Researchers Aim to Develop PET Technology for Precise Multitracer Brain Imaging

UC Santa Cruz Associate Professor of Electrical and Computer Engineering Shiva Abbaszadeh is developing technology that will enable precise multitracer positron emission tomography imaging of the human body’s most complex organ.  

Positron emission tomography, or PET, uses radiotracers to allow researchers and clinicians to take images of organs and tissues inside the body. Abbaszadeh, an expert in PET imaging, is collaborating with researchers and clinicians at multiple institutions to create a new modality for the technology that will enable the detection of multiple biomarkers at once and improve the spatial resolution of brain imaging. 

The research team will develop their technology with the support of a $4 million grant from the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies

(BRAIN) Initiative. The five-year project will consist of two years in simulation and proof-of-principle phase, followed by three years of exploratory and developmental phase to build the tomographic system.

The project is led by Professor of Medical Imaging at the University of Arizona Lars Furenlid, and other collaborators include Professor of Radiology at UMass Chan Medical School Michael King, Professor of Medicine at the University of Arizona Phillip Kuo, and Professor of Optical Sciences at the University of Arizona Matthew Kupinski.

“The start of this technology was the first grant of my career, and now seeing that we are using the idea I had in my mind and implementing it for something bigger is very important,” Abbaszadeh said.

The technology, in line with the directive of the BRAIN Initiative, is not disease-specific, and instead is a general demonstration of technology that could be used for anything from cancer to neurodegenerative disease.  

PET imaging has been long seen as highly useful for the study of the brain. However, it has not been possible to do imaging of multiple biomarkers at the same time because the positron signals are emitted at the same frequency and cannot be distinguished from each other. 

However, Abbaszadeh’s technology aims to introduce a method for tracing multiple biomarkers at once by taking advantage of prompt gamma signals in addition to the positron signals. Prompt gamma signals are a second type of signal that can be detected through sophisticated PET imaging, making it possible to trace multiple biomarkers with one PET scan. Developing the scanners with a very wide dynamic range of detection enables the technology to measure both low to high energy tracers. 

Multitracer imaging is useful for clinicians who want to observe multiple health indicators at once, such as the metabolic activity of a region and how well the region filters chemicals across the brain blood barrier. Mutlitracer imaging was not in high demand in the field just a few years ago, but now it has become increasingly relevant with more clarity on the clinical benefit of this imaging and the emergence of theranostics, which combines cancer diagnosis and treatment with radiotracers.

Despite the surge of interest in multitracer imaging for theranostics, at this point groups must use two separate scanners to do so, a cost and space hurdle that could be overcome by Abbaszadeh’s technology. 

Using prompt gamma signals also helps to overcome spatial resolution limitations in PET imaging. This is particularly relevant for the BRAIN initiative as higher spatial resolution imaging is especially important for studying very small features of the brain.

PET imaging with positron signals is inherently limited by the nature of the physics involved, in that positrons can only travel for a limited distance, and the tracer does not capture the exact point of the positron in the body. Prompt gamma signals, on the other hand, do not have this spatial resolution issue, meaning imaging can be much more accurate.

“These tools haven’t been available before,” Abbaszadeh said. “We are leveraging the physics and the engineering of those tracers to come up with a new modality.”

The technology is direct conversion technology, which also improves spatial resolution image quality. Direct conversion detects high energy particles directly, whereas indirect conversion transforms high energy to visible light and then detect, which causes light to be isotropically scattered and thus lower resolution. 

Once Abbaszadeh’s technology has been able to detect both the positron and the prompt-gamma signals, those signals must be reconstructed into a usable image. Using a joint reconstruction technique will greatly enhance the utility of the imaging. To do this, Abbaszadeh and her group will collaborate with researchers at the University of Arizona, world leaders in joint reconstruction.  

Veins and the flow of blood through the body introduce an element of motion into the imaging, further complicating the process. Michael King at the UMass Chan Medical School is an expert in motion and will also collaborate on this project, correcting for motion in the imaging. “I am very excited because three very good teams are coming together for this grant,” Abbaszadeh said. “Something really good is going to come out of it because we have all of the expertise that will lead to the success of this project.”  

A fourth collaborator, Phillip Kuo, is professor of medicine, cancer biology, and biomedical engineering at the University of Arizona and a clinician who can help champion the technology among physicians to demonstrate its impact and advocate for adoption in the clinical world. 

In general, Abbaszadeh sees this technology as a platform which can be adapted to the needs of different stakeholders, in this case doctors and clinicians within varying medical fields. In the future she hopes to expand the technology to a myriad of fields that could benefit from improved tomographic imaging. Abbaszadeh has seen the manufacturing costs of PET and semiconductor technology drop over the past ten years, and hopes to see this trend continue with innovation in the field. 

This project is funded under the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative, which was established in 2013 to accelerate the development of innovative neurotechnologies.