In-vivo imaging with a low-cost MRI scanner and cloud data processing in low-resource settings

Area of Science:

• Medical Imaging
• Biophysics
• Engineering

Background:

• Low-field magnetic resonance imaging (MRI) systems offer a potentially cost-effective solution for medical diagnostics in resource-limited settings.
• Operational challenges, including electromagnetic noise and power instability, hinder the widespread adoption of MRI in low-resource environments.
• Developing sustainable MRI technology requires addressing hardware limitations and optimizing software for challenging conditions.

Purpose of the Study:

• To showcase in-vivo imaging capabilities of a low-cost, low-field MRI scanner developed and operated in Africa.
• To illustrate how targeted hardware and software enhancements can overcome operational limitations in low-resource settings.
• To validate the feasibility of advanced MRI techniques on an upgraded, affordable system.

Main Methods:

• A 46 mT Halbach MRI scanner underwent significant upgrades, including improved grounding, shielding, and new control electronics with open-source software.
• Noise performance was rigorously assessed using a standardized protocol.
• Three-dimensional (3D) Rare-sequence brain imaging was performed, with distortion correction implemented via cloud-based reconstructions using magnetic field maps.

Main Results:

• The upgraded MRI system achieved noise levels significantly below the thermal limit, ensuring stable operation.
• High-quality, 3D T1- and T2-weighted brain images were successfully acquired.
• Distortion correction was effectively applied, with near real-time visualization enabled by remote GPU processing.

Conclusions:

• Clinically relevant MRI image quality is achievable with low-cost systems by effectively managing electromagnetic interference and power fluctuations.
• This study confirms the viability of developing sustainable MRI technology in low-resource regions.
• Future clinical translation hinges on ensuring stable power supply and fostering local expertise in MRI operation and maintenance.