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Anders Dyhr Sandgaard¹, Valerij G. Kiselev², Noam Shemesh³, and Sune Nørhøj Jespersen^1,4
1Center for functionally integrative neuroscience, department of clinical medicine, Aarhus University, Aarhus, Denmark, ²Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany, ³Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, ⁴Department of Phsysics and Astronomy, Aarhus University, Aarhus, Denmark

Keywords: Susceptibility, Quantitative Susceptibility mapping

Magnetic susceptibility can provide valuable information about chemical composition and microstructural organization in tissues. However, its estimation from the MRI signal phase is particularly difficult, as it depends on both magnetic tissue properties on all length scales. Here we investigate the feasibility of inverting our recently presented model of WM magnetic microstucture to estimate susceptibility. This is done on a digital brain phantom based on actual dMRI measurements of an ex-vivo mouse brain at ultra-high field.

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Lin Chen^1,2, Deng Mao³, Guillaume Gilbert⁴, Maarten Versluis⁵, Peter van Zijl^1,2, and Xu Li^1,2
1Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ³MR Clinical Science, Philips Healthcare, Baltimore, MD, United States, ⁴MR Clinical Science, Philips Healthcare, Mississauga, ON, Canada, ⁵MRI Clinical Science, Philips Healthcare, Best, Netherlands

Keywords: Microstructure, White Matter

A hollow cylinder fiber model (HCFM) with two orientation-dispersed fiber populations was used to characterize white matter microstructure-based susceptibility effects. The resulting TE-dependent frequency shifts were fitted with a curve function parameterized by a microstructure induced frequency difference (Δf) and bulk susceptibility induced frequency shift (C_f). Local frequency and QSM reconstruction using the fitted C_f versus using weighted echo averaging were compared by a head phantom and in vivo human brain data. Δf provided a useful contrast to illustrate the underlying white matter microstructure and C_f helped to improve the quantification accuracy of tissue magnetic susceptibility using QSM.

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Gregory Simchick^1,2, Ronald T Wakai², Roland Fischer³, Oswaldo Baffa^2,4, Kevin Pratt⁵, Doug Paulson⁵, Scott B Reeder^1,2,6,7,8, and Diego Hernando^1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ³University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ⁴Physics, University of Sao Paulo, Ribeirao Preto, Brazil, ⁵Tristan Technologies, Inc, San Diego, CA, United States, ⁶Medicine, University of Wisconsin-Madison, Madison, WI, United States, ⁷Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁸Emergency Medicine, University of Wisconsin-Madison, Madison, WI, United States

Keywords: Validation, Susceptibility

Many quantitative susceptibility mapping (QSM) studies lack independent reference measurements of susceptibility (χ) for validation. In this work, superconducting quantum interference device (SQUID-) based susceptometry and QSM data were acquired for phantoms with varying manganese chloride (MnCl₂) concentrations. χ_SQUID demonstrated low uncertainty and excellent agreement with the nominal susceptibility values. χ_QSM and R2* agreed relatively well with the nominal values and previously published results. However, χ_QSM demonstrated higher uncertainty in comparison to χ_SQUID. SQUID susceptometry has the potential to identify sources of bias and variability in QSM methods by serving as an independent reference measurement of susceptibility.

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Keywords: Susceptibility, Quantitative Susceptibility mapping

The inversion of tissue magnetic susceptibility from a single-orientation phase measurement is an ill-posed problem. In this work, we propose a novel learning-based constrained reconstruction to integrate the jointly learned tissue field and susceptibility priors with the physics-based dipole inversion formalism such that the non-Gaussian model biased caused by the substantial errors in the estimated tissue field and the streaking artifacts in the tissue susceptibility can be effectively reduced. An efficient solver was also developed to solve the optimization problem. We demonstrated the superior performance of the proposed method over the state-of-the-art dipole inversion method using in vivo datasets.

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Siyun Jung¹, Soohyun Jeon¹, and Dong-Hyun Kim^1
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of

Keywords: Susceptibility, Quantitative Susceptibility mapping

Acquisition of whole brain Quantitative Susceptibility Mapping (QSM)  is time-consuming that requires the patient’s effort. On the other hand, limiting the QSM field-of-view to only the region of interest (e.g., deep grey matter) can shorten scan time and lessen the patient’s burden. However, reducing spatial coverage degrades conventional background field removal performance, resulting in an underestimation of susceptibility values. To overcome these limitations, we propose a harmonic field extension method using a physics-informed generative adversarial network. According to the experimental results, the proposed method significantly improves the accuracy of both the local field and QSM at reduced spatial coverage.

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Patrick Fuchs¹, Carlos Milovic², and Karin Shmueli^1
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²School of Electrical Engineering, Pontificia Universidad Catolica de Valparaiso, Valparaiso, Chile

Keywords: Susceptibility, Quantitative Susceptibility mapping

Since its inception, the most recent QSM challenge and corresponding dataset have helped to improve dipole-inversion algorithms. To date, only global metrics have been used to evaluate performance of these algorithms. Typically, in clinical applications of QSM, the susceptibility value in a specific brain region or structure is of interest. Therefore, we compared the accuracy of QSM algorithms in 28 regions in several ways including regional metrics and median differences, which is important to facilitate clinical translation of QSM. We found that, according to regional metrics, some direct QSM methods are surprisingly accurate considering their low global scores.

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Sooyeon Ji¹, Juhyung Park¹, Hyeong-Geol Shin^2,3, Minjun Kim¹, and Jongho Lee^1
1Department of Electrical Computer Engineering, Seoul National University, Seoul, Korea, Republic of, ²Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

Keywords: Susceptibility, Data Processing

Fine structures in the human brain are delineated in the positive and negative susceptibility maps reconstructed in less than 25 min of scan time. The reconstruction pipeline consists of four deep learning networks, each of which performs multi-echo denoising, QSM reconstruction, χ-separation, and super-resolution. The reconstructed maps delineate two laminar structures within globus pallidus, the fibers of internal capsule, and nigrosome structures in the substantia nigra.

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Rong Guo^1,2, Yudu Li^2,3, Yibo Zhao^2,4, Aaron Anderson², Pallab Bhattacharyya⁵, Mark Lowe⁵, Yao Li⁶, Brad Sutton^2,3,4,7,8, and Zhi-Pei Liang^2,3,4
1Siemens Medical Solutions USA, Inc., Urbana, IL, United States, ²Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ³National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁴Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁵Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, ⁶School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ⁷Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁸Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Keywords: Susceptibility, Quantitative Susceptibility mapping

The feasibility of simultaneous QSM and MRSI has been recently demonstrated using SPICE. But the resolution of QSM obtained by SPICE at 7T is limited to only 3 mm due to bandwidth requirements. To overcome the resolution limitation, this work proposes a fast acquisition sequence for high-resolution encoding, and a model-based method to reconstruct from sparse sampling. As a result, submillimeter QSM can be achieved within only 1 minute, which enables simultaneous QSM (at 0.8 mm) and MRSI (at 3.0 mm) in an 8-minute scan at 7T.

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Kyu-Jin Jung¹, Thierry G.Meerbothe^2,3, Chuanjiang Cui¹, Mina Park⁴, Jaeuk Yi¹, Cornelis A.T. van den Berg^2,3, Dong-Hyun Kim¹, and Stefano Mandija^2,3
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of, ²Department of Radiotherapy, UMC Utrecht, Utrecht, Netherlands, ³Computational Imaging Group for MR Therapy and Diagnostics, UMC Utrecht, Utrecht, Netherlands, ⁴Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea, Republic of

Keywords: Electromagnetic Tissue Properties, Electromagnetic Tissue Properties

This work presents a neural network informed fitting approach for conductivity reconstructions in MR-Electrical Properties Tomography. First, an artificial neural network is used to predict weights from T2-weighted images. These weights are used in a weighted fitting approach to calculate polynomial coefficients that parametrize the phase map. The conductivity is finally reconstructed from these coefficients. The reconstruction approach is tested on simulated data and in-vivo data and shows more accurate results than conventional fitting methods.

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Thierry G. Meerbothe^1,2, Cornelis A.T. van den Berg^1,2, and Stefano Mandija^1,2
1Department of Radiotherapy, UMC Utrecht, Utrecht, Netherlands, ²Computational Imaging Group for MR Therapy and Diagnostics, UMC Utrecht, Utrecht, Netherlands

Keywords: Electromagnetic Tissue Properties, Electromagnetic Tissue Properties

This work presents ADEPT, A Database for MR-Electrical Properties Tomography applications. ADEPT is an open database that contains simulated MRI field data from electromagnetic simulations on brain models with and without tumor inclusion for EPT reconstructions. These data can serve as common ground to benchmark EPT reconstruction methods developed in different centers and will alleviate the computational burden for the creation of simulated data for training data-driven EPT methods. In the future, the database will be openly accessible and will be extended with phantom and in-vivo data. Other centers are also encouraged to share their data.

Henghui Liu¹, Guofang Xu¹, Yinhao Ren¹, Feng Liu², Xiang Nan³, and Jijun Han^1
1School of Biomedical Engineering, Anhui Medical University, Hefei, China, ²School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia, ³Department of Anatomy, Anhui Medical University, Hefei, China

Keywords: Electromagnetic Tissue Properties, Liver

Magnetic resonance electrical properties tomography provides a non-invasive approach to extracting pixel-wise electrical properties by B1 field mapping. However, there is a void in our understanding of the underlying biophysical mechanism of electrical properties changes accompanied by pathogenesis at the microscopic cellular level. In this work, we build a microscopic tissue model to study fatty liver disease, which focuses on exploring the relationship between fat fraction and electrical properties. Our findings could bridge microscopic lesions and pixel-wise EPT images and may offer a novel strategy for retrieving electrical properties via fat quantification techniques such as Dixon directly.

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Nitish Katoch¹, Bup Kyung Choi¹, Ji Ae Park², Tae Hoon Kim³, Young Hoe Hur⁴, Jin Woong Kim⁵, and Hyung Joong Kim^1
1Department of Biomedical Engineering, Kyung Hee University, Seoul, Korea, Republic of, ²Division of Applied RI, Korea Institute of Radiological and Medical Science, Seoul, Korea, Republic of, ³Medical Convergence Research Center, Wonkwang University Hospital, Iksan, Korea, Republic of, ⁴Department of Hepato-Biliary-Pancreas Surgery, Chonnam National University Medical School, Gwangju, Korea, Republic of, ⁵Department of Radiology, Chosun University Hospital and Chosun University College of Medicine, Gwangju, Korea, Republic of

Keywords: Electromagnetic Tissue Properties, Electromagnetic Tissue Properties, Electrical Conductivity, MREPT, Radiation Therapy, High-field MRI

Radiation-induced injury can damage normal tissues caused by unintentional exposure to ionizing radiation. Image-based evaluation of tissue damage by irradiation has an advantage for the early assessment of therapeutic effects. This study aims to non-invasively evaluate tissue response following radiation therapy in phantoms and in vivo mouse brains at 3T and 9.4T MRI scanner. Due to changes in ionic strength in tissue after radiation, magnetic resonance (MR)-based electrical properties tomography could be a suitable imaging tool to assess the radiation therapy response on biological tissues.

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Michelle Medina^1,2,3, Lara Bartels^1,2,3, Jonathan Doucette^1,2,3, Andrew Yung⁴, Kirsten Bale⁴, Piotr Kozlowski^4,5, Christoph Birkl^4,6, and Alexander Rauscher^1,2,3,7
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, ²UBC MRI Research Center, Vancouver, BC, Canada, ³Pediatrics, University of British Columbia, Vancouver, BC, Canada, ⁴UBC MRI Research Centre, Vancouver, BC, Canada, ⁵Radiology and Urologic Sciences, University of British Columbia, Vancouver, BC, Canada, ⁶Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria, ⁷Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada

Keywords: Microstructure, White Matter, Relaxometry

In this study, we investigated the orientation dependence of T2 in fresh and fixed spinal cord white matter (WM). Scans from three pig spinal cord tissues were acquired at 7T at 6 different orientations with respect to the main magnetic field. We found a considerable orientation dependence in the short fraction relaxation rate R2 (=1/T2) in fresh WM as opposed to a weak orientation effect in fixed WM. To our knowledge, this is the first direct comparison of orientation dependence in a WM tissue sample in the fresh and fixed state. Orientation dependence was not observed in long fraction R2.

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Jitka Starekova¹, David Rutkowski², Won C Bae³, Hung Do⁴, Ananth Madhuranthakam⁵, Vadim Malis³, Sujoy Mukherjee⁵, Sheng Qing Lin⁵, Suraj Serai⁶, Takeshi Yokoo⁵, Scott B Reeder^1,7,8,9,10, Jean H Brittain², and Diego Hernando^1,8
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Calimetrix, Madison, Wisconsin, Madison, WI, United States, ³Radiology, University of California, San Diego, San Diego, CA, United States, ⁴Canon Medical Systems, Tustin, CA, United States, ⁵Radiology, UT Southwestern, Medical Center, Dallas, TX, United States, ⁶Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States, ⁷Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁸Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ⁹Medicine, University of Wisconsin-Madison, Madison, WI, United States, ¹⁰Emergency Medicine, University of Wisconsin-Madison, Madison, WI, United States

Keywords: Validation, Phantoms

Reliable, quantitative assessment of fat and iron is important in the management of chronic liver diseases. Confounder-corrected chemical-shift-encoded (CSE)-MRI estimates proton-density fat-fraction (PDFF) and R2* as quantitative biomarkers for fat and iron, which have been shown to be highly reproducible across centers, field strengths and manufacturers. However, reproducibility in the setting of concomitantly high levels of fat and iron is poorly understood.

To ensure the fidelity of CSE-MRI in clinical routine, a validation study was performed under controlled conditions on a phantom that modulates fat and iron simultaneously. Excellent multi-center and multi-vendor reproducibility of CSE-MRI PDFF and R2* was found.

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Keywords: Validation, Brain, Marmoset

Several studies have compared myelin-sensitive MRI maps to myelin staining to demonstrate the degree of correlation of the MRI metric with myelin content. This study in the common marmoset compares six myelin-sensitive MRI metrics acquired in vivo to stains for myelin, cell nuclei, and ferritin. T₂^*-based myelin water fraction (MWF) and inhomogeneous magnetization transfer saturation (ihMT_sat) presented the greatest specificity for myelin content, with ihMT_sat having a higher signal in grey matter regions. T₁w/T₂w had the strongest correlation with the iron-storage protein ferritin, and T₂^* presented the greatest correlation with the cell nuclei stain.