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Low-field MRI: Clinical promise and challenges
Thomas Campbell Arnold1,2, Colbey W Freeman3, Brian Litt2,4
1Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Journal of Magnetic Resonance Imaging : JMRI
|September 19, 2022
Summary
Low-field MRI scanners offer a cost-effective and portable alternative to high-field systems, increasing medical imaging access. Innovations are enhancing image quality and expanding clinical applications for this accessible technology.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Radiology
Background:
- High-field MRI scanners provide superior signal and resolution but are costly and inaccessible in many regions.
- Low-field MRI (LF-MRI) is gaining interest for its potential to increase imaging accessibility due to lower costs and portability.
Purpose of the Study:
- To review the advantages and disadvantages of LF-MRI scanners.
- To describe innovations in hardware and software for LF-MRI.
- To explore potential clinical applications of next-generation LF-MRI devices.
Main Methods:
- Review of current literature on LF-MRI technology and applications.
- Analysis of hardware and software advancements mitigating LF-MRI limitations.
- Exploration of clinical use cases, including neuroimaging, MRI-guided procedures, and musculoskeletal imaging.
Main Results:
- LF-MRI offers significant cost and portability benefits, potentially broadening access to medical imaging.
- Innovations in hardware and software are improving LF-MRI image quality and addressing signal limitations.
- Potential clinical applications span high-acuity brain imaging to musculoskeletal diagnostics, with tailored approaches for diverse settings.
Conclusions:
- LF-MRI presents a transformative opportunity to expand medical imaging access globally.
- Addressing challenges in clinical translation, validation, and integration is crucial for widespread adoption.
- Next-generation LF-MRI devices hold promise for enhancing healthcare delivery in both high- and low-resource settings.
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