Abstract: Systems, methods, and apparatus are provided for determining a risk prediction for major adverse cardiovascular event (MACE) for a patient based on a computed tomography (CT) calcium score image of the patient's chest. In one example, a method includes receiving a computed tomography (CT) calcium score image of a chest; identifying tissue of interest in the CT calcium score image; analyzing the CT calcium score image to determine features of the identified tissue of interest; and determining a risk prediction of MACE based on the features.

Abstract: The present disclosure, in some embodiments, relates to a method of generating a prognosis for a patient. The method includes accessing automatically segmented pericoronary adipose tissue (PCAT) corresponding to a patient within an electronic memory. A plurality of non-confounding PCAT features are generated by measuring values of Hounsfield units for an imaging unit within the PCAT. The measured values of the Hounsfield units are predominately free of iodine confounding and artifacts. The plurality of non-confounding PCAT features are provided to a regression model.