Researchers developed an AI model to measure chronic stress using adrenal gland volume on routine CT scans.
Key Details
- 1Researchers created a deep learning model to analyze adrenal gland volume from routine chest CT scans.
- 2The model links larger adrenal volume to chronic or severe stress.
- 3Algorithm was retrospectively tested on 2,842 CT scans from the Multi-Ethnic Study of Atherosclerosis.
- 4Results were validated with stress questionnaires and cortisol markers for objective and subjective comparison.
- 5The method allows use of existing imaging data for non-invasive chronic stress evaluation.
Why It Matters
This development demonstrates the power of AI to extract new, actionable biomarkers from routine radiology exams, potentially enabling large-scale, cost-effective risk assessments for chronic stress. It highlights how imaging AI can impact preventive care beyond traditional disease diagnosis.
Source
Radiology Business
Related News
•AuntMinnie
Study: Computer Vision Models Best LLMs in Chest CT Breast Abnormality Detection
Computer vision models (CVMs) surpass large language models (LLMs) in accurately labeling incidental breast abnormalities on chest CT scans.
•Cardiovascular Business
Radiology Maintains Lead in FDA-Cleared AI Algorithms, Cardiology Follows
Radiology remains the top specialty for FDA-cleared AI, with cardiology as a strong second, particularly in cardiovascular imaging.
•AuntMinnie
Deep Learning Models Rival Radiologists for Pancreatic Cancer Detection on CT
Deep-learning models achieved comparable or superior accuracy to experienced radiologists in detecting pancreatic cancer on CT scans, especially for small tumors.