000864417 001__ 864417
000864417 005__ 20210130002549.0
000864417 0247_ $$2doi$$a10.1016/j.neuroimage.2019.116077
000864417 0247_ $$2ISSN$$a1053-8119
000864417 0247_ $$2ISSN$$a1095-9572
000864417 0247_ $$2altmetric$$aaltmetric:64683518
000864417 0247_ $$2pmid$$apmid:31398433
000864417 0247_ $$2WOS$$aWOS:000491861000081
000864417 037__ $$aFZJ-2019-04201
000864417 082__ $$a610
000864417 1001_ $$0P:(DE-Juel1)166343$$aIordanishvili, Elene$$b0$$ufzj
000864417 245__ $$aQuantitative MRI of cerebral white matter hyperintensities: A new approach towards understanding the underlying pathology
000864417 260__ $$aOrlando, Fla.$$bAcademic Press$$c2019
000864417 3367_ $$2DRIVER$$aarticle
000864417 3367_ $$2DataCite$$aOutput Types/Journal article
000864417 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1568039877_22205
000864417 3367_ $$2BibTeX$$aARTICLE
000864417 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000864417 3367_ $$00$$2EndNote$$aJournal Article
000864417 520__ $$aInterest in white matter hyperintensities (WMH), a radiological biomarker of small vessel disease, is continuously increasing. This is, in most part, due to our better understanding of their association with various clinical disorders, such as stroke and Alzheimer’s disease, and the overlapping pathology of WMH with these afflictions. Although post-mortem histological studies have reported various underlying pathophysiological substrates, in vivo research has not been specific enough to fully corroborate these findings. Furthermore, post-mortem studies are not able to capture which pathological processes are the driving force of the WMH severity. The current study attempts to fill this gap by non-invasively investigating the influence of WMH on brain tissue using quantitative MRI (qMRI) measurements of the water content (H2O), the longitudinal (T1) and effective transverse relaxation times (T2∗), as well as the semi-quantitative magnetization transfer ratio (MTR), and bound proton fraction (ƒbound). In total, seventy subjects (age range 50–80 years) were selected from a population-based aging cohort study, 1000BRAINS. Normal appearing grey (NAGM) and white matter (NAWM), as well as deep (DWMH) and periventricular (PWMH) white matter hyperintensities, were segmented and characterized in terms of their quantitative properties. The subjects were then further divided into four grades according to the Fazekas rating scale of severity. Groupwise analyses of the qMRI values in each tissue class were performed. All five qMRI parameters showed significant differences between WMH and NAWM (p < 0.001). Importantly, the parameters differed between DWMH and PWMH, the latter having higher H2O, T1, T2∗ and lower MTR and ƒbound values (p < 0.001). Following grading according to the Fazekas scale, DWMH showed an increase in the water content, T1 and a decrease in bound proton fraction corresponding to severity, exhibiting significant changes in grade 3 (p < 0.001), while NAWM revealed significantly higher H2O values in grade 3 compared to grade 0 (p < 0.001). PWMH demonstrated an increase in T2∗ values (significant in grade 3, P < 0.001). These results are in agreement with previous histopathological studies and support the interpretation that both edema and myelin loss due to a possible breakdown of the blood-brain barrier and inflammation are the major pathological substrates turning white matter into DWMH. Edema being an earlier contributing factor to the pathology, as expressed in the elevated water content values in NAWM with increasing severity. In the case of PWMH, an altered fluid dynamic and cerebrospinal fluid leakage exacerbate the changes. It was also found that the pathology, as monitored by qMRI, evolves faster in DWMH than in the PWMH following the severity.
000864417 536__ $$0G:(DE-HGF)POF3-573$$a573 - Neuroimaging (POF3-573)$$cPOF3-573$$fPOF III$$x0
000864417 588__ $$aDataset connected to CrossRef
000864417 7001_ $$0P:(DE-Juel1)161242$$aSchall, Melissa$$b1$$ufzj
000864417 7001_ $$0P:(DE-Juel1)169114$$aLoução, Ricardo$$b2$$ufzj
000864417 7001_ $$0P:(DE-Juel1)162442$$aZimmermann, Markus$$b3$$ufzj
000864417 7001_ $$0P:(DE-HGF)0$$aKotetishvili, Ketevan$$b4
000864417 7001_ $$0P:(DE-Juel1)131794$$aShah, N. Jon$$b5$$ufzj
000864417 7001_ $$0P:(DE-Juel1)131782$$aOros-Peusquens, Ana-Maria$$b6$$eCorresponding author$$ufzj
000864417 773__ $$0PERI:(DE-600)1471418-8$$a10.1016/j.neuroimage.2019.116077$$gp. 116077 -$$p116077 -$$tNeuroImage$$v202$$x1053-8119$$y2019
000864417 909CO $$ooai:juser.fz-juelich.de:864417$$pVDB
000864417 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)166343$$aForschungszentrum Jülich$$b0$$kFZJ
000864417 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161242$$aForschungszentrum Jülich$$b1$$kFZJ
000864417 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169114$$aForschungszentrum Jülich$$b2$$kFZJ
000864417 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)162442$$aForschungszentrum Jülich$$b3$$kFZJ
000864417 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131794$$aForschungszentrum Jülich$$b5$$kFZJ
000864417 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131782$$aForschungszentrum Jülich$$b6$$kFZJ
000864417 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
000864417 9141_ $$y2019
000864417 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000864417 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000864417 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000864417 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000864417 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNEUROIMAGE : 2017
000864417 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000864417 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000864417 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000864417 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000864417 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000864417 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000864417 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences
000864417 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000864417 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bNEUROIMAGE : 2017
000864417 9201_ $$0I:(DE-Juel1)INM-11-20170113$$kINM-11$$lJara-Institut Quantum Information$$x0
000864417 9201_ $$0I:(DE-Juel1)INM-4-20090406$$kINM-4$$lPhysik der Medizinischen Bildgebung$$x1
000864417 9201_ $$0I:(DE-82)080010_20140620$$kJARA-BRAIN$$lJARA-BRAIN$$x2
000864417 980__ $$ajournal
000864417 980__ $$aVDB
000864417 980__ $$aI:(DE-Juel1)INM-11-20170113
000864417 980__ $$aI:(DE-Juel1)INM-4-20090406
000864417 980__ $$aI:(DE-82)080010_20140620
000864417 980__ $$aUNRESTRICTED