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Keywords: Low-Field MRI, Low-Field MRI

Point-of-care (POC) low-field MRI systems have a large potential to increase the accessibility and sustainability of MRI in low- and middle-income countries (LMICs). An important step in translating scientific developments from high-income countries to LMICs is technology that can be assembled or constructed locally.  We describe the construction and testing of a POC system on site in Africa. All components to assemble a 50 mT Halbach magnet based system, together with the necessary tools, were air-freighted from The Netherlands to Uganda. With four instructors and six untrained personnel, the complete project from delivery to first image took approximately 11 days.  

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Beatrice Lena¹, Chloé Najac¹, Lena Václavu¹, Thomas O'Reilly¹, and Andrew Webb^1
1Leids Universitair Medisch Centrum, Leiden, Netherlands

Keywords: Low-Field MRI, RF Pulse Design & Fields, Saturation RF pulses

Contrast mechanisms such as T_1ρ and MT are interesting for point-of-care (POC) low field systems, to supplement/augment standard T₁- and T₂- weighting. However they typically require high B₀ homogeneity. Here, we use a high homogeneity Halbach-magnet array POC to perform experiments involving either direct on- or off-resonance pulses, and to calculate T_1ρ and MT ratio in tissue-mimicking phantoms. T_1ρ showed different white matter (WM)/gray matter (GM) contrast compared to T₂. The measured magnetization transfer ratio (MTR) showed higher values in the WM than in the GM.

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Shi Su^1,2, Jiahao Hu^1,2, Linfang Xiao^1,2, Ye Ding^1,2, Vick Lau^1,2, Yujiao Zhao^1,2, Junhao Zhang^1,2, Christopher Man^1,2, Alex T. L. Leong^1,2, and Ed X. Wu^1,2
1Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong, China, ²Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong, China

Keywords: Low-Field MRI, Brain

Recent development of ultra-low-field (ULF) MRI presents opportunities for low-cost and portable brain imaging in point-of-care scenarios or/and low- and mid-income countries. Magnetic resonance angiography (MRA) is an essential part of MR neuroimaging protocols especially for stroke assessment, yet its feasibility at ULF remains unknown.  In this study, we explore the time-of-flight MRA at 0.055 Tesla. We demonstrate cerebral MRA using flow-compensated gradient echo sequences, enabling visualization of main cerebral arteries and veins. We envision that usable and quality brain MRA can be potentially achieved at ULF with further sequence/reconstruction optimization and use of intravascular contrast agent. 

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Koos Zevenhoven¹, Marko Havu¹, Iiro Lehto¹, Antti Mäkinen¹, Juho Luomahaara², Petteri Laine³, Mikko Kiviranta², and Risto J Ilmoniemi^1
1Aalto University, Espoo, Finland, ²VTT, Espoo, Finland, ³MEGIN Oy, Espoo, Finland

Keywords: Low-Field MRI, New Devices, SQUID, MEG

We have built the first full-scale brain scanner performing both MRI and neuromagnetic measurements. Many improvements have been made compared to previous-generation systems. Parts of the system include a helmet-shaped array of 120 superconducting sensors and a pulsed superconducting polarizing coil. An open-geometry coil system provides unobstructed access, and MRI signal acquisition is performed at ultra-low field. The first MEG and MRI data have been successfully obtained with the device. The new prototype is an important milestone on the way towards a commercial implementation.

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Marco Fiorito¹, Mauro Spreiter¹, Mathieu Sarracanie^1,2, and Najat Salameh^1,2
1Center for Adaptable MRI Technology (AMT Center), Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland, ²AMT Center, Institute of Medical Sciences, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom

Keywords: Low-Field MRI, Relaxometry

Quantitative T₁ mapping has proven useful in several clinical applications, nevertheless it is not widely deployed as it generally suffers from long acquisition times. This problem is exacerbated at low magnetic fields, due to inherent lower sensitivity. In spite of more favourable magnetisation properties (e.g., shorter recovery times, higher dispersion), exotic acquisition strategies and reconstruction pipelines are key to make quantitative MRI at low field fast, and compatible with clinical routines. Here, we present a low-rank matrix completion-based reconstruction method applied to heavily undersampled Look-Locker data for accelerated T₁ mapping at 0.1 T.

Parker JB Jenkins¹, Xiaoping Wu², Gregor Adriany², and Mike Garwood^2
1Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States, ²Radiology, University of Minnesota, Minneapolis, MN, United States

Keywords: Low-Field MRI, New Trajectories & Spatial Encoding Methods, RF encoding, Machine Learning, Low Cost MRI

Frequency-modulated Rabi Encoded Echoes (FREE) is a RF encoding technique that has the potential reduce the overall costs of MRI by eliminating B₀ gradient hardware and infrastructure. However, linear encoding quality has limited its efficacy. To address this problem, we present Sequential Gradient Superposition (SGS) FREE. With SGS-FREE we can decompose the net effective RF gradient into a series of sequentially applied RF gradient sets. This ultimately allows imcreased flexability in linear encoding. This simulation study explores the principle and demonstrates high resolution imaging potential with FREE technology.

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David E. J. Waddington¹, Efrat Shimron², Shanshan Shan¹, Neha Koonjoo³, Sheng Shen³, and Matthew S. Rosen^3,4,5
1Image X Institute, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia, ²Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, CA, United States, ³A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁴Harvard Medical School, Boston, MA, United States, ⁵Department of Physics, Harvard University, Cambridge, MA, United States

Keywords: Low-Field MRI, Image Reconstruction

Portable MRI scanners that operate at very low magnetic fields are increasingly being deployed in clinical settings. However, accelerated acquisition and reconstruction methods that boost the quality of low-field MR images are needed to improve the diagnostic accuracy of the modality. Here, we compare leading data-driven and model-driven deep learning frameworks to compressed sensing (CS) for the reconstruction of undersampled ultralow field MRI data, finding that neural network approaches can boost quantitative image reconstruction metrics.

Ting-Ou Liang¹, Erping Li², Wenwei Yu³, and Shao Ying Huang^1
1Singapore University of Technology and Design, Singapore, Singapore, ²Zhejiang University, Hangzhou, China, ³Chiba University, Chiba, Japan

Keywords: Low-Field MRI, Low-Field MRI, back imaging

A compact and lightweight single-sided Inward-outward (IO)-ring permanent magnet array is proposed for back imaging. Its size is 1396×528×1080mm³ and it weighs 924 kg. Within a field-of-view (FoV) of 300×80×20mm³, it has an axial magnetic field with an average strength of 129.8mT, a built-in gradient (averaged at 158mT/m) that corresponds to a radiofrequency (RF) bandwidth of 9.7% and a good linearity with a R²-coefficient of 0.952. It has a compact 5-Gauss zone of 400×320×460mm³.

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Keywords: Low-Field MRI, Relaxometry

We demonstrated quantitative T₂ mapping at 0.064 T using a multi-echo spin-echo sequence and CALIPR subspace constrained image reconstruction. CALIPR reconstruction results had minimal evidence of undersampling, providing better artifact suppression and preservation of fine anatomical detail than compressed sensing reconstruction.

Phantom validation work was performed using 14 vials doped with known concentrations of MnCl₂ and showed a relationship between measured T₂ and MnCl₂ concentration in agreement with expectations from a mathematical model. In-vivo, we demonstrated short acquisition time (8m:40s or 5m:59s), strong agreement with a highly-sampled reference acquisition, and T₂ maps with good contrast between tissue types.

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Andrew T Curtis¹, Sofia Chavez¹, and Jeff Stainsby^1
1Research & Development, Synaptive Medical, Toronto, ON, Canada

Keywords: Low-Field MRI, Tissue Characterization

We report on protocol optimizations to produce white matter nulled images as well as to optimize visualization of subcortical structures. Quantitative T1 mapping of brain tissue at 0.5T estimated the T1 of white and grey matter as 510 and 760 ms respectively. From this an MPRAGE protocol with optimal subcortical matter contrast was found with TI=415ms. Deep brain grey/white matter visualization can be improved with a white matter nulled protocol using TI=250ms. 

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Ally Klassen¹, James Rioux^2,3, Chris Bowen³, Curtis Wiens⁴, Sharon Clarke^5,6, and Steven Beyea^3,7
1Biomedical Engineering, Dalhousie University, Halifax, NS, Canada, ²BIOTIC / Biomedical Translational Imaging Centre, Nova Scotia Health, Halifax, NS, Canada, ³Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada, ⁴Synaptive Medical, Toronto, ON, Canada, ⁵Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada, ⁶Diagnostic Radiology, Nova Scotia Health, Halifax, NS, Canada, ⁷BIOTIC / Biomedical Translational Imaging Centre, IWK Health, Halifax, NS, Canada

Keywords: Low-Field MRI, Susceptibility, Susceptibility distortion

Multi-shot echo planar imaging (EPI) can be used to reduce spatial distortion and improve spatial resolution in diffusion-weighted imaging; however, patient motion between shots can result in large intra-shot phase differences and increased artifact.  It is unknown whether multiplexed sensitivity encoding (MUSE) can be applied to reduce these phase differences in DW-EPI images acquired at low field due to the inherently lower SNR. In this work we evaluate the performance of MUSE in DW-EPI data acquired at 0.5T, in terms of SNR and ghost-to-noise ratio (GNR) as a function of signal averaging, and demonstrate that multi-shot DW-EPI is feasible.

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Jeffery Wong¹, Prakash Kumar¹, Krishna S. Nayak¹, and Ye Tian^1
1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States

Keywords: Low-Field MRI, Low-Field MRI, Speech, RT-MRI

We demonstrate reduced artifacts for real-time MRI of speech production at 0.55T with a gradient echo sequence using spiral out-in sampling, and constrained image reconstruction. This approach avoids banding artifacts experienced by spiral bSSFP sequences, and exhibits reduced blurring artifact compared to a spiral out gradient echo sequence at the same readout duration.

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Shu-Fu Shih^1,2, Zhaohuan Zhang^1,2, Bilal Tasdelen³, Ecrin Yagiz³, Sophia X. Cui⁴, Xiaodong Zhong⁴, Krishna S. Nayak³, and Holden H. Wu^1,2
1Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States, ²Bioengineering, University of California Los Angeles, Los Angeles, CA, United States, ³Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angles, CA, United States, ⁴MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Los Angles, CA, United States

Keywords: Low-Field MRI, Low-Field MRI

Liver fat and R₂* quantification has been extensively validated at 1.5T and 3T. Recently, there is renewed interest in lower-field MRI because of potential advantages such as a larger bore and lower costs. However, it is challenging to acquire images with sufficient signal-to-noise ratio for accurate fat and R₂* quantification at 0.55T. Previous random matrix theory (RMT)-based approaches leverage Gaussian noise characteristics to markedly reduce the noise without compromising the tissue signal. In this work, we investigated a multi-coil multi-contrast RMT-based denoising approach which is compatible with parallel imaging and we demonstrated improved liver fat and R₂* quantification at 0.55T.

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Bili Wang¹, Jerzy Walczyk¹, Mary Bruno¹, Mahesh Keerthivasan², Robert Rehner³, and Ryan Brown^1
1Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), New York University, Grossman School of Medicine, New York City, NY, United States, ²Siemens Medical Solutions USA Inc., Malvern, PA, United States, ³Siemens Healthcare GmbH, Erlangen, Germany

Keywords: Low-Field MRI, Brain

Flexible coils have the potential to improve SNR over rigid coils but have been rarely applied to head imaging. We built a flexible 13-channel coil for 0.55T based on RG-223 cable loops arranged with dodecahedral geometry. The coil closely fit the head and provided 30-50% SNR gain in the ventricles and significant image quality improvements over a conventional rigid coil. While the current minimalistic prototype coil showed promising performance, practical advances, such as an insulating layer that can be easily sanitized and a structure to immobilize the head, must be integrated to make the coil user friendly.

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Keywords: Heart, Low-Field MRI

Real-time MR applications are often highly undersampled due to the high temporal resolution required. Here, we propose a novel linear forward model combining virtual coils and multi-scale low-rank to enable highly accelerated real-time cardiac MR. The virtual coil concept leverages Hermitian symmetry, whereas multi-scale low-rank attempts to model real-time motion as a combination of subspaces across multiple image scales. Experiments in five healthy subjects demonstrate a considerable improvement in image quality over conventional iterative SENSE, enabling real-time cardiac imaging at 0.55T.