Cost and Performance of Low Field Magnetic Resonance Imaging

1987 ◽  
Vol 96 ◽  
Author(s):  
Lawrence E. Crooks ◽  
Ching Yao ◽  
Mitsuaki Arakawa ◽  
James D. Hale ◽  
Joseph W. Carlson ◽  
...  

ABSTRACTMagnetic Resonance Imaging technology has advanced on many fronts. Two important areas are the improvement of signal-to-noise levels and the understanding of imaging pulse sequence optimization. Based on these advances, low cost imagers using very low field permanent magnets are providing images of diagnostic quality.

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Michael W. Vogel ◽  
Ruben Pellicer Guridi ◽  
Jiasheng Su ◽  
Viktor Vegh ◽  
David C. Reutens

2021 ◽  
Vol 9 ◽  
Author(s):  
Konstantin Wenzel ◽  
Hazem Alhamwey ◽  
Tom O’Reilly ◽  
Layla Tabea Riemann ◽  
Berk Silemek ◽  
...  

Low-field (B0 < 0.2 T) magnetic resonance imaging (MRI) is emerging as a low cost, point-of-care alternative to provide access to diagnostic imaging technology even in resource scarce environments. MRI magnets can be constructed based on permanent neodymium-iron-boron (NdFeB) magnets in discretized arrangements, leading to substantially lower mass and costs. A challenge with these designs is, however, a good B0 field homogeneity, which is needed to produce high quality images free of distortions. In this work, we describe an iterative approach to build a low-field MR magnet based on a B0-shimming methodology using genetic algorithms. The methodology is tested by constructing a small bore (inner bore diameter = 130 mm) desktop MR magnet (<15 kg) at a field strength of B0 = 0.1 T and a target volume of 4 cm in diameter. The configuration consists of a base magnet and shim inserts, which can be placed iteratively without modifying the base magnet assembly and without changing the inner dimensions of the bore or the outer dimensions of the MR magnet. Applying the shims, B0 field inhomogeneity could be reduced by a factor 8 from 5,448 to 682 ppm in the target central slice of the magnet. Further improvements of these results can be achieved in a second or third iteration, using more sensitive magnetic field probes (e.g., nuclear magnetic resonance based magnetic field measurements). The presented methodology is scalable to bigger magnet designs. The MR magnet can be reproduced with off-the-shelf components and a 3D printer and no special tools are needed for construction. All design files and code to reproduce the results will be made available as open source hardware.


2013 ◽  
Vol 54 (3) ◽  
pp. 253-262 ◽  
Author(s):  
Rebecca Manley ◽  
Andrea R. Matthews ◽  
Federica Morandi ◽  
George A. Henry ◽  
Katherine H. DeAnna ◽  
...  

Author(s):  
Qingqian Guo ◽  
Changyu Ma ◽  
Xin Zhang ◽  
Yajie Xu ◽  
Meisheng Fan ◽  
...  

Ultra-low field magnetic resonance imaging (ULF MRI) is an effective imaging technique that applies the ultrasensitive detector of superconducting quantum interference device (SQUID) sensor to detect the MR signal at a microtesla field range. In this work, we designed and developed a SQUID-based ULF MRI system with a frequency-adjustable measurement field, the performance of which was characterized via water phantoms. In order to enhance the MR signals, a 500 mT Halbach magnet was used to prepolarize the magnetization of the sample prior to excitation. The signal-to-noise-ratio (SNR) of the spin-echo- (SE-) based pulse sequence can reach up to 70 in a single scan. The images were then reconstructed successfully by using the maximum likelihood expectation maximization (MLEM) algorithm based on the backprojection imaging method. It was demonstrated that an in-plane resolution of 1.8 × 1.8 mm2 can be achieved which indicated the feasibility of SQUID-based MRI at the ULF.


2015 ◽  
Vol 59 (2) ◽  
pp. 317-319
Author(s):  
Zbigniew Adamiak ◽  
Yauheni Zhalniarovich ◽  
Paulina Przyborowska ◽  
Joanna Głodek ◽  
Adam Przeworski

AbstractThe aim of the study was to identify magnetic resonance imaging (MRI) sequences that contribute to a quick and reliable diagnosis of brachial plexus tumours in dogs. The tumours were successfully diagnosed in 6 dogs by the MRI with the use of SE, FSE, STIR, Turbo 3 D, 3D HYCE, and GE sequences and the gadolinium contrast agent


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