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Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Limitations of rapid myelin water quantification using 3D bSSFP
C Lenz1, M Klarhöfer, K Scheffler
1Division of Radiological Physics, University of Basel Hospital, Petersgraben 4, 4031, Basel, Switzerland. claudia.lenz@unibas.ch
Magma (New York, N.Y.)
|April 29, 2010
Summary
This study explored using 3D balanced steady-state free precession (bSSFP) for myelin water fraction (MWF) mapping. While feasible, the method
Area of Science:
- Neuroimaging
- Magnetic Resonance Imaging (MRI)
- Biophysics
Background:
- Conventional myelin water fraction (MWF) imaging uses multi-echo spin-echo sequences, which have long acquisition times and limited volume coverage.
- Developing faster MRI techniques for accurate MWF quantification is crucial for neurological research.
Purpose of the Study:
- To investigate the feasibility of using 3D balanced steady-state free precession (bSSFP) sequences for high-resolution myelin water mapping.
- To assess the potential of bSSFP as an alternative to conventional MWF imaging methods.
Main Methods:
- Derived an approximate bSSFP signal equation based on a two-pool water exchange model.
- Fitted the flip angle dependence of in vivo bSSFP signals to determine MWF and signal amplitude, making assumptions for other parameters.
- Investigated the influence of factors like magnetization transfer and field inhomogeneities on MWF values.
Main Results:
- Acquisition and calculation of quantitative, high-resolution MWF maps from healthy volunteers using bSSFP were demonstrated as feasible.
- Averaged MWF results obtained with bSSFP showed agreement with existing literature values.
- Numerical simulations revealed a significant dependency of derived MWF values on the assumed two-pool model parameters.
Conclusions:
- The proposed bSSFP method for MWF mapping is feasible but requires careful consideration of underlying model parameters.
- The dependence of MWF on two-pool parameters significantly limits the current applicability of this bSSFP-based approach.

