ESMRMB course on Diffusion weighted MRS

Diffusion weighted MRS

October 10-12, 2018
Paris/FR

Course Venue
ICM - Institut du Cerveau et de la Moelle épinière
Hôpital Pitié-Salpêtrière
Paris/FR

Course Organisers
Francesca Branzoli
Center for neuroimaging research (CENIR) – ICM
Paris/FR

Itamar Ronen
C.J. Gorter Center for High Field MRI
Leiden University Medical Center
Leiden/NL

Julien Valette
Molecular Imaging Research Center
Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
Fontenay-aux-Roses/FR  

Goals of the Course
This course is designed to provide a strong practical foundation in the principles of diffusion weighted magnetic resonance spectroscopy (DW-MRS) in all of its aspects. DW-MRS provides unique cell-specific microstructural information based on the diffusion properties of intracellular metabolites in neural and muscle tissue, and it thus complements most sensitive but less specific methods such as diffusion tensor imaging (DTI). In clinical and preclinical research, incorporation of DW-MRS in a comprehensive protocol aimed at microstructural characterisation of tissue allows disentangling the effect of multiple pathological processes on tissue microstructure, and thus significantly increases the explanatory power of MR for the overall pathology.

At present, however, incorporation of DW-MRS in standard protocols poses significant challenges: robust DW-MRS sequences are not offered on any of the commercially available MR scanners. DW-MRS data acquisition is highly susceptible to physiological fluctuations, and the DW-MRS signal is strongly affected by e.g. eddy currents generated by the strong diffusion weighting gradients and cardiac pulsation. As a result, the robustness and reproducibility of DW-MRS strongly depends on a highly specialized pipeline of acquisition and processing that takes into account as many possible adverse effects as possible.

Educational Level
Attendees of the course are expected to have a good background in MR physics and be familiar with basic concepts in diffusion MR and in vivo MRS. A basic knowledge of MATLAB is preferred, and an acquaintance with principles of signal processing is advantageous.