My primary research interests are to improve patient-specific medical diagnosis and treatment planning, by using engineering skills like advanced mathematical modeling, image analysis, data analysis and quantitative measurement techniques. Specifically, my research focuses on the application of patient-specific mathematical models in clinical practice to support clinical decision-making by adequately predicting the hemodynamics after vascular treatment (e.g. surgery or PTA). My research strategy focuses on the complete chain of model development, model personalization and model corroboration. During model development, advanced mathematical models are developed and experimentally validated in close collaboration with the Cardiovascular Biomechanics group of Prof. Dr.Ir. Frans van de Vosse of the Eindhoven University of Technology (The Netherlands). After model development, sensitivity analysis techniques are applied to the model to identify the model parameters which need to be assessed patient-specifically and which model parameters can be based on generic values from literature. By using these insights, a measurement protocol can be defined to assess the model parameters for model personalization. Finally, the model is corroborated by comparing the clinical outcome predicted by the model with clinical data. During this model corroboration step also the uncertainty in the model predictions resulting from measurements uncertainties is considered by applying uncertainty analysis techniques to the model. Current applications of this strategy are vascular access surgery, peripheral and coronary arterial disease, and small vessel disease.
My expertise is to:
1. Develop advanced mathematical models of (part of) the cardiovascular system that describe the (patho)physiology and hemodynamics of interest.
2. Develop and apply tools for sensitivity analysis of (advanced) mathematical models to determine the important model parameters that need to be assessed patient-specifically and to determine the model parameters that can be based on literature during model personalization.
3. Improve available measurements modalities and/or improve and develop measurement protocols for model personalization and corroboration.
4. Develop and apply tools to estimate the uncertainty in model predictions.
5. Perform clinical corroboration of the mathematical models.
-AVF surgery planning - Neurovascular modeling (a.o. cerebral aneurysm, cerebral autoregulation) - AVG (needle) hemodynamics - Venous (valve) hemodynamics after head-up-tilt - Claudication intermittens - Aortic dissection