With a magnetic field strength of 7 Tesla, more than four times that of MRI scanners used in most hospitals, the Keck School’s 7T Terra has a strong signal-to-noise ratio, allowing researchers and clinicians to collect images of the living human brain with higher spatial resolution and better contrast than was previously possible.

In a typical 1.5 Tesla scanner, each cubic unit of the image — each “voxel” — contains about 100,000 brain cells. At 7 Tesla, a voxel depicts just a few thousand cells, allowing scientists to study the brain with more precision and detail.

“It’s really a dramatic improvement,” said Danny JJ Wang, PhD, director of imaging technology innovation at the INI and professor of neurology and radiology at the Keck School. “Ideally, we want to look at the smallest group of neurons possible so we can start to pinpoint what’s happening at the cellular level.”

The 7T Terra is ideal for high-resolution structural and functional neuroimaging, exploration of neurodegenerative diseases such as Alzheimer’s and Parkinson’s, and diagnosis and treatment of other diseases that affect the brain, including multiple sclerosis, stroke and vascular dementia.

In 2017, Toga and Gabriel Zada, MD, of the Keck School, used the 7T Terra to perform the first ultra-high-resolution scan of a Cushing’s disease patient in the United States.

They were able to localize an extremely small pituitary tumor not visible on 1.5T or 3T MRI scanners, suggesting that the new technology could replace the standard invasive diagnostic methods for Cushing’s disease. Their findings were published in March 2018 in the Journal of Neurosurgery.

“The 7T may save patients an invasive procedure. It also makes it easier for neurosurgeons to selectively remove a tumor without damaging surrounding areas,” said Zada, associate professor of neurological surgery (clinical scholar) at the Keck School.

Reconfiguring the 7T Terra for clinical use involved minor hardware and software updates to comply with FDA standards. For more information about the scanner, visit cia.ini.usc.edu.

— Zara Greenbaum