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Phase imaging with multiple phase-cycled balanced steady-state free precession at 9.4 T
Jae-Woong Kim1, Seong-Gi Kim2,3, Sung-Hong Park1
1Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.
NMR in Biomedicine
|February 11, 2017
Summary
Multiple phase-cycled balanced steady-state free precession (bSSFP) offers superior anatomical phase imaging contrast compared to gradient echo (GRE) techniques. However, its functional MRI (fMRI) capabilities remain limited with current methods.
Area of Science:
- Magnetic Resonance Imaging
- Neuroimaging
- Biophysics
Background:
- Gradient echo (GRE) sequences are widely used for phase imaging in MRI.
- Balanced steady-state free precession (bSSFP) phase imaging is less explored but holds potential for enhanced contrast.
- Phase imaging reveals tissue properties and functional brain activity.
Purpose of the Study:
- To investigate anatomical and functional phase imaging using multiple phase-cycled bSSFP sequences.
- To improve spatial coverage of phase-change regions in bSSFP imaging.
- To compare bSSFP phase imaging with conventional GRE phase imaging.
Main Methods:
- Dynamic 2D and 3D bSSFP sequences with varying phase-cycling (PC) angles and echo/repetition times (TE/TR) were applied to rat brains.
- Electrical forepaw stimulation was used to elicit functional responses.
- Phase images were analyzed for anatomical contrast and functional MRI (fMRI) signal changes, compared against magnitude images and GRE sequences.
Main Results:
- bSSFP phase imaging demonstrated significantly higher white matter to gray matter contrast than GRE, especially at specific PC angles.
- Combined multi-PC bSSFP phase images yielded stronger phase contrast and clearer visualization of neuronal fiber-like structures than GRE within equivalent scan times.
- Both bSSFP and GRE showed weak phase fMRI signals, primarily localized to draining veins.
Conclusions:
- Multiple phase-cycled bSSFP is a promising technique for high-contrast anatomical MRI.
- Current bSSFP approaches are not ideal for functional MRI (fMRI) applications due to weak signal detection.
