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Magnetic resonance fingerprinting: from evolution to clinical applications
Jean J L Hsieh1,2, Imants Svalbe3
1Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore, Singapore.
Journal of Medical Radiation Sciences
|June 30, 2020
Summary
Magnetic Resonance Fingerprinting (MRF) offers fast, quantitative MRI by matching tissue signals to pre-computed models. This technique provides accurate T1, T2, and proton density maps, improving imaging efficiency and diagnostic capabilities.
Area of Science:
- Quantitative imaging science
- Biomedical engineering
- Medical physics
Background:
- Magnetic Resonance Fingerprinting (MRF) introduced in 2013 enables rapid, quantitative Magnetic Resonance Imaging.
- This review covers MRF advancements up to early 2020, emphasizing its benefits for medical imaging professionals.
Purpose of the Study:
- To review the current status of MRF technology and its applications.
- To highlight the advantages of MRF for medical imaging professionals.
- To discuss the potential of MRF in clinical settings.
Main Methods:
- MRF acquires scan data using pseudorandom sampling to generate unique tissue 'fingerprints'.
- It matches randomized free induction decay acquisitions against pre-computed simulated tissue responses.
- Generates quantitative T1, T2, and proton density (PD) images with co-registered voxels.
Main Results:
- MRF achieves high accuracy and reproducibility (2–8%) in quantitative pixel values.
- The method is robust to significant k-space undersampling, with optimized sequences reducing artifacts.
- AI and machine learning enhance matching speed and precision.
- Early clinical trials show reliable differentiation of prostate and hippocampal tissues.
Conclusions:
- MRF offers reduced scan times, fewer artifacts, and improved patient comfort.
- Quantitative MRF data can establish numeric biomarkers for disease classification.
- Potential for standardized, repeatable scans enabling multi-center studies and individual patient monitoring.
- MRF is progressing towards routine clinical application with promising trial results.
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