Most of the recent research on calcium scoring has focused on calcium in the coronary arteries and its link to cardiovascular disease. But a new study in American Heart Journal used abdominal CT scans with AI analysis for opportunistic measurement of abdominal aortic calcium to predict cardiac events – possibly earlier than CAC scores.
CT-derived CAC scores have become a powerful tool for predicting cardiovascular disease, helping physicians determine when to begin preventive therapy with treatments like statins.
- CAC scores can be generated from dedicated cardiac CT scans, or even lung screening exams as part of a two-for-one test.
Abdominal CT represents another promising area for calculating calcium.
- Previous research has found that atherosclerosis in the abdominal aorta may occur before its development in the coronary arteries, creating the opportunity to detect calcium earlier.
Researchers from NYU Langone did just that in the new study, performing abdominal and cardiac CT scans in 3.6k patients and using an AI algorithm they developed in partnership with Visage Imaging to calculate AAC. They found that over an average three-year follow-up period …
- AI analysis of AAC severity was positively associated with CAC.
- AAC could be used to rule out the presence of CAC relative to two versions of the PREVENT score (AUC=0.701 and 0.7802).
- The presence of AAC was associated with a higher adjusted risk of major adverse cardiovascular events (HR=2.18).
- A doubling of the AAC score was linked to 11% higher risk of MACE.
The Takeaway
The new results are an exciting demonstration of opportunistic screening’s value, especially given the volume of abdominal CT scans performed annually. AI analysis of routinely acquired abdominal CT could give radiologists a tool for detecting heart disease risk even earlier than what’s possible with CAC scoring.
