Role of On-site CT-derived FFR in the Management of Suspect CAD Patients

When subjects are randomized to the CTA/CT-FFR arm, FFR based on the coronary CTA imaging will be measured. DEEPVESSEL FFR workstation is very dedicated software utilizing the original CTA imaging to meter simulated FFR values based on a machine learning algorithm. The first step is to extract a 3D coronary artery model and generate coronary centerlines which are similar to the routine reconstruction of coronary CTA. The centerlines are extracted using a minimal path extraction filter. Then a novel path-based deep learning model, referred to DEEPVESSEL FFR, is used to predict the simulated FFR values on the vascular centerlines. Deep learning algorithm is used to establish characteristic sample database of coronary hemodynamics characteristic parameters. When deep training model is proved to be valid, it is applied to a new lesion-specific measurement. Lesion-specific CT-FFR is defined as simulated FFR value at distance of 20mm away from the lesion of interest.