Emerging ethical issues raised by highly portable MRI research in remote and resource-limited international settings

Proof of concept: Portable ultra-low-field magnetic resonance imaging for the diagnosis of epileptogenic brain pathologies

OBJECTIVE

High-field magnetic resonance imaging (MRI) is a standard in the diagnosis of epilepsy. However, high costs and technical barriers have limited adoption in low- and middle-income countries. Even in high-income nations, many individuals with epilepsy face delays in undergoing MRI. Recent advancements in ultra-low-field (ULF) MRI technology, particularly the development of portable scanners, offer a promising solution to the limited accessibility of MRI. In this study, we present and evaluate the imaging capability of ULF MRI in detecting structural abnormalities typically associated with epilepsy and compare it to high-field MRI at 3 T.

METHODS

Data collection was conducted within 3 consecutive weeks at the University Hospital Bonn. Inclusion criteria were a minimum age of 18 years, diagnosed epilepsy, and clinical high-field MRI with abnormalities. We used a .064 T Swoop portable MR Imaging System. Both high-field MRI and ULF MRI scans were evaluated independently by two experienced neuroradiologists as part of their clinical routine, comparing pathology detection and diagnosis completeness.

RESULTS

Twenty-three individuals with epilepsy were recruited. One subject presented with a dual pathology. Across the entire cohort, in 17 of 24 (71%) pathologies, an anomaly colocalizing with the actual lesion was observed on ULF MRI. For 11 of 24 (46%) pathologies, the full diagnosis could be made based on ULF MRI. Tumors and posttraumatic lesions could be diagnosed best on ULF MRI, whereas cortical dysplasia and other focal pathologies were the least well diagnosed.

SIGNIFICANCE

This single-center series of individuals with epilepsy demonstrates the feasibility and utility of ULF MRI for the field of epileptology. Its integration into epilepsy care offers transformative potential, particularly in resource-limited settings. Further research is needed to position ULF MRI within imaging modalities in the diagnosis of epilepsy.

Can biosampling really be "non-invasive"? An examination of the socially invasive nature of physically non-invasive biosampling in urban and rural Malawi

Glucocorticoids are understood to represent useful biomarkers of stress and can be measured in saliva, hair, and breastmilk. The collection of such biosamples is increasingly included in biobank and cohort studies. While collection is considered "non-invasive" by biomedical researchers (compared to sampling blood), community perspectives may differ. This cross-sectional, qualitative study utilising eight focus groups aimed to determine the feasibility and acceptability of collecting ostensibly "non-invasive" biological samples in Malawi. Breastfeeding women, couples, field workers, and healthcare providers were purposively sampled. Data about prior understandings of, barriers to, and feasibility of "non-invasive" biosampling were analysed. Participants described biomaterials intended for "non-invasive" collection as sometimes highly sensitive, with sampling procedures raising community concerns. Sampling methods framed as physically "non-invasive" within biomedicine can consequently be considered socially "invasive" by prospective sample donors. Biomedical and community framings of "invasiveness' can therefore diverge, and the former must respond to and be informed by the perspectives of the latter. Further, considerations of collection procedures are shaped by therapeutic misconceptions about the immediate health-related utility of biomedical and public health research. When researchers engage with communities about biosampling, they must ensure they are not furthering therapeutic misconceptions and actively seek to dispel these.

Scientists' perspectives on ethical issues in research with emerging portable neuroimaging technology: The need for guidance on ethical, legal, and societal implications (ELSI)

Deployment of new, more portable, and less costly neuroimaging technologies such as portable magnetoencephalography, electroencephalography, positron emission tomography, functional near-infrared spectroscopy, high-density diffuse optical tomography, and magnetic resonance imaging is advancing rapidly. Given this trajectory toward increasing use of neuroimaging outside the hospital, we sought to identify ethical, legal, and societal implications (ELSI) of these new technologies by understanding the perspectives of those scientists and engineers developing and implementing portable neuroimaging technologies in the United States, Europe, and Asia. Based on a literature review, we identified and contacted 19 potential interviewees and then conducted 11 semi-structured interviews in English by Zoom. Analysis of the interviews revealed key themes and ELSI issues. Developers reported that without proper ELSI guidance, portable and accessible neuroimaging technology could be misused, fail to comply with applicable regulation and policy, and ultimately fall short in its mission to provide neuroimaging for the world. Our interviews suggested that ELSI guidance should address differences between imaging modalities because they vary in capability, limitations, and likelihood of generating incidental findings.

Feasibility and success of a non-sedated brain MRI training protocol in 7-year-old children from rural and semi-rural Colombia

BACKGROUND

Brain magnetic resonance imaging (MRI) is a crucial tool for clinical evaluation of the brain and neuroscience research. Obtaining successful non-sedated MRI in children who live in resource-limited settings may be an additional challenge.

OBJECTIVE

To present a feasibility study of a novel, low-cost MRI training protocol used in a clinical research study in a rural/semi-rural region of Colombia and to examine neurodevelopmental factors associated with successful scans.

MATERIALS AND METHODS

Fifty-seven typically developing Colombian children underwent a training protocol and non-sedated brain MRI at age 7. Group training utilized a customized booklet, an MRI toy set, and a simple mock scanner. Children attended MRI visits in small groups of two to three. Resting-state functional and structural images were acquired on a 1.5-Tesla scanner with a protocol duration of 30-40 minutes. MRI success was defined as the completion of all sequences and no more than mild motion artifact. Associations between the Wechsler Preschool and Primary Scale of Intelligence (WPPSI), Movement Assessment Battery for Children (MABC), Behavioral Rating Inventory of Executive Function (BRIEF), Child Behavior Checklist (CBCL), and Adaptive Behavior Assessment System (ABAS) scores and MRI success were analyzed.

RESULTS

Mean (SD) age at first MRI attempt was 7.2 (0.2) years (median 7.2 years, interquartile range 7.1-7.3 years). Twenty-six (45.6%) participants were male. Fifty-one (89.5%) children were successful across two attempts; 44 (77.2%) were successful on their first attempt. Six (10.5%) were unsuccessful due to refusal or excessive motion. Age, sex, and scores across all neurodevelopmental assessments (MABC, TVIP, ABAS, BRIEF, CBCL, NIH Toolbox Flanker, NIH Toolbox Pattern Comparison, WPPSI) were not associated with likelihood of MRI success (P=0.18, 0.19, 0.38, 0.92, 0.84, 0.80, 1.00, 0.16, 0.75, 0.86, respectively).

CONCLUSION

This cohort of children from a rural/semi-rural region of Colombia demonstrated comparable MRI success rates to other published cohorts after completing a low-cost MRI familiarization training protocol suitable for low-resource settings. Achieving non-sedated MRI success in children in low-resource and international settings is important for the continuing diversification of pediatric research studies.

Building Radiology Equity: Themes from the 2023 RAD-AID Conference on International Radiology and Global Health

Low- and middle-income countries are significantly impacted by the global scarcity of medical imaging services. Medical imaging is an essential component for diagnosis and guided treatment, which is needed to meet the current challenges of increasing chronic diseases and preparedness for acute-care response. We present some key themes essential for improving global health equity, which were discussed at the 2023 RAD-AID Conference on International Radiology and Global Health. They include (1) capacity building, (2) artificial intelligence, (3) community-based patient navigation, (4) organizational design for multidisciplinary global health strategy, (5) implementation science, and (6) innovation. Although not exhaustive, these themes should be considered influential as we guide and expand global health radiology programs in low- and middle-income countries in the coming years.

Fast, high-quality, and unshielded 0.2 T low-field mobile MRI using minimal hardware resources

OBJECTIVE

To propose a deep learning-based low-field mobile MRI strategy for fast, high-quality, unshielded imaging using minimal hardware resources.

METHODS

Firstly, we analyze the correlation of EMI signals between the sensing coil and the MRI coil to preliminarily verify the feasibility of active EMI shielding using a single sensing coil. Then, a powerful deep learning EMI elimination model is proposed, which can accurately predict the EMI components in the MRI coil signals using EMI signals from at least one sensing coil. Further, deep learning models with different task objectives (super-resolution and denoising) are strategically stacked for multi-level post-processing to enable fast and high-quality low-field MRI. Finally, extensive phantom and brain experiments were conducted on a home-built 0.2 T mobile brain scanner for the evaluation of the proposed strategy.

RESULTS

20 healthy volunteers were recruited to participate in the experiment. The results show that the proposed strategy enables the 0.2 T scanner to generate images with sufficient anatomical information and diagnostic value under unshielded conditions using a single sensing coil. In particular, the EMI elimination outperforms the state-of-the-art deep learning methods and numerical computation methods. In addition, 2 × super-resolution (DDSRNet) and denoising (SwinIR) techniques enable further improvements in imaging speed and quality.

DISCUSSION

The proposed strategy enables low-field mobile MRI scanners to achieve fast, high-quality imaging under unshielded conditions using minimal hardware resources, which has great significance for the widespread deployment of low-field mobile MRI scanners.

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.

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.

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.

Growth in early infancy drives optimal brain functional connectivity which predicts cognitive flexibility in later childhood

Functional brain network organization, measured by functional connectivity (FC), reflects key neurodevelopmental processes for healthy development. Early exposure to adversity, e.g. undernutrition, affects neurodevelopment, observable via disrupted FC, and leads to poorer outcomes from preschool age onward. We assessed longitudinally the impact of early growth trajectories on developmental FC in a rural Gambian population from age 5 to 24 months. To investigate how these early trajectories relate to later childhood outcomes, we assessed cognitive flexibility at 3-5 years. We observed that early physical growth before the fifth month of life drove optimal developmental trajectories of FC that in turn predicted cognitive flexibility at pre-school age. In contrast to previously studied developmental populations, this Gambian sample exhibited long-range interhemispheric FC that decreased with age. Our results highlight the measurable effects that poor growth in early infancy has on brain development and the subsequent impact on pre-school age cognitive development, underscoring the need for early life interventions throughout global settings of adversity.

Attention control in autism: Eye-tracking findings from pre-school children in a low- and middle-income country setting

LAY ABSTRACT

The development of cognitive processes, such as attention control and learning, has been suggested to be altered in children with a diagnosis of autism spectrum disorder. However, nearly all of our understanding of the development of these cognitive processes comes from studies with school-aged or older children in high-income countries, and from research conducted in a controlled laboratory environment, thereby restricting the potential generalisability of results and away from the majority of the world's population. We need to expand our research to investigate abilities beyond these limited settings. We address shortcomings in the literature by (1) studying attention control and learning in an understudied population of children in a low- and middle-income country setting in India, (2) focusing research on a critical younger age group of children and (3) using portable eye-tracking technology that can be taken into communities and healthcare settings to increase the accessibility of research in hard-to-reach populations. Our results provide novel evidence on differences in attention control and learning responses in groups of children with and without a diagnosis of autism spectrum disorder. We show that learning responses in children that we assessed through a portable eye-tracking task, called the 'antisaccade task', may be specific to autism. This suggests that the methods we use may have the potential to identify and assess autism-specific traits across development, and be used in research in low-resource settings.

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.

Developing and deploying deep learning models in brain magnetic resonance imaging: A review

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to alleviate the burden on radiologists and MR technologists, and improve throughput. The easy accessibility of DL tools has resulted in a rapid increase of DL models and subsequent peer-reviewed publications. However, the rate of deployment in clinical settings is low. Therefore, this review attempts to bring together the ideas from data collection to deployment in the clinic, building on the guidelines and principles that accreditation agencies have espoused. We introduce the need for and the role of DL to deliver accessible MRI. This is followed by a brief review of DL examples in the context of neuropathologies. Based on these studies and others, we collate the prerequisites to develop and deploy DL models for brain MRI. We then delve into the guiding principles to develop good machine learning practices in the context of neuroimaging, with a focus on explainability. A checklist based on the United States Food and Drug Administration's good machine learning practices is provided as a summary of these guidelines. Finally, we review the current challenges and future opportunities in DL for brain MRI.

Unlocking the Hidden Depths: Multi-Modal Integration of Imaging Mass Spectrometry-Based and Molecular Imaging Techniques

Multimodal imaging (MMI) has emerged as a powerful tool in clinical research, combining different imaging modes to acquire comprehensive information and enabling scientists and surgeons to study tissue identification, localization, metabolic activity, and molecular discovery, thus aiding in disease progression analysis. While multimodal instruments are gaining popularity, challenges such as non-standardized characteristics, custom software, inadequate commercial support, and integration issues with other instruments need to be addressed. The field of multimodal imaging or multiplexed imaging allows for simultaneous signal reproduction from multiple imaging strategies. Intraoperatively, MMI can be integrated into frameless stereotactic surgery. Recent developments in medical imaging modalities such as magnetic resonance imaging (MRI), and Positron Emission Topography (PET) have brought new perspectives to multimodal imaging, enabling early cancer detection, molecular tracking, and real-time progression monitoring. Despite the evidence supporting the role of MMI in surgical decision-making, there is a need for comprehensive studies to validate and perform integration at the intersection of multiple imaging technologies. They were integrating mass spectrometry-based technologies (e.g., imaging mass spectrometry (IMS), imaging mass cytometry (IMC), and Ion mobility mass spectrometry ((IM-IM) with medical imaging modalities, offering promising avenues for molecular discovery and clinical applications. This review emphasizes the potential of multi-omics approaches in tissue mapping using MMI integrated into desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI), allowing for sequential analyses of the same section. By addressing existing knowledge gaps, this review encourages future research endeavors toward multi-omics approaches, providing a roadmap for future research and enhancing the value of MMI in molecular pathology for diagnosis.

From the lab to the field: acceptability of using electroencephalography with Indian preschool children

Background: Measurement of social and cognitive brain development using electroencephalography (EEG) offers the potential for early identification of children with elevated risk of developmental delay. However, there have been no published reports of how acceptable EEG technology is to parents and children within communities, especially in low-resource contexts such as in low and middle income countries (LMICs), which is an important question for the potential scalability of these assessments. We use a mixed-methods approach to examine whether EEG assessments are acceptable to children and their caregivers in a low resource community setting in India. Methods: We assessed the acceptability of neurophysiology research and Braintools (a novel neurodevelopmental assessment toolkit using concurrent EEG and eye-tracking technology) using: 1) a child engagement measure, 2) interviews with caregivers (n=8); 3) survey about caregiver's experience (n=36). Framework analysis was used to analyse interview data. Results: A high level of child engagement in EEG tasks was demonstrated, with children's gaze at the screen during the task averaging at 85.4% (±12.06%) of the task time. External distractions and noise during the tasks were measured, but not found to significantly effect child's attention to the screen during EEG tasks. Key topics were examined using the framework analysis: 1) parental experience of the assessment; and 2) the acceptability of research. From topic 1, four sub-themes were identified: i) caregivers' experience of the assessment, ii) caregivers' perception of child's experience of assessment, iii) logistical barriers and facilitators to participation, and iv) recommendations for improvement. Results from interviews and the survey indicated acceptability for gaze-controlled EEG research for parents and children. From topic 2, three themes were identified: i) caregivers' understanding of the research, ii) barriers to participation, and iii) facilitators to participation. Barriers to participation mainly included logistical challenges, such as geographic location and time, whereas involvement of the wider family in decision making was highlighted as an important facilitator to partake in the research. Conclusions: We demonstrate for the first time the acceptability of conducting neurodevelopmental assessments using concurrent EEG and eye-tracking in preschool children in uncontrolled community LMIC settings. This kind of research appears to be acceptable to the community and we identify potential barriers and facilitators of this research, thus allowing for future large scale research projects to be conducted investigating neurodevelopment and risk factors for suboptimal development in LMICs.

Low-field MRI: A report on the 2022 ISMRM workshop

In March 2022, the first ISMRM Workshop on Low-Field MRI was held virtually. The goals of this workshop were to discuss recent low field MRI technology including hardware and software developments, novel methodology, new contrast mechanisms, as well as the clinical translation and dissemination of these systems. The virtual Workshop was attended by 368 registrants from 24 countries, and included 34 invited talks, 100 abstract presentations, 2 panel discussions, and 2 live scanner demonstrations. Here, we report on the scientific content of the Workshop and identify the key themes that emerged. The subject matter of the Workshop reflected the ongoing developments of low-field MRI as an accessible imaging modality that may expand the usage of MRI through cost reduction, portability, and ease of installation. Many talks in this Workshop addressed the use of computational power, efficient acquisitions, and contemporary hardware to overcome the SNR limitations associated with low field strength. Participants discussed the selection of appropriate clinical applications that leverage the unique capabilities of low-field MRI within traditional radiology practices, other point-of-care settings, and the broader community. The notion of "image quality" versus "information content" was also discussed, as images from low-field portable systems that are purpose-built for clinical decision-making may not replicate the current standard of clinical imaging. Speakers also described technical challenges and infrastructure challenges related to portability and widespread dissemination, and speculated about future directions for the field to improve the technology and establish clinical value.

Current role of portable MRI in diagnosis of acute neurological conditions

Neuroimaging is an inevitable component of the assessment of neurological emergencies. Magnetic resonance imaging (MRI) is the preferred imaging modality for detecting neurological pathologies and provides higher sensitivity than other modalities. However, difficulties such as intra-hospital transport, long exam times, and availability in strict access-controlled suites limit its utility in emergency departments and intensive care units (ICUs). The evolution of novel imaging technologies over the past decades has led to the development of portable MRI (pMRI) machines that can be deployed at point-of-care. This article reviews pMRI technologies and their clinical implications in acute neurological conditions. Benefits of pMRI include timely and accurate detection of major acute neurological pathologies such as stroke and intracranial hemorrhage. Additionally, pMRI can be potentially used to monitor the progression of neurological complications by facilitating serial measurements at the bedside.

Brain imaging with portable low-field MRI

The advent of portable, low-field MRI (LF-MRI) heralds new opportunities in neuroimaging. Low power requirements and transportability have enabled scanning outside the controlled environment of a conventional MRI suite, enhancing access to neuroimaging for indications that are not well suited to existing technologies. Maximizing the information extracted from the reduced signal-to-noise ratio of LF-MRI is crucial to developing clinically useful diagnostic images. Progress in electromagnetic noise cancellation and machine learning reconstruction algorithms from sparse k-space data as well as new approaches to image enhancement have now enabled these advancements. Coupling technological innovation with bedside imaging creates new prospects in visualizing the healthy brain and detecting acute and chronic pathological changes. Ongoing development of hardware, improvements in pulse sequences and image reconstruction, and validation of clinical utility will continue to accelerate this field. As further innovation occurs, portable LF-MRI will facilitate the democratization of MRI and create new applications not previously feasible with conventional systems.

Gone Too Soon: priorities for action to prevent premature mortality associated with mental illness and mental distress

Globally, too many people die prematurely from suicide and the physical comorbidities associated with mental illness and mental distress. The purpose of this Review is to mobilise the translation of evidence into prioritised actions that reduce this inequity. The mental health research charity, MQ Mental Health Research, convened an international panel that used roadmapping methods and review evidence to identify key factors, mechanisms, and solutions for premature mortality across the social-ecological system. We identified 12 key overarching risk factors and mechanisms, with more commonalities than differences across the suicide and physical comorbidities domains. We also identified 18 actionable solutions across three organising principles: the integration of mental and physical health care; the prioritisation of prevention while strengthening treatment; and the optimisation of intervention synergies across social-ecological levels and the intervention cycle. These solutions included accessible, integrated high-quality primary care; early life, workplace, and community-based interventions co-designed by the people they should serve; decriminalisation of suicide and restriction of access to lethal means; stigma reduction; reduction of income, gender, and racial inequality; and increased investment. The time to act is now, to rebuild health-care systems, leverage changes in funding landscapes, and address the effects of stigma, discrimination, marginalisation, gender violence, and victimisation.

Feasibility of and experience using a portable MRI scanner in the neonatal intensive care unit

OBJECTIVE

A portable, low-field MRI system is now Food and Drug Administration cleared and has been shown to be safe and useful in adult intensive care unit settings. No neonatal studies have been performed. The objective is to assess our preliminary experience and assess feasibility of using the portable MRI system at the bedside in a neonatal intensive care unit (NICU) at a quaternary children's hospital.

STUDY DESIGN

This was a single-site prospective cohort study in neonates ≥2 kg conducted between October and December 2020. All parents provided informed consent. Neonates underwent portable MRI examination in the NICU with support equipment powered on and attached to the neonate during the examination. A paediatric radiologist interpreted each portable MRI examination. The study outcome variable was percentage of portable MRI examinations completed without artefacts that would hinder diagnosis. Findings were compared between portable MRI examinations and standard of care examinations.

RESULTS

Eighteen portable, low-field MRI examinations were performed on 14 neonates with an average age of 29.7 days (range 1-122 days). 94% (17 of 18) of portable MRI examinations were acquired without significant artefact. Significant intracranial pathology was visible on portable MRI, but subtle abnormalities were missed. The examination reads were concordant in 59% (10 of 17) of cases and significant pathology was missed in 12% (2 of 17) of cases.

CONCLUSION

This single-centre series demonstrated portable MRI examinations can be performed safely with standard patient support equipment present in the NICU. These findings demonstrate that portable MRI could be used in the future to guide care in the NICU setting.

TRIAL REGISTRATION NUMBER

NCT04629469.

Low-field MRI: Clinical promise and challenges

Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high-field devices remain expensive to install and operate, making them scarce outside of high-income countries and major population centers. Low-field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low-field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low-field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low-field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI-guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low-field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.

Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions

Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34-0.5 × 0.34-0.5 × 3-5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = -19.0-15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Practical needs and considerations for refugees and other forcibly displaced persons with neurological disorders: Recommendations using a modified Delphi approach

Background: There are >70 million forcibly displaced people worldwide, including refugees, internally displaced persons, and asylum seekers. While the health needs of forcibly displaced people have been characterized in the literature, more still needs to be done globally to translate this knowledge into effective policies and actions, particularly in neurology. Methods: In 2020, a global network of published experts on neurological disease and refugees was convened. Nine physician experts from nine countries (2 low, 1 lower-middle income, 5 upper-middle, 1 high income) with experience treating displaced people originating from 18 countries participated in three survey and two discussion rounds in accordance with the Delphi method. Results: A consensus list of priority interventions for treating neurological conditions in displaced people was created, agnostic to cost considerations, with the ten highest ranking tests or treatments ranked as: computerized tomography scans, magnetic resonance imaging scans, levetiracetam, acetylsalicylic acid, carbamazepine, paracetamol, sodium valproate, basic blood tests, steroids and anti-tuberculous medication. The most important contextual considerations (100% consensus) were all economic and political, including the economic status of the displaced person's country of origin, the host country, and the stage in the asylum seeking process. The annual cost to purchase the ten priority neurological interventions for the entire displaced population was estimated to be 220 million USD for medications and 4.2 billion USD for imaging and tests. Conclusions: A need for neuroimaging and anti-seizure medications for forcibly displaced people was emphasized. These recommendations could guide future research and investment in neurological care for forcibly displaced people.

From the lab to the field: acceptability of using electroencephalography with Indian preschool children

Background: Measurement of social and cognitive brain development using electroencephalography (EEG) offers the potential for early identification of children with elevated risk of developmental delay. However, there have been no published reports of how acceptable EEG technology is to parents and children within communities, especially in low-resource contexts such as in low and middle income countries (LMICs), which is an important question for the potential scalability of these assessments. We use a mixed-methods approach to examine whether EEG assessments are acceptable to children and their caregivers in a low resource community setting in India. Methods: We assessed the acceptability of neurophysiology research and Braintools (a novel neurodevelopmental assessment toolkit using concurrent EEG and eye-tracking technology) using: 1) a child engagement measure, 2) interviews with caregivers (n=8); 3) survey about caregiver’s experience (n=36). Framework analysis was used to analyse interview data. Results: Key topics were examined using the framework analysis: 1) parental experience of the assessment; and 2) the acceptability of research. From topic 1, four sub-themes were identified: i) caregivers’ experience of the assessment, ii) caregivers’ perception of child's experience of assessment, iii) logistical barriers and facilitators to participation, and iv) recommendations for improvement. From topic 2, three themes were identified: i) caregivers' understanding of the research, ii) barriers to participation, and iii) facilitators to participation. Conclusions: We demonstrate for the first time the acceptability of conducting neurodevelopmental assessments using concurrent EEG and eye-tracking in preschool children in uncontrolled community LMIC settings. This kind of research appears to be acceptable to the community and we identify potential barriers and facilitators of this research, thus allowing for future large scale research projects to be conducted investigating neurodevelopment and risk factors for suboptimal development in LMICs.

Practical needs and considerations for refugees and other forcibly displaced persons with neurological disorders: Recommendations using a modified Delphi approach

Background: There are >70 million forcibly displaced people worldwide, including refugees, internally displaced persons, and asylum seekers. While the health needs of forcibly displaced people have been characterized in the literature, more still needs to be done globally to translate this knowledge into effective policies and actions, particularly in neurology. Methods: In 2020, a global network of published experts on neurological disease and refugees was convened. Nine physician experts from nine countries (2 low, 1 lower-middle income, 5 upper-middle, 1 high income) with experience treating displaced people originating from 18 countries participated in three survey and two discussion rounds in accordance with the Delphi method. Results: A consensus list of priority interventions for treating neurological conditions in displaced people was created, agnostic to cost considerations, with the ten highest ranking tests or treatments ranked as: computerized tomography scans, magnetic resonance imaging scans, levetiracetam, acetylsalicylic acid, carbamazepine, paracetamol, sodium valproate, basic blood tests, steroids and anti-tuberculous medication. The most important contextual considerations (100% consensus) were all economic and political, including the economic status of the displaced person's country of origin, the host country, and the stage in the asylum seeking process. The annual cost to purchase the ten priority neurological interventions for the entire displaced population was estimated to be 220 million USD for medications and 4.2 billion USD for imaging and tests. Conclusions: A need for neuroimaging and anti-seizure medications for forcibly displaced people was emphasized. These recommendations could guide future research and investment in neurological care for forcibly displaced people.