In a recent study, Harvard researchers used an AI-based body composition tool to analyze 1,277 emergency abdominal CT scans of individuals in their 30s, aiming to predict major adverse cardiovascular events (MACE) and issues like high cholesterol (dyslipidemia).
The AI tool, ClariMetabo from Claripi.ai, processed CT images from different machines with just one click. It provided measurements of subcutaneous and visceral fat, as well as muscle mass around the abdomen, focusing on the T12 to L4 vertebrae levels. Dr. Emiliano Garza Frias from Massachusetts General Hospital and Harvard Medical School will present the study, showing how measurements of abdominal visceral fat and waist circumference were the strongest predictors of MACE and dyslipidemia.
Specifically, the study found that higher amounts of visceral fat (hazard ratio [HR]: 1.7) and a larger waist circumference (HR: 2) increased the risk of MACE and dyslipidemia. On the other hand, lower CT values, indicating less fat, appeared to offer some protection against dyslipidemia.
This presentation will discuss how AI tools like this can help in early screening, allowing doctors to identify young patients at risk and take preventive steps to reduce heart health risks.
Source: auntminnie
