AI helps experts ‘see’ stress on routine CT scans

An Adrenal Volume Index for each participant was calculated by dividing the glands’ volume by its height. This measurement was compared to individuals’ salivary cortisol levels (collected via swab eight times per day over two days) and allostatic load, which was based on body mass index, creatinine, hemoglobin, albumin, glucose, white blood count, heart rate and blood pressure. 

The algorithm’s AVI calculations were found to have significant associations with increased cortisol levels, allostatic load and psychosocial stress measured via stress questionnaires. Those with the highest perceived stress also had the highest AVI measurements; each 1 cm³/m² increase in AVI was linked to greater risk of heart failure and other adverse cardiac events in the future.

“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. “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.” 

“For over three decades, we’ve known that chronic stress can wear down the body across multiple systems,” added Teresa E. Seeman, PhD, study co-author, professor of epidemiology at UCLA and a 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.” 

The full research is set to be presented during this year’s annual Radiological Society of North America (RSNA) meeting, set to begin Sunday, Nov. 30, in Chicago.