The rate of tech expansion has always amazed me. MRI is the result of an incredible interaction between so many disciplines. These almost magical machines would never have materialized without such an enormous multi-disciplinary collaboration between chemistry, physics, electrical engineering, computer science, radiofrequency coil design, and cryogenics. Since that point we’ve been able to progress from acquiring single slices to dynamic volumes, capturing thousands of images in minutes.
What do you predict as the next big changes we will see in the sector?
I’ve always found that new breakthroughs are often things you can’t predict – the whole evolution of CT and MRI is indicative of this. We certainly didn’t predict we would be doing live functional MRI when things were starting. It just didn't seem possible.
Our work at Robarts, and here at the BMEIS School, is focused on minimally invasive surgery with dedicated, intelligent instruments, coupled with imaging to help us approach surgical targets more precisely and safely. I think we have tremendous opportunities to use developments in computing, robotics and artificial intelligence, along with imaging, to help us achieve these goals – and it’s absolutely essential that we work together.
A shift in the field is the way we’re using the latest technologies to develop more economic solutions to clinical practice. For example, Robarts has Canada’s only 7T scanner, but it would be impossible to expect to scan every patient who requires an MRI with this facility. However, with the advantage of the higher resolution and sensitivity offered by the 7T, we can identify characteristics of the brain which aren’t currently visible on lower field scanners, and this in turn informs us about how to improve protocols to extract similar information with the more widely available 3T machines.
Another example is the opportunity to use low footprint and affordable ultrasound, (whose quality has improved dramatically over the past couple of decades), combined with augmented reality visualization techniques, to develop low cost solutions for minimally-invasive therapies for widespread deployment in less developed countries.
What will you be focusing on during your sabbatical with the School?
I’m here to learn as much as I can. We’ve already started writing a joint grant between King’s and Western University concerned with using High Field imaging to better diagnose epilepsy by more accurately locating the signals we get from electrodes placed in the brain.
I also want to learn more about what’s going on in Deep Learning and if there’s a way we can use this approach to predict the histology of affected brain areas from MRI in epilepsy patients. At MICCAI, which took place just last week, there’s been a definite shift towards Deep Learning in medical image computing, and I’m particularly interested in how that can help the computer assisted image-guidance community. I’m planning to work closely with Prof Julia Schnabel, Chair in Computational Imaging, and her team to learn more about her work using Deep Learning to analyse MRI scans.
At Robarts, we also work a lot with cardiac interventions. I want to find out what techniques I can take back to Canada to understand heart valve pathologies using MRI imaging to help us design better therapies and treatments.
My lab also has an ongoing collaboration with King’s College Hospital at Denmark Hill on mitral valve repair, where we are creating patient-specific valve models to help understand the impact of new therapies.
On the other hand, I also hope I can bring some expertise from Robarts’ to the table. My colleagues already have 10 years’ experience with 7T MRI, developing new pulse sequences and building customized coils in their radiofrequency labs. This expertise will be of huge benefit when setting up the new 7T facilities at St Thomas’.