Grading and interpretation of white matter hyperintensities using statistical maps

Wi Sun Ryu, Sung Ho Woo, Dawid Schellingerhout, Moo K. Chung, Chi Kyung Kim, Min Uk Jang, Kyoung Jong Park, Keun Sik Hong, Sang Wuk Jeong, Jeong Yong Na, Ki Hyun Cho, Joon Tae Kim, Beom Joon Kim, Moon Ku Han, Jun Lee, Jae Kwan Cha, Dae Hyun Kim, Soo Joo Lee, Youngchai Ko, Yong Jin ChoByung Chul Lee, Kyung Ho Yu, Mi Sun Oh, Jong Moo Park, Kyusik Kang, Kyung Bok Lee, Tai Hwan Park, Juneyoung Lee, Heung Kook Choi, Kiwon Lee, Hee Joon Bae, Dong Eog Kim

Research output: Contribution to journalArticle

21 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)3567-3575
Number of pages9
JournalStroke
Volume45
Issue number12
DOIs
Publication statusPublished - 2014 Jan 1

Fingerprint

Stroke
Left Ventricular Hypertrophy
Hypertension
White Matter
Atrial Fibrillation
Diabetes Mellitus
Brain
Hyperlipidemias
Libraries
Cholesterol
Datasets

Keywords

  • Cerebral infarction
  • Leukoaraiosis
  • Magnetic resonance imaging
  • Topographic brain mapping

ASJC Scopus subject areas

  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine
  • Advanced and Specialised Nursing

Cite this

Ryu, W. S., Woo, S. H., Schellingerhout, D., Chung, M. K., Kim, C. K., Jang, M. U., ... Kim, D. E. (2014). Grading and interpretation of white matter hyperintensities using statistical maps. Stroke, 45(12), 3567-3575. https://doi.org/10.1161/STROKEAHA.114.006662

Grading and interpretation of white matter hyperintensities using statistical maps. / 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.

In: Stroke, Vol. 45, No. 12, 01.01.2014, p. 3567-3575.

Research output: Contribution to journalArticle

Ryu, WS, Woo, SH, Schellingerhout, D, Chung, MK, Kim, CK, Jang, MU, Park, KJ, Hong, KS, Jeong, SW, Na, JY, Cho, KH, Kim, JT, Kim, BJ, Han, MK, Lee, J, Cha, JK, Kim, DH, Lee, SJ, Ko, Y, Cho, YJ, Lee, BC, Yu, KH, Oh, MS, Park, JM, Kang, K, Lee, KB, Park, TH, Lee, J, Choi, HK, Lee, K, Bae, HJ & Kim, DE 2014, 'Grading and interpretation of white matter hyperintensities using statistical maps', Stroke, vol. 45, no. 12, pp. 3567-3575. https://doi.org/10.1161/STROKEAHA.114.006662
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. / Grading and interpretation of white matter hyperintensities using statistical maps. In: Stroke. 2014 ; Vol. 45, No. 12. pp. 3567-3575.
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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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T1 - Grading and interpretation of white matter hyperintensities using statistical maps

AU - Ryu, Wi Sun

AU - Woo, Sung Ho

AU - Schellingerhout, Dawid

AU - Chung, Moo K.

AU - Kim, Chi Kyung

AU - Jang, Min Uk

AU - Park, Kyoung Jong

AU - Hong, Keun Sik

AU - Jeong, Sang Wuk

AU - Na, Jeong Yong

AU - Cho, Ki Hyun

AU - Kim, Joon Tae

AU - Kim, Beom Joon

AU - Han, Moon Ku

AU - Lee, Jun

AU - Cha, Jae Kwan

AU - Kim, Dae Hyun

AU - Lee, Soo Joo

AU - Ko, Youngchai

AU - Cho, Yong Jin

AU - Lee, Byung Chul

AU - Yu, Kyung Ho

AU - Oh, Mi Sun

AU - Park, Jong Moo

AU - Kang, Kyusik

AU - Lee, Kyung Bok

AU - Park, Tai Hwan

AU - Lee, Juneyoung

AU - Choi, Heung Kook

AU - Lee, Kiwon

AU - Bae, Hee Joon

AU - Kim, Dong Eog

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N2 - 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.

AB - 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.

KW - Cerebral infarction

KW - Leukoaraiosis

KW - Magnetic resonance imaging

KW - Topographic brain mapping

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