Alzheimer’s Disease affects millions worldwide, but we still lack early detection and effective therapies. ECE assistant professor Pengfei Song is developing a super-resolution ultrasound imaging technique to evaluate brains affected by Alzheimer’s Disease and other neurodegenerative diseases. Song has received a $1.2 million Chan Zuckerberg Initiative Ben Barres Early Career Acceleration Award to fund this research.
Alzheimer’s Disease affects millions worldwide, but we still lack early detection and effective therapies. Although researchers have made strides in understanding and treating the disease, many scientific and clinical unknowns remain.
Pengfei Song, assistant professor of electrical and computer engineering at The Grainger College of Engineering, is developing a super-resolution ultrasound imaging technique to evaluate brains affected by Alzheimer’s Disease and other neurodegenerative diseases. Song has received a $1.2 million Chan Zuckerberg Initiative Ben Barres Early Career Acceleration Award to fund this research.
Song’s team focuses on the impact of neurodegenerative diseases on small blood vessels inside the brain – the microvasculature system. Patients with Alzheimer’s Disease have missing and damaged blood vessels, but scientists still do not know enough about what causes these changes. Super-resolution ultrasound may be able to provide the answers. Ultrasounds can go deeper than optical imaging, with better resolution than MRI scans, providing a unique opportunity to study the tiny vessels of the deep brain in detail.
Super-resolution ultrasound imaging has two important components. The first is microbubbles, which are gas spheres in a protein or lipid shell that are used to increase the clarity of ultrasound images. These bubbles are roughly the size of red blood cells, about two to five microns in diameter (for comparison, a human hair is about 70 microns in diameter). The tiny bubbles travel through the bloodstream. The second component is ultra-fast imaging: Song’s team uses an ultrafast imaging scanner with a frame rate of 1000s of hertz to track these bubbles, analyzing the blood flow through the brain.
Alzheimer’s Disease is one example, but this method can be applied to many conditions that can benefit from blood flow markers, including other neurodegenerative diseases and disorders.
“At the core, we are engineers who want to develop new and useful methods,” Song said. “We’re mainly focusing on the neurodegenerative diseases in this award for now, because you can’t just make hammers, you have to find a nail.”
This is the second cycle of the Ben Barres Early Career Acceleration Award, which supports early career academic investigators in their research, especially those who are new to the field of neurodegeneration. The CZI Neurodegeneration Challenge Network launched in 2018, aiming to bring people from diverse disciplines together to combat neurogenerative diseases. As well as $1.2 million in funding over four years, the award also provides mentorship opportunities and workshops with other awardees.
Song’s background in medical imaging physics and instrumentation is different from the neuroscience and biology specialisms of traditional neurodegenerative disease researchers. He realized he had a significant contribution to make:
“The common goal is tackling neurodegenerative diseases from very different perspectives. I’m a tool developer, so I think I can be helpful. I’m also genuinely interested in learning their needs because they are my users. I hope that after this award, we will have established this technology, and have the tools we built disseminated to the neuroscience community.”
Pengfei Song is also a member of the Beckman Institute for Advanced Science and Technology, the Department of Bioengineering, Neuroscience Program, Cancer Center at Illinois and Carle Illinois College of Medicine.