Abstract #4184

Computationally efficient multi-echo QSM

Korbinian Eckstein¹, Thanh Thuy Dao², Ashley Stewart^2,3, Simon Daniel Robinson^4,5,6,7, Markus Barth^2,3,4, and Steffen Bollmann^2,3,4

¹School of Information Technology and Electrical Engineering, The University of Queensland, Dutton Park, Australia, ²School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia, ³ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia, ⁴Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, ⁵Department of Neurology, Medical University of Graz, Graz, Austria, ⁶Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria, ⁷High Field MR Center, Medical University of Vienna, Vienna, Austria

Synopsis

Keywords: Electromagnetic Tissue Properties, Quantitative Susceptibility mapping, Multi-echo, ROMEO, PhaseWith increasingly popular multi-echo QSM, the combination of echoes becomes important in terms of accuracy, SNR and computation time. We compared 6 different pipelines with quantitative and Laplacian unwrapping and three different echo combination approaches, weighted averaging of QSMs, combination of the phase, and non-linear fitting. We compared the pipelines on the QSM challenge brain dataset and 7 T in vivo data and conclude that quantitative unwrapping (ROMEO) with weighted frequency combination achieves the best outcomes in terms of accuracy, SNR and computation time.

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