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Grading and Interpretation of White Matter Hyperintensities Using Statistical Maps
DC Field | Value | Language |
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dc.contributor.author | Ryu, Wi-Sun | - |
dc.contributor.author | Woo, Sung-Ho | - |
dc.contributor.author | Schellingerhout, Dawid | - |
dc.contributor.author | Chung, Moo K. | - |
dc.contributor.author | Kim, Chi Kyung | - |
dc.contributor.author | Jang, Min Uk | - |
dc.contributor.author | Park, Kyoung-Jong | - |
dc.contributor.author | Hong, Keun-Sik | - |
dc.contributor.author | Jeong, Sang-Wuk | - |
dc.contributor.author | Na, Jeong-Yong | - |
dc.contributor.author | Cho, Ki-Hyun | - |
dc.contributor.author | Kim, Joon-Tae | - |
dc.contributor.author | Kim, Beom Joon | - |
dc.contributor.author | Han, Moon-Ku | - |
dc.contributor.author | Lee, Jun | - |
dc.contributor.author | Cha, Jae-Kwan | - |
dc.contributor.author | Kim, Dae-Hyun | - |
dc.contributor.author | Lee, Soo Joo | - |
dc.contributor.author | Ko, Youngchai | - |
dc.contributor.author | Cho, Yong-Jin | - |
dc.contributor.author | Lee, Byung-Chul | - |
dc.contributor.author | Yu, Kyung-Ho | - |
dc.contributor.author | Oh, Mi-Sun | - |
dc.contributor.author | Park, Jong-Moo | - |
dc.contributor.author | Kang, Kyusik | - |
dc.contributor.author | Lee, Kyung Bok | - |
dc.contributor.author | Park, Tai Hwan | - |
dc.contributor.author | Lee, Juneyoung | - |
dc.contributor.author | Choi, Heung-Kook | - |
dc.contributor.author | Lee, Kiwon | - |
dc.contributor.author | Bae, Hee-Joon | - |
dc.contributor.author | Kim, Dong-Eog | - |
dc.date.accessioned | 2024-08-08T01:41:10Z | - |
dc.date.available | 2024-08-08T01:41:10Z | - |
dc.date.created | 2021-04-12 | - |
dc.date.created | 2021-04-12 | - |
dc.date.issued | 2014-12 | - |
dc.identifier.citation | Stroke, Vol.45 No.12, pp.3567-3575 | - |
dc.identifier.issn | 0039-2499 | - |
dc.identifier.uri | https://hdl.handle.net/10371/207327 | - |
dc.description.abstract | Background 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.language | 영어 | - |
dc.publisher | Lippincott Williams & Wilkins Ltd. | - |
dc.title | Grading and Interpretation of White Matter Hyperintensities Using Statistical Maps | - |
dc.type | Article | - |
dc.identifier.doi | 10.1161/STROKEAHA.114.006662 | - |
dc.citation.journaltitle | Stroke | - |
dc.identifier.wosid | 000345516600246 | - |
dc.identifier.scopusid | 2-s2.0-84922480006 | - |
dc.citation.endpage | 3575 | - |
dc.citation.number | 12 | - |
dc.citation.startpage | 3567 | - |
dc.citation.volume | 45 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Han, Moon-Ku | - |
dc.contributor.affiliatedAuthor | Bae, Hee-Joon | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordPlus | VASCULAR RISK-FACTORS | - |
dc.subject.keywordPlus | SMALL VESSEL DISEASE | - |
dc.subject.keywordPlus | BLOOD-PRESSURE | - |
dc.subject.keywordPlus | ENDOTHELIAL FUNCTION | - |
dc.subject.keywordPlus | ATRIAL-FIBRILLATION | - |
dc.subject.keywordPlus | STROKE | - |
dc.subject.keywordPlus | LESIONS | - |
dc.subject.keywordPlus | VOLUME | - |
dc.subject.keywordPlus | LEUKOARAIOSIS | - |
dc.subject.keywordPlus | DETERMINANTS | - |
dc.subject.keywordAuthor | cerebral infarction | - |
dc.subject.keywordAuthor | leukoaraiosis | - |
dc.subject.keywordAuthor | magnetic resonance imaging | - |
dc.subject.keywordAuthor | topographic brain mapping | - |
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