Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker

The authors aimed to develop a radiomic biomarker, termed cardiovascular age (CV-Age), based on peri-aortic adipose tissue (PAAT) from routine chest CT scans to better assess cardiovascular aging and its associated risks. They found that the PAAT-derived CV-Age, particularly the age gap (ΔAge) between CV-Age and chronological age, effectively stratified the risk of major adverse cardiovascular events (MACE) and improved risk classification compared to traditional age-based assessments. This study suggests that CV-Age can enhance the identification of individuals at higher cardiovascular risk who may otherwise be overlooked.