Ashish Gautam

Bachelor of Technology

KardioLabs LLC

Research Scientist

NLST (Learn more about this study)

NLST-774

Mar 30, 2021

Identification and Quantification of Cardiac Calcium and cardiovascular Risk Stratification

Cardiovascular disease (CVD) is the leading cause of death and 42% of these deaths are caused by the coronary artery disease (CAD). The degree and amount of coronary artery calcification (CAC) is the strong predictor of cardiovascular events and mortality. Routinely, CAC is detected and quantified as Agatston score by the human operator by manually identifying the CAC lesions and utilizing a commercially available software. This could be a very tedious and time-consuming operator dependent process and potential of error. CAC is seen commonly in patients with risk factors undergoing chest CT. We have developed a fully automated, AI powered method using spatial features and CAC segmentation to rapidly calculate Agatston score from ECG gated non contrast Cardiac CT (Cardiac CT). We Propose to compare the efficacy of our solution in detecting and quantification of cardiac calcium in a large scale NLST cohort of Non-ECG Synchronized Chest CT. We also intend to compare the efficacy of chest CT with Non-Contrast ECG gated Cardiac CT regarding coronary calcium detection and CVD risk prediction. This will help in better treatment options in this high-risk group and better resource utilization.