Background: Four-dimensional CT is increasingly used for functional cardiac imaging, including prognosis for conditions such as heart failure and post myocardial infarction. However, radiation dose from an acquisition spanning the full cardiac cycle remains a concern. This work investigates the possibility of dose reduction in 4DCT using deep learning (DL)-based segmentation techniques as an objective observer.
View Article and Find Full Text PDFBackground: The absence of coronary artery calcium (CAC) measured via CT is associated with very favorable prognosis, and current guidelines recommend low-density lipoprotein cholesterol (LDL-c) lowering therapy for individuals with any CAC. This motivates early detection of small granules of CAC; however, calcium scan sensitivity for detecting very low levels of calcium has not been quantified.
Purpose: In this work, the size limit of detectability of small calcium hydroxyapatite (CaHA) granules with clinical CAC scanning was assessed using validated simulations.
Objectives: The goal of this study was to assess the utility of a genetic risk score (GRS) in targeted coronary artery calcium (CAC) screening among young individuals.
Background: Early CAC screening and preventive therapy may reduce long-term risk of a coronary heart disease (CHD) event. However, identifying younger individuals at increased risk remains a challenge.
Background: 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.
Methods: Using the results of the most recent genome-wide association studies, we calculated a GRS in 6660 individuals from the Multi-Ethnic Study of Atherosclerosis and used it to determine the optimal age for an individual to undergo CAC screening.