A deep learning model has identified and validated the first imaging biomarker for chronic stress using adrenal gland measurements from routine chest CT scans.
Key Details
- 1Researchers at Johns Hopkins developed an AI model to measure adrenal gland volume on chest CT scans.
- 2The study used data from 2,842 participants in the Multi-Ethnic Study of Atherosclerosis, integrating imaging, cortisol, and psychosocial stress measures.
- 3AI-derived Adrenal Volume Index (AVI) correlated with stress questionnaires, cortisol levels, and allostatic load.
- 4Higher AVI was associated with greater stress indicators and increased risk of heart failure and mortality over 10 years of follow-up.
- 5This method leverages routinely performed CT scans without additional testing or radiation.
Why It Matters
This is the first validated AI-driven imaging biomarker for chronic stress, offering radiologists a new quantitative tool for assessing the physiological impact of stress using existing CT data. The approach could improve risk stratification and guide preventive care for stress-related diseases.
Source
EurekAlert
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