Surgical interventions often require vascular procedures consisting in cutting vessels, removing organ parts or suturing new connections. Intervention planning is based on patient data and surgeons experience. Even the best plans are often revised in real-time during surgery. Can we understand and predict blood flow changes due to a surgery? Complex interactions must be foreseen between three scales: the local point of intervention, whole organ perfusion and function, and the entire circulation. Such complexity calls for modelling and simulation, which should become part of the surgical decision process.
Yet, the modelling community does not sufficiently respond to these challenges. Despite great advances in blood flow simulation, clinical translation remains largely unfulfilled, as existing tools are too heavy, pathological interactions complex and multidisciplinary collaboration uneasy. Organ interactions and remodelling due to surgery or diseases are missing from comprehensive models. Besides, simulations must be based on patient data, ideally non-invasive ones. Despite great advances in dynamic imaging, the link between signal and underlying tissue perfusion and function remains to be elucidated, beyond current pharmacokinetics models. Their better understanding will bring new data for personalised simulation.
Our ambition is to gear hemodynamics modelling towards diseased organs to guide associated surgical acts, focusing on lung and liver. We will investigate a novel approach of an injected substance model transported through the cardiovascular system; i.e. enhancing pharmacokinetics modelling by transport phenomena based on hemodynamics. Numerical simulations of such models will unravel the interplay between architecture, perfusion and function in diseased organs, and provide peri- & peroperative guiding information. This project will impact bioengineering, pathophysiology, dynamic imaging, and surgery through the final aim of software clinical translation.
Call for proposal
See other projects for this call