AI detects myosteatosis as strong COPD risk predictor

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A study using artificial intelligence to analyze CT scans found that myosteatosis — a measure of fatty infiltration and reduced muscle quality — predicts future COPD risk more strongly than emphysema-like lung measurements, suggesting muscle quality assessment could become an important tool for identifying people at risk of developing COPD.

  • AI-derived myosteatosis measurements predicted COPD with a hazard ratio of 2.74, compared to 1.50 for emphysema-like measurements from the same CT scans
  • The study followed 5,535 participants from the Multi-Ethnic Study of Atherosclerosis for approximately 20 years, with 396 participants (7.1%) diagnosed with COPD
  • The AI-CVD platform analyzes visible thoracic muscles throughout the entire scan rather than relying on single manual images, enabling reproducible measurement of muscle fat infiltration
  • Additional validation studies are needed to establish myosteatosis as a clinical COPD biomarker and determine whether interventions improving muscle quality could reduce respiratory disease risk

Myosteatosis measurements derived from artificial intelligence of coronary artery calcium (CAC) CT scans have shown potential in predicting future COPD risk.

That’s according to the paper, “Artificial Intelligence-Derived Measurements From Coronary Artery Calcium CT Scan To Predict COPD: The Multi-Ethnic Study of Atherosclerosis,” published in Radiology: Cardiothoracic Imaging.

According to a press release, the study analyzed baseline CAC CT exams from 5,535 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) and followed clinical outcomes for about 20 years. During follow-ups, 396 participants (7.1%) were diagnosed with COPD.

Investigators used a platform developed by HeartLung.AI called AI-CVD, which uses artificial intelligence to analyze CT screening and identify hidden risks, to identify myosteatosis — a CT marker of fatty infiltration and reduced muscle quality. They compared the predictive value of this measurement with another AI-derived emphysema-like lung measurement obtained from the same CT scans.

Rsna Aidoi: 10.1148/ryct.250205The AI-CVD tool analyzed visible thoracic muscles throughout the scan volume rather than relying on a single, manually selected image or region of interest. The researchers found myosteatosis predicted COPD more strongly than the emphysema-like lung measurement with a hazard ratio of 2.74 vs. 1.50. That means, according to the study, that participants with myosteatosis demonstrated a 2.74-fold increased risk of developing COPD.

“The association between myosteatosis and COPD remained consistent across age, sex, obesity, smoking status and activity subgroups,” the authors wrote. This is the first study to investigate the association between AI-quantified myosteatosis and future COPD diagnosis.

“This is exactly where AI can change medicine,” said HeartLung.AI Founder and President Morteza Nachavi, MD. He explained that AI enables subtle quantitative findings, such as muscle fat infiltration, to be measured reproducibly from CT images even when they may not be practical to quantify visually during routine clinical interpretation.

The researchers stated that additional validation and studies are needed before myosteatosis can be established as a clinical COPD biomarker. Future studies are expected to examine additional populations, evaluate whether changes in muscle quality precede deterioration in pulmonary function and determine whether interventions that improve muscle quality may influence future COPD risk.

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