Ferdinand Schweser^1,2, Wei Li³, Hongfu Sun⁴, Dong Zhou⁵, Nicola Bertolino¹, Paul Polak¹, Yi Wang⁵, Alan H Wilman⁴, Kristian Bredies⁶, Robert Zivadinov¹, and Simon Daniel Robinson^7
1Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, Buffalo, NY, United States, ²MRI Molecular and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, Buffalo, NY, United States, ³Research Imaging Institute, The University of Texas Health Science Center, San Antonio, TX, United States, ⁴Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada, ⁵Department of Radiology, Weill Cornell Medical College, New York, NY, United States, ⁶Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria, ⁷High Field MR Center of Excellence, Department of Radiology, Medical University of Vienna, Vienna, Austria

Elimination of background fields is an essential step in phase MRI and QSM, with many different approaches proposed over the past years. However, it is currently unclear how the various methods perform relative to each other and what their respective strengths and weaknesses are, because a multi-center quantitative comparison of all techniques has not yet been carried out.

In this work we quantitatively compare inverse Laplace filtering, SHARP , V-SHARP, iSMV , LBV, HARPERELLA, iHARPERELLA, PDF, and RE-SHARP in a collaborative effort.

The background correction performance was similar with all methods, with iSMV and LBV yielding the best results.

Amanda Ching Lih Ng¹, Meei Pyng Ng², Sonal Josan³, Shawna Farquharson⁴, Claire Mulcahy⁴, and Roger J Ordidge^1
1Dept of Anatomy & Neuroscience, The University of Melbourne, Parkville, Australia, ²Dept of Mathematics & Statistics, The University of Melbourne, Parkville, Australia, ³Siemens Healthcare, Melbourne, Australia,⁴Imaging, The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia

Laplacian-based phase unwrapping is commonly used to pre-process phase for methods such as Quantitative Susceptibility Mapping (QSM). However, the formulation was derived with the assumption of a continuous signal and a continuous Fourier transform. When applied to discrete MRI phase data, serious errors in phase can occur, resulting in substantial errors in QSM estimates. We present a mathematically correct Laplacian-based phase unwrapping formula, based on the assumption of the discrete nature of MRI phase data and processing. Our results reflect the mathematical predictions of the old and new formulations.

Hongjiang Wei¹, Luke Xie², Russell Dibb³, Wei Li⁴, Kyle Decker³, G. Allan Johnson^3,5, and Chunlei Liu^1,5
1Brain Imaging and Analysis Center, Duke University, Durham, NC, United States, ²Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, UT, United States, ³Center for In Vivo Microscopy, Duke University, Durham, NC, United States, ⁴Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, United States, ⁵Department of Radiology, School of Medicine, Duke University, Durham, NC, United States

In this study, we demonstrate that whole brain cytoarchitecture can be revealed by QSM at 10-μm resolution at 9.4T. Using QSM, we are able to reveal exquisite anatomical details such as retina layers of the eyeball, glomeruli in olfactory bulb, barrel cortex, medium-sized spiny neurons in striatum, cell layers of cerebellum, and hippocampus. This ultra-high resolution QSM of the intact mouse brain is a powerful dataset to allow analysis and visualization of the brain cytoarchitecture in 3D.

Debra E. Horng^1,2, Samir D. Sharma¹, Scott B. Reeder^1,2,3,4,5, and Diego Hernando^1
1Radiology, University of Wisconsin, Madison, WI, United States, ²Medical Physics, University of Wisconsin, Madison, WI, United States, ³Medicine, University of Wisconsin, Madison, WI, United States, ⁴Biomedical Engineering, University of Wisconsin, Madison, WI, United States, ⁵Emergency Medicine, University of Wisconsin, Madison, WI, United States

We introduce a QSM background field removal method based on harmonic function theory. Methods based on the mean value theorem compute the value at the center of a spherical kernel. Conversely, a new method based on the extended Poisson kernel can compute the value at any location in a spherical kernel. The new kernel is evaluated for accuracy near air/tissue interfaces, resulting in low errors compared to existing methods. Our new method is fast (analytic) and is designed for performance near air/tissue interfaces in abdominal QSM.

Andreas Deistung¹, Verena Endmayr², Simon Hametner², Hans Lassmann², Jürgen Rainer Reichenbach¹, Simon Daniel Robinson³, Thomas Haider⁴, Hannes Traxler⁵, Evelin Haimburger⁶, Siegfried Trattnig³, and Günther Grabner^3,6
1Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital – Friedrich Schiller University Jena, Jena, Germany, ²Center for Brain Research, Medical University of Vienna, Vienna, Austria, ³High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ⁴University Clinic for Trauma Surgery, Medical University of Vienna, Vienna, Austria, ⁵Center of Anatomy and Cellbiology, Medical University of Vienna, Vienna, Austria, ⁶Department of Health Sciences and Social Work, Carinthia University of Applied Sciences, Klagenfurt, Austria

Quantitative susceptibility mapping (QSM) provides a unique view into cerebral iron distribution in vivo. However, not only paramagnetic iron complexes but also diamagnetic myelin around axons contribute to the magnetic susceptibility. To further validate QSM for iron mapping we present a histochemical-driven approach to quantify iron in post mortem brain tissue and compare the spatial distribution of iron with in situmagnetic susceptibility maps. Direct comparison between histological iron concentration and susceptibility maps revealed excellent correspondence between iron accumulations and elevated susceptibility in deep gray matter and can improve the understanding of biophysical origins of susceptibility variations within brain tissue.

Zhe Wu^1,2, Hongjian He^1,2, Ying Chen^1,2, Song Chen^1,2, Hui Liu³, Yiping P. Du², and Jianhui Zhong^1,2
1Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, China, People's Republic of, ²Department of Biomedical Engineering, Zhejiang University, Hangzhou, China, People's Republic of,³NEA MR Collaboration, Siemens Ltd., China, Shanghai, China, People's Republic of

A three-step method for high resolution myelin water fraction (MWF) and frequency shift mapping of white matter components using tissue susceptibility is presented in this study. Tissue susceptibility induced phase was calculated by the simultaneously acquired QSM from the same multi-echo GRE (mGRE) dataset, and was used as the phase part of complex data for a subsequent fitting to a three-pool white matter model.  Benefit from the background phase removal and magnetic dipole deconvolution procedures during QSM calculation, the result reveals much less misfitting when comparing with direct fitting to original mGRE data. These generated quantitative maps can be potentially used for quantitative studies of demyelinated diseases.

Zhe Liu¹, Youngwook Kee², Dong Zhou², Pascal Spincemaille², and Yi Wang^1,2
1Biomedical Engineering, Cornell University, Ithaca, NY, United States, ²Radiology, Weill Cornell Medical College, New York, NY, United States

We propose a Preconditioned QSM calculating susceptibility over the entire field of view (FOV), which eliminates the errors associated with background field removal. The background is regarded as part of the region with large susceptibilities, which is determined by a preconditioned conjugate gradient solver with enhanced convergence. Our data demonstrate that our preconditioned QSM provides a susceptibility map of the entire head accurately depicting skin, bone, air filled sinuses and hemorrhages.

Vanessa Wiggermann^1,2, Simon Hametner³, Enedino Hernandez-Torres^2,4, Verena Endmayr³, Christian Kames⁵, and Alexander Rauscher^2
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, ²Pediatrics, University of British Columbia, Vancouver, BC, Canada, ³Neuroimmunology, Medical University of Vienna, Vienna, Austria,⁴UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada, ⁵Engineering Physics, University of British Columbia, Vancouver, BC, Canada

Quantitative Susceptibility Mapping has shown great potential to be used for clinical diagnoses due to its high sensitivity to change and high spatial resolution. Notably, the ability to quantify damage has been appealing. However, attributing susceptibility increases or decreases to certain mechanisms has been challenging. In particular, interpretation of MR signal changes during multiple sclerosis lesion formation is lacking consistency and histological validation. Here, we investigated the hypothesis that apparent changes of the lesion tissue may be in fact due to changes in the lesions vicinity and caution is required when interpreting the quantitative susceptibility signal in multiple sclerosis lesions.

Karthik Chary¹, Mikko J. Nissi^2,3, Ramón I. Rey⁴, Eppu Manninen¹, Karin Shmueli⁵, Alejandra Sierra¹, and Olli Gröhn^1
1Department of Neurobiology, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland, ²Department of Applied Physics, University of Eastern Finland, Kuopio, Finland, ³Finland Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland, ⁴Department of Neurology, Clinical Neurosciences Research Laboratory, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), University of Santiago de Compostela, Santiago de Compostela, Spain, ⁵Department of Medical Physics & Biomedical Engineering, University College London, London, United Kingdom

Our aim was to test the sensitivity of QSM to demyelination, iron and calcifications in a rat model of TBI. Ex vivo QSM data were obtained from five injured and four sham control rats, six months after TBI. Our results showed susceptibility changes in white matter areas consistent with myelin staining. Perilesional cortex became more diamagnetic after TBI. Thalamic nuclei showed variable responses as diamagnetic calcification and paramagnetic iron accumulation occurred in the same brain areas. Overall, QSM showed sensitivity to TBI changes. However, further studies are required to better understand the influence of potentially counteracting pathological processes.

Sina Straub¹, Till Schneider^2,3, Martin T. Freitag³, Christian H. Ziener³, Heinz-Peter Schlemmer³, Mark E. Ladd¹, and Frederik B. Laun^1
1Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany, ³Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

Since QSM is only able to quantify magnetic susceptibility relative to a reference value, a suitable reference tissue must be available to be able to compare different subjects and stages of disease. To find such a suitable reference tissue for QSM of the brain, melanoma patients with and without brain lesions were measured. 12 reference tissues were chosen and assessed in multiple measurements of the same patient and amongst different patients. The posterior limb of the internal capsule and a cerebrospinal fluid volume in the atrium of the lateral ventricles appeared to be most suitable reference tissues.