A Computational Modeling Approach For Magnetic Resonance Navigation In Targeted Embolization

The proposed project is centered on developing an advanced technique known as Magnetic Resonance Navigation (MRN) for liver cancer treatment. This cutting-edge method employs the magnetic field of MRI machines to create micro-particle aggregates, which are then precisely directed to liver tumor-feeding arteries using magnetic field gradients. This approach promises to be less invasive and more accurate than existing treatments. A critical aspect of this project involves a thorough study of particle aggregation to ensure the safe delivery of treatment without harming healthy tissues. The aim is to refine and perfect the MRN process by modeling the various forces that influence these aggregates under blood flow conditions.

This initiative is a collaborative venture between CR-CHUM in Canada and Inria in France, bringing together their respective strengths in medical research and computational modeling. The expected benefit of this collaboration is twofold: firstly, to establish a new benchmark in liver cancer treatment that could significantly enhance patient outcomes; and secondly, to exemplify the power of international collaboration in fostering medical technological advancements. In addition to advancing liver cancer treatment, this project will significantly bolster the research capabilities of both institutions.

Faculty Supervisor:

Gilles Soulez

Student:

Partner:

Institut Polytechnique de Paris

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Other

University:

Université de Montréal

Program: