Researchers said they have uncovered a novel sign of chronic stress and its damaging effects on the body by using an artificial intelligence algorithm to analyze common CT scans for what they describe as a “biological barometer.”
In a study presented at the annual meeting of the Radiological Society of North America, being held in Chicago this week, researchers from Johns Hopkins University and the University of California, Los Angeles (UCLA) were able to link a person’s quantifiable measure of chronic stress to medical issues years later, including cardiovascular complications such as high blood pressure and heart failure.
Compared to cortisol levels—which can change throughout the day and only offer a snapshot of the body’s response to stimuli—the researchers found that capturing the volume of the adrenal gland provided a clearer and more practical picture of the burden of stress over time.
They applied a deep learning model to automatically identify, segment and measure adrenal glands across a record of past chest CT exams—scans the researchers say are performed tens of millions of times in the U.S. each year.
“Our approach leverages widely available imaging data and opens the door to large-scale evaluations of the biological impact of chronic stress across a range of conditions using existing chest CT scans,” said the study’s lead author, Elena Ghotbi, a postdoctoral research fellow at Johns Hopkins. “This AI-driven biomarker has the potential to enhance cardiovascular risk stratification and guide preventive care without additional testing or radiation.”
After obtaining a person’s adrenal volume index, or AVI, the researchers were then able to track patients for years and connect their scan results with stress questionnaires and symptoms of depression, as well as their cortisol levels collected through saliva tests.
By using retrospective data from a clinical study of atherosclerosis that included more than 2,800 scanned participants, they were also able to calculate measures of allostatic load—or a reading of chronic stress impacts and inflammation that accounts for a person’s body mass index; creatinine, hemoglobin, albumin and glucose levels; white blood cell count; and their heart rate and blood pressure.
“For the first time, we can ‘see’ the long-term burden of stress inside the body, using a scan that patients already get every day in hospitals across the country,” said senior author Shadpour Demehri, M.D., a professor of radiology at Johns Hopkins. “Until now, we haven’t had a way to measure and quantify the cumulative effects of chronic stress, other than questionnaires, surrogate serum markers like chronic inflammation, and cortisol measurement, which is very cumbersome to obtain.”
A higher AVI was linked to higher cortisol and allostatic load, as well as perceived stress levels—while each 1 cm³/m² increase in AVI was tied to a greater risk of heart failure and mortality.
“With up to 10-year follow-up data on our participants, we were able to correlate AI-derived AVI with clinically meaningful and relevant outcomes,” Ghotbi said in a statement. “This is the very first imaging marker of chronic stress that has been validated and shown to have an independent impact on a cardiovascular outcome, namely, heart failure.”
The researchers said the imaging biomarker could also potentially be used in a variety of diseases tied to chronic stress, including in middle-aged and older adults.
“For over three decades, we’ve known that chronic stress can wear down the body across multiple systems,” said co-author Teresa Seeman, Ph.D., professor of epidemiology at UCLA. “What makes this work so exciting is that it links a routinely obtained imaging feature, adrenal volume, with validated biological and psychological measures of stress and shows that it independently predicts a major clinical outcome. It’s a true step forward in operationalizing the cumulative impact of stress on health.”