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
PubMed
Abstract

Insights

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.

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