Detection of tiny oscillatory magnetic fields using low-field MRI: A combined phantom and simulation study

Magnetic resonance imaging simulation with spin-lock preparations to detect tiny oscillatory magnetic fields

Low-field magnetic resonance (MR) images suffer from inherent low Signal-to-noise ratio (SNR) compared to images acquired using high-field MRI scanners. Denoising these images could help and improve further processing, such as image segmentation. In this paper a Convolutional Neural Network AutoEncoder was designed with a dedicated loss function for noise reduction. A transfer learning approach was employed in which high-field high-SNR MR images, served as targets for learning from their noise-added counterparts. Evaluation of network performances was measured on both noisy high-field and low-field MR images that had not been included in the learning step. The proposed method outperformed major denoising methods applied to MR images. SNR improvements were quantified on low-field MR images.

Foot imbalance and malalignment of the digits are common in horses. Angle and distance measurements performed on bones, joints and hoof wall on radiographs provide essential guidance for precise corrective trimming and shoeing. This study aimed to investigate, if selected standing low-field magnetic resonance (MR) images can be used to accurately measure dorsopalmar and lateromedial foot conformation parameters in comparison to the radiographic gold standard. Images of 100 horses referred for standing low-field MR examination were selected. Foot conformation angles and distances were measured and compared between radiographs and MR images. Measurements from most imaging sources were significantly different from each other. Moderate to high correlation of foot conformation angles between radiographs and MR images in the lateromedial and dorsopalmar planes was found, with exception of the proximal interphalangeal joint angle, where there was only moderate agreement between radiographs and the 5-plane MR pilot (0.47, P < .001) and between radiographs and the 3-plane MR pilot (0.4, P < .001), respectively. Measurement of foot conformation parameters from low-field MR images should be used with caution in clinical practice and acquisition of current foot radiographs immediately before or after MR examination should be considered to facilitate precise trimming and shoeing.

Over the past decade, the resurgence of low-field (LF) magnetic resonance imaging (MRI) sensor systems designed to operate up to 1 tesla range has proven well suited to inspire new solutions and design strategies to address frontline medical challenges where environmental factors are most extreme. Examples of successful low-field MRI devices in resource-limited environments include: (1) classification of infant hydrocephalus in Africa and (2) in remote small hospitals where the low-field scanner travels to the patient's bedside to observe volumetric changes in brain structure [1,2]. These low-field MRI design examples have been effective in leveraging MRI information in the setting where it is used with minimal available resources. In developing countries, access to high-field (HF) MRI is limited and requires support and infrastructure to be used. These lower-cost systems can potentially benefit from many developments that have occurred in higher fields, such as signal-to-noise dependence on static magnetic fields and hardware components (i.e., magnet, gradient coils, etc.) [3]. In addition, improvements in machine learning now provide superior noise reduction compared to traditional methods, resulting in improved performance with smaller size and lower power consumption. With improved access to medical imaging equipment, people around the world who cannot afford it due to the high cost of conventional MRIs will be able to obtain high- quality imaging data with improved contrast resolution and acquisition times. SNR (signal-to-noise ratio) is an important measure of the quality of a signal in low-field MRI. The amount of useful information in a signal compared to background noise directly affects the effectiveness of a low-field scan [4].

A cross-sectional observational study. To investigate whether there is a difference in findings of lumbar Modic changes in low-field (0.3 T) magnetic resonance imaging (MRI) compared with high-field (1.5 T). It is a challenge to give patients with low back pain a specific diagnosis. Modic changes as seen on MRI have been reported to be a possible source of pain. However, it is unclear whether the diagnosis is independent on the field strength. Twenty patients with Modic changes, 11 women and 9 men (mean age, 53.6 yr; range, 29-81 yr), with or without sciatica, seen in a Danish outpatient low back pain clinic were included. All patients obtained MRI scans on both a high-field and a low-field MRI scanner. Two radiologists evaluated all lumbar endplates independently, using a standardized evaluation protocol. Kappa statistics were used to analyze the interobserver reproducibility. We used paired t test to analyze the difference between low- and high-field MRI. The total number of Modic changes diagnosed with high-field MRI was significantly higher than that with low-field MRI. However, 3 to 4 times as many Modic type 1 changes were found with low-field MRI compared with high-field MRI. Contrarily, with high-field MRI type 2 changes were diagnosed twice as often. There was a significant difference between low- and high-field MRI regarding the overall prevalence of any Modic change, but this had opposite directions for types 1 and 2: type 2 dominated in high field and conversely in high field [corrected]. The type of MRI unit should be taken into consideration when diagnosing patients with Modic changes

High- and low-field magnetic resonance (MR) imaging systems are available for clinical diagnosis of collateral desmopathy of the equine distal interphalangeal joint (DIJ). Knowledge of the normal appearance, size, shape,and signal variation of these ligaments on high- and low-field MR images is essential when assessing desmopathy detected by MR imaging. However, there are no descriptions of the normal features of DIJ collateral ligaments on images obtained with a standing low-field MR system. Low-field MR imaging characteristics of normal collateral ligaments of the DIJ of cadaver feet were corroborated with high-field MR imaging and histologic examination to exclude desmopathy. The size and shape of the collateral ligaments of the DIJ was similar among limbs; however, the signal pattern of the ligaments varied depending on the segment of the ligament being assessed and the MR sequence used. In limbs positioned within the magnet as recommended for clinical MR imaging, collateral ligaments of the DIJ have heterogeneous signal pattern with a peripheral region of increased signal intensity at the level of the middle phalanx that can be confused with a desmopathy.The MR imaging characteristics of normal collateral ligaments of the DIJ are related to their anatomy and fiber configuration. The results of this study support the presence of magic angle effect within the axial margin of the CL of the DIJ at the level of fiber divergence within the proximal to mid-portion of the ligament.

Extracting quantitative information of neuronal signals by non-invasive imaging is an outstanding challenge for understanding brain function and pathology. However, state-of-the-art techniques offer low sensitivity to deep electrical sources. Stimulus induced rotary saturation is a recently proposed magnetic resonance imaging sequence that detects oscillatory magnetic fields using a spin-lock preparation. Phantom experiments and simulations proved its efficiency and sensitivity, but the susceptibility of the method to field inhomogeneities is still not well understood. In this study, we simulated and analyzed the dynamic of three spin-lock preparations and their response to field inhomogeneities in the presence of a resonant oscillating field. We show that the composite spin-lock preparation is more robust against field variations within the double resonance effect. In addition, we tested the capability of the chosen composite spin-lock preparation to recover information about the spectral components of a composite signal. This study sets the bases to move one step further towards the clinical application of MR-based neuronal current imaging.

Background: Low-field magnetic resonance imaging (LF-MRI) has become a valuable tool in the diagnosis of brain tumors due to its high spatial resolution and ability to acquire images in a short amount of time. However, the use of LF-MRI for intraoperative imaging during brain tumor surgeries has not been extensively studied. The aim of this systematic review is to investigate the impact of low-field intraoperative magnetic resonance imaging (LF-IMRI) on the duration of brain tumor surgery and the extent of tumor resection.Methods: A comprehensive literature search was conducted using PubMed, Scopus, and Google Scholar from February 2000 to December 2022. The studies were selected based on the inclusion criteria and reviewed independently by two reviewers. The gathered information was organized and analyzed using Excel.Results: Our review of 21 articles found that low-field intraoperative MRI (LF-IMRI) with a field below 0.3T was used in most of the studies, specifically 15 studies used 0.15T LF-IMRI. The T1-weighted sequence was the most frequently reported, and the average scanning time was 24.26 min. The majority of the studies reported a positive impact of LF-IMRI on the extent of tumor resection, with an increase ranging from 11% to 52.5%. Notably, there were no studies describing the use of ultra-low-field (ULF) intraoperative MRI.Conclusion: The results of this systematic review will aid neurosurgeons and neuroradiologists in making informed decisions about the use of LF-MRI in brain tumor surgeries. Further, research is needed to fully understand the impact of LF-MRI in brain tumor surgeries and to optimize its use in the clinical setting. There is an opportunity to study the utility of ULF-MRI in brain tumor surgeries.

We utilize a permanent magnet (PM) pair for sample prepolarization to improve the signal-to-noise ratio of low-field nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) measurements with a tuned high- Tc rf superconducting quantum interference device as a signal detector. The sample is first prepolarized in the gap of the PM pair and then automatically transported to the measuring position underneath the tuned superconducting quantum interference device in a magnetically shielded room. The transportation can be repeated in order to perform signal averaging. Because of the strong magnetic polarization field of about 1 T and the highly sensitive detector with a noise floor of about 7 fT/√Hz, the nuclear magnetic resonance spectrum of 0.5 ml fluorobenzene reaches a signal-to-noise ratio of about 13 in a single measurement, and 55 with 30 times averaging. The MRI images are acquired by using filtered back projection reconstruction. Twenty-four projections are obtained by recording free induction decay or spin echo signals with a gradient field applied at angular steps of 7.5° each. Two-dimensional low-field MRI images of pepper and carrot pieces were acquired with different numbers of averages. Here, a spatial resolution of about 0.3 mm × 0.3 mm is achieved.

Nuclear magnetic resonance imaging (MRI) has become the gold standard for many imaging applications. It is routinely used to detect diseases and tissue pathologies due to its superior soft tissue contrast and high spatial resolution. Unlike other imaging techniques such as X-rays, computed tomography, it does not harm patients with ionising radiation.However, MRIs are expensive and only a small portion of patients who would benefit from them can access them. The pursuit of higher sensitivity has generated a trend towards increasing the already large static magnetic field. This has improved imaging quality but has made this technology more expensive and further hindered MRI accessibility. The main cost driver of MRI machines is the strong magnet.The collection of techniques being developed to overcome the intrinsic low NMR sensitivity has fostered interest in low field (LF) MRI to improve cost-effectiveness of MRI. First, the purchase and operational cost of LF systems is relatively low. Second, they are more compatible with other instrumentation which enables versatile concepts such as application-specific open systems and intraoperative imaging. LF systems can offer a wide range of configurations by using permanent magnets. Third, the small fringe field lowers the risk to patients and workers and makes the magnet easier to site. Fourth, artefacts which rely on the strength of field are reduced, as well as the specific absorption rate (SAR) in tissues.Ultra-low field (ULF) MRI systems employ field strengths lower than 10 mT. These systems can complement the advantages of LF systems mentioned above with additional potential benefits. The requirement of homogeneity in ULF is relaxed extensively. It is possible to adjust the strength and direction of the measurement field, allowing flexibility in pulse sequences. Moreover, ULF systems operate in the low kHz frequency range, avoiding the need for radio frequency (RF) noise shielding and enhancing T1-weighted contrast.Most ULF MRI research concentrates on using expensive and fragile sensors, produces the magnetic fields through resistive coils and employs linear gradient fields for encoding. Although ULF systems are important low-cost and portable MRI candidates, they still need considerable space to generate linear fields and need expensive and bulky high permeability shielding to suppress ambient noise.This PhD project develops two major solutions towards a portable and low-cost ULF MRI system: a software gradiometer based on machine learning for ambient noise cancellation and a fast iterative algorithm with total variation (TV) regularisation for image reconstruction. In addition, a concept for a dynamical permanent magnet array (PMA) ULF MRI system is proposed with nonlinear 3D spatial encoding.First, I introduce an experimental setup as a platform for evaluating the MR signal in the ULF regime using a Helmholtz coil as a framework. It is composed of a measurement field, an NMR console, a transmit and receive coil, and a shielding box. The NMR signal is successfully acquired and analysed in partial shielding and full shielding. The results suggest that partial shielding of ULF MRI instruments has the potential to generate a strong signal. This system is built for a subsequent study on noise cancellation presented in following chapter.The second study is a convolutional neural network (CNN) based software gradiometer for background noise cancellation. It includes three ambient noise monitoring coils which are placed away from the NMR sensing coil. The noise induced in the sensing coils is estimated using machine learning. The results show that the software gradiometer reduces ambient noise and can be used to relax shielding requirements, thereby reducing the size and weight of the shielding box.The concept of using small magnets for 3D-spatial encoding in dynamical PMA based ULF MRI is described. It uses small rectangular permanent magnets to generate a 3D-spatial encoding field. The encoding magnets move along an optimised trajectory to achieve an encoding matrix with a low condition number. A prototype of the 3D-spatial encoding has been built and its feasibility tested. The described encoding system can reduce the volume and energy requirements and improve the portability of ULF MRI systems.Finally, iterative imaging reconstruction algorithms for ULF MR are studied. The current state-of-the-art methods are evaluated, which includes Simultaneous Iterative Reconstruction Technique (ART/SIRT), Conjugate Gradient Least Squares (CGLS), and the Chambolle-Pock (CP) algorithms. A dynamic weight Column Action Reconstruction Technique (dwCART) method is proposed and applied to image reconstruction with TV regularisation in the setting of undersampling. In the absence of having a finalised prototype to acquire real ULF MRI imaging data, the methods are tested on CT models (using both simulated and real CT data). The dwCART algorithm performed best on the tested CT problems. It paves the way for fast and accurate imaging with the PMA-based ULF MRI system.

We report the use of a low-field magnetic resonance (MR) imaging system for the detection of desmopathy of the collateral ligament of the distal interphalangeal joint and the long-term outcome. Twenty horses were studied and their medical records and MR images were reviewed retrospectively. Long-term follow-up information was obtained by telephonic questionnaires of owners, trainers, or referring veterinarians. Desmopathy of the medial collateral ligament (80%) and enthesopathy of the affected collateral ligament (80%) were common MR imaging features. Treatment consisted of stall rest followed by a rehabilitation period. Additional treatments included shoeing, extracorporeal shock wave therapy, application of a half limb or foot cast, and medication of the distal interphalangeal joint. Twelve (60%) horses returned to their previous level of exercise and maintained their previous level, whereas eight horses had a poor outcome. Low-field MR imaging in the standing patient can be used to detect collateral ligament desmopathy of the distal interphalangeal joint without a need for general anesthesia.

SAT0100 Bone marrow OEDEMA is more associated with rapid radiographic progression than synovitis or bone erosion by using low field MRI in bio-naïve rheumatoid arthritis patients treated with adalimumab and...

Magnetic resonance (MR) examination of the lumbar spine was performed in 51 patients using a resistive magnet with a field strength of 0.02 T. The results at 105 intervertebral levels were compared with those of computed tomography (CT). Due to the extremely low field strength, an unfavourable signal-to-noise ratio degraded the image quality. Some improvement was achieved with the development of a dedicated surface coil. The diagnostic information was not comparable with that obtained with CT, nor was the image quality comparable to that obtained at higher field strengths. Compared with CT there was no false information. Therefore, it is suggested that extremely low field units may permit exclusion of pathology on the basis of a normal examination and in this way help in the selection of those patients who need further investigation and treatment.

Functional magnetic resonance imaging (fMRI) is a unique window to the brain, enabling scientists to follow changes in brain activity in response to hormones, ageing, environment, drugs of abuse and other stimuli. There are two features that make fMRI unique when compared with other imaging modalities used in behavioural neuroscience. First, it can be entirely noninvasive: each animal can serve as its own control over the natural course of its life, vital for following neuroadaptation and other developmental processes critical to understanding behaviour. Second, fMRI has the spatial and temporal resolution to observe patterns of neuronal activity across the entire brain in less than a minute. Although fMRI does not have the cellular spatial resolution of immunostaining, nor the millisecond temporal resolution of electrophysiology, synchronised changes in neuronal activity across multiple brain areas seen with functional MRI can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviours. Thus, fMRI affords a systems approach to the study of the brain, complementing and building from other neurobiological techniques to understand how behaviour is organised across multiple brain regions. In this review, we present a general background to fMRI and the different imaging modalities that can be used in fMRI studies. Included are examples of the application of fMRI in behavioural neuroscience research, along with discussion of the advantages and disadvantages of this technology.

BACKGROUND:Early detection of acute brain injury (ABI) at the bedside is critical in improving survival for patients with extracorporeal membrane oxygenation (ECMO) support. We aimed to examine the safety of ultra–low-field (ULF; 0.064-T) portable magnetic resonance imaging (pMRI) in patients undergoing ECMO and to investigate the ABI frequency and types with ULF-pMRI.METHODS:This was a multicenter prospective observational study (SAFE MRI ECMO study [Assessing the Safety and Feasibility of Bedside Portable Low-Field Brain Magnetic Resonance Imaging in Patients on ECMO]; NCT05469139) from 2 tertiary centers (Johns Hopkins, Baltimore, MD and University of Texas–Houston) with specially trained intensive care units. Primary outcomes were safety of ULF-pMRI during ECMO support, defined as completion of ULF-pMRI without significant adverse events.RESULTS:Of 53 eligible patients, 3 were not scanned because of a large head size that did not fit within the head coil. ULF-pMRI was performed in 50 patients (median age, 58 years; 52% male), with 34 patients (68%) on venoarterial ECMO and 16 patients (32%) on venovenous ECMO. Of 34 patients on venoarterial ECMO, 11 (22%) were centrally cannulated and 23 (46%) were peripherally cannulated. In venovenous ECMO, 9 (18%) had single-lumen cannulation and 7 (14%) had double-lumen cannulation. Of 50 patients, adverse events occurred in 3 patients (6%), with 2 minor adverse events (ECMO suction event; transient low ECMO flow) and one serious adverse event (intra-aortic balloon pump malfunction attributable to electrocardiographic artifacts). All images demonstrated discernible intracranial pathologies with good quality. ABI was observed in 22 patients (44%). Ischemic stroke (36%) was the most common type of ABI, followed by intracranial hemorrhage (6%) and hypoxic-ischemic brain injury (4%). Of 18 patients (36%) with both ULF-pMRI and head computed tomography within 24 hours, ABI was observed in 9 patients with a total of 10 events (8 ischemic, 2 hemorrhagic events). Of the 8 ischemic events, pMRI observed all 8, and head computed tomography observed only 4 events. For intracranial hemorrhage, pMRI observed only 1 of them, and head computed tomography observed both (2 events).CONCLUSIONS:Our study demonstrates that ULF-pMRI can be performed in patients on ECMO across different ECMO cannulation strategies in specially trained intensive care units. The incidence of ABI was high, seen in 44% of ULF-pMRI studies. ULF-pMRI imaging appears to be more sensitive to ABI, particularly ischemic stroke, compared with head computed tomography.