These 2019 EN
Mapping the electrical properties of the brain with MRI
Dr Paulo LOUREIRO de SOUSA (Lab. ICube, Université de Strasbourg)
Dr Stéphanie SALMON (Laboratoire de Mathématiques de Reims, Université de Reims)
Co-supervisor: Dr Julien LAMY (Lab. ICube, Université de Strasbourg)
Scientist or engineer, with a strong background in physics (electromagnetism). The candidate should also have good scientific programming skills.
1,400€/month approximately, via a Doctoral Research Contract. This is a three-year contract offered by the University of Strasbourg; it is awarded after a selection organized by the Doctoral School “Mathématiques, Sciences de l'Information et de l'Ingénieur (MSII)”.
- ICube : Laboratoire des sciences de l’Ingénieur, de l’Informatique et de l’Imagerie, UMR 7357 Université de Strasbourg / CNRS
- Laboratoire de Mathématiques de l’université de Reims-Champagne-Ardenne
Several studies have shown that some diseases cause local changes in the electrical properties (EP) of biological tissues: increased values of electrical conductivity have been reported in brain tumors; significant changes in EP values have also been reported in brain tissue in relation to stroke; local ischemia and the swelling of cells which occur due to a focal seizure during epilepsy can also alter the electrical properties. In vivo EP mapping would therefore provide relevant information regarding the health status of the tissue. To date, no method can accurately and rapidly estimate, in a non-invasive manner, the distribution of EP of the brain in humans.
Nuclear Magnetic Resonance Imaging (MRI) is a versatile medical imaging modality which can collect a great deal of information on the bio-physical properties of tissues. Because of its underlying electromagnetic principles, MRI is a logical approach to non-invasively map tissue EP in vivo and in humans.
The objective of this thesis proposal is to evaluate the feasibility of mapping the electrical properties of the human brain, in vivo, by MRI. This project also aims to better understand the relationship between tissue, cell changes and EP, measured at different frequencies. One of the original aspects of this project is the close collaboration between acquisition, image processing, and numerical simulations of the direct and inverse problems of electromagnetic propagation phenomena. To reduce scan time and increase image quality, fast acquisition methods will be explored. New strategies will be used to improve the stability and robustness of reconstructions of electrical parameter maps, such as the integration of a priori knowledge. A mathematical sensitivity analysis can be conducted to better understand the influence of the EP on the acquired measurements and thus make it possible to quantify the errors.
This doctoral thesis will be carried out in the Laboratory of Engineering Sciences, Computer Science and Imaging (ICube) in collaboration with the Mathematical Laboratory of the University of Reims-Champagne-Ardenne.
The ICube laboratory has extensive experience in the development of MRI methodology, for clinical research applications, mainly in neurology, but also for interventional imaging applications. With three MRI scanners dedicated to research in humans (1.5T and 3T SIEMENS) and in small animals (7T Bruker), the MRI methodology research at ICube laboratory focuses mainly on the issues related to the acquisition of data and reconstructions of property maps of biological tissues.
The Reims Mathematical Laboratory (LMR) brings together experts in mathematics: analysis, algebra and applied mathematics. The members of the LMR applied mathematics team have long been involved in medicine-oriented projects (ANR VIVABRAIN and MAIA) and work on numerical simulations of electromagnetism phenomena and on inverse problems.
To apply, please send CV, cover letter, and grades and rank of Master’s degree to email@example.com .
The application deadline is May 13, 2019.
Voigt, T., Katscher, U., & Doessel, O. (2011). Quantitative conductivity and permittivity imaging of the human brain using electric properties tomography. Magnetic Resonance in Medicine, 66(2), 456-466.
Katscher, U., Kim, D. H., & Seo, J. K. (2013). Recent progress and future challenges in MR electric properties tomography. Computational and mathematical methods in medicine, 2013.
Zhang, X., Liu, J., & He, B. (2014). Magnetic-resonance-based electrical properties tomography: a review. IEEE reviews in biomedical engineering, 7, 87-96.
Katscher, U., & van den Berg, C. A. (2017). Electric properties tomography: Biochemical, physical and technical background, evaluation and clinical applications. NMR in Biomedicine, 30(8), e3729