Abstract TMP96: Automated Segmentation of White Matter Hyperintensities and Enlarged Perivascular Spaces in a Cohort of Patients With Acute Ischemic Stroke or Transient Ischemic Attack

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Kimerly A Powell ◽  
Katie M Gallagher ◽  
Yousef Hannawi

Introduction: Cerebral Small Vessel Disease (CSVD) is a major cause of acute ischemic stroke (AIS), intracerebral hemorrhage and cognitive impairment. Methods to quantify the disease burden have been largely limited to white matter hyperintensities (WMH) as the disease surrogate and focused mainly on MRI sequences acquired for research purposes. We develop here novel methods to quantify WMH and enlarged perivascular spaces (EPVs) based on clinically acquired MRI sequences in patients with transient ischemic attack (TIA) or AIS. Methods: Subjects presenting with TIA or AIS and had brain MRI within 24 hour of hospital admission were selected for this study. Preprocessing pipeline was developed locally that included bias correction, image rescaling, rigid body registration to the Montreal Neurological Institute (MNI) space, skull stripping and intensity normalization. WMH segmentation was performed using a combination of global thresholding of FLAIR sequences that was spatially restricted to the white matter regions which were defined using a population-based atlas of age matched controls. EPVs in the basal ganglia were segmented on T2 sequences using adaptive thresholding of basal ganglia mask that was created from the ICBM template image and age-matched population average atlas. Segmented objects less than 3 mm in diameter were labelled as EPVs. Validation of the accuracy of EPVs segmentation was performed by expert counting of EPVs and WMH was validated using volume similarity against expert manual segmentation of WMH. Results: 41 patients (age 61.2±16.1, 65% males, 19.5% had TIAs, and 79.5% had AIS) were included. WMH volume was (manual: 21.34±20.48 mls vs automated: 15.74±14.56 mls) achieving a volume similarity of 0.92±0.01. EPVs in the basal ganglia counts were 16.32±5.4 using the automated method. Validation through comparison with manual segmentation of the axial slice with the highest EPVs (Doubal Method) showed significant correlation (Spearman’s rho=0.53, P = 0.0004). Conclusions: We describe successful segmentation of WMH and EPVs on clinically acquired MRI sequences in patients with TIA or AIS. This method will have applications to quantify CSVD burden in large clinical trials and clinical practice.

2018 ◽  
Vol 40 (12) ◽  
pp. 2041-2049
Author(s):  
Huai Wu Yuan ◽  
Ren Jie Ji ◽  
Ya Jie Lin ◽  
Han Feng Chen ◽  
Guo Ping Peng ◽  
...  

2021 ◽  
pp. jim-2020-001675
Author(s):  
Jian-Feng Qu ◽  
Huo-Hua Zhong ◽  
Wen-Cong Liang ◽  
Yang-Kun Chen ◽  
Yong-Lin Liu ◽  
...  

The aim of the present study was to determine the neuroimaging predictors of poor participation after acute ischemic stroke. A total of 443 patients who had acute ischemic stroke were assessed. At 1-year recovery, the Reintegration to Normal Living Index was used to assess participation restriction. We also assessed the Activities of Daily Living Scale and modified Rankin Scale (mRS) score. Brain MRI measurement included acute infarcts and pre-existing abnormalities such as enlarged perivascular spaces, white matter lesions, ventricular-brain ratio, and medial temporal lobe atrophy (MTLA). The study included 324 men (73.1%) and 119 women (26.9%). In the univariate analysis, patients with poor participation after 1 year were older, more likely to be men, had higher National Institutes of Health Stroke Scale (NIHSS) score on admission, with more histories of hypertension and atrial fibrillation, larger infarct volume, more severely enlarged perivascular spaces and MTLA, and more severe periventricular hyperintensities and deep white matter hyperintensities. Patients with participation restriction also had poor activities of daily living (ADL) and mRS score. Multiple logistic regression showed that, in model 1, age, male gender, NIHSS score on admission, and ADL on follow-up were significant predictors of poor participation, accounting for 60.2% of the variance. In model 2, which included both clinical and MRI variables, male gender, NIHSS score on admission, ADL on follow-up, and MTLA were significant predictors of poor participation, accounting for 61.2% of the variance. Participation restriction was common after acute ischemic stroke despite good mRS score. Male gender, stroke severity, severity of ADL on follow-up, and MTLA may be predictors of poor participation.Trial registration number ChiCTR1800016665.


Stroke ◽  
2018 ◽  
Vol 49 (Suppl_1) ◽  
Author(s):  
Liseth Lavado ◽  
Salma Yousuf ◽  
Bakhtiar Rasul ◽  
Shyam Patel ◽  
Gull Mahvish ◽  
...  

2019 ◽  
Vol 76 (8) ◽  
pp. 932 ◽  
Author(s):  
M. Julia Machline-Carrion ◽  
Eliana Vieira Santucci ◽  
Lucas Petri Damiani ◽  
M. Cecilia Bahit ◽  
Germán Málaga ◽  
...  

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