Second year PhD student, Olivier Jaubert, is conducting his PhD under the supervision of Dr. Claudia Prieto (King's College London) and Dr. Daniel Rueckert (Imperial College London). The main focus of his research is on tailoring the new Magnetic Resonance Fingerprinting method to cardiac applications. This project is part of a collaboration between KCL, Imperial and Philips Healthcare.
What is the SmartHeart project and how did you come to be involved in it?
The current approach to cardiovascular MR imaging (cMRI) is essentially serial: image acquisition is followed by image analysis and clinical interpretation. In addition, cardiac/respiratory motion is currently resulting in long scanning times for cMRI, with only a small fraction of the data (10-20%) being used for image reconstruction. This leads to breath-holds that are difficult to tolerate by sick patients.
Furthermore, the characterization of clinically relevant tissue parameters requires the acquisition of multiple images which is inefficient. The absolute quantification of tissue parameters also remains a major technical challenge, leading to difficulties in interpreting tissue contrast parameters across scanners, clinical centres and patient populations. Finally, the objective interpretation of comprehensive, multi-parametric cMRI in the context of other complex non-imaging data is highly challenging for clinicians.
We propose a transformative approach in which acquisition, analysis and interpretation are tightly coupled, with feedback between the different stages in order to optimize the overall objective: Extracting clinically useful information. Developing such an integrated approach to cardiac imaging will enable rapid, continuous and comprehensive imaging that is both simpler and more efficient than current practice, eliminating “dead time” between separate specialized acquisitions and allowing extraction of multiple dynamic as well as tissue contrast parameters simultaneously.
I came to be involved in this project as my research aims at fast quantitative imaging which could extract more comprehensive, robust, reproducible and clinically relevant information in one efficient scan.
Why is the partnership with Imperial College London and Phillips important and who focuses on what?
Each partner has it's own expertise. Philips support is essential for Image acquisition and obtaining the best quality raw data. Imperial provides machine learning expertise which can be used for Image reconstruction and analysis.
What for you is the most exciting thing about working on this?
I was quite amazed by the variety and complexity of MR acquisition and image reconstruction. I was also impressed by the usefulness of MR for the medical teams They are powerful tool for diagnosis and can be determinant in curing patients.
What do you see as the biggest challenge?
The biggest challenges in my project is overcoming the problems linked to cardiac acquisitions such as motion and other sources of artifacts while keeping a good quality signal.