Automated Segmentation and Quantification of White Matter Hyperintensities in Acute Ischemic Stroke Patients with Cerebral Infarction

Abstract

White matter hyperintensities (WMHs) of presumed vascular origin are common in ageing population, especially in patients with acute cerebral infarction and the volume has been reported to be associated with mental impairment and the risk of hemorrhage from antithrombotic agents. WMHs delineation can be computerized to minimize human bias. However, the presence of cerebral infarcts greatly degrades the accuracy of WMHs detection and thus limits the application of computerized delineation to patients with acute cerebral infarction. We propose a computer-assisted segmentation method to depict WMHs in the presence of cerebral infarcts in combined T1-weighted, fluid attenuation inversion recovery, and diffusion-weighted magnetic resonance imaging (MRI). The proposed method detects WMHs by empirical threshold and atlas information, with subtraction of white matter voxels affected by acute infarction. The method was derived using MRI from 25 hemispheres with WMHs only and 13 hemispheres with both WMHs and cerebral infarcts. Similarity index (SI) and correlation were utilized to assess the agreement between the new automated method and a gold standard visually guided semi-automated method done by an expert rater. The proposed WMHs segmentation approach produced average SI, sensitivity and specificity of 83.142±11.742, 84.154±16.086 and 99.988±0.029% with WMHs only and of 68.826±14.036, 74.381±18.473 and 99.956±0.054% with both WMHs and cerebral infarcts in the derivation cohort. The performance of the proposed method with an external validation cohort was also highly consistent with that of the experienced rater.

Serum albumin and beta-amyloid deposition in the human brain

“…We followed the validated automatic procedure reported previously. 33 Briefly, the procedure consisted of 11 steps: spatial coregistration of T1 and FLAIR images; fusion of T1 and FLAIR images; segmentation of T1; attainment of transformation parameters; deformation and obtainment of the white matter mask; obtainment of FLAIR within the white matter mask; intensity normalization of the masked FLAIR; nomination of candidate WMH with a designated threshold; creation of a junction map; and elimination of the junction. There were 2 modifications in the current processing procedure compared to the original study: (1) an optimal threshold of 70 was applied because it was more suitable for our data compared to the threshold of 65 used in the original study; and, (2) given that individuals with acute cerebral infarcts were not enrolled in our sample, we did not use diffusion-weighted imaging in the current automated procedure.…”

Association of carotid and intracranial stenosis with Alzheimer’s disease biomarkers

“…The volume of white matter hyperintensities (WMH) on FLAIR images was calculated using a validated automatic procedure [28] with two modifications, as follows: First, an optimal threshold of 70 instead of 65 in the original reference was applied, as the original study [28] recommended adjustment of the threshold for each study dataset to capture the voxels with WMH better than 65 without including non-WMH voxels. More detailed information on the adjustment of the threshold is described in Methods S2 (Additional file 1).…”

Multiparity, Brain Atrophy, and Cognitive Decline

“…Cerebral WMH volumes were measured using fluid-attenuated inversion recovery (FLAIR) images obtained with the same MRI scanner. We adopted a previously validated automatic procedure (Tsai et al, 2014) with two modifications. First, a threshold value of 70 instead of 65 from the original reference was applied, which was more suitable for our data.…”