Sunday, May 11, 2025
5/11/2025
Novel methods for earlier detection of coronary artery calcium using CT - Project Summary/Abstract Coronary heart disease (CHD) is the most common form of heart disease, the leading cause of death worldwide. Traditional risk prediction tools such as the Framingham Risk Score use clinical biomarkers to identify individuals who are of higher risk for an adverse CHD event and would therefore benefit from preventive LDL-C lowering therapy. However, these tools identify very few younger individuals who are at increased risk, despite the fact that longer cumulative exposure to lower LDL-C shows increased protection from CHD events. Coronary artery calcium (CAC) measured via CT is the best novel predictor of CHD events and is predictive of CHD events among young individuals. Recent guideline updates recommend LDL-C lowering therapy in individuals with any detectable CAC. Coronary calcification progresses with age, so scanning all younger individuals will result in a very low positive rate of detection. Age independent risk factors, such as genetic risk, are needed to determine which younger individuals will benefit the most from early calcium screening. Additionally, current CAC scoring methods are based on outdated technology, and there is a critical need to understand scan sensitivity to non- zero CAC detection. CAC detection is a function of both plaque size and calcium density, and the influence of motion introduces an additional technical challenge. The focus of this work is to develop novel image scanning and reconstruction methods for earlier CAC detection using CT and to apply innovative risk prediction tools to develop a successful CAC screening strategy. This work will identify the appropriate age for each individual to begin CAC screening with CT using the age independent risk factors of sex and genetics. Additionally, the minimum detectable mass of CAC by CT will be assessed and improved by optimizing scan acquisition and reconstruction methods. Finally, new image analysis techniques for discovery of non-zero CAC in standard helical chest CT scans with motion artifact will be derived. The proposed project will establish novel scan acquisition, image reconstruction, and risk prediction tools for CAC detection that will improve CAC measurement as a screening strategy for CHD. These developments will permit earlier detection of CAC in young individuals who have previously been misclassified as disease free.
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