Association of deep white matter hyperintensity with left ventricular hypertrophy in acute ischemic stroke

2021 ◽  
Author(s):  
Nandakumar Nagaraja ◽  
Amreen Farooqui ◽  
Mehmet S. Albayram
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Left Ventricular Hypertrophy ◽  
Acute Ischemic Stroke ◽  
Ventricular Hypertrophy ◽  
Left Ventricular ◽  
White Matter Hyperintensity ◽  
Deep White Matter

Abstract TP476: White Matter Hyperintensity Burden is Associated With Poor Collateral Flow and Worse Outcomes in an Acute Ischemic Stroke Cohort

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Rami-James Assadi ◽  
Hongyu An ◽  
Yasheng Chen ◽  
Andria Ford ◽  
Jin-Moo Lee
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Pearson Correlation ◽  
Stroke Onset ◽  
White Matter Hyperintensity ◽  
Flow Index ◽  
Acute Ischemia ◽  
Collateral Flow ◽  
Core Volume

Introduction: White matter hyperintensity volume (WMHv), a quantitative neuroimaging biomarker of cerebral small vessel disease (CSVD), is associated worse outcomes after ischemic stroke. In this study, we hypothesized that worse outcomes in CSVD patients were due to poor collateral flow during acute ischemia. Methods: 47 patients with acute ischemic stroke (AIS) were prospectively enrolled in this study. Serial MRIs were performed at 3 hours and 30 days after stroke onset. 3-hour FLAIR images were used to determine WMHv, after manually delineating lesions with MIPAV. An index of collateral flow (delayed perfusion to the penumbra) was determined by subtracting core volume (volume of tissue with ADC<600) from the volume of brain tissue with Tmax>2. Patient’s NIHSS was scored at 3 hours and 30 days after stroke onset and the difference was calculated (ΔNIHSS). Log-transformed WMHv was correlated to ΔNIHSS and the collateral flow index, using Pearson correlation. Results: Mean age = 63.9 years (SD 13.5); 37% female; median 3-hour NIHSS = 13 (IQR 6.5-20); median change in NIHSS between 3h and 30d = 4 (IQR: 0-7); median core volume = 13cm3 (IQR 4.3-35.6); median WMHv = 1.257cm3 (IQR 641-3595). WMHv was associated with reduced improvement in ΔNIHSS (R=-0.42, ρ=0.005). Furthermore, WMHv demonstrated a trend for association with poor collateral flow (R=-0.28, ρ=0.062). In this dataset, we will explore the relationship between WMHv and other tissue-based metrics of collateral flow, including the hypoperfusion intensity ratio (HIR) and the cerebral blood volume ratio (rCBV). Conclusions: Our study confirms that patients with CSVD have worse outcomes after AIS. The data also raise the possibility that these worse outcomes in CSVD patients may be mediated by compromised collateral flow in the setting of acute ischemia.

Abstract MP16: Excessive White Matter Hyperintensity Burden and Functional Outcomes After Acute Ischemic Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Sungmin Hong ◽  
Anne-katrin Giese ◽  
Markus D Schirmer ◽  
Adrian V Dalca ◽  
Anna Bonkhoff ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Functional Outcomes ◽  
Life Time ◽  
Stroke Recovery ◽  
White Matter Hyperintensity ◽  
Brain Health ◽  
Stroke Outcomes ◽  
The Brain

Objective: Ability of the brain to recover after an acute ischemic stroke (AIS) is linked to the pre-stroke burden of white matter hyperintensity (WMH), a radiographic marker of brain health. We sought to determine the excessive WMH burden in an AIS population and investigate its association with 3-month stroke outcomes. Data: We used 2,435 subjects from the MRI-GENIE study. Three-month functional outcomes of 872 subjects among those subjects were measured by 90-day modified Ranking Scale (mRS). Methods: We automatically quantified WMH volume (WMHv) on FLAIR images and adjusted for a brain volume. We modeled a trend using the factor analysis (FA) log-linear regression using age, sex, atrial fibrillation, diabetes, hypertension, coronary artery disease and smoking as input variables. We categorized three WMH burden groups based on the conditional probability given by the model (LOW: lower 33%, MED: middle 34%, and HIGH: upper 33%). The subgroups were compared with respect to mRS (median and dichotomized odds ratio (OR) (good/poor: mRS 0-2/3-6)). Results: Five FA components out of seven with significant relationship to WMHv (p<0.001) were used for the regression modeling (R 2 =0.359). The HIGH group showed higher median (median=2, IQR=2) mRS score than LOW (median=1, IQR=1) and MED (median=1, IQR=1). The odds (OR) of good AIS outcome for LOW and MED were 1.8 (p=0.0001) and 1.6 (p=0.006) times higher than HIGH, respectively. Conclusion: Once accounted for clinical covariates, the excessive WMHv was associated with worse 3-month stroke outcomes. These data suggest that a life-time of injury to the white matter reflected in WMH is an important factor for stroke recovery and an indicator of the brain health.

scholarly journals Homocysteine Level Is Associated with White Matter Hyperintensity Locations in Patients with Acute Ischemic Stroke

PLoS ONE ◽  
2015 ◽  
Vol 10 (12) ◽  
pp. e0144431 ◽  
Author(s):  
Yuan Gao ◽  
Sen Wei ◽  
Bo Song ◽  
Jie Qin ◽  
Hui Fang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Homocysteine Level ◽  
White Matter Hyperintensity

Abstract WP205: Pipeline for Automated White Matter Hyperintensity Segmentation in Patients With Acute Ischemic Stroke: The MRI-GENIE Study

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Markus D Schirmer ◽  
Adrian V Dalca ◽  
Ramesh Sridharan ◽  
Anne-Katrin Giese ◽  
Joseph P Broderick ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Large Scale ◽  
Current Knowledge ◽  
Principal Component ◽  
White Matter Hyperintensity ◽  
Brain Extraction ◽  
Fluid Attenuated Inversion Recovery ◽  
Good Agreement

Introduction: White matter hyperintensity volume (WMHv) is an important and highly heritable cerebrovascular phenotype; however, manual or semi-automated approaches to clinically acquired MRI analysis hinder large-scale studies in acute ischemic stroke (AIS). In this work, we develop a high-throughput, fully automated WMHv analysis pipeline for clinical fluid-attenuated inversion recovery (FLAIR) images to facilitate rapid genetic discovery in AIS. Methods: Automated WMHv extraction from multiple subjects relies on significant pre-processing of medical scans, including co-registration of the images. To reduce the effects of anisotropic voxel sizes, each FLAIR image is upsampled using bi-cubic interpolation. Brain extraction is performed using RObust Brain EXtraction (ROBEX). Images are then registered to an in-house FLAIR template using Advanced Normalization Tools (ANTs). The spatial covariation of WMH is learned through principal component analysis (PCA) of manual outlines from 100 subjects. Areas of leukoaraiosis are identified and separated from other lesions using the PCA modes. Volumes are then computed using non-interpolated slices for each subject. Standard deviation (SD) in WMHv (9 subjects; 6 raters each) is calculated as a measure of variability. Good agreement between automated and manual outlines is assessed in 358 subjects (automated WMHv within 3SD of manual WMHv). Results: As part of the MRI - Gen etics I nterface E xploration (MRI-GENIE) study, WMHv were calculated on a set of 2703 FLAIR images of patients from 12 independent AIS cohorts (sites). Results are shown in Figure 1. Comparing manual and automated WMHv shows that 88% of the automated WMHv fall within 3 SD from the manual WMHv, suggesting good agreement. Conclusion: WMHv segmentation using a fully-automated pipeline for analysis of clinical MRIs is both feasible and accurate. Ongoing analysis of the extracted WMHv is expected to advance current knowledge of risks and outcomes in AIS.

scholarly journals Effects of White Matter Hyperintensities on 90-Day Functional Outcome after Large Vessel and Non-Large Vessel Stroke

2020 ◽  
Vol 49 (4) ◽  
pp. 419-426
Author(s):  
Christoph Johannes Griessenauer ◽  
David McPherson ◽  
Andrea Berger ◽  
Ping Cuiper ◽  
Nelson Sofoluke ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Brain Mri ◽  
Large Vessel ◽  
Favorable Outcome ◽  
White Matter Hyperintensity ◽  
Vessel Occlusion ◽  
Brain Extraction

Introduction: White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype related to the diagnosis and prognosis of acute ischemic stroke. The effect of WMH burden on functional outcome in large vessel occlusion (LVO) stroke has only been sparsely assessed, and direct LVO and non-LVO comparisons are currently lacking. Material and Methods: We reviewed acute ischemic stroke patients admitted between 2009 and 2017 at a large healthcare system in the USA. Patients with LVO were identified and clinical characteristics, including 90-day functional outcomes, were assessed. Clinical brain MRIs obtained at the time of the stroke underwent quantification of WMH using a fully automated algorithm. The pipeline incorporated automated brain extraction, intensity normalization, and WMH segmentation. Results: A total of 1,601 acute ischemic strokes with documented 90-day mRS were identified, including 353 (22%) with LVO. Among those strokes, WMH volume was available in 1,285 (80.3%) who had a brain MRI suitable for WMH quantification. Increasing WMH volume from 0 to 4 mL, age, female gender, a number of stroke risk factors, presence of LVO, and higher NIHSS at presentation all decreased the odds for a favorable outcome. Increasing WMH above 4 mL, however, was not associated with decreasing odds of favorable outcome. While WMH volume was associated with functional outcome in non-LVO stroke (p = 0.0009), this association between WMH and functional status was not statistically significant in the complete case multivariable model of LVO stroke (p = 0.0637). Conclusion: The burden of WMH has effects on 90-day functional outcome after LVO and non-LVO strokes. Particularly, increases from no measurable WMH to 4 mL of WMH correlate strongly with the outcome. Whether this relationship of increasing WMH to worse outcome is more pronounced in non-LVO than LVO strokes deserves additional investigation.

scholarly journals White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts – The MRI-GENIE study

2019 ◽  
Vol 23 ◽  
pp. 101884 ◽  
Author(s):  
Markus D. Schirmer ◽  
Adrian V. Dalca ◽  
Ramesh Sridharan ◽  
Anne-Katrin Giese ◽  
Kathleen L. Donahue ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Large Scale ◽  
White Matter Hyperintensity

Abstract P317: White Matter Hyperintensity Lesion Burden Modulates Functional Outcome After Acute Ischemic Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Anna K Bonkhoff ◽  
Sungmin Hong ◽  
Markus Schirmer ◽  
Martin Bretzner ◽  
Anne-Katrin Giese ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
White Matter Hyperintensity ◽  
Study Cohort ◽  
Stroke Severity ◽  
Ischemic Lesion ◽  
Long Term Outcome ◽  
Index Stroke

Introduction: As a radiographic signature of end-stage small vessel disease, white matter hyperintensity (WMH) burden impacts recovery and outcomes after acute ischemic stroke (AIS). In this study, we sought to investigate the effect of WMH volume (WMHv) on stroke severity and functional outcomes independent of the infarct size and topography. Methods: We analyzed 503 AIS patients with MRI data obtained on admission for index stroke enrolled in the multi-center MRI-GENIE study (cohort 1), followed by validation of the findings in an independent single-site study of 555 AIS patients (cohort 2). Stroke severity (NIHSS score) at index stroke and the long-term outcome (3-6 months mRS score) were modeled via Bayesian linear regression. Models included WMHv, age, sex, a 10-dimensional spatial ischemic lesion representation, acute infarct (DWI) volume, and common vascular risk factors (hypertension, diabetes mellitus, atrial fibrillation, coronary artery disease). Results: Cohorts did not differ significantly in major clinical characteristics [cohort 1: age: 65.0±14.6, 41% female, NIHSS: 5.5±5.4, mRS: 1(iqr 2); cohort 2: age: 65.0±14.8, 38% female, NIHSS: 5.0±6.0, mRS: 1(iqr 3), p >0.05 for all comparisons]. WMHv did not substantially affect AIS severity ( Fig A ); in contrast, it emerged as an independent predictor of functional outcome in both datasets ( Fig B ). Conclusions: When accounted for AIS lesion topography and stroke volume, total WMH lesion burden did not appear to modulate initial stroke severity but was associated with worse functional post-stroke outcomes. Future studies are needed to explore potential origins of these detrimental effects of pre-existing WMH burden on recovery after AIS.

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