Researchers have used a deep learning artificial intelligence model to identify what they describe as the first biomarker of chronic stress that can be directly seen on standard medical images. The findings are being presented next week at the annual meeting of the Radiological Society of North America (RSNA).

Chronic stress does not just affect mood. It can influence both physical and mental health, contributing to problems such as anxiety, trouble sleeping, muscle pain, high blood pressure and a less effective immune system, according to the American Psychological Association. Studies have also linked ongoing stress to major conditions including heart disease, depression and obesity.

AI measures adrenal glands on routine CT scans

The study's lead author, Elena Ghotbi, M.D., a postdoctoral research fellow at Johns Hopkins University School of Medicine in Baltimore, Maryland, created and trained a deep learning tool designed to calculate the size of the adrenal glands using CT scans that had already been performed.

Each year, tens of millions of chest CT scans are performed in the United States alone.

"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," Dr. Ghotbi said. "This AI-driven biomarker has the potential to enhance cardiovascular risk stratification and guide preventive care without additional testing or radiation."

Making the burden of stress visible in the body

Senior author Shadpour Demehri, M.D., professor of radiology at Johns Hopkins, noted that chronic stress is extremely common and is something many adults experience every day.

"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. 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." Dr. Demehri said.

Unlike a single cortisol test, which reflects stress at just one point in time, the size of the adrenal glands functions more like a long-term gauge of chronic stress.

Large multi-ethnic cohort links imaging, hormones and stress load

In this research, the team analyzed information from 2,842 participants (mean age 69.3; 51% women) enrolled in the Multi-Ethnic Study of Atherosclerosis, a large study that combines chest CT imaging, validated stress questionnaires, cortisol measurements and indicators of allostatic load -- the cumulative physiological and psychological effects of chronic stress on the body. Because it integrates imaging, biochemical data and psychosocial assessments in the same individuals, this cohort was uniquely suited, and likely the only one available, for creating an imaging-based marker of chronic stress.

The investigators applied their deep learning model to the CT scans to automatically outline and measure adrenal gland volume. They defined Adrenal Volume Index (AVI) as adrenal volume (cm³) divided by height² (m²). To capture hormonal patterns, participants provided salivary cortisol eight times per day over the course of two days. Allostatic load was calculated using body mass index, creatinine, hemoglobin, albumin, glucose, white blood count, heart rate and blood pressure.

Adrenal Volume Index tracks stress, hormones and heart risk

The team then examined how AVI related to cortisol, allostatic load and a range of psychosocial stress indicators, such as depression scores and perceived stress questionnaires. They discovered that AVI generated by the AI model aligned with established stress questionnaires, with circulating cortisol levels and with future adverse cardiovascular events.

Higher AVI values were linked with greater overall cortisol exposure, higher peak cortisol levels and increased allostatic load. People who reported high levels of perceived stress had higher AVI compared with those who reported low stress. AVI was also connected to a higher left ventricular mass index, a measure related to heart structure. For every 1 cm³/m² increase in AVI, the risk of heart failure and death increased.

"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," Dr. Ghotbi said. "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."

A new way to quantify the cumulative impact of stress

"For over three decades, we've known that chronic stress can wear down the body across multiple systems," said Teresa E. Seeman, Ph.D., study co-author and professor of epidemiology at UCLA and a pioneering researcher in stress and health. "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."

Dr. Demehri explained that connecting a simple imaging measure with several well-established markers of stress and disease outcomes creates a new, practical approach to measuring chronic stress in everyday clinical practice.

"The key significance of this work is that this biomarker is obtainable from CTs that are performed widely in United States for various reasons," Dr. Demehri said. "Secondly, it is a physiologically sound measure of adrenal volume, which is part of the chronic stress physiologic cascade."

The researchers noted that this imaging biomarker could potentially be applied to many stress-related diseases that commonly affect middle-aged and older adults.

Other co-authors are Roham Hadidchi, Seyedhouman Seyedekrami, Quincy A. Hathaway, M.D., Ph.D., Michael Bancks, Nikhil Subhas, Matthew J. Budoff, M.D., David A. Bluemke, M.D., Ph.D., R. Graham Barr and Joao A.C. Lima, M.D.

The study, published in the journal Nutrients, monitored nearly 10,000 women aged 65 and older for ten years to examine whether regularly drinking coffee or tea was connected to changes in bone mineral density (BMD). BMD is a central marker used to assess osteoporosis risk.

Osteoporosis affects one in three women over 50 and leads to millions of fractures every year, making bone health an important global issue. Because coffee and tea are part of daily routines for billions of people, researchers note that understanding their long-term effects on bones is essential. Previous findings have often been inconsistent, and few studies have followed such a large group across an entire decade.

Study Design and Long-Term Tracking

Researchers at Flinders University used information from the Study of Osteoporotic Fractures, drawing on repeated measures of beverage intake and BMD at the hip and femoral neck. These areas are closely tied to fracture risk.

Throughout the ten-year period, participants regularly reported how much coffee and tea they consumed. At the same time, bone density was assessed using advanced imaging tools.

Tea's Modest but Meaningful Bone Benefits

Results showed that women who drank tea had slightly higher total hip BMD than those who did not. Although the improvement was small, it was statistically significant and may matter when considering the health of a large population.

"Even small improvements in bone density can translate into fewer fractures across large groups," says Adjunct Associate Professor Enwu Liu from the College of Medicine and Public Health.

Coffee Consumption and Bone Density Risks

Findings for coffee were more varied. Moderate intake, roughly two to three cups a day, was not associated with harm. However, consuming more than five cups per day was linked to lower BMD, indicating that very high levels of coffee could negatively affect bone strength.

Women with higher lifetime alcohol intake appeared particularly vulnerable to coffee's negative effects, whereas tea showed stronger benefits in women with obesity.

Ryan Liu, co-author of the study, explains that tea is rich in catechins, compounds that may encourage bone formation and help slow bone loss.

"Coffee's caffeine content, by contrast, has been shown in laboratory studies to interfere with calcium absorption and bone metabolism, though these effects are small and can be offset by adding milk," says Ryan Liu from Flinders University.

Practical Implications for Aging Women

Adjunct Associate Professor Enwu Liu notes that the research suggests drinking tea daily may be an easy way to support bone health as people grow older.

"While moderate coffee drinking appears safe, very high consumption may not be ideal, especially for women who drink alcohol," he says.

The researchers emphasize that while the results are statistically meaningful, the differences are not dramatic enough to require sweeping lifestyle changes.

"Our results don't mean you need to give up coffee or start drinking tea by the gallon," says Associate Professor Liu.

"But they do suggest that moderate tea consumption could be one simple way to support bone health, and that very high coffee intake might not be ideal, especially for women who drink alcohol.

"While calcium and vitamin D remain cornerstones of bone health, what's in your cup could play a role too. For older women, enjoying a daily cup of tea may be more than a comforting ritual, it could be a small step toward stronger bones," he concludes.

Study Funding

The SOF study received support from the National Institute on Aging (NIA) and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), with funding provided through grants (AG05407, AR35582, AG05394, AR35584, and AR35583).

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