ $$2ISSN$$a1931-7565
000826796 0247_ $$2Handle$$a2128/25628
000826796 0247_ $$2pmid$$apmid:27796731
000826796 0247_ $$2WOS$$aWOS:000416555800014
000826796 037__ $$aFZJ-2017-01013
000826796 082__ $$a150
000826796 1001_ $$0P:(DE-HGF)0$$aLange, Catharina$$b0
000826796 245__ $$aMental speed is associated with the shape irregularity of white matter MRI hyperintensity load
000826796 260__ $$aNew York, NY [u.a.]$$bSpringer$$c2017
000826796 3367_ $$2DRIVER$$aarticle
000826796 3367_ $$2DataCite$$aOutput Types/Journal article
000826796 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1599659002_20795
000826796 3367_ $$2BibTeX$$aARTICLE
000826796 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000826796 3367_ $$00$$2EndNote$$aJournal Article
000826796 520__ $$aBrain MRI white matter hyperintensities (WMHs) are common in elderly subjects. Their impact on cognition, however, appears highly variable. Complementing conventional scoring of WMH load (volume and location) by quantitative characterization of the shape irregularity of WMHs might improve the understanding of the relationship between WMH load and cognitive performance. Here we propose the “confluency sum score” (COSU) as a marker of the total shape irregularity of WMHs in the brain. The study included two independent patient samples: 87 cognitively impaired geriatric inpatients from a prospective neuroimaging study (iDSS) and 198 subjects from the National Alzheimer’s Coordinating Center (NACC) database (132 with, 66 w/o cognitive impairment). After automatic segmentation and clustering of the WMHs on FLAIR (LST toolbox, SPM8), the confluency of the i-th contiguous WMH cluster was computed as confluencyi = [1/(36π)∙surfacei 3/volumei 2]1/3–1. The COSU was obtained by summing the confluency over all WMH clusters. COSU was tested for correlation with CERAD-plus subscores. Correlation analysis was restricted to subjects with at least moderate WMH load (≥ 13.5 ml; iDSS / NACC: n = 52 / 80). In the iDSS sample, among the 12 CERAD-plus subtests the trail making test A (TMT-A) was most strongly correlated with the COSU (Spearman rho = −0.345, p = 0.027). TMT-A performance was not associated with total WMH volume (rho = 0.147, p = 0.358). This finding was confirmed in the NACC sample (rho = −0.261, p = 0.023 versus rho = −0.040, p = 0.732). Cognitive performance in specific domains including mental speed and fluid abilities seems to be more strongly associated with the shape irregularity of white matter MRI hyperintensities than with their volume.
000826796 536__ $$0G:(DE-HGF)POF3-573$$a573 - Neuroimaging (POF3-573)$$cPOF3-573$$fPOF III$$x0
000826796 588__ $$aDataset connected to CrossRef
000826796 7001_ $$0P:(DE-HGF)0$$aSuppa, Per$$b1
000826796 7001_ $$0P:(DE-HGF)0$$aMäurer, Anja$$b2
000826796 7001_ $$0P:(DE-HGF)0$$aRitter, Kerstin$$b3
000826796 7001_ $$0P:(DE-Juel1)131667$$aPietrzyk, Uwe$$b4
000826796 7001_ $$0P:(DE-HGF)0$$aSteinhagen-Thiessen, Elisabeth$$b5
000826796 7001_ $$0P:(DE-HGF)0$$aFiebach, Jochen B.$$b6
000826796 7001_ $$0P:(DE-HGF)0$$aSpies, Lothar$$b7
000826796 7001_ $$0P:(DE-HGF)0$$aBuchert, Ralph$$b8$$eCorresponding author
000826796 773__ $$0PERI:(DE-600)2377165-3$$a10.1007/s11682-016-9647-x$$p1720–1730$$tBrain imaging and behavior$$v11$$x1931-7565$$y2017
000826796 8564_ $$uhttps://juser.fz-juelich.de/record/826796/files/nihms840351.pdf$$yPublished on 2016-10-28. Available in OpenAccess from 2017-10-28.
000826796 8564_ $$uhttps://juser.fz-juelich.de/record/826796/files/nihms840351.pdf?subformat=pdfa$$xpdfa$$yPublished on 2016-10-28. Available in OpenAccess from 2017-10-28.
000826796 909CO $$ooai:juser.fz-juelich.de:826796$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000826796 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131667$$aForschungszentrum Jülich$$b4$$kFZJ
000826796 9131_ $$0G:(DE-HGF)POF3-573$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vNeuroimaging$$x0
000826796 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000826796 915__ $$0StatID:(DE-HGF)0530$$2StatID$$aEmbargoed OpenAccess
000826796 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBRAIN IMAGING BEHAV : 2015
000826796 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000826796 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000826796 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000826796 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000826796 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000826796 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine
000826796 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000826796 9201_ $$0I:(DE-Juel1)INM-4-20090406$$kINM-4$$lPhysik der Medizinischen Bildgebung$$x0
000826796 9201_ $$0I:(DE-82)080010_20140620$$kJARA-BRAIN$$lJARA-BRAIN$$x1
000826796 980__ $$ajournal
000826796 980__ $$aVDB
000826796 980__ $$aUNRESTRICTED
000826796 980__ $$aI:(DE-Juel1)INM-4-20090406
000826796 980__ $$aI:(DE-82)080010_20140620
000826796 9801_ $$aFullTexts