Project Details
Description
In congenital heart disease, it is crucial to decide the timing of surgical interventions, and cardiovascular flow imaging has strong potential to provide the required information for surgical decision-making. However, current imaging is not sufficient for this task. Therefore, we aim to:
1. Develop a novel simulation-based imaging framework for flow magnetic resonance imaging, providing high quality images with ultra-high resolution and fast scan times.
2. Apply the framework to long-standing problems in congenital heart disease: a) to use power loss in Fontan patients as a predictor for long-term surgery outcome and b) to provide quantitative predictors of re-coarctation in children with aortic coarctation.
1. Develop a novel simulation-based imaging framework for flow magnetic resonance imaging, providing high quality images with ultra-high resolution and fast scan times.
2. Apply the framework to long-standing problems in congenital heart disease: a) to use power loss in Fontan patients as a predictor for long-term surgery outcome and b) to provide quantitative predictors of re-coarctation in children with aortic coarctation.
Short title | eSSENCE@LU 6:6 |
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Status | Finished |
Effective start/end date | 2020/01/01 → 2021/12/31 |
Funding
- Swedish Research Council
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):