White Matter Hyperintensity Quantification in Large-Scale Clinical Acute Ischemic Stroke Cohorts – The MRI-GENIE Study

AbstractWhite matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery.In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95) and Pearson correlation of total brain volume (r=0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N=2783) and identify a decrease in total brain volume of -2.4cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing.Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2,533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.

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

Stroke ◽

10.1161/str.48.suppl_1.wp205 ◽

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.

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

Cerebrovascular Diseases ◽

10.1159/000509071 ◽

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.

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

NeuroImage Clinical ◽

10.1016/j.nicl.2019.101884 ◽

2019 ◽

Vol 23 ◽

pp. 101884 ◽

Cited By ~ 11

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

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Cognition, structural brain changes and complicated grief. A population-based study

Psychological Medicine ◽

10.1017/s0033291714002499 ◽

2014 ◽

Vol 45 (7) ◽

pp. 1389-1399 ◽

Cited By ~ 20

Author(s):

H. C. Saavedra Pérez ◽

M. A. Ikram ◽

N. Direk ◽

H. G. Prigerson ◽

R. Freak-Poli ◽

...

Keyword(s):

White Matter ◽

Brain Volume ◽

Complicated Grief ◽

Population Based ◽

Word Fluency ◽

Total Brain Volume ◽

Population Based Study ◽

Total Brain ◽

Fluency Task ◽

Structural Brain

BackgroundSeveral psychosocial risk factors for complicated grief have been described. However, the association of complicated grief with cognitive and biological risk factors is unclear. The present study examined whether complicated grief and normal grief are related to cognitive performance or structural brain volumes in a large population-based study.MethodThe present research comprised cross-sectional analyses embedded in the Rotterdam Study. The study included 5501 non-demented persons. Participants were classified as experiencing no grief (n = 4731), normal grief (n = 615) or complicated grief (n = 155) as assessed with the Inventory of Complicated Grief. All persons underwent cognitive testing (Mini-Mental State Examination, Letter–Digit Substitution Test, Stroop Test, Word Fluency Task, word learning test – immediate and delayed recall), and magnetic resonance imaging to measure general brain parameters (white matter, gray matter), and white matter lesions. Total brain volume was defined as the sum of gray matter plus normal white matter and white matter lesion volume. Persons with depressive disorders were excluded and analyses were adjusted for depressive symptoms.ResultsCompared with no-grief participants, participants with complicated grief had lower scores for the Letter–Digit Substitution Test [Z-score −0.16 v. 0.04, 95% confidence interval (CI) −0.36 to −0.04, p = 0.01] and Word Fluency Task (Z-score −0.15 v. 0.03, 95% CI −0.35 to −0.02, p = 0.02) and smaller total volumes of brain matter (933.53 ml v. 952.42 ml, 95% CI −37.6 to −0.10, p = 0.04).ConclusionsParticipants with complicated grief performed poorly in cognitive tests and had a smaller total brain volume. Although the effect sizes were small, these findings suggest that there may be a neurological correlate of complicated grief, but not of normal grief, in the general population.

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

Stroke ◽

10.1161/str.51.suppl_1.tp476 ◽

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.

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

Stroke ◽

10.1161/str.52.suppl_1.mp16 ◽

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.

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

PLoS ONE ◽

10.1371/journal.pone.0144431 ◽

2015 ◽

Vol 10 (12) ◽

pp. e0144431 ◽

Cited By ~ 8

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

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Atrial Fibrillation and Brain Magnetic Resonance Imaging Abnormalities

Stroke ◽

10.1161/strokeaha.118.024143 ◽

2019 ◽

Vol 50 (4) ◽

pp. 783-788 ◽

Cited By ~ 6

Author(s):

Jeremy P. Berman ◽

Faye L. Norby ◽

Thomas Mosley ◽

Elsayed Z. Soliman ◽

Rebecca F. Gottesman ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Brain Volume ◽

Brain Mri ◽

Brain Magnetic Resonance Imaging ◽

White Matter Hyperintensity ◽

Resonance Imaging ◽

Total Brain Volume ◽

Cross Sectional ◽

Total Brain ◽

Sectional Analysis

Background and Purpose— Atrial fibrillation (AF) is associated with dementia independent of clinical stroke. The mechanisms underlying this association remain unclear. In a community-based cohort, the ARIC study (Atherosclerosis Risk in Communities), we evaluated (1) the longitudinal association of incident AF and (2) the cross-sectional association of prevalent AF with brain magnetic resonance imaging (MRI) abnormalities. Methods— The longitudinal analysis included 963 participants (mean age, 73±4.4 years; 62% women; 51% black) without prevalent stroke or AF who underwent a brain MRI in 1993 to 1995 and a second MRI in 2004 to 2006 (mean, 10.6±0.8 years). Outcomes included subclinical cerebral infarctions, sulcal size, ventricular size, and, for the cross-sectional analysis, white matter hyperintensity volume and total brain volume. Results— In the longitudinal analysis, 29 (3.0%) participants developed AF after the first brain MRI. Those who developed AF had higher odds of increase in subclinical cerebral infarctions (odds ratio [OR], 3.08; 95% CI, 1.39–6.83), worsening sulcal grade (OR, 3.56; 95% CI, 1.04–12.2), and worsening ventricular grade (OR, 9.34; 95% CI, 1.24–70.2). In cross-sectional analysis, of 969 participants, 35 (3.6%) had prevalent AF at the time of the 2004 to 2006 MRI scan. Those with AF had greater odds of higher sulcal (OR, 3.9; 95% CI, 1.7–9.1) and ventricular grade (OR, 2.4; 95% CI, 1.0–5.7) after multivariable adjustment and no difference in white matter hyperintensity or total brain volume. Conclusions— AF is independently associated with increase in subclinical cerebral infarction and worsening sulcal and ventricular grade—morphological changes associated with aging and dementia. More research is needed to define the mechanisms underlying AF-related neurodegeneration.

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Age-specific adult rat brain MRI templates and tissue probability maps

10.31219/osf.io/htgqn ◽

2021 ◽

Cited By ~ 1

Author(s):

Eilidh MacNicol ◽

Paul Wright ◽

Eugene Kim ◽

Irene Brusini ◽

Oscar Esteban ◽

...

Keyword(s):

White Matter ◽

Rat Brain ◽

Grey Matter ◽

Brain Volume ◽

Grey Matter Volume ◽

Total Brain Volume ◽

Adult Rat ◽

Matter Volume ◽

Probability Maps ◽

Total Brain

Age-specific resources mitigate biases in human MRI processing arising from structural changes across the lifespan. There are fewer age-specific resources for preclinical imaging, and they only represent developmental periods rather than adulthood. Since rats recapitulate many facets of human aging, it was hypothesized that brain volume and each tissue’s relative contribution to total brain volume would change with age in the adult rat. However, the currently available tissue probability maps, which provide a priori information for tissue volume estimation, provide inaccurate grey matter probabilities in subcortical structures, particularly the thalamus. Consequently, age-specific templates and tissue probability maps were generated from a longitudinal study that scanned a cohort of rats at 3, 5, 11, and 17 months old. Mixed-effects models assessed the effect of age on brain, grey matter, white matter, and CSF volumes, and the relative tissue proportions. Grey and white matter volume increased with age, and the tissue proportions relative to total brain volume varied throughout adulthood. Furthermore, we present evidence of a systematic underestimation of thalamic grey matter volume with existing resources, which is mitigated with the use of age-specific tissue probability maps since the derived estimates better matched histological evidence. To reduce age-related biases in image pre-processing, a set of rat brain resources from across the adult lifespan is consequently released to expand the preclinical MRI community’s fundamental resources.

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Abstract 28: Genetic Variants From Lysine-Specific Demethylase 4C (KDM4C) Associated With White Matter Hyperintensity Burden in Ischemic Stroke Patients

Stroke ◽

10.1161/str.51.suppl_1.28 ◽

2020 ◽

Vol 51 (Suppl_1) ◽

Author(s):

Jiang Li ◽

Vida Abedi ◽

Anne-Karin Giese ◽

Markus D Schirmer ◽

Kathleen Donahue ◽

...

Keyword(s):

Ischemic Stroke ◽

White Matter ◽

Genetic Variants ◽

Genome Wide Association Study ◽

European Ancestry ◽

White Matter Hyperintensity ◽

Significance Level ◽

Brain Extraction ◽

Lysine Specific Demethylase ◽

A Genome

Introduction: Although white matter hyperintensities (WMH) have been linked to cerebrovascular disease, the exact pathogenesis is not known. The purpose of this study was to identify common variants associated with WMH burden among patients with an acute ischemic stroke (AIS) through a genome-wide association study (GWAS). Methods: A total of 946 AIS patients with validated European ancestry and MRI data were included in this study. WMH volume (WMHv), as a quantitative trait, was calculated by a fully-automated quantification process, which integrates the automated brain extraction, intensity normalization, and WMH segmentation using spatial priors. The GWAS was carried out by a linear mixed regression model (GEMMA), adjusted for covariates, to account for the potential population structure and relatedness. The WMHv ranked in top and bottom quantile were converted to a binary trait which represent high and low WMHv subgroups. Results: The rs10815506 (MAF = 0.043; β=3.89; p=6.66E-09), at an intronic region of KDM4C , which encodes Lysine-specific demethylase 4C , was the top signal associated with WMHv. This SNP is in high linkage disequilibrium (LD) (R 2 = 0.79; D’ = 0.93) with rs35389625, a nonsynonymous variant (Asn>Ser), predicted to be pathogenic by SIFT and Polyphen. The rs35389625 was also associated with WMHv but at a lower significance level (MAF=0.040; β=3.19; p=3.21E-06). Patients with homozygous mutant alleles (GG) of rs35389625 showed significantly increased WMHv (14.93±10.15) than GA (7.94±8.48) and AA (5.09±5.85) carriers. Both rs10815506 and rs35389625 also predicted a subset of high and low WMHv group (OR=2.81, p=0.005; OR=2.42, p=0.016, respectively). No significant interaction between the top SNPs at KDM4C and other risk factors was identified in their association with WMHv. We also conducted a candidate-gene analysis by including several known SNPs, gathered from a reported meta-analysis for WMH. The frequency of MTHFR677 cytosine/thymine (rs1801133) showed difference between lower and upper quantile groups with OR=2.18 for T allele (p=0.030), the direction of which was consistent with previous studies. Conclusion: This study provides the first evidence that genetic variants at KDM4C are associated with WMH in AIS patients.

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