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 and how we still know so little about it extremely fascinating. MRI provides a window to learn more about the brain’s mysteries, and can help to diagnose, monitor, and treat disorders that affect it.
I am interested in developing new MRI tools and applying them to better understand and diagnose neurological disease. To achieve this goal, we are developing imaging biomarkers for MRI that provide specific insight into microscopic tissue properties. An important tool in our arsenal is diffusion MRI, which measures the random motion of water molecules. The motion of the molecules is altered by cell membranes, and because of this, diffusion MRI can give insight into specific microstructure characteristics of the tissue like cell size, shape, and density. Accordingly, this technique allows non-invasive virtual microscopy of tissue inside the brain, which can help us to learn more about the brain and diseases that affect it.
How can we measure specific tissue properties with diffusion MRI, and how can we do it efficiently?
The traditional form of diffusion MRI gives only a single parameter – the “apparent diffusion coefficient” – that is not specific to any particular cellular property. However, diffusion MRI is governed by a rich set of physics that can be exploited to improve our specificity to things like cell shape and cell size. We are developing brand new methods to enable these types of measurements in clinically relevant scan times.
Can we learn more about disease via microscopic tissue properties measured with MRI?
Traditional methods to measure cellular tissue properties are destructive – one must extract a tissue specimen and put it under a microscope. By using MRI to measure these cellular properties without affecting the tissue whatsoever, we can examine them in a completely new way. For example, we can repeatedly scan the same subject to see how tissue abnormalities change as a disease progresses, or we can see how treatments affect them. We are performing these types of longitudinal studies in animal models (for example, in concussion), which also allows verification of the accuracy our virtual microscopy measurements using traditional microscopy. These results can be translated to studies with patients, where we can directly contrast animal and human results and interpretations of results by using identical MRI approaches between the two types of subjects.
Can advanced diffusion MRI detect better detect changes in the brain in neurological disorders?
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.
Education and Training
- Sc. Engineering Physics, University of Alberta, 2007
- Sc. Electrical Engineering, University of Alberta, 2009
- D. Biomedical Engineering, University of Alberta, 2014
- Postdoctoral Fellow, Stanford University, 2014-2017
- Tier 2 Canada Research Chair of Diffusion MRI, 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