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The Hypoxic Ischemic Encephalopathy Model of Perinatal Ischemia
Published on: November 19, 2008
3-Dimensional quantification of ischemic brain injury in post-cardiac arrest patients with hypoxic-ischemic brain
Gaurav Ambwani1, Connor A Larkey2, Warda Limaye3
1Department of Cellular and Physiological Sciences, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Introduction:
Brain tissue hypoxia and ischemia are central to the pathophysiology of hypoxic-ischemic brain injury (HIBI). Magnetic resonance imaging (MRI) techniques including diffusion-weighted imaging (DWI) and associated apparent diffusion coefficient (ADC) maps offer a non-invasive method for identifying ischemic tissue, but their use is often limited to the provision of summary data. We developed a reproducible, semi-automated analysis pipeline to three-dimensionally quantify and anatomically localize ischemic brain injury using DWI-ADC data in HIBI patients.
Methods:
A retrospective cohort of post-cardiac arrest patients with HIBI (n = 10) was included. MRI preprocessing included skull stripping, spatial normalization to MNI152 space, and anatomical parcellation using FreeSurfer atlases. Ischemic regions were defined by an ADC threshold (<650e-6 mm2/s), and lesion burden was computed voxel-wise by segment, hemisphere, and tissue type. Susceptibility-weighted imaging (SWI) hypointensities were also quantified.
Results:
Ischemic injury was spatially heterogeneous but consistently affected the putamen, thalamus, and posterior cortical regions (e.g., pericalcarine and perirolandic cortices). The overall mean relative lesion volume was 28.4 ± 14.1% of total brain volume, with greater involvement in white matter (33.3 ± 17.8%) than gray matter (24.1 ± 11.4%; P = 0.005). Overlap of SWI and ADC hypointensities was minimal (<1% of all voxels), indicating negligible confounding by intraparenchymal blood.
Discussion:
We present a robust, observer-independent workflow for anatomically resolved quantification of ischemic injury in HIBI. Atlas-based segmentation integrated with voxel-intensity ADC analysis, enabled generation of granular data on the pattern and extent of ischemic brain injury following cardiac arrest.
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