Charting ‘road maps’ of the body: The many worlds of Jim Duncan
Jim Duncan straddles a lot of different spaces, both figuratively and literally.
He has offices both on Science Hill as well as at the Yale School of Medicine. He has a background in electrical engineering, but his research focuses on the biomedical sciences. He is an expert at interpreting images of everything from individual cells to the entire human brain. And his research, which takes place in the lab, extends into real-world operating rooms and beyond.
Even his Yale titles — the Ebenezer K. Hunt Professor of Biomedical Engineering, professor of diagnostic radiology and professor of electrical engineering — make Duncan’s diverse interests apparent. But the complex ways in which he brings all of them together is more subtle.
Duncan applies engineering principles and mathematical models to analyze biomedical images on the organ scale down to the sub-cellular level; this information is produced by a range of technology that includes everything from MRI to ultrasound to x-ray. On any given day, he might be working on ways to help surgeons map the brain in real-time during surgery, or figuring out how the heart deforms during a heart attack, or how fast vesicles in a cell move and change when a cell has been wounded.
YaleNews recently spoke with Duncan to learn more about his research and the many worlds in which he operates.
With an electrical engineering background, how did you get interested in this field?
That’s a good question! I worked for 10 years before this in the aerospace industry. Originally I was working on circuit design for infrared imaging — things that would go in satellites and aircraft — and I went from there to getting interested in “How do you process that information?” A lot of it was defense funded or commercially funded.
While I was doing that I was always interested in, “How could you do this to benefit different sectors?” And biomedical research always seemed like a direct application. Some of the ideas being used to find helicopters and enemy aircraft could be used to target tumors and disease. I got interested in that problem and found there were some parallels. But there were some interesting differences, and I had to learn about different things.
That’s really what got me to Yale. I stayed in the same basic career but kind of switched direction, and Yale was an opportunity where I could be involved with an engineering department that was top-notch but still small and very integrated across campus. There was also a strong medical school.
How has the field of imaging changed over the years?
When I first started working on it, it was sort of two-dimensional, static images of cells and simple structures for the most part. The real evolution is that now we can talk about three-dimensional variation over time of full organ imaging, or cells across different sources, and can even think about pulling that information together to do multi-spectral analysis.
For example, I have a big project with the chair of neurosurgery here, Dr. Dennis Spencer, that’s aimed at integrating information using functional magnetic resonance imaging (fMRI) on structure and blood flow in the brain, and positron emission tomography that shows variation in the brain. We’re putting it all together to create road maps for the surgeon to help navigate in order to remove sensitive parts of the brain — for instance, to stop seizures in epilepsy, but not cut out parts of the brain that are going to impair vision or things like that.
So this ability to amass and assess data at higher fidelity and put it all together has really evolved over the past 25 years or so.
You must have learned a lot about the medical field that you didn’t expect to learn when you started out as an electrical engineer.
Absolutely. And in the last 10 years or so we formed the biomedical engineering department. That was an interesting experience. I think, in many cases, scientists and engineers end up more or less differentiating early on into physics or math or biology or chemistry. Biomedical engineering tries to put those back together. I learned a lot of the biology and medicine completely by osmosis, then went back and tried to relearn it. But it’s fun to learn new things.
What is one of the interesting things you’re working on right now?
One thing I’m working on now is in the area of imaging the brain to try to understand autism. We’ve had a grant for that for 10 or 11 years, and we’ve mostly looked at the structure of the brain and how it might change in kids with autism spectrum disorders.
What we’ve just been working on with some collaborators at the Yale Child Study Center is something where we give kids images of biological and non-biological things to look at to see what parts of their brains light up. We’ve been quite pleased that we’ve been able to bring together ideas that integrate fMRI with structural imaging of white matter in the brain to come up with a methodology that differentiates these biological and non-biological responses and could help identify kids in the autism spectrum.
The simple idea is that kids in control groups light up when looking at faces, for example, but not when looking at a house. For kids with autism, there’s no difference between the two. So that’s been neat work, using new ideas that seem to be working out.