Low-Field Magnetic Resonance Imaging in Critical Care of Stroke.
Authors
Affiliations (5)
Affiliations (5)
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, China (L.Z., X.N., X. Liu, W.D., Z. Zhang, J.L., Y. Wei, Z. Zhao, Y. Wang, L.L.).
- China National Clinical Research Center for Neurological Diseases, Beijing (L.Z., X.N., X. Liu, W.D., Z. Zhang, J.L., Y. Wei, Z. Zhao, Y. Wang, L.L.).
- Department of Medicine, Faculty of Medicine, National University of Malaysia (Z.K.L.).
- Department of Medicine & Therapeutics, the Chinese University of Hong Kong (X. Leng).
- Department of Neurology, Yale School of Medicine, New Haven, CT (A.H.).
Abstract
Neurological deterioration is a frequent and clinically significant challenge in patients with acute stroke admitted to neurocritical care units, where timely neuroimaging is essential but access to advanced imaging may be limited by patient instability and logistical constraints. Low-field magnetic resonance imaging (LF-MRI) has recently emerged as a novel approach to extend MRI capability into critical care environments. This topic review synthesizes current evidence on the feasibility, safety, and evolving clinical applications of LF-MRI in neurocritical care stroke. Existing studies demonstrate its utility in diagnostic clarification, longitudinal monitoring of brain injury, and detection of selected secondary complications. Key applications include intracerebral hemorrhage detection and volumetric assessment, quantification of midline shift, ventricular monitoring, evaluation of infarct evolution and cerebral edema, and assessment of unexplained neurological deterioration. Beyond these applications, LF-MRI offers a unique opportunity to support repeated imaging during periods when neurological examination is unreliable or limited. LF-MRI should be viewed as a complementary imaging modality rather than a replacement for computed tomography or conventional high-field MRI. Future advances in sequence development, workflow integration, and rigorously validated artificial intelligence-assisted quantitative tools are expected to further define its role in risk stratification, time-sensitive decision-making, and longitudinal neurocritical care pathways. As access to portable imaging expands, LF-MRI has the potential to reshape neuroimaging strategies in critically ill patients with stroke.