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

Abstract

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.