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Grading and Interpretation of White Matter Hyperintensities Using Statistical Maps

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dc.contributor.authorRyu, Wi-Sun-
dc.contributor.authorWoo, Sung-Ho-
dc.contributor.authorSchellingerhout, Dawid-
dc.contributor.authorChung, Moo K.-
dc.contributor.authorKim, Chi Kyung-
dc.contributor.authorJang, Min Uk-
dc.contributor.authorPark, Kyoung-Jong-
dc.contributor.authorHong, Keun-Sik-
dc.contributor.authorJeong, Sang-Wuk-
dc.contributor.authorNa, Jeong-Yong-
dc.contributor.authorCho, Ki-Hyun-
dc.contributor.authorKim, Joon-Tae-
dc.contributor.authorKim, Beom Joon-
dc.contributor.authorHan, Moon-Ku-
dc.contributor.authorLee, Jun-
dc.contributor.authorCha, Jae-Kwan-
dc.contributor.authorKim, Dae-Hyun-
dc.contributor.authorLee, Soo Joo-
dc.contributor.authorKo, Youngchai-
dc.contributor.authorCho, Yong-Jin-
dc.contributor.authorLee, Byung-Chul-
dc.contributor.authorYu, Kyung-Ho-
dc.contributor.authorOh, Mi-Sun-
dc.contributor.authorPark, Jong-Moo-
dc.contributor.authorKang, Kyusik-
dc.contributor.authorLee, Kyung Bok-
dc.contributor.authorPark, Tai Hwan-
dc.contributor.authorLee, Juneyoung-
dc.contributor.authorChoi, Heung-Kook-
dc.contributor.authorLee, Kiwon-
dc.contributor.authorBae, Hee-Joon-
dc.contributor.authorKim, Dong-Eog-
dc.date.accessioned2021-09-05T02:38:45Z-
dc.date.available2021-09-05T02:38:45Z-
dc.date.created2021-06-15-
dc.date.issued2014-12-
dc.identifier.issn0039-2499-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/96689-
dc.description.abstractBackground and Purpose-We aimed to generate rigorous graphical and statistical reference data based on volumetric measurements for assessing the relative severity of white matter hyperintensities (WMHs) in patients with stroke. Methods-We prospectively mapped WMHs from 2699 patients with first-ever ischemic stroke (mean age=66.8 +/- 13.0 years) enrolled consecutively from 11 nationwide stroke centers, from patient (fluid-attenuated-inversion-recovery) MRIs onto a standard brain template set. Using multivariable analyses, we assessed the impact of major (age/hypertension) and minor risk factors on WMH variability. Results-We have produced a large reference data library showing the location and quantity of WMHs as topographical frequency-volume maps. This easy-to-use graphical reference data set allows the quantitative estimation of the severity of WMH as a percentile rank score. For all patients (median age=69 years), multivariable analysis showed that age, hypertension, atrial fibrillation, and left ventricular hypertrophy were independently associated with increasing WMH (0-9.4%, median=0.6%, of the measured brain volume). For younger (<= 69) hypertensives (n=819), age and left ventricular hypertrophy were positively associated with WMH. For older (>= 70) hypertensives (n=944), age and cholesterol had positive relationships with WMH, whereas diabetes mellitus, hyperlipidemia, and atrial fibrillation had negative relationships with WMH. For younger nonhypertensives (n=578), age and diabetes mellitus were positively related to WMH. For older nonhypertensives (n=328), only age was positively associated with WMH. Conclusions-We have generated a novel graphical WMH grading (Kim statistical WMH scoring) system, correlated to risk factors and adjusted for age/hypertension. Further studies are required to confirm whether the combined data set allows grading of WMH burden in individual patients and a tailored patient-specific interpretation in ischemic stroke-related clinical practice.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherLIPPINCOTT WILLIAMS & WILKINS-
dc.subjectVASCULAR RISK-FACTORS-
dc.subjectSMALL VESSEL DISEASE-
dc.subjectBLOOD-PRESSURE-
dc.subjectENDOTHELIAL FUNCTION-
dc.subjectATRIAL-FIBRILLATION-
dc.subjectSTROKE-
dc.subjectLESIONS-
dc.subjectVOLUME-
dc.subjectLEUKOARAIOSIS-
dc.subjectDETERMINANTS-
dc.titleGrading and Interpretation of White Matter Hyperintensities Using Statistical Maps-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Juneyoung-
dc.identifier.doi10.1161/STROKEAHA.114.006662-
dc.identifier.scopusid2-s2.0-84922480006-
dc.identifier.wosid000345516600246-
dc.identifier.bibliographicCitationSTROKE, v.45, no.12, pp.3567 - +-
dc.relation.isPartOfSTROKE-
dc.citation.titleSTROKE-
dc.citation.volume45-
dc.citation.number12-
dc.citation.startPage3567-
dc.citation.endPage+-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaNeurosciences & Neurology-
dc.relation.journalResearchAreaCardiovascular System & Cardiology-
dc.relation.journalWebOfScienceCategoryClinical Neurology-
dc.relation.journalWebOfScienceCategoryPeripheral Vascular Disease-
dc.subject.keywordPlusVASCULAR RISK-FACTORS-
dc.subject.keywordPlusSMALL VESSEL DISEASE-
dc.subject.keywordPlusBLOOD-PRESSURE-
dc.subject.keywordPlusENDOTHELIAL FUNCTION-
dc.subject.keywordPlusATRIAL-FIBRILLATION-
dc.subject.keywordPlusSTROKE-
dc.subject.keywordPlusLESIONS-
dc.subject.keywordPlusVOLUME-
dc.subject.keywordPlusLEUKOARAIOSIS-
dc.subject.keywordPlusDETERMINANTS-
dc.subject.keywordAuthorcerebral infarction-
dc.subject.keywordAuthorleukoaraiosis-
dc.subject.keywordAuthormagnetic resonance imaging-
dc.subject.keywordAuthortopographic brain mapping-
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