Approved Research

An Adaptive Artificial Intelligence Approach to Improve Efficiency and Quality in Cardiac MRI

Lay summary

Aim:

This project aims to reduce the numbers of visits that patients and doctors need to spend waiting for and taking images of the heart. It aims to this by developing AI-based tools for use during the scanning of patients in order to ensure that all necessary data is acquired in order to make more confident diagnoses about potential heart problems within a shorter timeframe.

Scientific rationale:

The recent use of AI in healthcare has been dominated by demonstrations of performance in analysing highly curated imaging data which has, to date, only rarely been translated into clinically deployable technology. This project considers the comparatively large burden on healthcare systems (both financially and in terms of human capital) and individual patients (in terms of anxiety and inconvenience) of obtaining the images optimally.

Project duration:

24 months

Public health impact:

The expected value us a reduction in scan times to allow more patients to benefit from cardiac magnetic resonance imaging, improved confidence in diagnosis (to improve care) and improved patient experience (by avoiding prolonged or unnecessary scans). Over the next decade, it is intended that it will be utilised alongside real-world practice and have a tangible effect on healthcare productivity and patient care.