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Updated: Aug 6, 2026

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A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Role of Low-Field MRI in Acute Stroke
Annabel Sorby-Adams1, Nandor K Pinter2,3, Keith W Muir4
1Department of Neurology and the Center for Genomic Medicine (A.S.-A., W.T.K.), Mass General Brigham and Harvard Medical School, Boston.
Stroke
|July 21, 2026
Summary
Portable, low-field (LF) magnetic resonance imaging (MRI) offers a promising solution for acute stroke care, improving accessibility in critical situations. This technology enhances stroke diagnosis and management, particularly in emergency settings.
Area of Science:
- Medical Imaging
- Neurology
- Biomedical Engineering
Background:
- Conventional neuroimaging access is often delayed or unavailable in acute stroke care.
- Portable, low-field (LF) magnetic resonance imaging (MRI) is emerging as a solution for point-of-care diagnostics.
- Advances in hardware and reconstruction methods have improved LF-MRI feasibility and image quality.
Purpose of the Study:
- To review the evolving role of LF-MRI in acute stroke management.
- To summarize LF sequence principles relevant to stroke evaluation.
- To discuss clinical evidence, implementation, and future directions for LF-MRI in stroke care.
Main Methods:
- Review of current literature on LF-MRI for acute stroke.
- Summary of LF sequence principles and their impact on image quality and quantification.
- Analysis of clinical evidence for LF-MRI in stroke diagnosis, triage, and post-treatment assessment.
Main Results:
- LF-MRI constraints (SNR, diffusion weighting, acquisition time) affect lesion conspicuity and quantification reliability.
- Clinical evidence supports LF-MRI for stroke-type classification, tissue confirmation, and wake-up stroke triage.
- LF-MRI can facilitate serial assessment in post-therapeutic settings.
Conclusions:
- LF-MRI is a valuable adjunct for acute stroke care, especially in resource-limited or emergency settings.
- Implementation requires careful consideration of use cases to complement, not replace, established imaging pathways.
- Future research should focus on workflow integration, hardware/sequence development, and AI applications for enhanced stroke management.
