For Beckman Institute faculty member Brad Sutton, a “shadow” experience during high school foreshadowed his future life as a research scientist. After spending two weeks in a clinical setting seeing firsthand how imaging technology and procedures work, Sutton said he knew what career path he wanted to follow.

“What really convinced me to do imaging and bioengineering was an opportunity I had during high school to shadow a radiologist,” Sutton said. “During that process I got to see a lot of what clinical and interventional medicine is, and really saw the need for being able to image and measure things without actually going in and taking a sample.”

Responding to that need is both a challenge for Sutton’s inner engineer and rewarding to him personally if his efforts someday lead to improved non-invasive diagnostic methods for people.

“That’s what got me interested in imaging: to try to develop things that will allow you to take measurements that will indicate whether disease is there or not, without going in and taking a sample,” he said. “And I really like being able to measure something that you would think couldn’t be measured with MRI non-invasively and at the spatial scale of MRI. That really gives me a great deal of satisfaction. I do like coming up with ways to measure these biomarkers that are changing things and will impact healthcare in the future.

“I also like solving problems. I still like to tinker and take things apart. That’s probably what I like most about the position: you’re trying to make these very fine, detailed, quantitative measurements and often your first try is not successful.”

Sutton is an Assistant Professor in the Department of Bioengineering at Illinois, member of Beckman’s Bioimaging Science and Technology group, and director of his own lab, the Magnetic Resonance Functional Imaging Laboratory (MRFIL). His research interests and projects are many, but the overall theme, according to his website is “developing novel methods to image structure and physiological function with magnetic resonance imaging. Application areas include functional neuroimaging and dynamic imaging of muscle function in speech.”

Practically, that means developing acquisition and image reconstruction strategies to advance MRI capabilities for biomedical and research purposes. It is a research mission that puts Sutton and his MRFIL lab in a unique position for a campus research group. He says they are trying to develop a different approach to the way magnetic resonance imaging is performed and used, one that quantifies how each component of a system works in order to create an accurate, comprehensive model of that biological system.

Sutton is a former senior research scientist at Beckman’s Biomedical Imaging Center who has been involved in many research projects that included MRI studies. As a researcher at Beckman and professor of bioengineering, his current list of projects is a long one, and includes complementary goals of advancing imaging techniques and doing basic scientific research: investigating sensitivity bias in functional MRI; using graphics processing units (GPUs) to add greater computing power for MRI; collaborating on research involving age-related demyelination in motor pathways and its effects on fine motor control; and imaging microvascular blood flow with MRI.      

The last project on that list is aimed at understanding the physics of functional blood flow through improved measurements, specifically the development of a new measure for microvascular blood flux, or volumetric flow, of blood through the arterioles, capillaries, and venules.

“It’s different from standard measures, which look to see how much blood is delivered from the arteries,” Sutton said. “We’re actually looking at a very localized level to see how much blood is flowing through that piece of tissue.”

The project involves writing new algorithms and engineering MRI scanners in order to acquire data that accurately reflect the measures.

“This is what is great about MRI ,” Sutton said. “It’s very flexible and there are lots of image contrasts available so I can see how much water is in tissue, I can see movement, and different chemical species in the water. MRI is great, but in order to get all those different contrasts you have to program the MRI scanner and give it exactly the set of instructions to give you an image that will reflect that contrast.”

The project also has potential translational value in projects such as those involving cognitive aging, where functional MRI is used to measure brain function.

“The blood flow project is one of these where somebody said ‘this is what’s happening when people are getting older; we see this change and we’d really like to measure this in vivo in adults without having to inject a contrast agent or something like that,’” Sutton said. “So working with the aging expertise of (Beckman colleagues) Art Kramer and Monica Fabiani we started developing ways to try to measure this change. That’s where FENSI (their blood flux method called ‘flow enhancement of signal intensity’) came from.”  

Sutton said his project investigating age-related demyelination (the destructive removal of the myelin sheath surrounding (neurons) in fine motor control is also informed by his model systems approach to doing imaging research.

“Other projects come from my desire to understand the brain as a system and how information is being transmitted and how that system changes status as a function of age,” he said. “You have the brain that is sending signals and you have the nerve fiber pathways which are communicating that information to the muscles, which are contracting. This project is all about trying to measure properties of those connections and seeing how much of the difference in performance is explained by that variation at the level of the system.

“But all levels of the system are going to affect the performance to some extent, so we’re really interested in modeling the system as a whole with all these different components and seeing if we can measure aspects of those different components to describe the behavior of the system.”   

The project is also tied to his work using high resolution 3-D diffusion tensor imaging of localized neuronal structures that focuses on connection pathways.

“We’ve developed technology that can give us sub-millimeter accuracy, sub-millimeter resolution of these different fiber pathways,” Sutton said. “So you have several fibers involved in several systems, such as tongue and finger systems. We can try to separate those out and make measurements related to each one of those and see how those are describing the overall performance of the system.”

Sutton is working with Beckman colleagues Jacob Sosnoff and Torrey Loucks on the fine motor control studies involving movements of speech and finger force pressure.

“My main goal here is to get this systems model approach applied to monitoring how the system performs,” he said. “I want to get different models of how the different components of the system interplay in order to get the total performance out. We hope that this measure will reflect a lot of the motor performance variation.”

Sutton is also involved in projects seeking to advance MRI techniques and capabilities, including one controlling for sensitivity bias between older and younger subjects in functional MRI, and another one that is aimed at accelerating advanced MRI reconstructions on GPUs. The latter involves development of very fast image reconstruction software to acquire data more efficiently.

“A lot of these reconstructions that we’re doing, for example the speech imaging, we’re acquiring data really fast, but it also suffers from several artifacts that have to be corrected in the reconstruction,” Sutton said. “So, although it may take 45 seconds to acquire images of the tongue while someone is saying something, it currently takes up to a full day, 24 hours, to reconstruct the data. So this graphics processing unit or GPU is going to give us speed-up factors of a hundred or more in terms of reconstructing that data.”

When he was in high school Sutton was able to imagine his future, and it was one that involved working to improve imaging methods for biomedical and other purposes. Today, he can look at where his research is headed and imagine its effects on how magnetic resonance imaging is used in research and biomedicine in the next 10 years.  

“I think we will have a very nice set of MRI sequences to probe different levels of the neural-muscular system,” Sutton said. “We’ll have a very nice reconstruction environment in order to acquire advanced datasets that we can apply these physics correction routines to so we can get high resolution, high information data very quickly and dynamically. I see us as changing the way that functional MRI is done in the future with this systems engineering approach, being able to quantify how each component of a system is performing.”