Magnetic resonance imaging (MRI) is one of the most important medical tests in modern medicine, enabling accurate diagnoses without the need for more invasive procedures. However, it is expensive and requires complex infrastructure, which limits the number of devices available in hospitals, making the test less accessible to many.
Technology that could transform diagnoses
A partnership between the University of Sheffield and GE HealthCare is launching a new MRI model. The low-field model aims to reduce costs, expand access, and revolutionize the way patients receive diagnoses.
What differentiates the new MRI machine from the older, more traditional model is that it uses a lower magnetic field. While this may seem like a disadvantage at first — since high-field scans offer more detailed images — researchers point out that by combining artificial intelligence and the new model, they will be able to reconstruct high-quality images from less complex data.
This technology represents a major advancement, especially relevant for people with respiratory diseases, such as asthma, pulmonary fibrosis, and chronic obstructive pulmonary disease (COPD), as these conditions generate significant costs for the healthcare system and are among the leading causes of death in some places, such as the United Kingdom. It is hoped that this new technology will be able to detect early signs of diseases like these, allowing doctors to begin treatment before the condition worsens.
Impact on patients
The biggest advantage of this new model for people is access. Currently, patients end up waiting months in line for MRI scans. With the low-field model, the test can be performed easily at local health facilities, reducing the wait for the exam and providing the technology at a closer distance. When implemented, this technology will restore quality of life for thousands of people.
Lower cost and greater sustainability
Another key factor in implementing this new technology is maintenance costs. Traditional MRIs rely on superconducting magnets, requiring a large amount of liquid helium to operate, an expensive and scarce resource. With this new model, less helium, or even none at all, is required, making the device more sustainable and financially viable for smaller hospitals and neighborhood clinics.
These savings extend beyond maintenance costs to the cost of the exam for patients. By facilitating early diagnoses, the healthcare system can save on the high cost of treating advanced diseases, prolonged hospital stays, and more expensive procedures. This upgrade to this equipment is an investment that generates significant returns across a variety of areas.
For now, the project is being initially tested in the United Kingdom, but it is expected to have a global impact. Low- and middle-income countries currently face difficulties in acquiring and maintaining high-field MRIs in their hospital facilities. With the arrival of this technology, regions that currently have virtually no access to testing will be able to offer more modern and efficient diagnoses and treatments to their populations.
Artificial intelligence and innovation in healthcare
The presence of artificial intelligence in this new MRI model is one of the key points of this technological revolution. By using databases of thousands of exams already performed on high-field equipment, the algorithms present in this device can “learn” to reconstruct and improve the quality of images obtained on simpler machines. The use of AI, inserted in this healthcare context, expands the reach of medical care technology.
This new model of MRI device, which operates in low-field, represents a scientific breakthrough and the achievement of greater health equity. With reduced costs, increased accessibility, and artificial intelligence incorporated to aid medical diagnosis, the project has great potential to save lives and transform healthcare systems around the world.