Dr. Antonio P. Strafella holds a Canada Research Chair in Movement Disorders and Neuroimaging and is a Professor in the department of Medicine/Neurology at University Health Network and University of Toronto. He is also a Senior Scientist at the Krembil Research Institute and a Senior Scientist at the Research Imaging Centre at the Centre for Addiction and Mental Health. His current research uses a number of Positron Emission Tomography (PET) tracers and novel radio-ligands along with MRI techniques to investigate the pathophysiology of motor, cognitive (e.g. executive dysfunction) and behavioral symptoms (e.g. impulse control disorders, visual hallucinations, anxiety) in Parkinson’s disease. (Source: Weston)
Click here for an introduction to neuroimaging…
The following has been paraphrased from an interview with Dr. Antonio P. Strafella on June 4th, 2018.
(Click above to listen to the full audio version or click here for a downloadable version)
How far have we come in the last 20 years in terms of our ability to image the human brain?
In the last 20 years, there have been exponential developments in the field of neuroimaging. The field includes mainly MRI and molecular imaging, and most of the changes have occurred in the latter with advances in positron emission tomography (PET imaging). Now, we are able to image many different chemicals in the brain. Before it was just dopamine, now we can also image serotonin, acetylcholine, and much more that we didn’t know were playing a role in diseases like Parkinson’s.
Over the course of your career, what were the biggest breakthrough moments in brain imaging?
In the past, most imaging was done using a technique called SPECT, which was fairly crude. Now using PET scans, we can really dissect the living brain. I like to compare it to micro-dialysis done in living animals, which is a technique where you put a probe into the brain of an animal and measure different chemicals. PET allows us to do something similar in a living human brain with very sophisticated spatial resolution.
What are the biggest barriers to better imaging?
The more sophisticated technology is, the more expensive it becomes. Not many centers are able to afford this type of technology, here in Canada we only have three. It also requires a significant amount of expertise and the right infrastructure in place. This limits the scale at which we are able to implement the developments that come from these enhanced techniques.
Just how much can we know about degeneration in a living person’s brain?
In the last 10 years, there has been a huge shift in the way we think about PD. Initially we only thought it involved abnormalities in the basal ganglia, and then we saw it spread to other parts of the brain as well. But now, using these techniques, we have learned that there are other parts of the body that are also affected, including the heart, intestines, and other organs.
What is the most promising new development in neuroimaging?
Within the next five years we should have a tracer for alpha-synuclein (the protein thought to be responsible for PD. It has been difficult to develop an accurate tracer because it is difficult to find a marker that can reliably bind to the protein and get through the blood brain barrier. Once we get one, it will be a big breakthrough in the field.
There are also promising tracers being developed that bind to activated microglia (brain cells responsible for neuroinflammation). There is huge interest in finding a reliable marker of neuroinflammation because it is closely tied with neurodegeneration.
Where do you think brain imaging will be in 20 years?
I think in 20 years we will do whole body imaging for people with Parkinson’s disease as we are learning more about the protein deposits outside of the brain. Once, we have a biomarker for alpha-synuclein we will probably start to do whole body scans.
What do combined PET/fMRI machines tell us?
These techniques are already available and they allow us to co-register the anatomy of the brain with its function. Once we are able to further refine these techniques it will give us a better sense of how complex the brain is. By generating very large data sets, we will need very sophisticated computational analysis to get a better idea of the different aspects of the disease. In the next five years, there will be an explosion of data collected from these techniques in Parkinson’s disease that will give us new insights and a better understanding of the disease.