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Updated: Aug 9, 2026

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A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Ischemic thresholds for gray and white matter: a diffusion and perfusion magnetic resonance study
Shuji Arakawa1, Peter M Wright, Masatoshi Koga
1National Stroke Research Institute, Heidelberg Heights, Victoria, 3084, Australia.
Stroke
|April 1, 2006
Summary
Gray matter (GM) has a higher infarction threshold than white matter (WM) in acute ischemic stroke patients. Tissue-specific thresholds improve prediction of stroke infarction likelihood for targeted therapies.
Area of Science:
- Neuroscience
- Radiology
- Stroke Research
Background:
- Animal models suggest differing neurochemical responses to ischemia between gray matter (GM) and white matter (WM).
- It remains unclear if these differences translate to distinct infarction thresholds in human ischemic stroke.
Purpose of the Study:
- To investigate whether gray matter (GM) and white matter (WM) exhibit different infarction thresholds in patients with acute ischemic stroke.
- To utilize magnetic resonance (MR) techniques to assess tissue-specific diffusion and perfusion parameters.
Main Methods:
- Magnetic resonance (MR) imaging was conducted on patients within 24 hours of acute hemispheric ischemic stroke.
- Calculated parameters included cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and apparent diffusion coefficient (ADC).
- Tissue-specific infarction thresholds were determined for GM and WM using probabilistic segmentation.
Main Results:
- Infarction thresholds for CBF were significantly higher in GM compared to WM (P<0.0001).
- GM also demonstrated significantly higher thresholds for CBV (P<0.0001) and ADC (P<0.001) than WM.
- A trend towards shorter MTT was observed in GM compared to WM (P=0.11).
Conclusions:
- Gray matter (GM) exhibits a higher infarction threshold for CBF, CBV, and ADC than white matter (WM) in acute ischemic stroke.
- Tissue-specific thresholds, rather than whole-brain values, offer a more precise method for predicting infarction likelihood in stroke patients.
- This finding has implications for assessing patient eligibility for potential stroke therapies.

