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Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review
Anmol Monga1, Dilbag Singh1, Hector L de Moura1
1Center of Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA.
Bioengineering (Basel, Switzerland)
|March 27, 2024
Summary
Magnetic resonance fingerprinting (MRF) accelerates quantitative MRI by simultaneously acquiring multiple tissue properties. This review explores MRF trends and applications, highlighting challenges and future directions for faster, more precise medical imaging.
Area of Science:
- Medical Imaging
- Quantitative MRI
- Biomedical Engineering
Background:
- Magnetic resonance imaging (MRI) offers high-resolution soft-tissue contrast but faces challenges in scan time and spatial resolution for quantitative analysis.
- Undersampled k-space data acquisition combined with compressed sensing (CS) and deep learning (DL) mitigates artifacts and reduces scan times.
- Magnetic resonance fingerprinting (MRF) emerges as an efficient framework for simultaneous, rapid quantification of multiple tissue properties.
Purpose of the Study:
- To provide an extensive literature review of the magnetic resonance fingerprinting (MRF) framework.
- To address trends in MRF's four key aspects: pulse sequence design, data acquisition, signal encoding, and quantitative map recovery.
- To review best practices and applications of MRF in cardiac, brain, and musculoskeletal imaging, assessing future translation potential.
Main Methods:
- Literature review of magnetic resonance fingerprinting (MRF) techniques.
- Analysis of trends in MRF pulse sequence design and rapid, undersampled data acquisition.
- Examination of MRF's encoding of tissue properties and simultaneous recovery of quantitative spatial maps.
Main Results:
- MRF enables efficient and versatile acquisition and quantification of multiple tissue properties in a single fast MRI scan.
- Trends in MRF pulse sequence design, data acquisition, and reconstruction methods are identified.
- Challenges and opportunities for MRF across various magnetic field strengths and anatomical regions are highlighted.
Conclusions:
- MRF presents a promising framework for overcoming limitations in quantitative MRI, offering simultaneous property mapping.
- The review identifies best practices and application-specific trends in MRF for diverse biomedical imaging areas.
- Further investigation into MRF challenges can drive its translation into clinical practice for improved diagnostic capabilities.
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