Stroke outcomes are worse with larger leukoaraiosis volumes

Ryu, Wi‐Sun; Woo, Sung Ho; Schellingerhout, Dawid; Jang, Min Uk; Park, Kyoung Jong; Hong, Kyung Soon; Jeong, Seonghun; Na, Jeong Yong; Cho, Ki-Hyun; Kim, Joon Tae; Kim, Beom Joon; Han, Moon Ku; Lee, Jun; Kwan, Jae; Kim, Dae Hyun; Lee, Soo Joo; Ko, Young Hwii; Cho, Yong Jin; Lee, Byung Chul; Yu, Kyung Ho; Oh, Mi Sun; Park, Jong‐Moo; Kang, Kyusik; Lee, Kyung Bok; Park, Tai Hwan; Lee, Jun-Young; Choi, Heung Kook; Lee, Ki-Won; Bae, Hee Joon; Kim, Dong Eog

doi:10.1093/brain/aww259

Cited by 98 publications

(99 citation statements)

References 49 publications

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“…All scans were transferred to the Korean Brain MRI Data Center for central data storage and quantitative analysis. As previously reported, [17][18][19] high-signal intensity lesions on DWIs were segmented and registered onto the Montreal Neurological Institute template. The registered binary images for acute infarcts in the ACA, MCA, and PCA group of patients were used to generate voxel-based lesion frequency maps and CI maps, with vascular territories encoded by color on the maps.…”

Section: Mri and Lesion Registration For Brain Mappingmentioning

confidence: 99%

Mapping the Supratentorial Cerebral Arterial Territories Using 1160 Large Artery Infarcts

et al. 2019

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IMPORTANCE Cerebral vascular territories are of key clinical importance in patients with stroke, but available maps are highly variable and based on prior studies with small sample sizes. OBJECTIVE To update and improve the state of knowledge on the supratentorial vascular supply to the brain by using the natural experiment of large artery infarcts and to map out the variable anatomy of the anterior, middle, and posterior cerebral artery (ACA, MCA, and PCA) territories. DESIGN, SETTING, AND PARTICIPANTS In this cross-sectional study, digital maps of supratentorial infarcts were generated using diffusion-weighted magnetic resonance imaging (MRI) of 1160 patients with acute (<1-week) stroke recruited (May 2011 to February 2013) consecutively from 11 Korean stroke centers. All had supratentorial infarction associated with significant stenosis or occlusion of 1 of 3 large supratentorial cerebral arteries but with patent intracranial or extracranial carotid arteries. Data were analyzed between February 2016 and August 2017. MAIN OUTCOMES AND MEASURES The 3 vascular territories were mapped individually by affected vessel, generating 3 data sets for which infarct frequency is defined for each voxel in the data set. By mapping these 3 vascular territories collectively, we generated data sets showing the Certainty Index (CI) to reflect the likelihood of a voxel being a member of a specific vascular territory, calculated as either ACA, MCA, or PCA infarct frequency divided by total infarct frequency in that voxel. RESULTS Of the 1160 patients (mean [SD] age, 67.0 [13.3] years old), 623 were men (53.7%). When the cutoff CI was set as 90%, the volume of the MCA territory (approximately 54% of the supratentorial parenchymal brain volume) was about 4-fold bigger than the volumes of the ACA and PCA territories (each approximately 13%). Quantitative studies showed that the medial frontal gyrus, superior frontal gyrus, and anterior cingulate were involved mostly in ACA infarcts, whereas the middle frontal gyrus and caudate were involved mostly by MCA infarcts. The PCA infarct territory was smaller and narrower than traditionally shown. Border-zone maps could be defined by using either relative infarct frequencies or CI differences. CONCLUSIONS AND RELEVANCE We have generated statistically rigorous maps to delineate territorial border zones and lines. The new topographic brain atlas can be used in clinical care and in research to objectively define the supratentorial arterial territories and their borders.

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Section: Mri and Lesion Registration For Brain Mappingmentioning

confidence: 99%

Mapping the Supratentorial Cerebral Arterial Territories Using 1160 Large Artery Infarcts

et al. 2019

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“…CT analytic software was recently developed that aims to delineate territorial infarcts (30) and acute ischemia (31), or to predict hemorrhagic transformation after ischemic stroke (19). One promising application for WML quantification is treatment selection for acute ischemic stroke because cerebral WML load predicts poor functional outcome (4,5) and intracranial hemorrhagic transformation (7,8). At present, this CT-imaging predictor of poor functional outcome and other predictors (eg, acute ischemia) have not been found to interact with revascularization therapy in their association with intracranial hemorrhage, and therefore are not recommended for treatment stratification (4,32).…”

Section: Ordinal Rating Validationmentioning

confidence: 99%

Rapid Automated Quantification of Cerebral Leukoaraiosis on CT Images: A Multicenter Validation Study

Chen¹,

Jones²,

Mair³

et al. 2018

Radiology

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Purpose To validate a random forest method for segmenting cerebral white matter lesions (WMLs) on computed tomographic (CT) images in a multicenter cohort of patients with acute ischemic stroke, by comparison with fluid-attenuated recovery (FLAIR) magnetic resonance (MR) images and expert consensus. Materials and Methods A retrospective sample of 1082 acute ischemic stroke cases was obtained that was composed of unselected patients who were treated with thrombolysis or who were undergoing contemporaneous MR imaging and CT, and a subset of International Stroke Thrombolysis-3 trial participants. Automated delineations of WML on images were validated relative to experts' manual tracings on CT images, and co-registered FLAIR MR imaging, and ratings were performed by using two conventional ordinal scales. Analyses included correlations between CT and MR imaging volumes, and agreements between automated and expert ratings. Results Automated WML volumes correlated strongly with expert-delineated WML volumes at MR imaging and CT (r = 0.85 and 0.71 respectively; P < .001). Spatial-similarity of automated maps, relative to WML MR imaging, was not significantly different to that of expert WML tracings on CT images. Individual expert WML volumes at CT correlated well with each other (r = 0.85), but varied widely (range, 91% of mean estimate; median estimate, 11 mL; range of estimated ranges, 0.2-68 mL). Agreements (κ) between automated ratings and consensus ratings were 0.60 (Wahlund system) and 0.64 (van Swieten system) compared with agreements between individual pairs of experts of 0.51 and 0.67, respectively, for the two rating systems (P < .01 for Wahlund system comparison of agreements). Accuracy was unaffected by established infarction, acute ischemic changes, or atrophy (P > .05). Automated preprocessing failure rate was 4%; rating errors occurred in a further 4%. Total automated processing time averaged 109 seconds (range, 79-140 seconds). Conclusion An automated method for quantifying CT cerebral white matter lesions achieves a similar accuracy to experts in unselected and multicenter cohorts.

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“…It is estimated that 20-42% of ischemic strokes are of small vessel origin [1], and conversely, patients with stroke have a higher burden of SVD compared to the population at large [2]. In addition, stroke patients with SVD have worse functional and cognitive outcomes [3,4]. Radiologically, SVD is characterized by white matter hyperintensities (WMH), lacunar infarctions, cerebral atrophy, cerebral microbleeds, and enlarged perivascular spaces [5].…”

Section: Introductionmentioning

confidence: 99%

“…Angiogram generated from PC-VIPR complex difference image. Cerebral arterial pulsatility was measured in the cavernous segment of the internal carotid arteries(1,2) and in the M1-(3,4) and M3(5,6) segments of the middle cerebral arteries…”

mentioning

confidence: 99%

Cerebral arterial pulsatility is associated with features of small vessel disease in patients with acute stroke and TIA: a 4D flow MRI study

et al. 2019

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Cerebral small vessel disease (SVD) is a major cause of stroke and cognitive impairment. However, the underlying mechanisms behind SVD are still poorly understood. High cerebral arterial pulsatility has been suggested as a possible cause of SVD. In population studies, arterial pulsatility has been linked to white matter hyperintensities (WMH), cerebral atrophy, and cognitive impairment, all features of SVD. In stroke, pulsatility data are scarce and contradictory. The aim of this study was to investigate the relationship between arterial pulsatility and SVD in stroke patients. With a cross-sectional design, 89 patients with acute ischemic stroke or TIA were examined with MRI. A neuropsychological assessment was performed 1 year later. Using 4D flow MRI, pulsatile indices (PI) were calculated for the internal carotid artery (ICA) and middle cerebral artery (M1, M3). Flow volume pulsatility (FVP), a measure corresponding to the cyclic expansion of the arterial tree, was calculated for the same locations. These parameters were assessed for associations with WMH volume, brain volume and cognitive function. ICA-FVP was associated with WMH volume (β = 1.67, 95% CI: [0.1, 3.24], p = 0.037). M1-PI and M1-FVP were associated with decreasing cognitive function (β = − 4.4, 95% CI: [− 7.7, − 1.1], p = 0.009 and β = − 13.15, 95% CI: [− 24.26, − 2.04], p = 0.02 respectively). In summary, this supports an association between arterial pulsatility and SVD in stroke patients, and provides a potential target for further research and preventative treatment. FVP may become a useful biomarker for assessing pulsatile stress with PCMRI and 4D flow MRI.

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Stroke outcomes are worse with larger leukoaraiosis volumes

Cited by 98 publications

References 49 publications

Mapping the Supratentorial Cerebral Arterial Territories Using 1160 Large Artery Infarcts

Mapping the Supratentorial Cerebral Arterial Territories Using 1160 Large Artery Infarcts

Rapid Automated Quantification of Cerebral Leukoaraiosis on CT Images: A Multicenter Validation Study

Cerebral arterial pulsatility is associated with features of small vessel disease in patients with acute stroke and TIA: a 4D flow MRI study

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