Abstract #4970

Application of SAME-ECOS to 7T gradient-echo based myelin water imaging: a comparison of model-free and model-based approaches

Hanwen Liu^1,2, Vladimir Grouza^1,2, Marius Tuznik^1,2, and David Rudko^1,2,3

¹McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada, ²Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada, ³Department of Biomedical Engineering, McGill University, Montreal, QC, Canada

Synopsis

Multi-echo gradient echo (GRE) based, myelin water imaging (MWI) is subject to data quality constraints related to signal to noise ratio (SNR), B₀ field inhomogeneities and gradient imperfections. These constraints pose challenges for conventional model-free, non-negative least squares (NNLS) fitting. As an alternative, a three-pool parametric model can be applied, with nonlinear least squares(NLLS) fitting to process MWI data. The three-pool model confers stability, but has the disadvantage of making prior assumptions. This study investigated the feasibility of using a novel, model-free approach called spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS) for the GRE MWI analysis.

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