Doctoral position at the Center for Biomedical and Healthcare Engineering,
Mines Saint-Etienne – SAINBIOSE (INSERM-U1059) – University of Lyon (France)

Funded by the Predisurge company ( under CIFRE agreement

Fast Numerical Simulations of Endovascular Procedures using Model Order Reduction

Keywords: biomechanics, finite-elements, explicit/implicit resolution, aortic aneurysm, endovascular repair, hyperelasticity, mesh morphing, open source solver, GPU computing
Clinical context: An Aortic Aneurysm (AA) is a pathological dilatation of the aorta that can burst and be lethal when the dilatation is too large, causing internal bleeding. 5% to 10% of western men over 65 will face this pathology in their lifetime (French National Authority for Health, 2012).
To treat an AA that is about to break, endovascular aneurysm repair (EVAR) is much less invasive and traumatic for the patient than open surgery. It consists in implanting a stent graft (SG) to exclude the AA from blood pressure and prevent its rupture. EVAR offers a treatment opportunity for weak patients who cannot withstand traditional surgery and allows reducing recovery period, hospitalization period as well as mortality. It is thus more and more commonplace: among the 200,000 AA procedures every year, more than 50% are EVAR (Thompson, Medtech Inside, 2013) and the number keeps increasing. However, EVAR currently faces 2 major challenges:
1. Design of customised SGs and planning of complex EVAR: Inappropriate positioning of the fenestrations and branches on the landing zone of the aorta will induce severe complications for the patient. The consequence is that planning procedures are very complex, expensive and time-consuming, resulting in delivery times of several months.
2. Placement of complex SGs during EVAR procedures: EVAR requires hybrid operating rooms that combine traditional operating room and a sophisticated radiography system. Unanticipated complications during complex EVAR can significantly lengthen procedures and hospitalization time, with important mortality rates. Moreover, the extensive use of X-rays is harmful both for the health of patients and medical staff.
Academic context: The PhD student will work in a team leading major international research projects in the domain of soft tissue biomechanics, focused especially on aortic aneurysms. He will collaborate with other researchers involved in two ERC projects ( and and in the start-up Predisurge offering innovative software solutions for patient-specific numerical simulation of surgical procedures.
Industrial context: Predisurge is a spin-off company of IMT Mines Saint-Etienne and University of Saint-Etienne. PrediSurge sells innovative software solutions for patient-specific numerical simulation of surgical procedures to address the challenges of endovascular surgery, enabling the automatic design of fully-customized fenestrated stent-grafts. Preliminary evaluations reveal huge benefits for patients requiring fenestrated EVAR every year: faster procedures, increased precision, near-zero risk of complications. Our vision for 2025 is that all EVAR procedures will have to be numerically simulated for ensuring the highest degree of safety.
Project summary: Our aim is to build a comprehensive and optimized framework of simulation and imaging technologies, clinically validated, to accelerate the process of our personalized numerical simulations. The goal of the project will be to reduce the order of complexity in finite-element models of stent-grafts and of aortas using an in-house computational platform combining image processing tools and a dedicated finite-element solver. The numerical processes will be automated through scripts and open source solvers will be considered. Specific attention will be paid to maximize the resolution speed considering GPU computing. After implementation, we will apply the model to simulate numerically the benefit of performing a surgical endovascular procedure. The simulations will be validated on a large database of aortic geometries obtained through different international clinical trials.
Candidate profile: Candidates with strong backgrounds in computational mechanics, and/or applied mathematics are expected. Motivation for ground-breaking computational work and interest in biomedical applications are recommended.

How to apply: Send CV, cover letter and references by email to