Magnetic resonance field fingerprinting.
PURPOSE: To develop and evaluate the magnetic resonance field fingerprinting method that simultaneously generates T1 , T2 , B0 , and B 1 + maps from a single continuous measurement. METHODS: An encoding pattern was designed to integrate true fast imaging with steady-state precession (TrueFISP), fast imaging with steady-state precession (FISP), and fast low-angle shot (FLASH) sequence segments with varying flip angles, radio frequency (RF) phases, TEs, and gradient moments in a continuous acquisition. A multistep matching process was introduced that includes steps for integrated spiral deblurring and the correction of intravoxel phase dispersion. The method was evaluated in phantoms as well as in vivo studies in brain and lower abdomen. RESULTS: Simultaneous measurement of T1 , T2 , B0 , and B 1 + is achieved with T1 and T2 subsequently being less afflicted by B0 and B 1 + variations. Phantom results demonstrate the stability of generated parameter maps. Higher undersampling factors and spatial resolution can be achieved with the proposed method as compared with solely FISP-based magnetic resonance fingerprinting. High-resolution B0 maps can potentially be further used as diagnostic information. CONCLUSION: The proposed magnetic resonance field fingerprinting method can estimate T1 , T2 , B0 , and B 1 + maps accurately in phantoms, in the brain, and in the lower abdomen.
Duke Scholars
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Related Subject Headings
- Vibration
- Reproducibility of Results
- Phantoms, Imaging
- Nuclear Medicine & Medical Imaging
- Magnetic Resonance Imaging
- Magnetic Fields
- Image Processing, Computer-Assisted
- Image Interpretation, Computer-Assisted
- Humans
- Healthy Volunteers
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Vibration
- Reproducibility of Results
- Phantoms, Imaging
- Nuclear Medicine & Medical Imaging
- Magnetic Resonance Imaging
- Magnetic Fields
- Image Processing, Computer-Assisted
- Image Interpretation, Computer-Assisted
- Humans
- Healthy Volunteers