Five steps to make MRI scanners more affordable to the world

Quantitative spatial visualization of X-ray irradiation via redox reaction by dynamic nuclear polarization magnetic resonance imaging

The dose of X-ray irradiation is commonly measured by point assessment with an ionization chamber dosimeter. However, to achieve spatially accurate delivery of X-ray to avoid the exposure to normal tissues, an accurate imaging method for spatially and quantitatively detecting exposure is required. Herein, we present a novel method to visualize X-ray exposure using low-field dynamic nuclear polarization magnetic resonance imaging (DNP-MRI) with nitroxyl radical tempol as the chemical dosimeter. In this system, gel phantoms containing glutathione (GSH) and the paramagnetic tempol radical were used to monitor the deposited X-ray-irradiation via the redox reaction. The tempol radical level was evaluated by DNP-MRI whose signal intensity was linearly correlated with the radical concentration. The radical level in the presence of GSH decreased in proportion to the dose of X-irradiation deposited. In an imaging experiment simulating clinical radiotherapy, we used a clinical linear accelerator with a radiotherapy planning software to confirm the utility of the exposure imaging. The X-ray exposure and its distribution were clearly visualized on the gel phantom image acquired by DNP-MRI. The results were consistent with those specified in the radiotherapy plan where the intensity of the radiation beam was modulated. This exposure estimation will be useful for determining an accurate irradiation field and reducing off-target exposure in clinical settings.

Global Workforce and Access: Demand, Education, Quality

There has long existed a substantial disparity in access to radiotherapy globally. This issue has only been exacerbated as the growing disparity of cancer incidence between high-income countries (HIC) and low and middle-income countries (LMICs) widens, with a pronounced increase in cancer cases in LMICs. Even within HICs, iniquities within local communities may lead to a lack of access to care. Due to these trends, it is imperative to find solutions to narrow global disparities. This requires the engagement of a diverse cohort of stakeholders, including working professionals, non-governmental organizations, nonprofits, professional societies, academic and training institutions, and industry. This review brings together a diverse group of experts to highlight critical areas that could help reduce the current global disparities in radiation oncology. Advancements in technology and treatment, such as artificial intelligence, brachytherapy, hypofractionation, and digital networks, in combination with implementation science and novel funding mechanisms, offer means for increasing access to care and education globally. Common themes across sections reveal how utilizing these new innovations and strengthening collaborative efforts among stakeholders can help improve access to care globally while setting the framework for the next generation of innovations.

Making a difference: 5 years of Cardiac Surgery Intersociety Alliance (CSIA)

Informed by the almost unimaginable unmet need for cardiac surgery in the developing regions of the world, leading surgeons, cardiologists, editors in chief of the major cardiothoracic journals as well as representatives of medical industry and government convened in December 2017 to address this unacceptable disparity in access to care. The ensuing "Cape Town Declaration" constituted a clarion call to cardiac surgical societies to jointly advocate the strengthening of sustainable, local cardiac surgical capacity in the developing world. The Cardiac Surgery Intersociety Alliance (CSIA) was thus created, comprising The Society of Thoracic Surgeons (STS), the American Association for Thoracic Surgery (AATS), the Asian Society for Cardiovascular and Thoracic Surgery (ASCVTS), the European Association for Cardio-Thoracic Surgery (EACTS) and the World Heart Federation (WHF). The guiding principle was advocacy for sustainable cardiac surgical capacity in low-income countries. As a first step, a global needs assessment confirmed rheumatic heart disease as the overwhelming pathology requiring cardiac surgery in these regions. Subsequently, CSIA published a request for proposals to support fledgling programs that could demonstrate the backing by their governments and health care institution. Out of 11 applicants, and following an evaluation of the sites, including site visits to the 3 finalists, Mozambique and Rwanda were selected as the first Pilot Sites. Subsequently, a mentorship and training agreement was completed between Mozambique and the University of Cape Town, a middle-income country with a comparable burden of rheumatic heart disease. The agreement entails regular video calls between the heart teams, targeted training across all aspects of cardiac surgery, as well as on-site presence of mentoring teams for complex cases with the strict observance of "assisting only." In Rwanda, Team Heart, a US and Rwanda-based nongovernmental organization (NGO) that has been performing cardiac surgery in Rwanda and helping to train the cardiac surgery workforce since 2008, has agreed to continue providing mentorship for the local team and to assist in the establishment of independent cardiac surgery with all that entails. This involves intermittent virtual conferences between Rwandan and US cardiologists for surgical case selection. Five years after CSIA was founded, its "Seal of Approval" for the sustainability of endorsed programs in Mozambique and Rwanda has resulted in higher case numbers, a stronger government commitment, significant upgrades of infrastructure, the nurturing of generous consumable donations by industry and the commencement of negotiations with global donors for major grants. Extending the CSIA Seal to additional deserving programs could further align the international cardiac surgical community with the principle of local cardiac surgery capacity-building in developing countries.

Making a Difference: 5 Years of Cardiac Surgery Intersociety Alliance (CSIA)

Informed by the almost unimaginable unmet need for cardiac surgery in the developing regions of the world, leading surgeons, cardiologists, editors in chief of the major cardiothoracic journals as well as representatives of medical industry and government convened in December 2017 to address this unacceptable disparity in access to care. The ensuing "Cape Town Declaration" constituted a clarion call to cardiac surgical societies to jointly advocate the strengthening of sustainable, local cardiac surgical capacity in the developing world. The Cardiac Surgery Intersociety Alliance (CSIA) was thus created, comprising The Society of Thoracic Surgeons (STS), the American Association for Thoracic Surgery (AATS), the Asian Society for Cardiovascular and Thoracic Surgery (ASCVTS), the European Association for Cardio-Thoracic Surgery (EACTS) and the World Heart Federation (WHF). The guiding principle was advocacy for sustainable cardiac surgical capacity in low-income countries. As a first step, a global needs assessment confirmed rheumatic heart disease as the overwhelming pathology requiring cardiac surgery in these regions. Subsequently, CSIA published a request for proposals to support fledgling programs that could demonstrate the backing by their governments and health care institution. Out of 11 applicants, and following an evaluation of the sites, including site visits to the 3 finalists, Mozambique and Rwanda were selected as the first Pilot Sites. Subsequently, a mentorship and training agreement was completed between Mozambique and the University of Cape Town, a middle-income country with a comparable burden of rheumatic heart disease. The agreement entails regular video calls between the heart teams, targeted training across all aspects of cardiac surgery, as well as on-site presence of mentoring teams for complex cases with the strict observance of "assisting only." In Rwanda, Team Heart, a US and Rwanda-based non-governmental organization (NGO) that has been performing cardiac surgery in Rwanda and helping to train the cardiac surgery workforce since 2008, has agreed to continue providing mentorship for the local team and to assist in the establishment of independent cardiac surgery with all that entails. This involves intermittent virtual conferences between Rwandan and US cardiologists for surgical case selection. Five years after CSIA was founded, its "Seal of Approval" for the sustainability of endorsed programs in Mozambique and Rwanda has resulted in higher case numbers, a stronger government commitment, significant upgrades of infrastructure, the nurturing of generous consumable donations by industry and the commencement of negotiations with global donors for major grants. Extending the CSIA Seal to additional deserving programs could further align the international cardiac surgical community with the principle of local cardiac surgery capacity-building in developing countries.

Scan With Me: A Train-the-Trainer Program to Upskill MRI Personnel in Low- and Middle-Income Countries

PURPOSE

Access to MRI in low- and middle-income countries (LMICs) remains among the poorest in the world. The lack of skilled MRI personnel exacerbates access gaps, reinforcing long-standing health disparities. The Scan With Me (SWiM) program aims to sustainably create a network of highly skilled MRI technologists in LMICs who will facilitate the transfer of MRI knowledge and skills to their peers and contribute to the implementation of highly valuable imaging protocols for effective clinical and research use.

METHODS

The program introduces a case-based curriculum designed using a novel train-the-trainer approach, integrated with peer-collaborative learning to upskill practicing MRI technologists in LMICs. The 6-week curriculum uses the teach-try-use approach, which combines self-paced didactic lectures covering the basics of MR image acquisition (teach) with hands-on expert-guided scanning experience (try) and the implementation of protocols tailored to provide the best possible images on their infrastructures (use). Each program includes research translation skills training using an established advanced MRI technique relevant to LMICs. A pilot program focused on cardiac MRI (CMR) was conducted to assess the program's curriculum, delivery, and evaluation methods.

RESULTS

Forty-three MRI technologists from 16 LMICs participated in the pilot CMR program and, over the course of the training, implemented optimized CMR protocols that reduced acquisition times while improving image quality. The training resources and scanner-specific standardized protocols are published openly for public use in an online repository. In general, at the end of the program, learners reported considerable improvements in CMR knowledge and skills. All respondents to the program evaluation survey agreed to recommend the program to their colleagues, while 87% indicated interest in returning to help train others.

CONCLUSIONS

The SWiM program is the first master class in MRI acquisition for practicing imaging technologists in LMICs. The program holds the potential to help reduce disparities in MRI expertise and access. The support of the MRI community, imaging societies, and funding agencies will increase its reach and further its impact in democratizing MRI.

Radiologists' Role in Decolonizing Global Health

The colonial origins and power imbalances between Western high-income countries and low- and middle-income countries (LMICs) are barriers to self-reliance and sustained structural improvements to health care systems. Radiologists working in global health (global radiologists) are tasked with improving the state of imaging in LMICs while mitigating the effects of colonial structures and processes. To accomplish this, we need to be aware of factors such as colonialism, neocolonialism, parachute research, and brain drain that contribute to global health inequities. Potential solutions to decolonizing global radiology include commitment to understanding local context; strengthening local capacity for technology advancement, research, and development; and policies and educational programs to combat medical brain drain from LMICs. In this article, we describe how the legacies of colonialism can interfere with improving health in LMICS, despite the best intentions, and provide a call to action for decolonizing our field with intentional approaches and equitable partnerships that emphasize investments in sustainable infrastructure, robust training of personnel, and policies that support self-reliance to match true health system strengthening with our passion for addressing health equity.

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.

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.

Making a difference: 5 years of Cardiac Surgery Intersociety Alliance (CSIA)

Informed by the almost unimaginable unmet need for cardiac surgery in the developing regions of the world, leading surgeons, cardiologists, editors in chief of the major cardiothoracic journals as well as representatives of medical industry and government convened in December 2017 to address this unacceptable disparity in access to care. The ensuing "Cape Town Declaration" constituted a clarion call to cardiac surgical societies to jointly advocate the strengthening of sustainable, local cardiac surgical capacity in the developing world. The Cardiac Surgery Intersociety Alliance (CSIA) was thus created, comprising The Society of Thoracic Surgeons (STS), the American Association for Thoracic Surgery (AATS), the Asian Society for Cardiovascular and Thoracic Surgery (ASCVTS), the European Association for Cardio-Thoracic Surgery (EACTS) and the World Heart Federation (WHF). The guiding principle was advocacy for sustainable cardiac surgical capacity in low-income countries. As a first step, a global needs assessment confirmed rheumatic heart disease as the overwhelming pathology requiring cardiac surgery in these regions. Subsequently, CSIA published a request for proposals to support fledgling programmes that could demonstrate the backing by their governments and health care institution. Out of 11 applicants, and following an evaluation of the sites, including site visits to the 3 finalists, Mozambique and Rwanda were selected as the first Pilot Sites. Subsequently, a mentorship and training agreement was completed between Mozambique and the University of Cape Town, a middle-income country with a comparable burden of rheumatic heart disease. The agreement entails regular video calls between the heart teams, targeted training across all aspects of cardiac surgery, as well as on-site presence of mentoring teams for complex cases with the strict observance of 'assisting only'. In Rwanda, Team Heart, a US and Rwanda-based non-governmental organization (NGO) that has been performing cardiac surgery in Rwanda and helping to train the cardiac surgery workforce since 2008, has agreed to continue providing mentorship for the local team and to assist in the establishment of independent cardiac surgery with all that entails. This involves intermittent virtual conferences between Rwandan and US cardiologists for surgical case selection. Five years after CSIA was founded, its 'Seal of Approval' for the sustainability of endorsed programmes in Mozambique and Rwanda has resulted in higher case numbers, a stronger government commitment, significant upgrades of infrastructure, the nurturing of generous consumable donations by industry and the commencement of negotiations with global donors for major grants. Extending the CSIA Seal to additional deserving programmes could further align the international cardiac surgical community with the principle of local cardiac surgery capacity-building in developing countries.

Making a difference: 5 years of Cardiac Surgery Intersociety Alliance (CSIA)

SUMMARY

Informed by the almost unimaginable unmet need for cardiac surgery in the developing regions of the world, leading surgeons, cardiologists, editors in chief of the major cardiothoracic journals as well as representatives of medical industry and government convened in December 2017 to address this unacceptable disparity in access to care. The ensuing "Cape Town Declaration" constituted a clarion call to cardiac surgical societies to jointly advocate the strengthening of sustainable, local cardiac surgical capacity in the developing world. The Cardiac Surgery Intersociety Alliance (CSIA) was thus created, comprising The Society of Thoracic Surgeons (STS), the American Association for Thoracic Surgery (AATS), the Asian Society for Cardiovascular and Thoracic Surgery (ASCVTS), the European Association for Cardio-Thoracic Surgery (EACTS) and the World Heart Federation (WHF). The guiding principle was advocacy for sustainable cardiac surgical capacity in low-income countries. As a first step, a global needs assessment confirmed rheumatic heart disease as the overwhelming pathology requiring cardiac surgery in these regions. Subsequently, CSIA published a request for proposals to support fledgling programmes that could demonstrate the backing by their governments and health care institution. Out of 11 applicants, and following an evaluation of the sites, including site visits to the 3 finalists, Mozambique and Rwanda were selected as the first Pilot Sites. Subsequently, a mentorship and training agreement was completed between Mozambique and the University of Cape Town, a middle-income country with a comparable burden of rheumatic heart disease. The agreement entails regular video calls between the heart teams, targeted training across all aspects of cardiac surgery, as well as on-site presence of mentoring teams for complex cases with the strict observance of 'assisting only'. In Rwanda, Team Heart, a US and Rwanda-based non-governmental organization (NGO) that has been performing cardiac surgery in Rwanda and helping to train the cardiac surgery workforce since 2008, has agreed to continue providing mentorship for the local team and to assist in the establishment of independent cardiac surgery with all that entails. This involves intermittent virtual conferences between Rwandan and US cardiologists for surgical case selection. Five years after CSIA was founded, it's 'Seal of Approval' for the sustainability of endorsed programmes in Mozambique and Rwanda has resulted in higher case numbers, a stronger government commitment, significant upgrades of infrastructure, the nurturing of generous consumable donations by industry and the commencement of negotiations with global donors for major grants. Extending the CSIA Seal to additional deserving programmes could further align the international cardiac surgical community with the principle of local cardiac surgery capacity-building in developing countries.

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.

High-Q metasurface signal isolator for 1.5T surface coil magnetic resonance imaging on the go

The combination of surface coils and metamaterials remarkably enhance magnetic resonance imaging (MRI) performance for significant local staging flexibility. However, due to the coupling in between, impeded signal-to-noise ratio (SNR) and low-contrast resolution, further hamper the future growth in clinical MRI. In this paper, we propose a high-Q metasurface decoupling isolator fueled by topological LC loops for 1.5T surface coil MRI system, increasing the magnetic field up to fivefold at 63.8 MHz. We have employed a polarization conversion mechanism to effectively eliminate the coupling between the MRI metamaterial and the radio frequency (RF) surface transmitter-receiver coils. Furthermore, a high-Q metasurface isolator was achieved by taking advantage of bound states in the continuum (BIC) for extremely high-resolution MRI and spectroscopy. An equivalent physical model of the miniaturized metasurface design was put forward through LC circuit analysis. This study opens up a promising route for the easy-to-use and portable surface coil MRI scanners.

MRI-Based Brain Volume Scoring in Cerebral Malaria Is Externally Valid and Applicable to Lower-Resolution Images

BACKGROUND AND PURPOSE

Children with cerebral malaria have an elevated risk of mortality and neurologic morbidity. Both mortality and morbidity are associated with initially increased brain volume on MR imaging, as graded by the Brain Volume Score, a subjective ordinal rating scale created specifically for brain MRIs in children with cerebral malaria. For the Brain Volume Score to be more widely clinically useful, we aimed to determine its independent reproducibility and whether it can be applicable to lower-resolution MRIs.

MATERIALS AND METHODS

To assess the independent reproducibility of the Brain Volume Score, radiologists not associated with the initial study were trained to score MRIs from a new cohort of patients with cerebral malaria. These scores were then compared with survival and neurologic outcomes. To assess the applicability to lower-resolution MRI, we assigned Brain Volume Scores to brain MRIs degraded to simulate a very-low-field (64 mT) portable scanner and compared these with the original scores assigned to the original nondegraded MRIs.

RESULTS

Brain Volume Scores on the new cohort of patients with cerebral malaria were highly associated with outcomes (OR for mortality = 16, P < .001). Scoring of the simulated degraded images remained consistent with the Brain Volume Scores assigned to the original higher-quality (0.35 T) images (intraclass coefficients > 0.86).

CONCLUSIONS

Our findings demonstrate that the Brain Volume Score is externally valid in reproducibly predicting outcomes and can be reliably assigned to lower-resolution images.

Real-time ultrasound-derived fat fraction in pediatric population: feasibility validation with MR-PDFF

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in children. To avoid limitations of liver biopsy and MRI, quantitative ultrasound has become a research focus. Ultrasound-derived fat fraction (UDFF) is based on a combination of backscatter coefficient and attenuation parameter.

OBJECTIVE

The objectives of the study were to determine (1) agreement between UDFF/MRI proton density fat fraction (MR-PDFF) and (2) whether BMI and age are predictive for UDFF.

MATERIALS AND METHODS

This cross-sectional prospective study included a convenience sample of 46 children referred for clinically indicated abdominal MRI. MR-PDFF and five acquisitions of UDFF were collected. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to assess agreement between MR-PDFF and UDFF. Receiver operating characteristic curves were calculated for UDFF prediction of liver steatosis (MR-PDFF ≥ 6%). Multivariable regression was performed to assess BMI and age as predictors for UDFF.

RESULTS

Twenty-two participants were male, 24 were female, and the mean age was 14 ± 3 (range: 7-18) years. Thirty-six out of 46 participants had normal liver fat fraction <6%, and 10/46 had liver steatosis. UDFF was positively associated with MR-PDFF (ICC 0.92 (95% CI, 0.89-0.96). The mean bias between UDFF and MR-PDFF was 0.64% (95% LOA, -5.3-6.6%). AUROC of UDFF for steatosis was of 0.95 (95% CI, 0.89-0.99). UDFF cutoff of 6% had a sensitivity of 90% (95% CI, 55-99%) and a specificity of 94% (95% CI, 81-0.99%). BMI was an independent predictor of UDFF (correlation: 0.55 (95% CI, 0.35-0.95)).

CONCLUSIONS

UDFF shows strong agreement with MR-PDFF in children. A UDFF cutoff of 6% provides good sensitivity and specificity for detection of MR-PDFF of ≥ 6%.

Deep learning enabled fast 3D brain MRI at 0.055 tesla

In recent years, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications. However, its quality is poor and scan time is long. We propose a fast acquisition and deep learning reconstruction framework to accelerate brain MRI at 0.055 tesla. The acquisition consists of a single average three-dimensional (3D) encoding with 2D partial Fourier sampling, reducing the scan time of T1- and T2-weighted imaging protocols to 2.5 and 3.2 minutes, respectively. The 3D deep learning leverages the homogeneous brain anatomy available in high-field human brain data to enhance image quality, reduce artifacts and noise, and improve spatial resolution to synthetic 1.5-mm isotropic resolution. Our method successfully overcomes low-signal barrier, reconstructing fine anatomical structures that are reproducible within subjects and consistent across two protocols. It enables fast and quality whole-brain MRI at 0.055 tesla, with potential for widespread biomedical applications.

Do magnetic resonance imaging features differ between persons with multiple sclerosis of various races and ethnicities?

Those of African American or Latin American descent have been demonstrated to have more severe clinical presentations of multiple sclerosis (MS) than non-Latin American White people with MS. Concurrently, radiological burden of disease on magnetic resonance imaging (MRI) in African Americans with MS has also been described as being more aggressive. Here, we review MRI studies in diverse racial and ethnic groups (adult and pediatric) investigating lesion burden, inflammation, neurodegeneration, and imaging response to disease modifying therapy. We also discuss why such disparities may exist beyond biology, and how future studies may provide greater insights into underlying differences.