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

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.

Clinical Outcome Comparison between CT-Guided Versus all MRI-Guided Scenarios in Brachytherapy for Cervical Cancer: A Single-Institute Experience

OBJECTIVES

Image-guided adaptive brachytherapy (IGABT) is the standard of care for patients with cervical cancer. The objective of this study was to compare the treatment outcomes and adverse effects of computed tomography (CT)-guided and magnetic resonance imaging (MRI)-guided scenarios.

MATERIALS AND METHODS

Data of patients with cervical cancer treated using external beam radiotherapy followed by IGABT from 2012 to 2016 were retrospectively reviewed. CT-guided IGABT was compared with the three modes of MRI-guided IGABT: pre-brachytherapy (MRI Pre-BT) without applicator insertion for fusion, planning MRI with applicator in-place in at least 1 fraction (MRI ≥1Fx), and MRI in every fraction (MRI EveryFx). Patient characteristics, oncologic outcomes, and late radiation toxicity were analyzed using descriptive, survival, and correlation statistics.

RESULTS

Overall, 354 patients were evaluated with a median follow-up of 60 months. The 5-year overall survival (OS) rates were 61.5%, 65.2%, 54.4%, and 63.7% with CT-guided, MRI PreBT, MRI ≥1Fx, and MRI EveryFx IGABT, respectively with no significant differences (p = 0.522). The 5-year local control (LC) rates were 92.1%, 87.8%, 80.7%, and 76.5% (p = 0.133), respectively, with a significant difference observed between the CT-guided and MRI ≥1Fx (p = 0.018). The grade 3-4 late gastrointestinal toxicity rates were 6% in the CT-guided, MRI ≥1Fx, and MRI EveryFx, and 8% in MRI PreBT. The grade 3-4 late genitourinary toxicity rates were 4% in the CT-guided, 2% in MRI PreBT, 1% in MRI ≥1Fx, and none in MRI EveryFx. No significant differences were observed in the oncologic and toxicity outcomes among MRI PreBT, MRI ≥1Fx, and MRI EveryFx.

CONCLUSIONS

CT-guided IGABT yielded an acceptable 5-year OS, LC, and toxicity profile compared with all MRI scenarios and is a potentially feasible option in resource-limited 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.

Upfront Thoracic Magnetic Resonance Imaging for the Evaluation of Thymic Lesions to Reduce Non-Therapeutic Diagnostic Thymectomy: A Narrative Review

Background: Thymic pathologies represent the most common lesions of the anterior mediastinum. They may be classified as malignant or benign. Current diagnostic pathways recommend an initial assessment with computed tomography (CT) imaging to delineate potentially malignant thymic lesions. Despite this, high rates of non-therapeutic thymectomy continue to be observed. This carries with it significant anaesthetic, operative, and post-operative risks, in addition to healthcare costs. Consequently, there is a growing interest in magnetic resonance imaging (MRI) as a primary diagnostic modality for lesions of the anterior mediastinum. This narrative review outlines the current approaches to the evaluation of thymic lesions, with a discussion of the strengths and limitations of CT and MRI imaging modalities. It also evaluates the current discourse on the use of upfront MRI for thymic and anterior mediastinal lesion assessment. Methods: A narrative review was performed following a search on the Medline database. Articles that were evaluated had explored the role of MRI on the evaluation of thymic and anterior mediastinal lesions. Results: Current work-up for thymic and anterior mediastinal lesions are highly variable and centre around the use of CT. Upfront MRI demonstrates a similar accuracy to CT for various thymic and anterior mediastinal pathologies; however, the efforts to integrate this approach into routine practice remain in their infancy, with no standardised guidelines that exist. Conclusions: This narrative review demonstrates that there is a paucity of evidence relating to the sensitivity and specificity of MRI compared to CT for thymic lesion analysis and their subsequent relationship with non-therapeutic thymectomy. Future prospective trials to assess the role of MRI in thymic lesion determination are required to understand whether MRI can more accurately characterise these lesions to reduce non-therapeutic thymectomy. Additionally, further research efforts are required to characterise best-practice methods for integrating MRI into diagnostic pathways for these lesions in a cost-effective and resource-conscious manner.

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.

Predicting Rheumatoid Arthritis Development Using Hand Ultrasound and Machine Learning-A Two-Year Follow-Up Cohort Study

BACKGROUND

The early diagnosis and treatment of rheumatoid arthritis (RA) are essential to prevent joint damage and enhance patient outcomes. Diagnosing RA in its early stages is challenging due to the nonspecific and variable clinical signs and symptoms. Our study aimed to identify the most predictive features of hand ultrasound (US) for RA development and assess the performance of machine learning models in diagnosing preclinical RA.

METHODS

We conducted a prospective cohort study with 326 adults who had experienced hand joint pain for less than 12 months and no clinical arthritis. We assessed the participants clinically and via hand US at baseline and followed them for 24 months. Clinical progression to RA was defined according to the ACR/EULAR criteria. Regression modeling and machine learning approaches were used to analyze the predictive US features.

RESULTS

Of the 326 participants (45.10 ± 11.37 years/83% female), 123 (37.7%) developed clinical RA during follow-up. At baseline, 84.6% of the progressors had US synovitis, whereas 16.3% of the non-progressors did (p < 0.0001). Only 5.7% of the progressors had positive PD. Multivariate analysis revealed that the radiocarpal synovial thickness (OR = 39.8), PIP/MCP synovitis (OR = 68 and 39), and wrist effusion (OR = 12.56) on US significantly increased the odds of developing RA. ML confirmed these US features, along with the RF and anti-CCP levels, as the most important predictors of RA.

CONCLUSIONS

Hand US can identify preclinical synovitis and determine the RA risk. The radiocarpal synovial thickness, PIP/MCP synovitis, wrist effusion, and RF and anti-CCP levels are associated with RA development.

Clinical application of bladder MRI and the Vesical Imaging-Reporting and Data System

Diagnostic work-up and risk stratification in patients with bladder cancer before and after treatment must be refined to optimize management and improve outcomes. MRI has been suggested as a non-invasive technique for bladder cancer staging and assessment of response to systemic therapy. The Vesical Imaging-Reporting And Data System (VI-RADS) was developed to standardize bladder MRI image acquisition, interpretation and reporting and enables accurate prediction of muscle-wall invasion of bladder cancer. MRI is available in many centres but is not yet recommended as a first-line test for bladder cancer owing to a lack of high-quality evidence. Consensus-based evidence on the use of MRI-VI-RADS for bladder cancer care is needed to serve as a benchmark for formulating guidelines and research agendas until further evidence from randomized trials becomes available.

Comparison of image quality and diagnostic efficacy of routine clinical lumbar spine imaging at 0.55T and 1.5/3T

PURPOSE

To compare image quality, assess inter-reader variability, and evaluate the diagnostic efficacy of routine clinical lumbar spine sequences at 0.55T compared with those collected at 1.5/3T to assess common spine pathology.

METHODS

665 image series across 70 studies, collected at 0.55T and 1.5/3T, were assessed by two neuroradiology fellows for overall imaging quality (OIQ), artifacts, and accurate visualization of anatomical features (intervertebral discs, neural foramina, spinal cord, bone marrow, and conus / cauda equina nerve roots) using a 4-point Likert scale (1 = non-diagnostic to 4 = excellent). For the 0.55T scans, the most appropriate diagnosis(es) from a picklist of common spine pathologies was selected. The mean ± SD of all scores for all features for each sequence and reader at 0.55T and 1.5/3T were calculated. Paired t-tests (p ≤ 0.05) were used to compare ratings between field strengths. The inter-reader agreement was calculated using linear-weighted Cohen's Kappa coefficient (p ≤ 0.05). Unpaired VCG analysis for OIQ was additionally employed to represent differences between 0.55T and 1.5/3T (95 % CI).

RESULTS

All sequences at 0.55T were rated as acceptable (≥2) for diagnostic use by both readers despite significantly lower scores for some compared to those at 1.5/3T. While there was low inter-reader agreement on individual scores, the agreement on the diagnosis was high, demonstrating the potential of this system for detecting routine spine pathology.

CONCLUSIONS

Clinical lumbar spine imaging at 0.55T produces diagnostic-quality images demonstrating the feasibility of its use in diagnosing spinal pathology, including osteomyelitis/discitis, post-surgical changes with complications, and metastatic disease.

Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study

BACKGROUND

The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been a long-standing but important challenge. We aimed to develop a deep convolutional neural network (dCNN) optimisation method for MRI reconstruction and to reduce scan times and evaluate its effect on image quality and accuracy of oncological imaging biomarkers.

METHODS

In this multicentre, retrospective, cohort study, MRI data from patients with glioblastoma treated at Heidelberg University Hospital (775 patients and 775 examinations) and from the phase 2 CORE trial (260 patients, 1083 examinations, and 58 institutions) and the phase 3 CENTRIC trial (505 patients, 3147 examinations, and 139 institutions) were used to develop, train, and test dCNN for reconstructing MRI from highly undersampled single-coil k-space data with various acceleration rates (R=2, 4, 6, 8, 10, and 15). Independent testing was performed with MRIs from the phase 2/3 EORTC-26101 trial (528 patients with glioblastoma, 1974 examinations, and 32 institutions). The similarity between undersampled dCNN-reconstructed and original MRIs was quantified with various image quality metrics, including structural similarity index measure (SSIM) and the accuracy of undersampled dCNN-reconstructed MRI on downstream radiological assessment of imaging biomarkers in oncology (automated artificial intelligence-based quantification of tumour burden and treatment response) was performed in the EORTC-26101 test dataset. The public NYU Langone Health fastMRI brain test dataset (558 patients and 558 examinations) was used to validate the generalisability and robustness of the dCNN for reconstructing MRIs from available multi-coil (parallel imaging) k-space data.

FINDINGS

In the EORTC-26101 test dataset, the median SSIM of undersampled dCNN-reconstructed MRI ranged from 0·88 to 0·99 across different acceleration rates, with 0·92 (95% CI 0·92-0·93) for 10-times acceleration (R=10). The 10-times undersampled dCNN-reconstructed MRI yielded excellent agreement with original MRI when assessing volumes of contrast-enhancing tumour (median DICE for spatial agreement of 0·89 [95% CI 0·88 to 0·89]; median volume difference of 0·01 cm3 [95% CI 0·00 to 0·03] equalling 0·21%; p=0·0036 for equivalence) or non-enhancing tumour or oedema (median DICE of 0·94 [95% CI 0·94 to 0·95]; median volume difference of -0·79 cm3 [95% CI -0·87 to -0·72] equalling -1·77%; p=0·023 for equivalence) in the EORTC-26101 test dataset. Automated volumetric tumour response assessment in the EORTC-26101 test dataset yielded an identical median time to progression of 4·27 months (95% CI 4·14 to 4·57) when using 10-times-undersampled dCNN-reconstructed or original MRI (log-rank p=0·80) and agreement in the time to progression in 374 (95·2%) of 393 patients with data. The dCNN generalised well to the fastMRI brain dataset, with significant improvements in the median SSIM when using multi-coil compared with single-coil k-space data (p<0·0001).

INTERPRETATION

Deep-learning-based reconstruction of undersampled MRI allows for a substantial reduction of scan times, with a 10-times acceleration demonstrating excellent image quality while preserving the accuracy of derived imaging biomarkers for the assessment of oncological treatment response. Our developments are available as open source software and hold considerable promise for increasing the accessibility to MRI, pending further prospective validation.

FUNDING

Deutsche Forschungsgemeinschaft (German Research Foundation) and an Else Kröner Clinician Scientist Endowed Professorship by the Else Kröner Fresenius Foundation.

Setting up a biomodeling, virtual planning, and three-dimensional printing service in Uruguay

Virtual surgical planning and three-dimensional (D) printing are rapidly becoming essential for challenging and complex surgeries around the world. An Ibero-American survey reported a lack of awareness of technology benefits and scarce financial resources as the two main barriers to widespread adoption of 3-D technologies. The Pereira Rossell Hospital Center is a publicly funded maternal and pediatric academic clinical center in Uruguay, a low-resource Latin American country, that successfully created and has been running a 3-D unit for 4 years. The present work is a step-by-step review of the 3-D technology implementation process in a hospital with minimal financial investment. References to training, software, hardware, and the management of human resources are included. Difficulties throughout the process and future challenges are also discussed.

Multi-contrast high-field quality image synthesis for portable low-field MRI using generative adversarial networks and paired data

Introduction

Portable low-field strength (64mT) MRI scanners promise to increase access to neuroimaging for clinical and research purposes, however these devices produce lower quality images compared to high-field scanners. In this study, we developed and evaluated a deep learning architecture to generate high-field quality brain images from low-field inputs using a paired dataset of multiple sclerosis (MS) patients scanned at 64mT and 3T.

Methods

A total of 49 MS patients were scanned on portable 64mT and standard 3T scanners at Penn (n=25) or the National Institutes of Health (NIH, n=24) with T1-weighted, T2-weighted and FLAIR acquisitions. Using this paired data, we developed a generative adversarial network (GAN) architecture for low- to high-field image translation (LowGAN). We then evaluated synthesized images with respect to image quality, brain morphometry, and white matter lesions.

Results

Synthetic high-field images demonstrated visually superior quality compared to low-field inputs and significantly higher normalized cross-correlation (NCC) to actual high-field images for T1 (p=0.001) and FLAIR (p<0.001) contrasts. LowGAN generally outperformed the current state-of-the-art for low-field volumetrics. For example, thalamic, lateral ventricle, and total cortical volumes in LowGAN outputs did not differ significantly from 3T measurements. Synthetic outputs preserved MS lesions and captured a known inverse relationship between total lesion volume and thalamic volume.

Conclusions

LowGAN generates synthetic high-field images with comparable visual and quantitative quality to actual high-field scans. Enhancing portable MRI image quality could add value and boost clinician confidence, enabling wider adoption of this technology.

Hypertrophic Cardiomyopathy Diagnosis and Treatment in High- and Low-Income Countries: A Narrative Review

Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac condition characterized by unexplained left ventricular hypertrophy without a hemodynamic cause. This condition is prevalent in the United States, resulting in various clinical manifestations, including diastolic dysfunction, left ventricular outflow obstruction, cardiac ischemia, and atrial fibrillation. HCM is associated with several genetic mutations, with sarcomeric mutations being the most common and contributing to a more complex disease course. Early diagnosis of HCM is essential for effective management, as late diagnosis often requires invasive treatments and creates a substantial financial burden. Disparities in HCM diagnosis and treatment exist between high-income and low-income countries. High-income countries have more resources to investigate and implement advanced diagnostic and treatment modalities. In contrast, low-income countries face challenges in accessing diagnostic equipment, trained personnel, and affordable medications, leading to a lower quality of life and life expectancy for affected individuals. Diagnostic tools for HCM include imaging studies such as 2D echocardiography, cardiovascular magnetic resonance (CMR), and electrocardiograms (ECGs). CMR is considered the gold standard but remains inaccessible to a significant portion of the world's population, especially in low-income countries. Genetics plays a crucial role in HCM, with numerous mutations identified in various genes. Genetic counseling is essential but often limited in low-income countries due to resource constraints. Disparities in healthcare access and adherence to treatment recommendations exist between high-income and low-income countries, leading to differences in patient outcomes. Addressing these disparities is essential to improve the overall management of HCM on a global scale. In conclusion, this review highlights the complex nature of HCM, emphasizing the importance of early diagnosis, genetic counseling, and access to appropriate diagnostic and therapeutic interventions. Addressing healthcare disparities is crucial to ensure that all individuals with HCM receive timely and effective care, regardless of their geographic location or socioeconomic status.