Three use-cases:
USE CASE 1 aims to quantify mechanical and electrical properties of cardiac stimulation devices using computer modelling and simulations. In particular, the UC1 focuses on bradycardia leads and aims at designing a numerical workflow that can be later extended to other implantable devices. To date, two distinct computational pipelines have been built by our teams: one aims to address several critical questions on the electrical pacing and sensing performances of the lead, while the other investigates the navigation possibilities of the lead, as well as long-term mechanical fatigue.
USE CASE 2 aims to generate in-silico personalised hemodynamic indices of left atrial geometries, complementing their morphological analysis. Furthermore, this case aims: to identify the risk of thrombus formation in atrial fibrillation patients; to improve patient selection for the implantation of left atrial appendage occluders (LAAO); and, to optimise their settings. To date, a computational modelling pipeline has already been designed and is able at-present to generate patient-specific meshes and patient-specific boundary conditions in a large number of cases. In addition, extensive sensitivity analyses and model calibrations are also being currently tested in order to determine the optimal methodological choices for simulations pertaining computational fluid dynamics prior to, during and after LAAO implantation. Detailed verification and validation (V&V) investigations enabled us to assess the credibility of these developed models, current research is on distinct aspects relevant to the clinical translation in silico LAAO studies to realistically predict the risk of stroke in relation to the device implantation.
USE CASE 3 aims to assess efficacy and safety of drugs in populations of electrophysiological and electromechanical models. A specific pipeline has been defined for this purpose, with the ultimate goal of integrating it in a cloud-based platform to implement in silico trials of efficacy and safety. To date, several stages in the pipeline are considered, starting with the construction of pharmacokinetic models for selected drugs. These models can provide the user with the precise drugs concentration that is needed to be considered in the pipeline. An important and realistic aspect of our population of models is that gender, age and pathology is properly considered. Moreover, the credibility of the models used through the pipeline was assessed by following a detailed verification and validation process, including sensitivity analyses and uncertainty quantification. Importantly, a crucial step in the assessment of efficacy and safety of drugs is the definition of biomarkers derived from our simulations, which will help in building accurate classifications tools and next generation models.
Several key results were achieved so far. In particular, we would like to highlight:
- the complete Verification and Validation process that has been performed for all the three use-cases, establishing the credibility of the in silico approach in answering the different questions of interest
- the implementation of three different in silico trials on the cloud-based platform in order to evaluate the performance on the different models
