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Abstract #4826

A realistic in-silico brain phantom for magnetic susceptibility-separation algorithm validation

Daniel Ridani1, Benjamin De-Leener1,2,3, and Eva Alonso-Ortiz1,3,4
1NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada, 2Department of Computer and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada, 3CHU Sainte-Justine Research Center, Montreal, QC, Canada, 4Department of Electrical Engineering, Polytechnique Montreal, Montreal, QC, Canada

Synopsis

Keywords: Susceptibility/QSM, Quantitative Imaging, Phantoms, QSM, Simulation, Susceptibility, Anisotropy

Motivation: Positive and negative susceptibility mapping is an emerging method that can benefit from the availability of validation tools.

Goal(s): To create an in-silico brain phantom for positive and negative susceptibility and to assess the impact of white matter’s anisotropic susceptibility on susceptibility-separation techniques.

Approach: Simulate positive and negative susceptibility maps and gradient-echo data with/without anisotropy. Process simulated data with different susceptibility-separation algorithms. Compare the results with the ground truth.

Results: The error associated with negative susceptibility measurements is ~9% greater when anisotropy effects are present in the phantom, suggesting that a new susceptibility-separation algorithm that considers myelin’s anisotropic susceptibility may be warranted.

Impact: Researchers developing novel magnetic susceptibility-separation methods can use our proposed phantom to test different aspects of their technique, ranging from the biophysical model to image processing methods and imaging protocol parameters.

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