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Review Open access

Role of low-field MRI in acute stroke

Jul 2026 · Stroke · Vol 57, pp. 2590 - 2603 · 0 citations · 44 references
Medicine

TL;DR

The current clinical evidence base is reviewed, including the role of LF-MRI in supporting stroke-type classification and tissue confirmation, in wake-up and unknown-onset stroke for tissue-based triage, and in post-therapeutic settings to enable serial assessment after thrombolysis or thrombectomy.

Abstract

Portable, low-field (LF) magnetic resonance imaging (MRI) is emerging as a clinically relevant adjunct in acute stroke care, enabling MRI in environments where conventional neuroimaging access is delayed, unavailable, or impractical. Advances in permanent magnet design, compact gradient and radiofrequency hardware, and the use of contemporary reconstruction methods have improved LF image quality and operational feasibility, supporting deployment at the point-of-care in emergency department, intensive care unit, and resource-limited settings. This review summarizes the evolving role of LF-MRI for acute stroke. LF sequence principles most relevant to stroke evaluation are summarized, focusing on how constraints in signal-to-noise ratio, achievable diffusion weighting, acquisition time, and diffusion direction sampling at LF influence lesion conspicuity and the reliability of quantification. The current clinical evidence base is then reviewed, including the role of LF-MRI in supporting stroke-type classification and tissue confirmation, in wake-up and unknown-onset stroke for tissue-based triage, and in post-therapeutic settings to enable serial assessment after thrombolysis or thrombectomy. Practical implementation considerations emphasize use case-driven deployment that preserves time-critical computed tomography and angiography pathways and clearly defines when LF-MRI should be used as an adjunct rather than a substitute for established initial imaging. Future directions include pragmatic workflow studies to determine where LF-MRI changes management, continued advances in hardware and pulse sequence development, and careful application of artificial intelligence for reconstruction and enhancement with task-specific validation in acute stroke.

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