ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore

Scientific Session: Magnetic Susceptibility

Monday, May 9, 2016
Room 324-326
10:45 - 12:45
Moderators: Berkin Bilgic

An illustrated comparison of background field elimination methods for phase MRI and QSM
Ferdinand Schweser1,2, Wei Li3, Hongfu Sun4, Dong Zhou5, Nicola Bertolino1, Paul Polak1, Yi Wang5, Alan H Wilman4, Kristian Bredies6, Robert Zivadinov1, and Simon Daniel Robinson7
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.

Fast Unwrapping using Discrete Gradient Evaluation (FUDGE): an analytical correction to the Laplacian-based phase unwrapping technique for discrete data.
Amanda Ching Lih Ng1, Meei Pyng Ng2, Sonal Josan3, Shawna Farquharson4, Claire Mulcahy4, and Roger J Ordidge1
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.

Imaging Whole Mouse Brain Cytoarchitecture by Quantitative Susceptibility Mapping at 10-µm Resolution
Hongjiang Wei1, Luke Xie2, Russell Dibb3, Wei Li4, Kyle Decker3, G. Allan Johnson3,5, and Chunlei Liu1,5
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.

A Novel Method for Background Field Removal in Abdominal QSM
Debra E. Horng1,2, Samir D. Sharma1, Scott B. Reeder1,2,3,4,5, and Diego Hernando1
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.

Toward Iron Distribution Mapping using Quantitative Susceptibility Mapping (QSM): A Comparison of Histological Iron Concentration Maps with Magnetic Susceptibility Maps
Andreas Deistung1, Verena Endmayr2, Simon Hametner2, Hans Lassmann2, Jürgen Rainer Reichenbach1, Simon Daniel Robinson3, Thomas Haider4, Hannes Traxler5, Evelin Haimburger6, Siegfried Trattnig3, and Günther Grabner3,6
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.

Feasibility Study of High Resolution Mapping for Myelin Water Fraction and Frequency Shift using Tissue Susceptibility
Zhe Wu1,2, Hongjian He1,2, Ying Chen1,2, Song Chen1,2, Hui Liu3, Yiping P. Du2, and Jianhui Zhong1,2
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.

Preconditioned QSM to Determine a Large Range of Susceptibility Over The Entire Field Of View from Total Field
Zhe Liu1, Youngwook Kee2, Dong Zhou2, Pascal Spincemaille2, and Yi Wang1,2
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.

MRI in Multiple Sclerosis: The curiosity of apparent susceptibility increases at simultaneous iron loss
Vanessa Wiggermann1,2, Simon Hametner3, Enedino Hernandez-Torres2,4, Verena Endmayr3, Christian Kames5, and Alexander Rauscher2
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.

Quantitative susceptibility mapping of the rat brain after traumatic brain injury
Karthik Chary1, Mikko J. Nissi2,3, Ramón I. Rey4, Eppu Manninen1, Karin Shmueli5, Alejandra Sierra1, and Olli Gröhn1
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.

Suitable reference tissues for quantitative susceptibility mapping of the brain
Sina Straub1, Till Schneider2,3, Martin T. Freitag3, Christian H. Ziener3, Heinz-Peter Schlemmer3, Mark E. Ladd1, and Frederik B. Laun1
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.

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