USC researchers at the Keck School of Medicine recently developed a new way to examine how blood flow and cellular organization align across layers of a human brain.

The finding may help scientists understand how blood vessels, cells and energy-producing mechanisms work together to support brain function. 

This research allows for more understanding of the biological mechanism behind the blood supply and its relation to several cellular architectures.

The cerebral cortex, which is the brain’s outermost layer, contains layers with cells that need a continuous supply of oxygen and nutrients, which they get from blood. To track and measure blood flow throughout the brain, the researchers used arterial spin labeling, a noninvasive MRI technique that magnetically identifies water in the blood and tracks it into brain tissue.

The research showed that areas with a better alignment between blood flow and cellular architecture are correlated with better mitochondrial respiratory capacity. Mitochondria generate energy with oxygen, which makes them less useful in environments where oxygen is limited. So, in regions of the brain where there is a good supply of oxygen, the mitochondria can be efficient, while other areas may have to find alternative metabolic pathways.

The study introduced the cerebral blood flow-cell-body staining intensity similarity index, which measures how closely blood flow and cellular density follow the same pattern across cortex layers. Higher scores indicate that layers dense in cells tended to receive more blood flow. 

“Usually, the lower functioning region[s], like a visual motor, match very well because this area — their circuits, their function, cell architecture — are well defined,” said Danny Wang, director of imaging technology innovation for the lab and a professor of neurology and biomedical engineering. “But in the association cortex, because the brain is needed to reorganize to meet the kind of environmental challenges, they are more dynamic.”

The researchers used a new, cutting-edge high-resolution technology to measure the cerebral blood flow. Chenyang Zhao, co-first author of the study, said this study wasn’t previously possible because the necessary high-resolution image technology was not available. 

“The cortex is very thin; [if] you want to see it in different layers, you really, really need high-resolution imaging,” Zhao said. “But the MRI for the high-resolution imaging, it is really constrained by the [signal-to-noise ratio] and the acquisition time.” 

Data from BigBrain atlas, a dataset created by dividing a human brain into small sections, was used to correlate the blood supply with the cellular structure. The researchers segmented the cortical gray matter into 12 equi-volume layers. 

“The cortical actually has some of its thickness on the brain surface, and we can detect the different layers, the perfusion of the blood flow and the cell density, so we can know which region the perfusion matches the cell,” said Fanhua Guo, co-first author of the paper. “So if it doesn’t match, maybe, for example, the oxygen or something else can’t be delivered to the cell.” 

This high-resolution technology allowed them to see not only how much blood was delivered to a volume of brain tissue, but to see, in detail, how blood flow is delivered across different depths of the cortex. 

The hope is that this research can lead to learning more about aging and neurodegenerative diseases, such as Alzheimer’s, Wang said. 

“It’s very likely these diseases alter the coupling,” Wang said. “Maybe the flow goes down first, maybe the cell dies. So there’s also a dynamic kind of change.”

The study included 30 healthy adult participants, 14 of whom returned for a second scan to test the consistency of the results. However, the cell density data was not derived from the participants but from an atlas of the brain.

In the future, the plan is to develop this research in vivo, which is a research approach that studies a living organism, as opposed to the BigBrain specimen. 

“If we can develop this in vivo, then it will be very nice to track aging, neurodegenerative disease and other disorders,” Wang said.