PREDICTION OF MAJOR ADVERSE CARDIOVASCULAR EVENTS (MACE) FROM AI ANALYSIS OF PERICORONARY FAT IN CT IMAGES

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. The regression model is configured to generate a prognosis for the patient using the plurality of non-confounding PCAT features