Open-source magnetic resonance imaging: Improving access, science, and education through global collaboration.

Open-source practices and resources in magnetic resonance imaging (MRI) have increased substantially in recent years. This trend started with software and data being published open-source and, more recently, open-source hardware designs have become increasingly available. These developments towards a culture of sharing and establishing nonexclusive global collaborations have already improved the reproducibility and reusability of code and designs, while providing a more inclusive approach, especially for low-income settings. Community-driven standardization and documentation efforts are further strengthening and expanding these milestones. The future of open-source MRI is bright and we have just started to discover its full collaborative potential. In this review we will give an overview of open-source software and open-source hardware projects in human MRI research.

MaRCoS, an open-source electronic control system for low-field MRI.

Every magnetic resonance imaging (MRI) device requires an electronic control system that handles pulse sequences and signal detection and processing. Here we provide details on the architecture and performance of MaRCoS, a MAgnetic Resonance COntrol System developed by an open international community of low-field MRI researchers. MaRCoS is inexpensive and can handle cycle-accurate sequences without hard length limitations, rapid bursts of events, and arbitrary waveforms. It has also been readily adapted to meet the requirements of the various academic and private institutions participating in its development. We describe the MaRCoS hardware, firmware and software that enable all of the above, including a Python-based graphical user interface for pulse sequence implementation, data processing and image reconstruction.

Benchmarking the performance of a low-cost magnetic resonance control system at multiple sites in the open MaRCoS community.

PURPOSE: To describe the current properties and capabilities of an open-source hardware and software package that is being developed by many sites internationally with the aim of providing an inexpensive yet flexible platform for low-cost MRI. METHODS: This article describes three different setups from 50 to 360 mT in different settings, all of which used the MaRCoS console for acquiring data, and different types of software interface (custom-built GUI or Pulseq overlay) to acquire it. RESULTS: Images are presented both from phantoms and in vivo from healthy volunteers to demonstrate the image quality that can be obtained from the MaRCoS hardware/software interfaced to different low-field magnets. CONCLUSIONS: The results presented here show that a number of different sequences commonly used in the clinic can be programmed into an open-source system relatively quickly and easily, and can produce good quality images even at this early stage of development. Both the hardware and software will continue to develop, and it is an aim of this article to encourage other groups to join this international consortium.

Portable magnetic resonance imaging of patients indoors, outdoors and at home.

Mobile medical imaging devices are invaluable for clinical diagnostic purposes both in and outside healthcare institutions. Among the various imaging modalities, only a few are readily portable. Magnetic resonance imaging (MRI), the gold standard for numerous healthcare conditions, does not traditionally belong to this group. Recently, low-field MRI technology companies have demonstrated the first decisive steps towards portability within medical facilities and vehicles. However, these scanners' weight and dimensions are incompatible with more demanding use cases such as in remote and developing regions, sports facilities and events, medical and military camps, or home healthcare. Here we present in vivo images taken with a light, small footprint, low-field extremity MRI scanner outside the controlled environment provided by medical facilities. To demonstrate the true portability of the system and benchmark its performance in various relevant scenarios, we have acquired images of a volunteer's knee in: (i) an MRI physics laboratory; (ii) an office room; (iii) outside a campus building, connected to a nearby power outlet; (iv) in open air, powered from a small fuel-based generator; and (v) at the volunteer's home. All images have been acquired within clinically viable times, and signal-to-noise ratios and tissue contrast suffice for 2D and 3D reconstructions with diagnostic value. Furthermore, the volunteer carries a fixation metallic implant screwed to the femur, which leads to strong artifacts in standard clinical systems but appears sharp in our low-field acquisitions. Altogether, this work opens a path towards highly accessible MRI under circumstances previously unrealistic.

A CNN Based Software Gradiometer for Electromagnetic Background Noise Reduction in Low Field MRI Applications.

The shielding of electromagnetic noise is critical in obtaining magnetic resonance imaging measurements in the ultra-low magnetic field regime where the intrinsic signal-to-noise ratio is very small. The traditional approach of using an enclosure for electromagnetic shielding is expensive and hinders system portability. We describe here the use of a CNN-based software gradiometer to suppress the effect of electromagnetic ambient background noise sources that inductively couple into the signal detection coils. The system involves three ambient noise monitoring coils placed at a distance from the magnetic resonance signal detector. The three coils were used to synthesize the ambient noise captured by the signal detector; a convolutional neural network approach was used. Mathematical foundations are provided to justify the noise suppression framework. The results show that as much as 20-fold noise suppression can be achieved using an optimized convolutional neural network and simultaneous ambient noise measurements. The proposed approach has the potential to replace the requirement for magnetically shielded enclosures and make ultra-low field magnetic resonance imaging truly portable.

Improved patient-specific hyperthermia planning based on parametrized electromagnetic and thermal models for the SIGMA-30 applicator.

OBJECTIVE: To create an improved planning method for pediatric regional hyperthermia (RHT) using the SIGMA-30 applicator (SIGMA-30). MATERIALS AND METHODS: An electromagnetic model of SIGMA-30 was generated for use with the finite-difference time-domain (FDTD) method. Applying special MATLAB-based algorithms, voxel models of a pediatric patient with pelvic rhabdomyosarcoma were created from Computed-Tomography (CT) contours for use with the FDTD method and the finite-difference (FD) method capable of using either temperature-independent or temperature-dependent perfusion models for solving the Bioheat Transfer Equation (BHTE). Patient models were parametrized regarding, first, the positioning in the applicator, second, the absorbed power range and, third, different perfusion models, resulting in the so-called Parametrized Treatment Models (PTMs). A novel dedicated optimization procedure was developed based on quantitative comparison of numerical calculations against temperature and power measurements from two RHT therapies. RESULTS: Using measured data, a realistic absorbed power range in the patient model was estimated. Within this range, several FDTD and BHTE runs were performed and, applying the aforementioned optimization scheme, the best PTMs and perfusion models were identified for each therapy via a retrospective comparison with measurements in 14 temperature sensor positions: 5 in the tumor, 8 in rectum and one in bladder. CONCLUSION: A novel dedicated optimization procedure for identification of suitable patient-specific electromagnetic and thermal models, which can be used for improved patient planning, was developed and evaluated by comparison with treatment-derived measurements using SIGMA-30. The optimization procedure can be extended to other hyperthermia applicators and to other patient types, including adults.

A numerical study of pre-polarisation switching in ultra-low field magnetic resonance imaging using dynamic permanent magnet arrays.

Dynamically adjustable permanent magnet arrays have been proposed to generate switchable magnetic fields for pre-polarisation in Ultra-Low Field magnetic resonance imaging. However, the optimal switching dynamics of the pre-polarisation magnetic field as well as the energy requirements, mechanical forces and stresses during switching of the pre-polarisation field have not been evaluated. We analysed these requirements numerically and estimated the magnetic resonance signal strength and image quality for two practical switching modes in an instrument suitable for scanning the human head. Von Mises stress analysis showed that although magnetic forces were significantly higher for two specific rungs, the structural integrity of magnet rungs would not be compromised. Our simulations suggest that a significantly higher signal yield is obtained by switching off the pre-polarisation field with the angular velocity in each rung dependent on its location.

Towards ultimate low frequency air-core magnetometer sensitivity.

Air-core magnetometers are amongst the most commonly used magnetic field detectors in biomedical instruments. They offer excellent sensitivity, low fabrication complexity and a robust, cost-effective solution. However, air-core magnetometers must be tailored to the specific application to achieve high sensitivity, which can be decisive in the accuracy of the diagnoses and the time required for the examination. Existing methods proposed for the design of air-core magnetometers are based on simplified models and simulations using a reduced number of variables, potentially leading to sensitivity that is suboptimal. To circumvent this we chose a method with fewer assumptions and a larger number of decision variables which employed a genetic algorithm, a global optimisation method. Experimental validation shows that the model is appropriate for the design of highly sensitive air-core magnetometers. Moreover, our results support the suitability of a genetic algorithm for optimization in this context. The new method described herein will be made publicly available via our website to facilitate the development of less costly biomedical instruments using air-core magnetometers with unprecedented sensitivity.

Rotatable Small Permanent Magnet Array for Ultra-Low Field Nuclear Magnetic Resonance Instrumentation: A Concept Study.

OBJECT: We studied the feasibility of generating the variable magnetic fields required for ultra-low field nuclear magnetic resonance relaxometry with dynamically adjustable permanent magnets. Our motivation was to substitute traditional electromagnets by distributed permanent magnets, increasing system portability. MATERIALS AND METHODS: The finite element method (COMSOL®) was employed for the numerical study of a small permanent magnet array to calculate achievable magnetic field strength, homogeneity, switching time and magnetic forces. A manually operated prototype was simulated and constructed to validate the numerical approach and to verify the generated magnetic field. RESULTS: A concentric small permanent magnet array can be used to generate strong sample pre-polarisation and variable measurement fields for ultra-low field relaxometry via simple prescribed magnet rotations. Using the array, it is possible to achieve a pre-polarisation field strength above 100 mT and variable measurement fields ranging from 20-50 µT with 200 ppm absolute field homogeneity within a field-of-view of 5 x 5 x 5 cubic centimetres. CONCLUSIONS: A dynamic small permanent magnet array can generate multiple highly homogeneous magnetic fields required in ultra-low field nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) instruments. This design can significantly reduce the volume and energy requirements of traditional systems based on electromagnets, improving portability considerably.