Anatomic reconstruction in personalised medicine: the more information the better?
Personalized medicine is increasingly relying on numerical simulations to aid clinicians in the diagnosis and/or treatment of several diseases. In particular, the possible benefits of computer simulations in the functional assessment of patient-specific hemodynamics are now widely acknowledged. Numerical models could, in fact, drastically reduce costs and the number of invasive procedures for the diagnosis of cardiovascular disease, which is one of the leading causes of mortality worldwide.
In our group, we are developing a complete framework for the simulation of patient specific hemodynamics to help patients with vascular diseases.
On the way to that goal, we need to identify what level of accuracy we need to reconstruct the vessel geometry from patient-specific computed tomography (CT) scans in relation to the output of the simulation (pressure drop, wall shear stress, identification of fluid structures).
The student undertaking the project will help us investigate the geometric level of detail required in the anatomic reconstruction to correctly diagnose patients with coronary artery disease. In a first step, the student will reconstruct the artery-tree anatomy of patients with stenosis of coronary arteries from CT scans. During this phase he or she will benefit from the interpretation of CT scans by expert clinicians closely collaborating with the project. The goal of this stage is to characterize and classify the anatomic features of the reconstructed geometries.
Thereafter, using our in-house numerical framework for the parametrized description of the Navier-Stokes equations, s/he will investigate the impact of the identified geometrical features in the hemodinamics of lesioned coronary arteries. Particularly, the main focus will bethe sensitivity of the pressure drop to the selected geometric features.
In this project, the student:
- will benefit from the collaboration with an interdisciplinary group with competences reaching from aerospace engineering to augmented reality to medicine and biology
- work with real anatomic data and state-of-the-art numerical models
- contribute to an existing framework for patient specific medicine
- basic understanding of computational fluid dynamics (preferably OpenFOAM)
- basic knowledge of programming languages such as Python and C++
- good knowledge of English
- strong motivation and willingness to integrate knew knowledge from our multidisciplinary environment and
- willingness to make a difference!
Type: Master Thesis
Prerequisites: basic knowledge of programming languages (e.g. Python and C++), basic understanding of computational fluid dynamics
For further information or to apply, please contact
Dr. Stefano Buoso
+41 44 635 50 53
Prof. Vartan Kurtcuoglu
+41 44 635 50 55