AI Analyzes Heart MRI for Faster Diagnosis

Researchers have introduced a groundbreaking AI-driven method for analyzing heart MRI scans, promising significant time and resource savings for the NHS, alongside enhanced patient care (1^✔ ✔Trusted Source
Development and validation of AI-derived segmentation of four-chamber cine cardiac magnetic resonance

Go to source). Collaborative efforts from the Universities of East Anglia (UEA), Sheffield, and Leeds led to the development of an intelligent computer model. This model leverages artificial intelligence to scrutinize heart images from MRI scans, specifically focusing on the four-chamber plane view.

NHS Time and Resource Savings with AI Heart MRI Analysis

The project is spearheaded by Dr. Pankaj Garg from the University of East Anglia’s Norwich Medical School, who also serves as a consultant cardiologist at the Norfolk and Norwich University Hospital. Dr. Garg and his team have been at the forefront of developing cutting-edge 4D MRI imaging technology. Their innovative work promises quicker, non-invasive, and highly accurate diagnoses for heart failure and various other cardiac conditions.

Dr Garg said: “The AI model precisely determined the size and function of the heart's chambers and demonstrated outcomes comparable to those acquired by doctors manually but much quicker.

“Unlike a standard manual MRI analysis, which can take up to 45 minutes or more, the new AI model takes just a few seconds.

“This automated technique could offer speedy and dependable evaluations of heart health, with the potential to enhance patient care.”

The retrospective observational study consisted of 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.

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To make sure the model’s results were accurate, scans and data from another 101 patients from the Norfolk and Norwich University Hospitals NHS Foundation Trust were then used for testing.

AI-Driven Method for Heart MRI Analysis

While other studies have investigated the use of AI in interpreting MRI scans, this latest AI model was trained using data from multiple hospitals and different types of scanners, as well as conducting the testing on a diverse group of patients from a different hospital. In addition, this AI model provides a complete analysis of the entire heart using a view that shows all four chambers, while most earlier studies focused on a view that only looks at the heart's two main chambers.

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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 efficient diagnoses, better treatment decisions, and ultimately, improved outcomes for patients with heart conditions.”

“Moreover, the potential of AI to predict mortality based on heart measurements highlights its potential to revolutionise cardiac care and improve patient prognosis.”

The researchers say future studies should test the model using larger groups of patients from different hospitals, with various types of MRI scanners, and including other common diseases seen in medical practice to see if it works well in a broader range of real-world situations.

Reference:

1. Development and validation of AI-derived segmentation of four-chamber cine cardiac magnetic resonance - (https://eurradiolexp.springeropen.com/articles/10.1186/s41747-024-00477-7)

Source-Eurekalert