Ashley Wilton Stewart1,2, Simon Daniel Robinson2,3,4,5, Kieran O'Brien1,2,6, Jin Jin1,2,6, Georg Widhalm7, Gilbert Hangel5,7, Angela Walls8, Jonathan Goodwin9,10, Korbinian Eckstein5, Monique Tourell1,2, Catherine Morgan11,12,13, Aswin Narayanan2, Markus Barth1,2,14, Steffen Bollmann1,2,14. 1. ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Queensland, Australia. 2. Centre for Advanced Imaging, University of Queensland, Brisbane, Australia. 3. Department of Neurology, Medical University of Graz, Graz, Austria. 4. Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria. 5. Department of Biomedical Imaging and Image-Guided Therapy, High Field MR Center, Medical University of Vienna, Vienna, Austria. 6. Siemens Healthcare Pty Ltd, Brisbane, Queensland, Australia. 7. Department of Neurosurgery, Medical University of Vienna, Vienna, Austria. 8. Clinical & Research Imaging Centre, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia. 9. Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, New South Wales, Australia. 10. School of Mathematical and Physical Science, University of Newcastle, Newcastle, New South Wales, Australia. 11. School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand. 12. Centre of Research Excellence, Brain Research New Zealand-Rangahau Roro Aotearoa, Auckland, New Zealand. 13. Centre for Advanced MRI, The University of Auckland, Auckland, New Zealand. 14. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia.
Abstract
PURPOSE: Quantitative susceptibility mapping (QSM) estimates the spatial distribution of tissue magnetic susceptibilities from the phase of a gradient-echo signal. QSM algorithms require a signal mask to delineate regions with reliable phase for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artifacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing. Moreover, this method is integrated within an open-source software framework: QSMxT. METHODS: A robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information and suppressing streaking artifacts. RESULTS: Compared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artifacts caused by unreliable phase and high dynamic ranges of susceptibility sources. It is also robust across a range of acquisitions at 3 T in volunteers and phantoms, at 7 T in tumor patients, and in an in silico head phantom, with significant artifact and error reductions, greater anatomical detail, and minimal parameter tuning. CONCLUSION: The two-pass masking and reconstruction procedure separates reliable from less reliable phase regions, enabling a more accurate QSM reconstruction that mitigates artifacts, operates without anatomical priors, and requires minimal parameter tuning. The technique and its integration within QSMxT makes QSM processing more accessible and robust to streaking artifacts.
PURPOSE: Quantitative susceptibility mapping (QSM) estimates the spatial distribution of tissue magnetic susceptibilities from the phase of a gradient-echo signal. QSM algorithms require a signal mask to delineate regions with reliable phase for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artifacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing. Moreover, this method is integrated within an open-source software framework: QSMxT. METHODS: A robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information and suppressing streaking artifacts. RESULTS: Compared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artifacts caused by unreliable phase and high dynamic ranges of susceptibility sources. It is also robust across a range of acquisitions at 3 T in volunteers and phantoms, at 7 T in tumor patients, and in an in silico head phantom, with significant artifact and error reductions, greater anatomical detail, and minimal parameter tuning. CONCLUSION: The two-pass masking and reconstruction procedure separates reliable from less reliable phase regions, enabling a more accurate QSM reconstruction that mitigates artifacts, operates without anatomical priors, and requires minimal parameter tuning. The technique and its integration within QSMxT makes QSM processing more accessible and robust to streaking artifacts.
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