A Framework for Multi-dimensional Adaptive Cardiac MRI using online motion estimators

Impaired cardiac function often results in heart failure which represents a major burden of morbidity and mortality. Cardiac magnetic resonance imaging (MRI) is considered to be the reference method for assessment of cardiac function. However, the relatively long scan times makes MRI sensitive to motion.

Most current cardiac MRI techniques require multiple breath holds, which many patients with heart failure are unable to perform., resulting in non-diagnostic image quality.

The aim of this project is to develop a novel framework for adaptive image acquisition, where the pulse sequence is controlled by online motion estimators.

This will enable acquisition that is robust to respiratory motion and arrhythmia, as well as fetal motion during examination of fetal hearts. The methods will be evaluated both in healthy volunteers, heart failure patients, and in pregnant women.

The pulse sequence and corresponding image reconstruction will be implemented directly on the clinical scanner platform, making it immediately available for clinical use.

The research will take place immersed in a clinical environment at the Karolinska University Hospital, with full access to dedicated cardiac MRI scanners and relevant patient populations.

The proposed approach is highly original, fills an important unmet clinical need in medicine, and involves novel approaches that push the technical limits of image acquisition and reconstruction beyond state-of-the-art.