Grading and Interpretation of White Matter Hyperintensities Using Statistical Maps
- Authors
- Ryu, Wi-Sun; Woo, Sung-Ho; Schellingerhout, Dawid; Chung, Moo K.; Kim, Chi Kyung; Jang, Min Uk; Park, Kyoung-Jong; Hong, Keun-Sik; Jeong, Sang-Wuk; Na, Jeong-Yong; Cho, Ki-Hyun; Kim, Joon-Tae; Kim, Beom Joon; Han, Moon-Ku; Lee, Jun; Cha, Jae-Kwan; Kim, Dae-Hyun; Lee, Soo Joo; Ko, Youngchai; Cho, Yong-Jin; Lee, Byung-Chul; Yu, Kyung-Ho; Oh, Mi-Sun; Park, Jong-Moo; Kang, Kyusik; Lee, Kyung Bok; Park, Tai Hwan; Lee, Juneyoung; Choi, Heung-Kook; Lee, Kiwon; Bae, Hee-Joon; Kim, Dong-Eog
- Issue Date
- 12월-2014
- Publisher
- LIPPINCOTT WILLIAMS & WILKINS
- Keywords
- cerebral infarction; leukoaraiosis; magnetic resonance imaging; topographic brain mapping
- Citation
- STROKE, v.45, no.12, pp.3567 - +
- Indexed
- SCIE
SCOPUS
- Journal Title
- STROKE
- Volume
- 45
- Number
- 12
- Start Page
- 3567
- End Page
- +
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/96689
- DOI
- 10.1161/STROKEAHA.114.006662
- ISSN
- 0039-2499
- 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.
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