First patients put through new-generation MRI scanner

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A ground-breaking 'Fast Field Cycling' MRI scanner that has been described as “100 MRIs in one” has been used on patients for the first time in Aberdeen.

The patients had all suffered strokes and agreed to be the first in the world to be scanned by the new machine.

Magnetic resonance imaging (MRI) uses strong magnetic fields and radio waves to produce detailed images of inside a patient’s body.

A team of researchers at the University of Aberdeen have been working on the technology for the last decade.

Fast Field Cycling scanners are able to extract much more information than traditional MRIs by switching the strength of the magnetic field during the scanning procedure.  

The research group leader, Professor David Lurie, said: “because Fast Field Cycling scanners can switch their magnetic field, it is almost like having 100 different MRI scanners in one.

“This gives an extra dimension to the data collected from each patient, greatly expanding the diagnostic potential.

“It is incredibly exciting to have imaged our first patients. This is a major step towards our technology being adopted by hospitals to benefit patients, which is the ultimate goal of our research.”

The prototype has been used to image the brains of patients who have recently suffered from a stroke, who are taking part in the so-called Puffins trial.

Researchers hope that additional information from the scanner will help doctors see the stroke-affected part of the brain more precisely, which could help with treatment and recovery plans.

The University of Aberdeen has a long history working on MRI technology. In the 1970s a research team from the university built the first full body-MRI scanner and used it to obtain the first clinically useful image of a patient.

These devices are now used in hospitals across the globe.

Dr Mary Joan MacLeod, lead for the trial, added: “Treatments for stroke have to be given very early to be effective, and the CT scans patients currently undergo on admission to hospital give us limited information to help plan that treatment.

“The Fast Field Cycling scanner has great potential, because it might give more accurate ‘real time’ information on what is happening in the brain tissue, helping to direct treatment.”

In April MRI images were used to predict a person’s ‘brain age’ with the help of machine learning. It is hoped the method can be used to help determine patients who might be at increased risk of poor health or early death. 

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