Monique Tourell^1,2, Jin Jin^2,3, Ashley Stewart^1,2, Saskia Bollmann¹, Steffen Bollmann^1,2,4, Simon Robinson^1,5,6, Kieran O'Brien^2,3, and Markus Barth^1,2,4
1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, ²ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia, ³Siemens Healthcare Pty Ltd, Brisbane, Australia, ⁴School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia, ⁵High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ⁶Department of Neurology, Medical University of Graz, Graz, Austria

High-resolution Quantitative Susceptibility Mapping (QSM) has the potential to improve multiple sclerosis imaging and pre-surgical planning for deep brain stimulation. Using a conventional 3D-gradient echo sequence, imaging times for submillimeter scans can be as long as 8 to 15 minutes. In this work, we implemented a multi-shot 3D-EPI sequence combined with 2D CAIPIRINHA acceleration to achieve high-quality susceptibility maps, with no visible distortions, at 0.80 mm and 0.65 mm isotropic resolutions in 58 and 87 seconds, respectively. Multi-echo 3D-GRE sequences producing similar QSMs required up to a 9-fold increase in acquisition time.

Hwihun Jeong¹, Hyeong-Geol Shin¹, Xu Li², Sooyeon Ji¹, and Jongho Lee^1
1Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea, Republic of, ²Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins Medicine, Baltimore, MD, United States

We introduce ChEST, a novel model that can estimate both chemical exchange and magnetic susceptibility tensor effects from resonance frequency shift. For reconstruction, an iterative algorithm is designed to solve the inverse problem of the new model. When tested using numerical simulation datasets, our method successfully generated mean magnetic susceptibility, magnetic susceptibility anisotropy, principal eigenvector, and chemical exchange maps in high accuracy as compared to conventional methods. Application to in-vivo human brain was conducted, revealing promising outcomes.

Thomas Jochmann¹, Dejan Jakimovski², Nora Küchler¹, Robert Zivadinov^2,3, Jens Haueisen¹, and Ferdinand Schweser^2,3
1Department of Computer Science and Automation, Technische Universität Ilmenau, Ilmenau, Germany, ²Buffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, ³Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, United States

Besides magnetic susceptibility, MRI phase contrast is caused by chemical exchange, anisotropic magnetic susceptibility, and anisotropic microstructural compartmentalization. These additional contributions are neglected by conventional QSM. This work presents an improved version of DEEPOLE QUASAR, a phase processing method that accounts for non-susceptibility signal contributions. We present preliminary results from studies on mice, volunteers, and multiple sclerosis (MS) patients.

Jingjia Chen¹, Nan-Jie Gong², and Chunlei Liu^1,3
1Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, ²Vector Lab for Intelligent Medical Imaging and Neural Engineering, International Innovation Center of Tsinghua University, Shanghai, China, ³Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States

We propose and develop a method to separate paramagnetic and diamagnetic components within one voxel based on a 3-pool signal model. Alternating between solving for linear and nonlinear parameters in the model, paramagnetic component susceptibility (PCS) and diamagnetic component susceptibility (DCS) maps are constructed to represent the sub-voxel compartments. 

Chaoyue Wang¹, Benjamin C. Tendler¹, Stephen M. Smith¹, Fidel Alfaro-Almagro¹, Alberto Llera², Cristiana Fiscone^3,4, Richard Bowtell³, Lloyd T. Elliott⁵, Karla L. Miller¹, and Aurea B. Martins-Bach^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ²Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands, ³Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom, ⁴Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy, ⁵Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, BC, Canada

UK Biobank is scanning 100,000 participants using multi-modal MRI (including swMRI). This rich resource also includes genome-wide characterisation of individuals. This provides a powerful opportunity to relate swMRI-derived measures to genetics. The aim of this work is to identify genetic associations of QSM-based measures. We carried out genome-wide association studies (GWAS) in over 30,000 subjects for both QSM and T2* based measures. Our results demonstrate that susceptibility and T2* measures are associated with genetic loci involved in a range of biological functions. Susceptibility and T2* IDPs share many common genetic associations but there are also complementary associations.

Christof Boehm¹, Nico Sollmann^2,3,4, Jakob Meineke⁵, Sophia Kronthaler¹, Stefan Ruschke¹, Michael Dieckmeyer^2,3, Kilian Weiss⁶, Claus Zimmer^2,3, Marcus R. Makowski¹, Thomas Baum^2,3, and Dimitrios C. Karampinos^1
1Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany, ²Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany, ³TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany, ⁴Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany, ⁵Philips Research Lab, Hamburg, Germany, ⁶Philips Healthcare, Hamburg, Germany

Body-QSM remains challenging for various reasons including, (a) the incomplete separation of background- and local-fields included by assumed approximations,(b) incorrect modeling at low-SNR-voxels included by linear modeling of the inverse problem and (c) streaking artifacts. A recently developed total-field-inversion (TFI) QSM method that directly estimates the susceptibility from multi-echo data showed significant alleviation of the above artifacts. However, the original TFI method can only be applied to regions with one species. This work proposes a QSM method that directly estimates susceptibility from multi-echo data in regions where water and fat are present and demonstrates its advantages over former proposed methods.

Allen A Champagne^1,2, Yan Wen³, Magdy Selim⁴, Aristotelis Filippidis ⁵, Ajith Thomas⁵, Pascal Spincemaille³, Yi Wang³, and Salil Soman ^6
1School of Medicine, Queen's University, Kingston, ON, Canada, ²Center for Neuroscience Studies, Queen's University, Kingston, ON, Canada, ³Radiology, Weill Cornell Medicine, New York, NY, United States, ⁴Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, ⁵Neurosurgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, ⁶Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States

The perceived acuity (hyperacute, acute, subacute) of intracerebral hemorrhage (ICH) dramatically impacts patient management. While CT and standard MRI are limited for staging ICH, Quantitative Susceptibility Imaging (QSM) has shown promising results for tracking the evolution of ICH, as a substrate for the pathophysiology within bleeds. Here, we compare novel multi-echo complex total field inversion (mcTFI) QSM for staging ICHs, in comparison to conventional Morphology Enabled Dipole Inversion (MEDI). mcTFI better distinguished hyperacute/acute timepoints from subacute ICHs, in comparison to MEDI, likely as a result of the robust inversion computation, inherently reducing susceptibility quantification errors and shadowing artifacts.

Oliver C. Kiersnowski¹, Anita Karsa¹, John S. Thornton², and Karin Shmueli^1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²UCL Queens Square Institute of Neurology, London, United Kingdom

Quantitative susceptibility mapping (QSM) using the MRI phase to calculate tissue magnetic susceptibility is finding increasing clinical applications. Oblique image slices are often acquired to facilitate radiological viewing and reduce artifacts. Here, we show that artifacts and errors arise in susceptibility maps if oblique acquisition is not properly taken into account in QSM. We performed a comprehensive analysis of the effects of oblique acquisition on brain susceptibility maps and compared tilt correction schemes for three susceptibility calculation methods, using a numerical phantom and human in-vivo images. We demonstrate a robust tilt correction method for accurate QSM with oblique acquisition.

Beata Bachrata^1,2, Korbinian Eckstein¹, Siegfried Trattnig^1,2, and Simon Daniel Robinson^1,3,4
1High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria, ²Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria, ³Centre of Advanced Imaging, University of Queensland, Brisbane, Australia, ⁴Department of Neurology, Medical University of Graz, Graz, Austria

We address the challenges of QSM in regions outside of the brain which contain disconnected structures - leading to difficulty in masking - and significant amounts of fat with chemical shift and relaxation differences relative to water - leading to errors in susceptibility estimates. We propose a mask generation approach based on signal phase and show that the errors in susceptibility estimates can be eliminated using simultaneous fat-water imaging with SMURF. Using multi-echo acquisition and inverse-variance-weighted echo combination, we generate high CNR, chemical shift and relaxation effects-free susceptibility maps of the head-and-neck at 7T.

Negin Yaghmaie^1,2, Warda Syeda^3,4, Chengchuan Wu^1,2, Yicheng Zhang^1,2, Bradford A. Moffat^1,4, Rebecca Glarin^1,5, Scott Kolbe^4,6,7, and Leigh Johnston^1,2
1Melbourne Brain Centre Imaging Unit, The University of Melbourne, Melbourne, Australia, ²Department of Biomedical Engineering, The University of Melbourne, Melbourne, Australia, ³Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Australia, ⁴Department of Medicine and Radiology, The University of Melbourne, Melbourne, Australia, ⁵Department of Radiology, Royal Melbourne Hospital, Melbourne, Australia, ⁶Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia, ⁷Department of Radiology, Alfred Hospital, Melbourne, Australia

We propose a two-stage QSM method, Quantitative Susceptibility Mapping Artifact Reduction Technique (QSMART), in which tissue and vein susceptibility values are estimated in parallel by generating a vasculature mask from the magnitude data using a Frangi filter. Spatially Dependent Filtering is employed for the background field removal and the two susceptibility estimates are combined in the final QSM map. QSMART is compared to RESHARP/iLSQR and V-SHARP/iLSQR inversion on 7T in vivo single and multiple-orientation scans. QSMART demonstrates superior artifact suppression in the cortex and near vasculature, and is a robust tool for susceptibility estimation. QSMART code is available at https://github.com/MBCIU/QSMART.