Assistant Professor, Department of Medical Biophysics
Canada Research Chair of Diffusion Magnetic Resonance Imaging
Why I Became a Scientist
I have always been interested in figuring out how things work, building things, and solving difficult puzzles. I became interested in magnetic resonance imaging (MRI) because it scratches that engineering ‘itch’ while having a direct impact on patients. On top of this, I find the brain extremely fascinating. MRI provides a window to learn more about this mysterious organ, as well as help to diagnose, monitor and treat disorders that affect it.
I am interested in developing multidimensional imaging biomarkers for ultra-high field MRI, and using them to learn more about the brain. Measuring a multidimensional imaging biomarker is another way of saying to measure multiple tissue parameters at the same time, which can greatly improve the ability to diagnose a condition. In MRI, there are many different types of tissue parameters that can be measured. I am especially interested in diffusion MRI, which measures the average random motion of molecules. The motion of the molecules is altered by cell membranes and organelles, and diffusion MRI can give insight into specific microstructure characteristics of the tissue like cell size, shape, and density. In essence, this allows a completely non-invasive virtual microscopy of tissue inside the brain.
How can we efficiently measure multidimensional imaging biomarkers?
While the measurement of a whole plethora of tissue parameters seems like a great idea in principle, it is limited in practice by how long a patient can stay in your scanner. In order to make this practical in the clinic, we need to find ways to measure the information much more efficiently. One part of the solution is to work at ultra-high field, where there is more signal strength that can be used to accelerate the scans. Also, every single parameter map acquired in a session looks like a brain – the same brain, in fact. Accordingly, there is a lot of redundancy in the data that we can potentially exploit to reduce the amount of raw data we need to acquire to get the same information.
Can we use diffusion-based virtual microscopy of the brain to gain a better understanding of changes that occur during development or disease?
MRI is typically used to assess structures with length scales of millimeters or centimeters. Advanced forms of diffusion MRI give us an ability to assess microscopic characteristics of brain tissue, down to cellular length scales, which gives us an opportunity to learn more about disorders at a very fundamental level.
Can multidimensional imaging biomarkers detect neurodegenerative disorders, like Alzheimer’s disease or Parkinson’s disease, before symptoms occur?
Neurodegenerative disorders are associated with volume decreases in certain structures in the brain, but by the time this occurs symptoms like dementia are already present. However, it is likely that the brain is already subtly changing before symptoms begin. Multidimensional biomarkers may give more sensitivity to detect small changes in the brain sooner, which could allow earlier treatment before irreversible damage occurs.
B.Sc. Engineering Physics, University of Alberta, 2007
M.Sc. Electrical Engineering, University of Alberta, 2009
Ph.D. Biomedical Engineering, University of Alberta, 2014
Stanford University, 2014-2017
Canada Research Chair of Diffusion Magnetic Resonance Imaging (Tier 2), 2018
Petro-Canada Young Innovator Program - Robarts Award, 2018
NSERC Postdoctoral Fellowship, 2014-2016
Vanier Canada Graduate Scholarship, 2009-2011
Alberta Innovates - Health Solutions Studentship Award, 2012-2014
NSERC Julie Payette Award, 2007-2008
Rt Honourable CD Howe Memorial Fellowship, 2007
Governor General's Silver Medal, 2007