Researchers have developed a ground-breaking method for analyzing heart MRIs with the help of artificial intelligence, which could save the NHS valuable time and resources, as well as improve patient care.
The teams from the Universities of East Anglia (UEA), Sheffield and Leeds created an intelligent computer model that uses artificial intelligence to examine heart images from MRI scans in a specific view known as the four-chamber plane.
The lead researcher Dr. Pankaj Garg, from the University of East Anglia’s Norwich School of Medicine and consultant cardiologist at the Norfolk and Norwich University Hospital, is leading a team of researchers who have pioneered the innovative and revolutionary 4D MRI imaging technology. This paves the way for faster, non-invasive and more accurate diagnosis of heart failure and other heart diseases.
The AI ​​model accurately determined the size and function of the heart’s chambers and showed results comparable to those obtained by doctors by hand, but much faster.
Unlike a typical manual MRI analysis, which can take up to 45 minutes or more, the new AI model only takes a few seconds.
This automated technique could provide rapid and reliable assessments of heart health, with the potential to enhance patient care.”
Dr Pankaj Garg, Norwich University of East Anglia School of Medicine
The retrospective observational study included data from 814 patients from Sheffield Teaching Hospitals NHS Foundation Trust and Leeds Teaching Hospitals NHS Trust, which was then used to train the AI ​​model.
To make sure the model’s results were accurate, scans and data from a further 101 patients from the Norfolk and Norwich University Hospitals NHS Foundation Trust were used.
While other studies have explored the use of AI in MRI interpretation, this latest AI model was trained using data from multiple hospitals and different types of scanners, as well as testing a different group of patients from a different hospital. Additionally, this AI model provides a complete analysis of the entire heart using a view that shows all four chambers, whereas most previous studies focused on a view that only looks at the two main chambers of the heart.
PhD student Dr Hosamadin Assadi, of UEA’s Norwich Medical School, said: “Automating the process of assessing heart function and structure will save time and resources and ensure consistent results for doctors.
“This innovation could lead to more effective diagnoses, better treatment decisions and ultimately improved outcomes for patients with heart disease.
“Additionally, AI’s ability to predict mortality based on heart measurements highlights its potential to revolutionize cardiac care and improve patient prognosis.”
The researchers say future studies should test the model using larger groups of patients from different hospitals, with different types of MRI scanners and other common diseases seen in medical practice to see if it works well in a wider range of real-world situations.
Other recent research from the UEA, Leeds and Sheffield teams improved the method of using cardiac MRI for female patients, particularly those with early or borderline heart disease, which meant 16.5% more women could be diagnosed.
The research was a collaboration between the University of East Anglia, University of Leeds, University of Sheffield, Leiden University Medical Centre, Norfolk and Norwich University Hospitals NHS Foundation Trust, Sheffield Teaching Hospitals NHS Foundation Trust and Leeds Teaching Hospitals NHS Trust.
The study was supported by Dr Pankaj Garg funding from a Wellcome Trust Clinical Research Career Development Fellowship.
“Development and validation of AI-derived CMR four-chamber cine segmentation” is published in EEuropean Experimental Radiology.
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