Personalized models with individual hemodynamics can be created by including pressure cuff measurements and informative imaging data such as four-dimensional magnetic resonance imaging (4D Flow MRI) data into the model. Through comparing and using the personalized models, new insights of the hemodynamic mechanisms behind hypertension can be found. Furthermore, an updated cardiovascular model could together with automated data processing provide a new clinical tool for individualized diagnostics and treatment planning in hypertension.
I use mathematical models to understand diseases such as cardiovascular diseases and obesity. My main research focus is modeling of the cardiovascular system to understand the underlying mechanisms of high blood pressure.