Project leader Universitat Pompeu Fabra (UPF)
The objective is to generate in-silico personalised haemodynamic indices of left atrial geometries, complementing their morphological analysis, to identify the risk of thrombus formation in atrial fibrillation patients, improve patient selection for the implantation of LAAO and optimise their settings (e.g. size, positioning).
This study covers in-silico fluid simulations, which are already a prerequisite in stent validation and certification. However, fluid simulations including more complex medical devices such as implantable devices were, until recently, not mature enough to be part of regulatory submissions. For LAAO devices, fluid simulations need common standards, best practices, sensitivity analyses and model calibration to determine the optimal set of boundary conditions to match experimental results.
This work will develop robust computational pipelines to process the large amount of data required for in-silico clinical trials. We will model the entire cycle of care for these patients, including patterns of thrombus formation and drug treatment, for improved patient selection, personalisation of device settings, and prediction of treatment response.
Course of action
- Development of computational pipeline for generating patient-specific meshes and patient-specific boundary conditions for large number of cases.
- Sensitivity analyses and model calibration to determine optimal methodological choices in fluid simulations.
- Verification and validation (V&V) studies to assess the credibility of the developed models.
- Derivation of in-silico haemodynamic indices to assess the risk of thrombus formation and predict the benefit of LAAO implantation.
- Optimisation of LAAO settings to minimise the risk of device-related thrombus in combination with appropriate drug therapy.