Mulitmedia Library
Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium
Original TOC summary: We used SHAP, an explainable machine learning (ML) technique, to determine the risk predictive value and age interaction of coronary artery calcium (CAC) characteristics among 63,215 asymptomatic patients in the CAC consortium. The addition of CAC density and number of calcified vessels to an ML model with clinical characteristics + CAC did not improve prediction for all-cause mortality (p = 0.23), but did improve for cardiovascular mortality (p = 0.03). Lower CAC density increased mortality, particularly very low CAC density ≤0.75, which occurred predominantly in CAC1-100. Explainable ML should be applied in clinical research for transparent predictive modeling.Cumulative exposure amount of PM2.5 in the ambient air is associated with coronary atherosclerosis - Serial coronary CT angiography study
TOC SUMMARY: It is unclear how air pollution contributes to the development of cardiovascular disease. We investigated the change of coronary atherosclerosis using serial CCTAs in relation to the cumulative amount of PM2.5 exposure between the two CCTAs in 3,127 healthy adults. Coronary calcification progressed in 1,361 (43.5%) subjects with a positive relationship between the cumulative amount of PM2.5 exposure and CACS. The cumulative amount of PM2.5 exposure, rather than the average concentration of PM2.5, was independently associated with progression of coronary calcification and diffuse development of de novo calcified plaques, with its impact higher than any other traditional cardiovascular risk factors.Detection of small coronary calcifications in patients with Agatston coronary artery calcium score of zero
The conventional Agatston coronary artery calcium score (CACS) method may fail to detect very small or less dense calcified plaques; smaller than 3 continuous pixels (1 mm2) or with a density lower than 130 Hounsfield Units (HU). A significant proportion of patients classified as CACS = 0, could potentially be reclassified as >0 by altering these thresholds. The increased sensitivity with lower HU threshold comes at a cost of reduced specificity by introducing false positive (noise) cases. Modifying the threshold to <1 mm 2 and HU > 120, allows 12.1% of patients with CACS = 0 to be reclassified as CACS> 0 while introducing only 0.9% of noise.A novel density-volume calcium score by non-contrast CT predicts coronary plaque burden on coronary CT angiography: Results from the MACS (Multicenter AIDS cohort study)
The purpose of this study is to determine if a new score calculated with coronary artery calcium (CAC) density and volume is associated with total coronary artery plaque burden and composition on coronary CT angiography (CCTA) compared to the Agatston score (AS).Using a genetic risk score to calculate the optimal age for an individual to undergo coronary artery calcium screening
Genetic risk scores (GRSs) have been associated with CHD events and coronary artery calcium (CAC). We sought to evaluate the ability of a GRS to improve CAC as a screening test.
