Lara Bartels^1,2,3, Jonathan Doucette^1,2,3, Christoph Birkl^2,4, Alexander M. Weber^2,3, and Alexander Rauscher^1,2,3,5,6
1Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada, ²MRI Research Centre, University of British Columbia, Vancouver, BC, Canada, ³Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada, ⁴Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria, ⁵Department of Radiology, University of British Columbia, Vancouver, BC, Canada, ⁶Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada

In this work we studied the orientation dependence of diffusivities measured in DTI of healthy human white matter in vivo. The observed orientation dependence of the mean diffusivity can be explained by the effects of diffusion-mediated dephasing in the presence of diamagnetic myelin. Orientation dependence was markedly different for the radial and axial components of the diffusivity and suggests the presence of residual dipole-dipole interaction between water molecules. 

Jiyo S Athertya¹, Johnny Akers², Sophia Dwek¹, Zhao Wei¹, Jiang Du¹, Eric Y Chang^1,3, Mya Thu², and Hyungseok Jang^1
1Radiology, University of California San Diego, San Diego, CA, United States, ²VisiCELL Medical Inc, San Diego, CA, United States, ³Radiology Service, VA San Diego Healthcare System, San Diego, CA, United States

Non-invasive, clinically applicable tracking of therapeutic cells by magnetic resonance imaging (MRI) offers unparalleled insight into the safety and efficacy of cell-based therapies in the body. Here we used a series of 3D quantitative UTE techniques including UTE-QSM, UTE-T₁, and UTE-T₂^* mapping to evaluate the MR characteristics of stem cells labeled with a proprietary nanoparticle formulation that simultaneously labels cells for both optical and MR imaging. In a phantom experiment, all quantitative UTE parameters showed strong correlation with concentrations of labeled stem cells. Interestingly, in ex vivo mouse imaging, only UTE-QSM and UTE-T₂^* mapping detected the injected, labeled stem cells.

Anders Dyhr Sandgaard¹, Valerij G. Kiselev², Noam Shemesh³, and Sune Nørhøj Jespersen^1,4
1Department of Clinical Medicine, Center for Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark, ²Medical Physics, Department of Radiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany, ³Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, ⁴Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark

Mapping tissue magnetic properties with MRI may improve the diagnosis of diseases and enhance our understanding of their basic mechanisms. However, MRI signals are sensitive to both structure and magnetic susceptibility, the so-called “magnetic microstructure”, rendering accurate susceptibility estimation a great challenge. Here, we present an analytical expression for the Larmor frequency of a white matter model of myelinated axons with axially symmetric microscopic susceptibility anisotropy and orientation dispersion. The modelled axons are surrounded by microscopic spherical inclusions with a scalar susceptibility. This goes beyond previous models of white matter magnetic microstructure.

Elena Kleban^1,2, Derek K Jones^1,3, and Chantal MW Tax^1,4
1CUBRIC, Cardiff University, Cardiff, United Kingdom, ²Inselspital, Bern University, Bern, Switzerland, ³Australian Catholic University, Melbourne, Australia, ⁴UMC Utrecht, Utrecht University, Utrecht, Netherlands

Recently observed anisotropy of compartmental white matter T₂-values as a function of tissue orientation w.r.t. B₀ in combination with echo-time-dependence of diffusion MRI signals suggest that similar tissue-orientational effects could be expected in standard diffusion tensor measures. In this work we show the change of up to 20-30% in diffusion tensor measures as a function of fibre orientation w.r.t. B₀ from in vivo experiments and support these observations by simplified two-compartment white matter signal simulations.

Kevin Koch¹, Brad Swearningen¹, and Andrew S Nencka^1
1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States

To address the unmet need for metal artifact suppressed susceptibility-weighted imaging (SWI) in neuroradiology, here we introduce a novel approach to the generation of SWI contrasts using conventional (currently available) 3D-multi-spectral imaging (MSI) metal-artifact-suppression sequences.   This approach leverages basic spin-echo based 3D-MSI sequences, and then utilizes the inherent spectral information within MSI to develop "phase-contrast" maps that can then used to generate SWI-like contrasts.  This new metal-suppressed SWI approach has potential applications in patients with high susceptibility intra-cranial hardware, such as aneurysm clips, vascular shunts, cochlear implants, and fixed dental/orthodontic hardware.    

Christian Kames^1,2, Jonathan Doucette^1,2, and Alexander Rauscher^1,2,3
1UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada, ²Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, ³Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada

We propose a two-pass multi-echo nonlinear dipole inversion method. In the first pass an initial susceptibility map is obtained. The susceptibility map is then further processed by deconvolving the residual of the forward computed phase and the input phase to recover remnant low frequency susceptibility sources. The proposed method attains a NRMSE of 18.8 on the QSM Reconstruction Challenge 2.0 calcification dataset (Sim2Snr1), decisively outperforming the best scoring submissions of the challenge (NRMSE 26.3, 28.3, 28.5).

Anita Karsa¹ and Karin Shmueli^1
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom

Tissue magnetic susceptibility maps calculated using any Quantitative Susceptibility Mapping (QSM) pipeline are often corrupted by streaking artifacts. Large streaking artifacts originating from extreme-susceptibility regions, such as interhemispheric calcifications or intracerebral bleeds, are common, not only in patients, but also in healthy, elderly subjects. Several variations on the two-pass masking approach have been proposed previously to suppress these artifacts. Here we propose a broadly-applicable two-pass masking method that is easy to implement and integrate into any QSM pipeline. We show that two-pass masking greatly reduces streaking from calcifications and cerebral bleeds without affecting susceptibility map anatomical features and values.

Carlos Milovic¹, Christian Langkammer², José Pedro Marques³, and Karin Shmueli^1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Department of Neurology, Medical University of Graz, Graz, Austria, ³Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands

The 2019 QSM Reconstruction Challenge compared how different algorithms reconstructed QSM from true local field maps. However, this neglects the importance of residual background fields, and how they degrade the solutions. Here, we used a realistic “total field” simulation to compare three different background field removal methods, and to estimate the susceptibility maps resulting from three state-of-the-art QSM algorithms. We also compared the performance of two single-step algorithms, that use the total field map as an input. Our results showed that the two-step Weak-Harmonic QSM method is robust against residual fields and achieved the lowest error scores, outperforming single-step methods.

Minjun Kim¹, Hyeong-Geol Shin¹, Chungseok Oh¹, Hwihun Jeong¹, Sooyeon Ji¹, Hongjun An¹, Jiye Kim¹, Jinhee Jang², Berkin Bilgic³, and Jongho Lee^1
1Seoul National University, Seoul, Korea, Republic of, ²Seoul St Mary’s Hospital, Seoul, Korea, Republic of, ³Harvard Medical School, Boston, MA, United States

 The separation of positive and negative susceptibility source distributions (e.g., iron and myelin distributions) has important meanings in neuroscience and clinic. In this study, a deep learning-based χ-separation method is proposed to generate high-quality susceptibility source maps. For network training, multi-orientation head data are utilized, providing artifact-free label data. For the input data, either R₂’ or R₂* maps are utilized in addition to local field and QSM maps, producing two neural networks, χ-sepnet-R₂’ and χ-sepnet-R₂* (the latter requires no T₂). The results of χ-sepnets outperformed the conventional method, revealing details of brain structures both in healthy volunteers and patients.

Hyeong-Geol Shin¹, Jingjia Chen², Jongho Lee¹, Tae Hyung Kim³, Jaejin Cho³, Gabriel Varela-Mattatall³, Borjan Gagoski⁴, Chunlei Liu², and Berkin Bilgic^3
1Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea, Republic of, ²Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, ³Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁴Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States

Quantitative MRI has demonstrated potential in clinical and neuroscience applications, but its adoption has been hampered by excessively long scan times. Recent biophysical models have enabled differentiation of para- and dia-magnetic contributions to the tissue, but the acquisition of multi-parametric maps required by such models have further increased the encoding burden. We propose a comprehensive 9.5 min exam at high isotropic resolution to address this, from which T1, T2, proton density, T2*, para- and dia-magnetic susceptibility maps are estimated. This exam flexibly lends itself to generation of contrast-weighted images, allowing it to be used for clinical reads as well.

Christof Boehm¹, Jakob Meineke², Kilian Weiss³, Marcus R Makowski¹, and Dimitrios C Karampinos^1
1Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany, ²Philips Research, Hamburg, Germany, ³Philips GmbH Market DACH, Hamburg, Germany

Gradient echo imaging using in-phase echoes has been proposed to reduce the field-map estimation in water–fat regions to a convex nonlinear least squares problem. Conventionally, the in-phase assumption is based on a single-peak fat-model. However, fat is known to have a complex spectrum rendering the definition of in-phase echo times problematic. In this work, the single-fat-peak in-phase assumption is replaced by a multi-peak effective in-phase assumption. QSM based on multi-peak in-phase echo times is shown to yield similar results to water–fat imaging based field- and susceptibility-mapping in a simulation and in vivo in the spine and the breast.

Carlos Milovic¹, Kristian Bredies², Christian Langkammer³, and Karin Shmueli^4
1University College London, London, United Kingdom, ²Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria, ³Department of Neurology, Medical University of Graz, Graz, Austria, ⁴Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom

Single-step quantitative susceptibility mapping (QSM) algorithms simplify the processing pipeline and promise to be more robust against background fields than traditional two-step methods but they often underestimate tissue susceptibilities. Here, we propose a highly efficient gradient descent Tikhonov-regularized proximal solver and a highly accurate ADMM TV-regularized proximal solver to improve the accuracy of two Laplacian-based single-step methods. Our solvers outperformed current single-step methods and showed in-vivo performance very similar to traditional two-step methods. This will simplify QSM processing pipelines, allowing further automation in future, although more research is needed to improve robustness against noise and boundary-conditions-related artifacts.

Nikou Louise Damestani¹, Ana Beatriz Solana², Florian Wiesinger², Brice Fernandez³, Steven Charles Rees Williams¹, and David John Lythgoe^1
1Department of Neuroimaging, King's College London, London, United Kingdom, ²GE Healthcare, Munich, Germany, ³GE Healthcare, Paris, France

Looping Star is an acoustically quiet T₂*-weighted acquisition technique, which has primarily been used to demonstrate functional sensitivity. We present the application of Looping Star to quantitative susceptibility mapping in a small cohort, directly comparing its outcomes with a conventional susceptibility-weighted imaging technique. We found that Looping Star produced comparable quantitative values in subcortical regions in comparison with conventional susceptibility-weighted imaging.