News | Neuro Imaging | March 22, 2019

NIH Study of Brain Energy Patterns Provides New Insights into Alcohol Effects

Researchers use PET and MRI to show alcohol significantly affects brain glucose metabolism and regional brain activity

NIH Study of Brain Energy Patterns Provides New Insights into Alcohol Effects

NIH scientists present a new method for combining measures of brain activity (left) and glucose consumption (right) to study regional specialization and to better understand the effects of alcohol on the human brain. Image courtesy of Ehsan Shokri-Kojori, Ph.D., of NIAAA.

March 22, 2019 — Assessing the patterns of energy use and neuronal activity simultaneously in the human brain improves our understanding of how alcohol affects the brain, according to new research by scientists at the National Institutes of Health. The new approach for characterizing brain energetic patterns could also be useful for studying other neuropsychiatric diseases. A report of the findings is now online in Nature Communications.1

“The brain uses a lot of energy compared to other body organs, and the association between brain activity and energy utilization is an important marker of brain health,” said George F. Koob, Ph.D., director of the National Institute on Alcohol Abuse and Alcoholism (NIAAA), part of NIH, which funded the study. “This study introduces a new way of characterizing how brain activity is related to its consumption of glucose, which could be very useful in understanding how the brain uses energy in health and disease.”

The research was led by Ehsan Shokri-Kojori, Ph.D., and Nora D. Volkow, M.D., of the NIAAA Laboratory of Neuroimaging. Volkow is also the director of the National Institute on Drug Abuse at NIH. In previous studies, they and their colleagues have shown that alcohol significantly affects brain glucose metabolism, a measure of energy use, as well as regional brain activity, which is assessed through changes in blood oxygenation.

“The findings from this study highlight the relevance of energetics for ensuring normal brain function and reveal how it is disrupted by excessive alcohol consumption,” said Volkow.

In their new study, the researchers combined human brain imaging techniques, including FDG-positron emission tomography (PET) and magnetic resonance imaging (MRI), for measuring glucose metabolism and neuronal activity to derive new measures, which they termed power and cost.

“We measured power by observing to what extent brain regions are active and use energy,” explained Shokri-Kojori. “We measured cost of brain regions by observing to what extent their energy use exceeds their underlying activity.”

In a group of healthy volunteers, the researchers showed that different brain regions that serve distinct functions have notably different power and different cost. They then investigated the effects of alcohol on these new measures by assessing a group of people that included light drinkers and heavy drinkers and found that both acute and chronic exposure to alcohol affected power and cost of brain regions.

“In heavy drinkers, we saw less regional power for example in the thalamus, the sensory gateway, and frontal cortex of the brain, which is important for decision making,” said Shokri-Kojori. “These decreases in power were interpreted to reflect toxic effects of long-term exposure to alcohol on the brain cells.”

The researchers also found a decrease in power during acute alcohol exposure in the visual regions, which was related to disruption of visual processing. At the same time, visual regions had the most significant decreases in cost of activity during alcohol intoxication, which is consistent with the reliance of these regions on alternative energy sources such as acetate, a byproduct of alcohol metabolism.

They conclude that despite widespread decreases in glucose metabolism in heavy drinkers compared to light drinkers, heavy drinking shifts the brain toward less efficient energetic states. Future studies are needed to investigate the mechanisms contributing to this relative inefficiency.

“Studying energetic signatures of brain regions in different neuropsychiatric diseases is an important future direction, as the measures of power and cost may provide new multimodal biomarkers for such disorders,” said Shokri-Kojori.

For more information: www.nature.com/ncomms

Reference

1. Shokri-Kojori E., Tomasi D., Alipanahi B., et al. Correspondence between cerebral glucose metabolism and BOLD reveals relative power and cost in human brain. Nature Communications, Feb. 11, 2019. https://doi.org/10.1038/s41467-019-08546-x

Related Content

#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 A brief article from Henry Ford Health System in Detroit, published today in Radiology, reports on the first presumptive case of COVID-19–associated acute necrotizing hemorrhagic encephalopathy.

A, Image from noncontrast head CT demonstrates symmetric hypoattenuation within the bilateral medial thalami (arrows). B, Axial CT venogram demonstrates patency of the cerebral venous vasculature, including the internal cerebral veins (arrows). C, Coronal reformat of aCT angiogram demonstrates normal appearance of the basilar artery and proximal posterior cerebral arteries. Image courtesy of the Radiological Society of North America (RSNA)

News | Coronavirus (COVID-19) | March 31, 2020
March 31, 2020 — A brief article fr
A University of Colorado Cancer Center study published in the Journal of the National Cancer Institute shows an important predictor of PET-CT use

Rustain Morgan, M.D., and colleagues show racial/ethnic disparities in use of important imaging during lung cancer diagnosis. Photo courtesy of University of Colorado Cancer Center

News | PET-CT | March 12, 2020
March 12, 2020 — The use of PET-CT
 “Cyclotrons used in Nuclear Medicine Report & Directory, Edition 2020” that describes close to 1,500 medical cyclotrons worldwide
News | Nuclear Imaging | March 10, 2020
March 10, 2020 — MEDraysintell released its new and unique report “...
SoftVue image stacks of sound speed, as shown for cases ranging across the four Breast Imaging Reporting and Data System (BI-RADS) breast density categories

Example: SoftVue image stacks of sound speed, as shown for cases ranging across the four Breast Imaging Reporting and Data System (BI-RADS) breast density categories ((a), fatty; (b), scattered; (c), heterogeneously dense; (d), extremely dense). Note the quantitative scale indicating that absolute measurements are obtained. Image courtesy of MDPI

News | Breast Imaging | March 10, 2020
March 10, 2020 — ...
Schematic depiction of the automated process for assessing fat, muscle, liver, aortic calcification, and bone from original abdominal CT scan data

Figure 1: Depiction of the fully automated CT biomarkers tools used in this study. (A) Schematic depiction of the automated process for assessing fat, muscle, liver, aortic calcification, and bone from original abdominal CT scan data. (B) Case example in an asymptomatic 52-year-old man undergoing CT for colorectal cancer screening. At the time of CT screening, he had a body-mass index of 27·3 and Framingham risk score of 5% (low risk). However, several CT-based metabolic markers were indicative of underlying disease. Multivariate Cox model prediction based on these three CT-based results put the risk of cardiovascular event at 19% within 2 years, at 40% within 5 years, and at 67% within 10 years, and the risk of death at 4% within 2 years, 11% within 5 years, and 27% within 10 years. At longitudinal clinical follow-up, the patient suffered an acute myocardial infarction 3 years after this initial CT and died 12 years after CT at the age of 64 years. (C) Contrast-enhanced CT performed 7 months before death for minor trauma was interpreted as negative but does show significant progression of vascular calcification, visceral fat, and hepatic steatosis. HU=Hounsfield units.

News | Computed Tomography (CT) | March 06, 2020
March 6, 2020 — Researchers at the National Institutes of Health a
M. Minhaj Siddiqui, M.D., associate professor of surgery at the University of Maryland School of Medicine, discusses benefits of MRI-targeted biopsy to more precisely diagnose aggressive prostate cancers

M. Minhaj Siddiqui, M.D., associate professor of surgery at the University of Maryland School of Medicine, discusses benefits of MRI-targeted biopsy to more precisely diagnose aggressive prostate cancers. (c) University of Maryland Greenebaum Comprehensive Cancer Center

News | Prostate Cancer | March 05, 2020
March 5, 2020 — Using a combination of...
MR Solutions’ dry magnet MRI system for molecular imaging on display at EMIM 2020
News | Magnetic Resonance Imaging (MRI) | February 28, 2020
February 28, 2020 — MR Solutions will be displaying its la