Portable, low-field magnetic resonance imaging enables highly accessible and dynamic bedside evaluation of ischemic stroke

Breast Coil Optimization for Low Field MRI and Future MR-Guided Proton Therapy

OBJECTIVE

Ultra-low field (ULF) magnetic resonance imaging of the breast and chest wall was conducted using optimized radiofrequency (RF) coil designs, and to explore future applications in MR-guided proton therapy (MRgPT), simulation studies of a pencil proton beam trajectory in low and ULFs were conducted.

METHODS

The focus in this study is the RF coil design, which is approached as a multi-objective optimization (MOO) problem and solved using a defined performance metric and Pareto optimality formalism. Our winding pattern algorithm was developed to simultaneously optimize the coil's magnetic field homogeneity, signal-to-noise ratio (SNR), and magnetic field drop-off into the chest wall for improved imaging of organs-at-risk. Five single-channel, transmit/receive breast-shaped RF coils were constructed. 3D phantom MRI was performed at 6.5 mT to evaluate field homogeneity and SNR. The first in vivo breast imaging at 6.5 mT was conducted. Monte Carlo simulations were employed to investigate the effects of copper wire and static field strengths on proton beam deflection.

RESULTS

The MOO method was validated - the observed field homogeneity, the relative ratio of SNRs, and the MRI chest signal agreed for all coils with the simulations. In vivo imaging revealed good breast tissue contrast and clear heart visualization. Our findings indicated that a ∼50 mT field with ∼10 mT/m gradient strengths can minimize proton beam deflection, achieving ∼2 × 2 × 5 mm3 spatial resolution within minutes, supporting the clinical feasibility of MRgPT.

CONCLUSION

Our MOO method can be used to design breast coils that meet a wide range of imaging requirements..

Closed-loop rehabilitation of upper-limb dyskinesia after stroke: from natural motion to neuronal microfluidics

This review proposes an innovative closed-loop rehabilitation strategy that integrates multiple subdomains of stroke science to address the global challenge of upper-limb dyskinesia post-stroke. Despite advancements in neural remodeling and rehabilitation research, the compartmentalization of subdomains has limited the effectiveness of current rehabilitation strategies. Our approach unites key areas-including the post-stroke brain, upper-limb rehabilitation robotics, motion sensing, metrics, neural microfluidics, and neuroelectronics-into a cohesive framework designed to enhance upper-limb motion rehabilitation outcomes. By leveraging cutting-edge technologies such as lightweight rehabilitation robotics, advanced motion sensing, and neural microfluidic models, this strategy enables real-time monitoring, adaptive interventions, and personalized rehabilitation plans. Furthermore, we explore the potential of closed-loop systems to drive neural plasticity and functional recovery, offering a transformative perspective on stroke rehabilitation. Finally, we discuss future directions, emphasizing the integration of emerging technologies and interdisciplinary collaboration to advance the field. This review highlights the promise of closed-loop strategies in achieving unprecedented integration of subdomains and improving post-stroke upper-limb rehabilitation outcomes.

Clinical Neuroimaging Over the Last Decade: Achievements and What Lies Ahead

ABSTRACT

The past decade has witnessed notable advancements in clinical neuroimaging facilitated by technological innovations and significant scientific discoveries. In conjunction with Investigative Radiology's 60th anniversary, this review examines key contributions from the past 10 years, emphasizing the journal's most accessed articles and their impact on clinical practice and research. Advances in imaging technologies, including photon-counting computed tomography, and innovations in low-field and high-field magnetic resonance imaging systems have expanded diagnostic capabilities. Progress in the development and translation of contrast media and rapid quantitative imaging techniques has further improved diagnostic accuracy. Additionally, the integration of advanced data analysis methods, particularly deep learning and medical informatics, has improved image interpretation and operational efficiency. Beyond technological developments, this review highlights basic neuroscience findings, such as the discovery and characterization of the glymphatic system. These insights have provided a deeper understanding of central nervous system physiology and pathology, bridging the gap between research and clinical applications. This review integrates these advancements to provide an overview of the progress and ongoing challenges in clinical neuroimaging, offering insights into its current state and potential future directions within the broader field of radiology.

Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques

OBJECTIVE

Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed.

METHODS

First, fast and high-quality unshielded imaging is achieved using active electromagnetic shielding and basic super-resolution. Then, the speed of basic super-resolution imaging is further improved by reducing the number of excitations. Next, the feasibility of using cross-field super-resolution to map low-field low-resolution images to high-field ultra-high-resolution images is analyzed. Finally, by cascading basic and cross-field super-resolution, the quality of the low-field low-resolution image is improved to the level of the high-field ultra-high-resolution image.

RESULTS

Under unshielded conditions, our 0.2 T scanner can achieve image quality comparable to that of a 1.5 T scanner (acquisition resolution of 512 × 512, spatial resolution of 0.45 mm2), and a single-orientation imaging time of less than 3.3 min.

DISCUSSION

The proposed strategy overcomes the physical limitations of the hardware and rapidly acquires images close to the high-field level on a low-field unshielded MRI scanner. These findings have significant practical implications for the advances in MRI technology, supporting the shift from conventional scanners to point-of-care imaging systems.

Ultra-low field magnetic resonance breast imaging in prone and seated positions for radiation therapy

Background & purpose

The aim of this first-in-human study was to investigate the potential of ultra-low field (ULF) magnetic resonance imaging (MRI) at 6.5 mT for breast imaging in healthy female participants in prone and seated positions for radiation therapy, especially compact proton therapy systems.

Materials & methods

An experimental setup for breast imaging in prone and seated positions utilizing an ULF MRI scanner and a conical RF coil was developed. ULF MR images of the left breast of ten healthy women were acquired in prone and seated positions using a 3D balanced steady-state free precession sequence without the use of contrast agents. The visibility of the breast outline, chest wall, and cardiac silhouette in prone and seated position ULF breast MR images was evaluated by two radiation oncologists (ROs) and two radiation therapists (RTTs), respectively.

Results

ULF breast MRI obtained at 6.5 mT can show breast outline, chest wall, and cardiac silhouette in prone and seated positions. ULF prone/seated images were found to be acceptable by the ROs (RTTs) for treatment planning (setup) purposes in 100%/95% (95%/85%) of cases for breast outline visibility, in 70%/50% (75%/70%) of cases for chest wall visibility, and in 65%/65% (0%/10%) of cases for cardiac silhouette visibility.

Conclusions

This proof-of-concept study demonstrated that breast imaging is feasible in prone and seated positions utilizing ULF MRI and partially suitable for treatment planning and setup in proton therapy. Yet an increased spatio-temporal resolution is required for applications to MRI-guided proton therapy. ULF MRI may enable position monitoring and adaptive treatment procedures in radiation therapy.

Tips and challenges for clinical use and interpretation of low field portable MRI in neuroimaging

Low field portable MRI (LF pMRI) is a new imaging tool that holds promise in offering a safe, cost-effective, point-of-care imaging solution in neuroimaging. There are however unique interpretive challenges and operational factors and limitations in its implementation in clinical practice. This paper aims to provide a comprehensive guide on the tips and tricks of interpreting LF pMRI, specifically the Hyperfine Swoop® MRI system, which operates at 0.064 T and is currently the only FDA and Health Canada approved LF pMRI system. This paper explores the operational aspects and interpretation challenges of low-field MRI, such as patient positioning, protocol selection, and the appearance of artifacts and common pathologies. Using illustrative examples, we aim to guide current and future operators of LF pMRI to optimize performance, provide accurate diagnoses, and avoid common pitfalls.

Case Report: Ultralow-field portable MRI improves the diagnosis of congenital hydrocephalus

Introduction

Congenital hydrocephalus is an increasing condition both in high as in low and middle income countries. Main causes include aqueductal stenosis, neonatal central nervous system infections, intracranial hemorrhage, malformations and tumors. Investigation of its etiology should include magnetic resonance imaging (MRI) to detect especially pathologies of the fossa cranii posterior. However, MRI is not available to every infant presenting with congenital hydrocephalus especially in those countries with the highest prevalence. New portable ultralow-field MRI (ULF) allows low resource and bedside imaging and thus widens the access to MRI for those infants. This study presents two cases of newborns with congenital hydrocephalus who underwent ULF scanning revealing a tumor of the fossa cranii posterior as cause of hydrocephalus. This study shows that ULF scanning allows to detect and characterize brain tumors as well as metastases.

Setting and patients

In this case report, we present two cases of newborns antenatally diagnosed with hydrocephalus with no further pathology detected in repeated cranial ultrasound and, in one case, fetal MRI. We performed ULF imaging using a portable 0.064T MRI during natural sleep and high-field 3T MRI to investigate the etiology of congenital hydrocephalus in these infants.

Main results

ULF imaging revealed a tumor of the fossa cranii posterior in both cases. MRI signalling detected in ULF imaging was specific for each tumor (ATRT, low grade glioma). In one case, ULF imaging also detected intracerebral metastasis.

Conclusions

We demonstrated that ULF imaging is able to detect tumors of the fossa cranii posterior that are not detected on ultrasound and shows their specific MR-signalling as well as detect metastasis. Additionally, compared to 3T MRI, ULF MRI was able to reveal significant findings while requiring fewer resources and being easier to perform. Therefore, we propose that children with congenital hydrocephalus not showing any abnormalities on cranial ultrasound should undergo ULF MRI. This imaging modality holds potential for monitoring neonatal tumors and detecting metastasis.

Portable ultra-low-field MRI for progressive multifocal leukoencephalopathy: Case studies, sensitivity, and potential applications

BACKGROUND AND OBJECTIVE

Progressive multifocal leukoencephalopathy (PML) is a severe, disabling infection caused by JC virus reactivation. PML-related disability complicates the MRI monitoring needed to assess treatment interventions in clinical trial or compassionate use settings. Portable ultra-low-field MRI (pULF-MRI) offers a convenient approach when such frequent imaging is needed. We evaluated the potential utility of pULF-MRI as an adjunctive tool for decreasing the burden of clinical study participation and clinical management in PML.

METHODS

We examined paired high-field (HF) and pULF-MRI scans from 11 patients, aged 49 ± 15 years. pULF-MRI images with corresponding HF-MRI were coupled to depict key imaging findings of PML, including three patients with longitudinal evaluations, one with bedside pULF-MRI. The images were then independently assessed by two blinded raters, not involved in image acquisition or initial evaluations, who sequentially rated diagnostic accuracy of pULF-MRI scans compared to the HF-MRI. Longitudinal evaluations were performed for three patients, one with bedside pULF-MRI.

RESULTS

T2-FLAIR lesions were detected with pULF-ULF in all cases when present on HF-MRI. Median sensitivity and specificity were 62% and 100%, respectively. T1WI hypointense areas showed similar performance. Focal volume loss was present in 8/11 HF-MRI scans, with sensitivity and specificity of detection by pULF-MRI of 100% and 94%, respectively. Contrast enhancement was seen in a single case on both pULF- and HF-MRI. Follow-up pULF-MRI showed lesion changes in two cases, and stable findings in one case, consistent with HF-MRI.

DISCUSSION

pULF-MRI shows promise in evaluation and monitoring of PML, showing moderate-to-high accuracy even when evaluations were unaided by HF-MRI. Our results highlight a potential application of pULF-MRI for facilitating participation in PML clinical research and more generally as a way to reduce burden of clinical management for this disabled patient population.

Recent advances in portable, low-field magnetic resonance imaging in cerebrovascular disease

PURPOSE OF REVIEW

This review aims to describe recent advances in low-field (0.064 T) magnetic resonance imaging (LF-MRI) of cerebrovascular disease, including ischemic and hemorrhagic stroke and white matter hyperintensities.

RECENT FINDINGS

Since 2023, several studies have highlighted the rapidly changing landscape of portable, low-field MRI (LF-MRI) and its applications in stroke and cerebrovascular disease. The advantages of using LF-MRI in these settings are multifold: cheaper and dynamic imaging of this patient population confers closer observation during the acute and chronic stages of cerebrovascular disease. Initial deployments of the device span a variety of acute and emergency settings, including imaging around thrombolytic administration, endovascular reperfusion, intracerebral hemorrhage management, and cardiovascular intensive care. LF-MRI also has an important role in cerebrovascular disease monitoring and prevention, namely white matter hyperintensity (WMH) progression and vascular and Alzheimer's dementia. Early studies suggest reliable sensitivity and specificity for these pathologies. With further improvements to LF-MRI hardware, software and postprocessing on the horizon, we anticipate the device's ability to provide inexpensive and flexible neuroimaging to a wide array of healthcare settings that treat, prevent, and manage cerebrovascular disease.

SUMMARY

Recent studies indicate that LF-MRI promotes rapid, cost-effective, and clinically useful neuroimaging at various clinical timepoints throughout stroke and cerebrovascular disease progression and management.

Learning to build low-field MRIs for remote northern communities

Low-field Magnetic Resonance Imaging (MRI) has the potential to provide autonomous accessible neuroimaging in remote communities, particularly in the Canadian north. Remoteness necessitates that these MRIs be built and maintained within the communities. This approach not only ensures that the MRIs remain operational but will also allow the youth from the communities to pursue technical careers at home. The first step in this vision is to establish that the technical resources needed for building MRIs are available in remote communities and to establish an educational program that will give students the required technical skills. Over the summer of 2024, a team of students working within an Aircraft Maintenance Engineering (AME) program built the hardware for a wrist-sized prototype MRI. The student team included a high school student, AME students, engineering students and a post doctoral fellow. The skills required to maintain aircraft, namely 3D printing, sheet metal work and electrical harness building, were sufficient to build a low-field MRI. The prototype built was a radio frequency (RF) encoding MRI, whose design was optimized for eventual use in space, but the techniques and procedures developed are applicable to other MRI designs. Furthermore the breadth of students from high school to the post doctoral fellow level facilitated an extremely rich learning environment for the students while they focused on the task of designing and building the prototype MRI. Educational programs around building low-field MRIs can be created at all levels.

High-Field-Blinded Assessment of Portable Ultra-Low-Field Brain MRI for Multiple Sclerosis

BACKGROUND AND PURPOSE

MRI is crucial for multiple sclerosis (MS), but the relative value of portable ultra-low field MRI (pULF-MRI), a technology that holds promise for extending access to MRI, is unknown. We assessed white matter lesion (WML) detection on pULF-MRI compared to high-field MRI (HF-MRI), focusing on blinded assessments, assessor self-training, and multiplanar acquisitions.

METHODS

Fifty-five adults with MS underwent pULF-MRI following their HF-MRI. Two neuroradiologists independently assessed pULF-MRI images in an evaluation process, including initial assessment blinded to HF-MRI, self-training with reference to HF-MRI and evaluation of 20 cases with additional T2-fluid-attenuated inversion recovery in an additional plane. A third rater conducted cross-referenced analysis with HF-MRI data to determine true-positive lesions, false-positive areas, and case-level sensitivity and positive predictive value.

RESULTS

The mean age of participants was 50 years (standard deviation: 11; 74% women). Initially, Rater 2 marked more false-positive areas than Rater 1 (p = 0.003). After self-training, both raters embraced a conservative approach, with Rater 2 marking fewer false-positive areas (p = 0.01). Both raters maintained 100% case-level sensitivity and positive predictive value for detecting at least one WML, particularly in periventricular areas. Multiplanar acquisitions reduced both false-positive areas and true-positive lesions. True-positive lesions and false-positive areas had similar contrast-to-noise ratios in the juxtacortical region (p = 0.73) but not in periventricular, deep parenchymal regions (p = 0.004, p = 0.01).

CONCLUSION

With adequate training, radiological interpretation of pULF-MRI has high sensitivity and positive predictive value for MS lesions but should be approached conservatively. These results suggest utility for patient triage, potentially reducing diagnostic delay, and screening high-risk individuals.

Clinical Use of Bedside Portable Ultra-Low-Field Brain Magnetic Resonance Imaging in Patients on Extracorporeal Membrane Oxygenation: Results From the Multicenter SAFE MRI ECMO Study

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.

Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease

Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-noise ratio. Here, we optimize LF-MRI acquisition and develop a freely available machine learning pipeline to quantify brain morphometry and white matter hyperintensities (WMH). We validate the pipeline and apply it to outpatients presenting with mild cognitive impairment or dementia due to AD. We find hippocampal volumes from ≤ 3 mm isotropic LF-MRI scans have agreement with conventional MRI and are more accurate than anisotropic counterparts. We also show WMH volume has agreement between manual segmentation and the automated pipeline. The increased availability and reduced cost of LF-MRI, in combination with our machine learning pipeline, has the potential to increase access to neuroimaging for dementia.

Ultra-low-field magnetization transfer imaging at 0.055T with low specific absorption rate

PURPOSE

To demonstrate magnetization transfer (MT) effects with low specific absorption rate (SAR) on ultra-low-field (ULF) MRI.

METHODS

MT imaging was implemented by using sinc-modulated RF pulse train (SPT) modules to provide bilateral off-resonance irradiation. They were incorporated into 3D gradient echo (GRE) and fast spin echo (FSE) protocols on a shielding-free 0.055T head scanner. MT effects were first verified using phantoms. Brain MT imaging was conducted in both healthy subjects and patients.

RESULTS

MT effects were clearly observed in phantoms using six SPT modules with total flip angle 3600° at central primary saturation bands of approximate offset ±786 Hz, even in the presence of large relative B0 inhomogeneity. For brain, strong MT effects were observed in gray matter, white matter, and muscle in 3D GRE and FSE imaging using six and sixteen SPT modules with total flip angle 3600° and 9600°, respectively. Fat, cerebrospinal fluid, and blood exhibited relatively weak MT effects. MT preparation enhanced tissue contrasts in T2-weighted and FLAIR-like images, and improved brain lesion delineation. The estimated MT SAR was 0.0024 and 0.0008 W/kg for two protocols, respectively, which is far below the US Food and Drug Administration (FDA) limit of 3.0 W/kg.

CONCLUSION

Robust MT effects can be readily obtained at ULF with extremely low SAR, despite poor relative B0 homogeneity in ppm. This unique advantage enables flexible MT pulse design and implementation on low-cost ULF MRI platforms to achieve strong MT effects in brain and beyond, potentially augmenting their clinical utility in the future.

Low-Field (64 mT) Portable MRI for Rapid Point-of-Care Diagnosis of Dissemination in Space in Patients Presenting with Optic Neuritis

BACKGROUND AND PURPOSE

Low-field 64 mT portable brain MRI has recently shown diagnostic promise for MS. This study aimed to evaluate the utility of portable MRI (pMRI) in assessing dissemination in space (DIS) in patients presenting with optic neuritis and determine whether deploying pMRI in the MS clinic can shorten the time from symptom onset to MRI.

MATERIALS AND METHODS

Newly diagnosed patients with optic neuritis referred to a tertiary academic MS center from July 2022 to January 2024 underwent both point-of-care pMRI and subsequent 3T conventional MRI (cMRI). Images were evaluated for periventricular (PV), juxtacortical (JC), and infratentorial (IT) lesions. DIS was determined on brain MRI per 2017 McDonald criteria. Test characteristics were computed by using cMRI as the reference. Interrater and intermodality agreement between pMRI and cMRI were evaluated by using the Cohen κ. Time from symptom onset to pMRI and cMRI during the study period was compared with the preceding 1.5 years before pMRI implementation by using Kruskal-Wallis with post hoc Dunn tests.

RESULTS

Twenty patients (median age: 32.5 years [interquartile range {IQR}, 28-40]; 80% women) were included, of whom 9 (45%) and 5 (25%) had DIS on cMRI and pMRI, respectively. Median time interval between pMRI and cMRI was 7 days (IQR, 3.5-12.5). Interrater agreement was very good for PV (95%, κ = 0.89), and good for JC and IT lesions (90%, κ = 0.69 for both). Intermodality agreement was good for PV (90%, κ = 0.80) and JC (85%, κ = 0.63), and moderate for IT lesions (75%, κ = 0.42) and DIS (80%, κ = 0.58). pMRI had a sensitivity of 56% and specificity of 100% for DIS. The median time from symptom onset to pMRI was significantly shorter (8.5 days [IQR 7-12]) compared with the interval to cMRI before pMRI deployment (21 days [IQR 8-49], n = 50) and after pMRI deployment (15 days [IQR 12-29], n = 30) (both P < .01). Time from symptom onset to cMRI in those periods was not significantly different (P = .29).

CONCLUSIONS

In patients with optic neuritis, pMRI exhibited moderate concordance, moderate sensitivity, and high specificity for DIS compared with cMRI. Its integration into the MS clinic reduced the time from symptom onset to MRI. Further studies are warranted to evaluate the role of pMRI in expediting early MS diagnosis and as an imaging tool in resource-limited settings.

Ultra-low-field magnetic resonance angiography at 0.05 T: A preliminary study

We aim to explore the feasibility of head and neck time-of-flight (TOF) magnetic resonance angiography (MRA) at ultra-low-field (ULF). TOF MRA was conducted on a highly simplified 0.05 T MRI scanner with no radiofrequency (RF) and magnetic shielding. A flow-compensated three-dimensional (3D) gradient echo (GRE) sequence with a tilt-optimized nonsaturated excitation RF pulse, and a flow-compensated multislice two-dimensional (2D) GRE sequence, were implemented for cerebral artery and vein imaging, respectively. For carotid artery and jugular vein imaging, flow-compensated 2D GRE sequences were utilized with venous and arterial blood presaturation, respectively. MRA was performed on young healthy subjects. Vessel-to-background contrast was experimentally observed with strong blood inflow effect and background tissue suppression. The large primary cerebral arteries and veins, carotid arteries, jugular veins, and artery bifurcations could be identified in both raw GRE images and maximum intensity projections. The primary brain and neck arteries were found to be reproducible among multiple examination sessions. These preliminary experimental results demonstrated the possibility of artery TOF MRA on low-cost 0.05 T scanners for the first time, despite the extremely low MR signal. We expect to improve the quality of ULF TOF MRA in the near future through sequence development and optimization, ongoing advances in ULF hardware and image formation, and the use of vascular T1 contrast agents.

Developing Hyperpolarized Butane Gas for Ventilation Lung Imaging

NMR hyperpolarization dramatically improves the detection sensitivity of magnetic resonance through the increase in nuclear spin polarization. Because of the sensitivity increase by several orders of magnitude, additional applications have been unlocked, including imaging of gases in physiologically relevant conditions. Hyperpolarized 129Xe gas recently received FDA approval as the first inhalable gaseous MRI contrast agent for clinical functional lung imaging of a wide range of pulmonary diseases. However, production and utilization of hyperpolarized 129Xe gas faces a number of translational challenges including the high cost and complexity of contrast agent production and imaging using proton-only (i.e., conventional) clinical MRI scanners, which are typically not suited to scan 129Xe nuclei. As a solution to circumvent the translational challenges of hyperpolarized 129Xe, we have recently demonstrated the feasibility of a simple and cheap process for production of proton-hyperpolarized propane gas contrast agent using ultralow-cost disposable production equipment and demonstrated the feasibility of lung ventilation imaging using hyperpolarized propane gas in excised pig lungs. However, previous pilot studies have concluded that the hyperpolarized state of propane gas decays very fast with an exponential decay T 1 constant of ∼0.8 s at 1 bar (physiologically relevant pressure); moreover, the previously reported production rates were too slow for potential clinical utilization. Here, we investigate the feasibility of high-capacity production of hyperpolarized butane gas via heterogeneous parahydrogen-induced polarization using Rh nanoparticle-based catalyst utilizing butene gas as a precursor for parahydrogen pairwise addition. We demonstrate a remarkable result: the lifetime of the hyperpolarized state can be nearly doubled compared to that of propane (T 1 of ∼1.6 s and long-lived spin-state T S of ∼3.8 s at clinically relevant 1 bar pressure). Moreover, we demonstrate a production speed of up to 0.7 standard liters of hyperpolarized gas per second. These two synergistic developments pave the way to biomedical utilization of proton-hyperpolarized gas media for ventilation imaging. Indeed, here we demonstrate the feasibility of phantom imaging of hyperpolarized butane gas in Tedlar bags and also the feasibility of subsecond 2D ventilation gas imaging in excised rabbit lungs with 1.6 × 1.6 mm2 in-plane resolution using a clinical MRI scanner. The demonstrated results have the potential to revolutionize functional pulmonary imaging with a simple and inexpensive on-demand production of proton-hyperpolarized gas contrast media, followed by visualization on virtually any MRI scanner, including emerging bedside low-field MRI scanner technology.

Super-Field MRI Synthesis for Infant Brains Enhanced by Dual Channel Latent Diffusion

In resource-limited settings, portable ultra-low-field (uLF, i.e., 0.064T) magnetic resonance imaging (MRI) systems expand accessibility of radiological scanning, particularly for low-income areas as well as underserved populations like neonates and infants. However, compared to high-field (HF, e.g., ≥ 1.5T) systems, inferior image quality in uLF scanning poses challenges for research and clinical use. To address this, we introduce Super-Field Network (SFNet), a custom swinUNETRv2 with generative adversarial network components that uses uLF MRIs to generate super-field (SF) images comparable to HF MRIs. We acquired a cohort of infant data (n=30, aged 0-2 years) with paired uLF-HF MRI data from a resource-limited setting with an underrepresented population in research. To enhance the small dataset, we present a novel use of latent diffusion to create dual-channel (uLF-HF) paired MRIs. We compare SFNet with state-of-the-art synthesis methods by HF-SF image similarity perceptual scores and by automated HF and SF segmentations of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The best performance was achieved by SFNet trained on the latent diffusion enhanced dataset yielding state-of-the-art results in Fréchet inception distance at 9.08 ± 1.21, perceptual similarity at 0.11 ± 0.01, and PSNR at 22.64 ± 1.31. True HF and SF segmentations had a strong overlap with Dice similarity coefficients of 0.71 ± 0.1, 0.79 ± 0.2, and 0.73 ± 0.08 for WM, GM, and CSF, respectively, in the developing infant brain with incomplete myelination, and displayed 166%, 107%, and 106% improvement over respective uLF-based segmentation metrics. SF MRI supports health equity by enhancing the clinical use of uLF imaging systems and improving the diagnostic capabilities of low-cost portable MRI systems in resource-limited settings and for underserved populations. Our code is made openly available at https://github.com/AustinTapp/SFnet.

Abbreviated MRI in the evaluation of dizziness: report turnaround times and impact on length of stay compared to CT, CTA, and conventional MRI

PURPOSE

Neuroimaging is often used in the emergency department (ED) to evaluate for posterior circulation strokes in patients with dizziness, commonly with CT/CTA due to speed and availability. Although MRI offers more sensitive evaluation, it is less commonly used, in part due to slower turnaround times. We assess the potential for abbreviated MRI to improve reporting times and impact on length of stay (LOS) compared to conventional MRI (as well as CT/CTA) in the evaluation of acute dizziness.

MATERIALS AND METHODS

We performed a retrospective analysis of length of stay via LASSO regression for patients presenting to the ED with dizziness and discharged directly from the ED over 4 years (1/1/2018-12/31/2021), controlling for numerous patient-level and logistical factors. We additionally assessed turnaround time between order and final report for various imaging modalities.

RESULTS

14,204 patients were included in our analysis. Turnaround time for abbreviated MRI was significantly lower than for conventional MRI (4.40 h vs. 6.14 h, p < 0.001) with decreased impact on LOS (0.58 h vs. 2.02 h). Abbreviated MRI studies had longer turnaround time (4.40 h vs. 1.41 h, p < 0.001) and was associated with greater impact on ED LOS than non-contrast CT head (0.58 h vs. 0.00 h), however there was no significant difference in turnaround time compared to CTA head and neck (4.40 h vs. 3.86 h, p = 0.06) with similar effect on LOS (0.58 h vs. 0.53 h). Ordering both CTA and conventional MRI was associated with a greater-than-linear increase in LOS (additional 0.37 h); the same trend was not seen combining CTA and abbreviated MRI (additional 0.00 h).

CONCLUSIONS

In the acute settings where MRI is available, abbreviated MRI protocols may improve turnaround times and LOS compared to conventional MRI protocols. Since recent guidelines recommend MRI over CT in the evaluation of dizziness, implementation of abbreviated MRI protocols has the potential to facilitate rapid access to preferred imaging, while minimizing impact on ED workflows.

Diffusion tensor brain imaging at 0.55T: A feasibility study

PURPOSE

To investigate the feasibility of diffusion tensor brain imaging at 0.55T with comparisons against 3T.

METHODS

Diffusion tensor imaging data with 2 mm isotropic resolution was acquired on a cohort of five healthy subjects using both 0.55T and 3T scanners. The signal-to-noise ratio (SNR) of the 0.55T data was improved using a previous SNR-enhancing joint reconstruction method that jointly reconstructs the entire set of diffusion weighted images from k-space using shared-edge constraints. Quantitative diffusion tensor parameters were estimated and compared across field strengths. We also performed a test-retest assessment of repeatability at each field strength.

RESULTS

After applying SNR-enhancing joint reconstruction, the diffusion tensor parameters obtained from 0.55T data were strongly correlated (R 2 ≥ 0 . 70 $$ {R}^2\ge 0.70 $$ ) with those obtained from 3T data. Test-retest analysis showed that SNR-enhancing reconstruction improved the repeatability of the 0.55T diffusion tensor parameters.

CONCLUSION

High-resolution in vivo diffusion MRI of the human brain is feasible at 0.55T when appropriate noise-mitigation strategies are applied.

Coupled stack-up volume RF coils for low-field open MR imaging

Background

Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities.

Purpose

In response to these challenges, we introduce the coupled stack-up volume coil, a novel RF coil design that addresses the shortcomings of conventional birdcage in the context of low-field open MRI.

Methods

The proposed coupled stack-up volume coil design utilizes a unique architecture that optimizes both transmit/receive efficiency and RF field homogeneity and offers the advantage of a simple design and construction, making it a practical and feasible solution for low-field MRI applications. This paper presents a comprehensive exploration of the theoretical framework, design considerations, and experimental validation of this innovative coil design.

Results

We demonstrate the superior performance of the coupled stack-up volume coil in achieving 47.7% higher transmit/receive efficiency and 68% more uniform magnetic field distribution compared to traditional birdcage coils in electromagnetic simulations. Bench tests results show that the B1 field efficiency of coupled stack-up volume coil is 57.3% higher compared with that of conventional birdcage coil.

Conclusions

The proposed coupled stack-up volume coil outperforms the conventional birdcage coil in terms of B1 efficiency, imaging coverage, and low-frequency operation capability. This design provides a robust and simple solution to low-field MR RF coil design.

Low-field MRI for use in neurological diseases

PURPOSE OF REVIEW

To review recent clinical uses of low-field magnetic resonance imaging (MRI) to guide incorporation into neurological practice.

RECENT FINDINGS

Use of low-field MRI has been demonstrated in applications including tumours, vascular pathologies, multiple sclerosis, brain injury, and paediatrics. Safety, workflow, and image quality have also been evaluated.

SUMMARY

Low-field MRI has the potential to increase access to critical brain imaging for patients who otherwise may not obtain imaging in a timely manner. This includes areas such as the intensive care unit and emergency room, where patients could be imaged at the point of care rather than be transported to the MRI scanner. Such systems are often more affordable than conventional systems, allowing them to be more easily deployed in resource constrained settings. A variety of systems are available on the market or in a research setting and are currently being used to determine clinical uses for these devices. The utility of such devices must be fully evaluated in clinical scenarios before adoption into standard practice can be achieved. This review summarizes recent clinical uses of low-field MR as well as safety, workflows, and image quality to aid practitioners in assessing this new technology.

Diffusion-Weighted Imaging Fluid-Attenuated Inversion Recovery Mismatch on Portable, Low-Field Magnetic Resonance Imaging Among Acute Stroke Patients

OBJECTIVE

For stroke patients with unknown time of onset, mismatch between diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) can guide thrombolytic intervention. However, access to MRI for hyperacute stroke is limited. Here, we sought to evaluate whether a portable, low-field (LF)-MRI scanner can identify DWI-FLAIR mismatch in acute ischemic stroke.

METHODS

Eligible patients with a diagnosis of acute ischemic stroke underwent LF-MRI acquisition on a 0.064-T scanner within 24 h of last known well. Qualitative and quantitative metrics were evaluated. Two trained assessors determined the visibility of stroke lesions on LF-FLAIR. An image coregistration pipeline was developed, and the LF-FLAIR signal intensity ratio (SIR) was derived.

RESULTS

The study included 71 patients aged 71 ± 14 years and a National Institutes of Health Stroke Scale of 6 (interquartile range 3-14). The interobserver agreement for identifying visible FLAIR hyperintensities was high (κ = 0.85, 95% CI 0.70-0.99). Visual DWI-FLAIR mismatch had a 60% sensitivity and 82% specificity for stroke patients <4.5 h, with a negative predictive value of 93%. LF-FLAIR SIR had a mean value of 1.18 ± 0.18 <4.5 h, 1.24 ± 0.39 4.5-6 h, and 1.40 ± 0.23 >6 h of stroke onset. The optimal cut-point for LF-FLAIR SIR was 1.15, with 85% sensitivity and 70% specificity. A cut-point of 6.6 h was established for a FLAIR SIR <1.15, with an 89% sensitivity and 62% specificity.

INTERPRETATION

A 0.064-T portable LF-MRI can identify DWI-FLAIR mismatch among patients with acute ischemic stroke. Future research is needed to prospectively validate thresholds and evaluate a role of LF-MRI in guiding thrombolysis among stroke patients with uncertain time of onset. ANN NEUROL 2024;96:321-331.

Neuroprotection of Transcranial Cortical and Peripheral Somatosensory Electrical Stimulation by Modulating a Common Neuronal Death Pathway in Mice with Ischemic Stroke

Therapeutic electrical stimulation, such as transcranial cortical stimulation and peripheral somatosensory stimulation, is used to improve motor function in patients with stroke. We hypothesized that these stimulations exert neuroprotective effects during the subacute phase of ischemic stroke by regulating novel common signaling pathways. Male C57BL/6J mouse models of ischemic stroke were treated with high-definition (HD)-transcranial alternating current stimulation (tACS; 20 Hz, 89.1 A/mm2), HD-transcranial direct current stimulation (tDCS; intensity, 55 A/mm2; charge density, 66,000 C/m2), or electroacupuncture (EA, 2 Hz, 1 mA) in the early stages of stroke. The therapeutic effects were assessed using behavioral motor function tests. The underlying mechanisms were determined using transcriptomic and other biomedical analyses. All therapeutic electrical tools alleviated the motor dysfunction caused by ischemic stroke insults. We focused on electrically stimulating common genes involved in apoptosis and cell death using transcriptome analysis and chose 11 of the most potent targets (Trem2, S100a9, Lgals3, Tlr4, Myd88, NF-kB, STAT1, IL-6, IL-1β, TNF-α, and Iba1). Subsequent investigations revealed that electrical stimulation modulated inflammatory cytokines, including IL-1β and TNF-α, by regulating STAT1 and NF-kB activation, especially in amoeboid microglia; moreover, electrical stimulation enhanced neuronal survival by activating neurotrophic factors, including BDNF and FGF9. Therapeutic electrical stimulation applied to the transcranial cortical- or periphery-nerve level to promote functional recovery may improve neuroprotection by modulating a common neuronal death pathway and upregulating neurotrophic factors. Therefore, combining transcranial cortical and peripheral somatosensory stimulation may exert a synergistic neuroprotective effect, further enhancing the beneficial effects on motor deficits in patients with ischemic stroke.

Bringing MRI to low- and middle-income countries: Directions, challenges and potential solutions

The global disparity of magnetic resonance imaging (MRI) is a major challenge, with many low- and middle-income countries (LMICs) experiencing limited access to MRI. The reasons for limited access are technological, economic and social. With the advancement of MRI technology, we explore why these challenges still prevail, highlighting the importance of MRI as the epidemiology of disease changes in LMICs. In this paper, we establish a framework to develop MRI with these challenges in mind and discuss the different aspects of MRI development, including maximising image quality using cost-effective components, integrating local technology and infrastructure and implementing sustainable practices. We also highlight the current solutions-including teleradiology, artificial intelligence and doctor and patient education strategies-and how these might be further improved to achieve greater access to MRI.

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction

PURPOSE

To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP).

METHODS

Deep-DSP is proposed to directly predict EMI-free MR signals. During scanning, MRI receive coil and EMI sensing coils simultaneously sample data within two windows (i.e., for MR data and EMI characterization data acquisition, respectively). Afterward, a residual U-Net model is trained using synthetic MRI receive coil data and EMI sensing coil data acquired during EMI signal characterization window, to predict EMI-free MR signals from signals acquired by MRI receive and EMI sensing coils. The trained model is then used to directly predict EMI-free MR signals from data acquired by MRI receive and sensing coils during the MR signal-acquisition window. This strategy was evaluated on an ultralow-field 0.055T brain MRI scanner without any RF shielding and a 1.5T whole-body scanner with incomplete RF shielding.

RESULTS

Deep-DSP accurately predicted EMI-free MR signals in presence of strong EMI. It outperformed recently developed EDITER and convolutional neural network methods, yielding better EMI elimination and enabling use of few EMI sensing coils. Furthermore, it could work well without dedicated EMI characterization data.

CONCLUSION

Deep-DSP presents an effective EMI elimination strategy that outperforms existing methods, advancing toward truly portable and patient-friendly MRI. It exploits electromagnetic coupling between MRI receive and EMI sensing coils as well as typical MR signal characteristics. Despite its deep learning nature, Deep-DSP framework is computationally simple and efficient.

Low-Field, Low-Cost, Point-of-Care Magnetic Resonance Imaging

Low-field magnetic resonance imaging (MRI) has recently experienced a renaissance that is largely attributable to the numerous technological advancements made in MRI, including optimized pulse sequences, parallel receive and compressed sensing, improved calibrations and reconstruction algorithms, and the adoption of machine learning for image postprocessing. This new attention on low-field MRI originates from a lack of accessibility to traditional MRI and the need for affordable imaging. Low-field MRI provides a viable option due to its lack of reliance on radio-frequency shielding rooms, expensive liquid helium, and cryogen quench pipes. Moreover, its relatively small size and weight allow for easy and affordable installation in most settings. Rather than replacing conventional MRI, low-field MRI will provide new opportunities for imaging both in developing and developed countries. This article discusses the history of low-field MRI, low-field MRI hardware and software, current devices on the market, advantages and disadvantages, and low-field MRI's global potential.

Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding-free MRI

At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding rooms, posing stringent installation requirements and causing patient discomfort. We aim to eliminate electromagnetic interference (EMI) for MRI with no or incomplete RF shielding. In this study, a method of active sensing and deep learning EMI prediction is presented to model, predict, and remove EMI signal components from acquired MRI signals. Specifically, during each MRI scan, separate EMI-sensing coils placed in various locations are utilized to simultaneously sample external and internal EMI signals within two windows (for both conventional MRI signal acquisition and EMI characterization acquisition). A convolution neural network model is trained using the EMI characterization data to relate EMI signals detected by EMI-sensing coils to EMI signals in the MRI receive coil. This model is then used to retrospectively predict and remove EMI signal components detected by the MRI receive coil during the MRI signal acquisition window. This strategy was implemented on a low-cost ultralow-field 0.055 T permanent magnet MRI scanner without RF shielding. It produced final image signal-to-noise ratios that were comparable with those obtained using a fully enclosed RF shielding cage, and outperformed existing analytical EMI elimination methods (i.e., spectral domain transfer function and external dynamic interference estimation and removal [EDITER] methods). A preliminary experiment also demonstrated its applicability on a 1.5 T superconducting magnet MRI scanner with incomplete RF shielding. Altogether, the results demonstrated that the proposed method was highly effective in predicting and removing various EMI signals from both external environments and internal scanner electronics at both 0.055 T (2.3 MHz) and 1.5 T (63.9 MHz). The proposed strategy enables shielding-free MRI. The concept is relatively simple and is potentially applicable to other RF signal detection scenarios in the presence of external and/or internal EMI.

Applications, limitations and advancements of ultra-low-field magnetic resonance imaging: A scoping review

BACKGROUND

Ultra-low-field magnetic resonance imaging (ULF-MRI) has emerged as an alternative with several portable clinical applications. This review aims to comprehensively explore its applications, potential limitations, technological advancements, and expert recommendations.

METHODS

A review of the literature was conducted across medical databases to identify relevant studies. Articles on clinical usage of ULF-MRI were included, and data regarding applications, limitations, and advancements were extracted. A total of 25 articles were included for qualitative analysis.

RESULTS

The review reveals ULF-MRI efficacy in intensive care settings and intraoperatively. Technological strides are evident through innovative reconstruction techniques and integration with machine learning approaches. Additional advantages include features such as portability, cost-effectiveness, reduced power requirements, and improved patient comfort. However, alongside these strengths, certain limitations of ULF-MRI were identified, including low signal-to-noise ratio, limited resolution and length of scanning sequences, as well as variety and absence of regulatory-approved contrast-enhanced imaging. Recommendations from experts emphasize optimizing imaging quality, including addressing signal-to-noise ratio (SNR) and resolution, decreasing the length of scan time, and expanding point-of-care magnetic resonance imaging availability.

CONCLUSION

This review summarizes the potential of ULF-MRI. The technology's adaptability in intensive care unit settings and its diverse clinical and surgical applications, while accounting for SNR and resolution limitations, highlight its significance, especially in resource-limited settings. Technological advancements, alongside expert recommendations, pave the way for refining and expanding ULF-MRI's utility. However, adequate training is crucial for widespread utilization.

Toward Next-Generation Molecular Imaging with a Clinical Low-Field (0.064 T) Point-of-Care MRI Scanner

Low-field (LF) MRI promises soft-tissue imaging without the expensive, immobile magnets of clinical scanners but generally suffers from limited detection sensitivity and contrast. The sensitivity boost provided by hyperpolarization can thus be highly synergistic with LF MRI. Initial efforts to integrate a continuous-bubbling SABRE (signal amplification by reversible exchange) hyperpolarization setup with a portable, point-of-care 64 mT clinical MRI scanner are reported. Results from 1H SABRE MRI of pyrazine and nicotinamide are compared with those of benchtop NMR spectroscopy. Comparison with MRI signals from samples with known H2O/D2O ratios allowed quantification of the SABRE enhancements of imaged samples with various substrate concentrations (down to 3 mM). Respective limits of detection and quantification of 3.3 and 10.1 mM were determined with pyrazine 1H polarization (PH) enhancements of ∼1900 (PH ∼0.04%), supporting ongoing and envisioned efforts to realize SABRE-enabled MRI-based molecular imaging.

Application of emerging technologies in ischemic stroke: from clinical study to basic research

Stroke is a primary cause of noncommunicable disease-related death and disability worldwide. The most common form, ischemic stroke, is increasing in incidence resulting in a significant burden on patients and society. Urgent action is thus needed to address preventable risk factors and improve treatment methods. This review examines emerging technologies used in the management of ischemic stroke, including neuroimaging, regenerative medicine, biology, and nanomedicine, highlighting their benefits, clinical applications, and limitations. Additionally, we suggest strategies for technological development for the prevention, diagnosis, and treatment of ischemic stroke.

Current State of Evidence for Neuroimaging Paradigms in Management of Acute Ischemic Stroke

Stroke is the chief differential diagnosis in patient presenting to the emergency room with abrupt onset focal neurological deficits. Neuroimaging, including non-contrast computed tomography (CT), magnetic resonance imaging (MRI), vascular and perfusion imaging, is a cornerstone in the diagnosis and treatment decision-making. This review examines the current state of evidence behind the different imaging paradigms for acute ischemic stroke diagnosis and treatment, including current recommendations from the guidelines. Non-contrast CT brain, or in some centers MRI, can help differentiate ischemic stroke and intracerebral hemorrhage (ICH), a pivotal juncture in stroke diagnosis and treatment algorithm, especially for early window thrombolytics. Advanced imaging such as MRI or perfusion imaging can also assist making a diagnosis of ischemic stroke versus mimics such as migraine, Todd's paresis, or functional disorders. Identification of medium-large vessel occlusions with CT or MR angiography triggers consideration of endovascular thrombectomy (EVT), with additional perfusion imaging help identify salvageable brain tissue in patients who are likely to benefit from reperfusion therapies, particularly in the ≥6 h window. We also review recent advances in neuroimaging and ongoing trials in key therapeutic areas and their imaging selection criteria to inform the readers on potential future transitions into use of neuroimaging for stroke diagnosis and treatment decision making. ANN NEUROL 2024;95:1017-1034.

Whole-body magnetic resonance imaging at 0.05 Tesla

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

Imaging without barriers

Low-field magnetic resonance imaging can be engineered for widespread point-of-care diagnostics.

Feasibility and tolerability of portable, low-field brain MRI for patients with multiple sclerosis

Low-field, portable MRI (LF-MRI) promises to expand neuroimaging access for patients with multiple sclerosis (MS). We aimed to measure the feasibility and tolerability of LF-MRI for clinical use in 50 people with MS (mean age 46.5 ± 15.3 years; 72 % female; median disease duration 5.9 years), 38 % of whom reported barriers to undergoing MRI, and 34 % of whom were low-income or unemployed. Experience ratings of LF-MRI were strongly positive (mean rating of 9.2 on a ten-point scale). Seventy percent of participants were willing to receive future LF-MRI scans, and 46 % preferred LF-MRI to standard MRI (35 % undecided). The overall feasibility and tolerability of LF-MRI support its integration into a one-stop, patient-centered model of outpatient MS care.

Breast imaging with an ultra-low field MRI scanner: a pilot study

Breast cancer screening is necessary to reduce mortality due to undetected breast cancer. Current methods have limitations, and as a result many women forego regular screening. Magnetic resonance imaging (MRI) can overcome most of these limitations, but access to conventional MRI is not widely available for routine annual screening. Here, we used an MRI scanner operating at ultra-low field (ULF) to image the left breasts of 11 women (mean age, 35 years ±13 years) in the prone position. Three breast radiologists reviewed the imaging and were able to discern the breast outline and distinguish fibroglandular tissue (FGT) from intramammary adipose tissue. Additionally, the expert readers agreed on their assessment of the breast tissue pattern including fatty, scattered FGT, heterogeneous FGT, and extreme FGT. This preliminary work demonstrates that ULF breast MRI is feasible and may be a potential option for comfortable, widely deployable, and low-cost breast cancer diagnosis and screening.

Quantitative brain mapping using magnetic resonance fingerprinting on a 50-mT portable MRI scanner

Ultralow-field magnetic resonance imaging (ULF-MRI) has broad application prospects because of its portable hardware system and low cost. However, the low B0 magnitude of ULF-MRI results in a reduced signal-to-noise ratio in qualitative images compared with that of commercial high-field MRI, which can affect the visibility and delineation of tissues and lesions. In this work, a magnetic resonance fingerprinting (MRF) approach is applied to a homemade 50-mT ULF-MRI scanner to achieve efficient quantitative brain imaging, which is an original and promising disease-diagnosis approach for portable MRI systems. An inversion recovery fast imaging with steady-state precession-based sequence is utilized for MRF through Cartesian acquisition. A microdictionary analysis method is proposed to select the optimal repetition time and flip angle variation schedule and ensure the best possible tissue discriminative ability of MRF. The T1 and T2 relaxation properties and the B1 + distribution are considered for estimation, and the results are compared with those of gold standard (GS) quantitative imaging or qualitative imaging methods. The phantom experiment indicates that the quantitative values obtained by schedule-optimized MRF show good agreement, and the bias from the GS results is acceptable. The in vivo experiment shows that the relaxation times of white and gray matter estimated by MRF are slightly lower than the reference data, and the relaxation times of lipid are within the range of the reference data. Compared with qualitative MRI under ULF, MRF can intuitively reflect various items of brain tissue information in a single scan, so it is a valuable addition to point-of-care imaging approaches.

Detection of Acute Brain Injury in Intensive Care Unit Patients on ECMO Support Using Ultra-Low-Field Portable MRI: A Retrospective Analysis Compared to Head CT

Early detection of acute brain injury (ABI) is critical to intensive care unit (ICU) patient management and intervention to decrease major complications. Head CT (HCT) is the standard of care for the assessment of ABI in ICU patients; however, it has limited sensitivity compared to MRI. We retrospectively compared the ability of ultra-low-field portable MR (ULF-pMR) and head HCT, acquired within 24 h of each other, to detect ABI in ICU patients supported on extracorporeal membrane oxygenation (ECMO). A total of 17 adult patients (median age 55 years; 47% male) were included in the analysis. Of the 17 patients assessed, ABI was not observed on either ULF-pMR or HCT in eight patients (47%). ABI was observed in the remaining nine patients with a total of 10 events (8 ischemic, 2 hemorrhagic). Of the eight ischemic events, ULF-pMR observed all eight, while HCT only observed four events. Regarding hemorrhagic stroke, ULF-pMR observed only one of them, while HCT observed both. ULF-pMR outperformed HCT for the detection of ABI, especially ischemic injury, and may offer diagnostic advantages for ICU patients. The lack of sensitivity to hemorrhage may improve with modification of the imaging acquisition program.

Development of a Helmet-Shape Dual-Channel RF coil for brain imaging at 54 mT using inverse boundary element method

Very-low field (VLF) magnetic resonance imaging (MRI) offers advantages in term of size, weight, cost, and the absence of robust shielding requirements. However, it encounters challenges in maintaining a high signal-to-noise ratio (SNR) due to low magnetic fields (below 100 mT). Developing a close-fitting radio frequency (RF) receive coil is crucial to improve the SNR. In this study, we devised and optimized a helmet-shaped dual-channel RF receive coil tailored for brain imaging at a magnetic field strength of 54 mT (2.32 MHz). The methodology integrates the inverse boundary element method (IBEM) to formulate initial coil structures and wiring patterns, followed by optimization through introducing regularization terms. This approach frames the design process as an inverse problem, ensuring a close fit to the head contour. Combining theoretical optimization with physical measurements of the coil's AC resistance, we identified the optimal loop count for both axial and radial coils as nine and eight loops, respectively. The effectiveness of the designed dual-channel coil was verified through the imaging of a CuSO4 phantom and a healthy volunteer's brain. Notably, the in-vivo images exhibited an approximate 16-25 % increase in SNR with poorer B1 homogeneity compared to those obtained using single-channel coils. The high-quality images achieved by T1, T2-weighted, and fluid-attenuated inversion-recovery (FLAIR) protocols enhance the diagnostic potential of VLF MRI, particularly in cases of cerebral stroke and trauma patients. This study underscores the adaptability of the design methodology for the customization of RF coil structures in alignment with individual imaging requirements.

Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people

Background

Portable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in low-resource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people.

Methods

T1- and T2-weighted structural MR images were obtained from a low-field (64mT) Hyperfine and high-field (3T) Siemens system in N = 70 individuals (mean age = 20.39 years, range 9-26 years). We tested two super-resolution approaches to improve image correspondence between images acquired at high- and low-field: (1) processing via a convolutional neural network ('SynthSR'), and (2) multi-orientation image averaging. We extracted brain region volumes, cortical thickness, and cortical surface area estimates. We used Pearson correlations to test the correspondence between these measures, and Steiger Z tests to compare the difference in correspondence between standard imaging and super-resolution approaches.

Results

Single pairs of T1- and T2-weighted images acquired at low field showed high correspondence to high-field-strength images for estimates of total intracranial volume, surface area cortical volume, subcortical volume, and total brain volume (r range = 0.60-0.88). Correspondence was lower for cerebral white matter volume (r = 0.32, p = 0.007, q = 0.009) and non-significant for mean cortical thickness (r = -0.05, p = 0.664, q = 0.664). Processing images with SynthSR yielded significant improvements in correspondence for total brain volume, white matter volume, total surface area, subcortical volume, cortical volume, and total intracranial volume (r range = 0.85-0.97), with the exception of global mean cortical thickness (r = 0.14). An alternative multi-orientation image averaging approach improved correspondence for cerebral white matter and total brain volume. Processing with SynthSR also significantly improved correspondence across widespread regions for estimates of cortical volume, surface area and subcortical volume, as well as within isolated prefrontal and temporal regions for estimates of cortical thickness.

Conclusion

Applying super-resolution approaches to low-field imaging improves regional brain volume and surface area accuracy in young people. Finer-scale brain measurements, such as cortical thickness, remain challenging with the limited resolution of low-field systems.

Fetal neuroimaging applications for diagnosis and counseling of brain anomalies: Current practice and future diagnostic strategies

Advances in fetal brain neuroimaging, especially fetal neurosonography and brain magnetic resonance imaging (MRI), allow safe and accurate anatomical assessments of fetal brain structures that serve as a foundation for prenatal diagnosis and counseling regarding fetal brain anomalies. Fetal neurosonography strategically assesses fetal brain anomalies suspected by screening ultrasound. Fetal brain MRI has unique technological features that overcome the anatomical limits of smaller fetal brain size and the unpredictable variable of intrauterine motion artifact. Recent studies of fetal brain MRI provide evidence of improved diagnostic and prognostic accuracy, beginning with prenatal diagnosis. Despite technological advances over the last several decades, the combined use of different qualitative structural biomarkers has limitations in providing an accurate prognosis. Quantitative analyses of fetal brain MRIs offer measurable imaging biomarkers that will more accurately associate with clinical outcomes. First-trimester ultrasound opens new opportunities for risk assessment and fetal brain anomaly diagnosis at the earliest time in pregnancy. This review includes a case vignette to illustrate how fetal brain MRI results interpreted by the fetal neurologist can improve diagnostic perspectives. The strength and limitations of conventional ultrasound and fetal brain MRI will be compared with recent research advances in quantitative methods to better correlate fetal neuroimaging biomarkers of neuropathology to predict functional childhood deficits. Discussion of these fetal sonogram and brain MRI advances will highlight the need for further interdisciplinary collaboration using complementary skills to continue improving clinical decision-making following precision medicine principles.

Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy

INTRODUCTION

Fast and accurate diagnosis of acute stroke is crucial to timely initiate reperfusion therapies. Conventional high-field (HF) MRI yields the highest accuracy in discriminating early ischaemia from haemorrhages and mimics. Rapid access to HF-MRI is often limited by contraindications or unavailability. Low-field (LF) MRI (<0.5T) can detect several types of brain injury, including ischaemic and haemorrhagic stroke. Implementing LF-MRI in acute stroke care may offer several advantages, including extended applicability, increased safety, faster administration, reduced staffing and costs. This multicentric prospective open-label trial aims to evaluate the diagnostic accuracy of LF-MRI, as a tool to guide treatment decision in acute stroke.

METHODS AND ANALYSIS

Consecutive patients accessing the emergency department with suspected stroke dispatch will be recruited at three Italian study units: Azienda Sanitaria Locale (ASL) Abruzzo 1 and 2, Istituto di Ricerca e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital. The estimated sample size is 300 patients. Anonymised clinical and LF-MRI data, along with conventional neuroimaging data, will be independently assessed by two external units: Marche Polytechnic University and 'G. Martino' Polyclinic University Hospital. Both units will independently adjudicate the best treatment option, while the latter will provide historical HF-MRI data to develop artificial intelligence algorithms for LF-MRI images interpretation (Free University of Bozen-Bolzano). Agreement with conventional neuroimaging will be evaluated at different time points: hyperacute, acute (24 hours), subacute (72 hours), at discharge and chronic (4 weeks). Further investigations will include feasibility study to develop a mobile stroke unit equipped with LF-MRI and cost-effectiveness analysis. This trial will provide necessary data to validate the use of LF-MRI in acute stroke care.

ETHICS AND DISSEMINATION

The study was approved by the Research Ethics Committee of the Abruzzo Region (CEtRA) on 11 May 2023 (approval code: richyvgrg). Results will be disseminated in peer-reviewed journals and presented in academic conferences.

TRIAL REGISTRATION NUMBER

NCT05816213; Pre-Results.

Clinical Use of Bedside Portable Low-field Brain Magnetic Resonance Imaging in Patients on ECMO: The Results from Multicenter SAFE MRI ECMO Study

Purpose

Early detection of acute brain injury (ABI) is critical for improving survival for patients with extracorporeal membrane oxygenation (ECMO) support. We aimed to evaluate the safety of ultra-low-field portable MRI (ULF-pMRI) and the frequency and types of ABI observed during ECMO support.

Methods

We conducted a multicenter prospective observational study (NCT05469139) at two academic tertiary centers (August 2022-November 2023). Primary outcomes were safety and validation of ULF-pMRI in ECMO, defined as exam completion without adverse events (AEs); secondary outcomes were ABI frequency and type.

Results

ULF-pMRI was performed in 50 patients with 34 (68%) on venoarterial (VA)-ECMO (11 central; 23 peripheral) and 16 (32%) with venovenous (VV)-ECMO (9 single lumen; 7 double lumen). All patients were imaged successfully with ULF-pMRI, demonstrating discernible intracranial pathologies with good quality. AEs occurred in 3 (6%) patients (2 minor; 1 serious) without causing significant clinical issues.ABI was observed in ULF-pMRI scans for 22 patients (44%): ischemic stroke (36%), intracranial hemorrhage (6%), and hypoxic-ischemic brain injury (4%). Of 18 patients with both ULF-pMRI and head CT (HCT) within 24 hours, ABI was observed in 9 patients with 10 events: 8 ischemic (8 observed on ULF-oMRI, 4 on HCT) and 2 hemorrhagic (1 observed on ULF-pMRI, 2 on HCT).

Conclusions

ULF-pMRI was shown to be safe and valid in ECMO patients across different ECMO cannulation strategies. The incidence of ABI was high, and ULF-pMRI may more sensitive to ischemic ABI than HCT. ULF-pMRI may benefit both clinical care and future studies of ECMO-associated ABI.

Single-sided magnetic resonance-based sensor for point-of-care evaluation of muscle

Magnetic resonance imaging is a widespread clinical tool for the detection of soft tissue morphology and pathology. However, the clinical deployment of magnetic resonance imaging scanners is ultimately limited by size, cost, and space constraints. Here, we discuss the design and performance of a low-field single-sided magnetic resonance sensor intended for point-of-care evaluation of skeletal muscle in vivo. The 11 kg sensor has a penetration depth of >8 mm, which allows for an accurate analysis of muscle tissue and can avoid signal from more proximal layers, including subcutaneous adipose tissue. Low operational power and shielding requirements are achieved through the design of a permanent magnet array and surface transceiver coil. The sensor can acquire high signal-to-noise measurements in minutes, making it practical as a point-of-care tool for many quantitative diagnostic measurements, including T2 relaxometry. In this work, we present the in vitro and human in vivo performance of the device for muscle tissue evaluation.

MRI scarcity in low- and middle-income countries

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations-leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD-AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI.

Improving portable low-field MRI image quality through image-to-image translation using paired low- and high-field images

Low-field portable magnetic resonance imaging (MRI) scanners are more accessible, cost-effective, sustainable with lower carbon emissions than superconducting high-field MRI scanners. However, the images produced have relatively poor image quality, lower signal-to-noise ratio, and limited spatial resolution. This study develops and investigates an image-to-image translation deep learning model, LoHiResGAN, to enhance the quality of low-field (64mT) MRI scans and generate synthetic high-field (3T) MRI scans. We employed a paired dataset comprising T1- and T2-weighted MRI sequences from the 64mT and 3T and compared the performance of the LoHiResGAN model with other state-of-the-art models, including GANs, CycleGAN, U-Net, and cGAN. Our proposed method demonstrates superior performance in terms of image quality metrics, such as normalized root-mean-squared error, structural similarity index measure, peak signal-to-noise ratio, and perception-based image quality evaluator. Additionally, we evaluated the accuracy of brain morphometry measurements for 33 brain regions across the original 3T, 64mT, and synthetic 3T images. The results indicate that the synthetic 3T images created using our proposed LoHiResGAN model significantly improve the image quality of low-field MRI data compared to other methods (GANs, CycleGAN, U-Net, cGAN) and provide more consistent brain morphometry measurements across various brain regions in reference to 3T. Synthetic images generated by our method demonstrated high quality both quantitatively and qualitatively. However, additional research, involving diverse datasets and clinical validation, is necessary to fully understand its applicability for clinical diagnostics, especially in settings where high-field MRI scanners are less accessible.

Priorities for Advancements in Neuroimaging in the Diagnostic Workup of Acute Stroke

STAIR XII (12th Stroke Treatment Academy Industry Roundtable) included a workshop to discuss the priorities for advancements in neuroimaging in the diagnostic workup of acute ischemic stroke. The workshop brought together representatives from academia, industry, and government. The participants identified 10 critical areas of priority for the advancement of acute stroke imaging. These include enhancing imaging capabilities at primary and comprehensive stroke centers, refining the analysis and characterization of clots, establishing imaging criteria that can predict the response to reperfusion, optimizing the Thrombolysis in Cerebral Infarction scale, predicting first-pass reperfusion outcomes, improving imaging techniques post-reperfusion therapy, detecting early ischemia on noncontrast computed tomography, enhancing cone beam computed tomography, advancing mobile stroke units, and leveraging high-resolution vessel wall imaging to gain deeper insights into pathology. Imaging in acute ischemic stroke treatment has advanced significantly, but important challenges remain that need to be addressed. A combined effort from academic investigators, industry, and regulators is needed to improve imaging technologies and, ultimately, patient outcomes.