MRI imaging

The overall objective of our research program is to improve our understanding of the changes in the brain associated with amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease.

The lab works in close collaboration with scientists in the departments of biomedical engineering and computing science to develop and apply advanced brain imaging techniques to study different characteristics of brain involvement in ALS, including changes in structure, chemistry, and function. These methods show immense promise in providing a biomarker, namely a test that can be used to detect disease earlier, monitor disease progression, and evaluate new therapies. Such a tool would accelerate drug testing and lead to the realization of effective treatment faster.

MR Spectroscopy MR Spectroscopy MR Spectroscopy Diffusion Tensor Imaging

Magnetic Resonance Imaging

A routine clinical MRI of the brain of a person with ALS typically does not reveal abnormalities. However, advanced techniquees can quantify different features of brain degeneration:

High Field Magnetic Resonance Spectrocopy

Measures different chemicals in the brain reflecting neuronal health and neurotransmitter metabolism.

Diffusion Tensor Imaging

Assesses the integrity of white matter tracts (the wiring) of the brain.

Functional Magnetic Resonance Imaging (fMRI)

Demostrates the activity of the cortex (the "computer"). It can show what parts of the brain become activate with specific motor or cognitive tasks.

Magnetic Resonance Volumetry

Used to measure the volumes of different structures in the brain (for example, grey matter, white matter, lobes, and cortical thickness).

Tissue Map

Our MR imaging is performed in the Peter S. Allen MR Research Centre. The Centre houses three research-dedicated MRI scanners with different magnetic field strengths (1.5 T, 3.0 T, and 4.7 T).

White matter tracts (brain wiring) visualized using Diffusion Tensor Tractography

Training Opportunities

The lab is seeking postdoctoral fellows and students wishing to pursue graduate level degrees in Neuroscience, Computing Science, and Biomedical Engineering. Please click here for more information.


We are grateful for the support provided by our funding partners: