Deoni, Sean

ABSTRACT The lower infrastructure requirements of portable ultra‐low field MRI (ULF‐MRI) systems have enabled their use in diverse settings such as intensive care units and remote medical facilities. The UNITY Project is an international neuroimaging network harnessing this technology, deploying portable ULF‐MRI systems globally to expand access to MRI for studies into brain development. Given the wide range of environments where ULF‐MRI systems may operate, there are external factors that might influence image quality. This work aims to introduce the quality control (QC) framework used by the UNITY Project to investigate how robust the systems are and how QC metrics compare between sites and over time. We present a QC framework using a commercially available phantom, scanned with 64 mT portable MRI systems at 17 sites across 12 countries on four continents. Using automated, open‐source analysis tools, we quantify signal‐to‐noise, image contrast, and geometric distortions. Our results demonstrated that the image quality is robust to the varying operational environment, for example, electromagnetic noise interference and temperature. The Larmor frequency was significantly correlated to room temperature, as was image noise and contrast. Image distortions were less than 2.5 mm, with high robustness over time. Similar to studies at higher field, we found that changes in pulse sequence parameters from software updates had an impact on QC metrics. This study demonstrates that portable ULF‐MRI systems can be deployed in a variety of environments for multi‐center neuroimaging studies and produce robust results.

Abstract Purpose Ultra‐low field MRI scanners have the potential to improve health care delivery, both through improved access in areas where there are few MRI scanners and allowing more frequent monitoring of disease progression and treatment response. This may be particularly true in white matter disorders, including leukodystrophies and multiple sclerosis, in which frequent myelin‐sensitive imaging, such as magnetization transfer (MT) imaging, might improve clinical care and patient outcomes. Methods We implemented an on‐resonance approach to MT imaging on a commercial point‐of‐care 64 mT scanner using a non‐balanced steady‐state free precession sequence. Phantom and in vivo experiments were used to evaluate and optimize the sequence sensitivity and reproducibility, and to demonstrate in vivo performance and inter‐site reproducibility. Results From phantom experiments, T 1 and T 2 effects were determined to have a negligible effect on the differential MT weighting. MT ratio (MTR) values in white matter were 23.1 ± 1.0% from 10 healthy volunteers, with an average reproducibility coefficient of variation of 1.04%. Normal‐appearing white matter MTR values in a multiple sclerosis participant (21.5 ± 6.2%) were lower, but with a similar spread of values, compared to an age‐matched healthy volunteer (23.3 ± 6.2%). Conclusion An on‐resonance MT imaging approach was developed at 64 mT that can be performed in as little as 4 min. A semi‐quantitative myelin‐sensitive imaging biomarker at this field strength is available for assessing both myelination and demyelination.