Automatic Anatomical and Functional Classification of Coronary Arteries With Artificial Intelligence.

The goal of this Category 3 research involving the human person is to predict the measurement of the post-stenosis flow (FFR) using CTTA coupled with an intelligent predictive analysis system and comparing it with invasive coronary angiography FFR as measurement of reference. The population studied are adult patients,- with no diagnosed coronary status or history of stenting or bypass surgery- with indication for FFR measurement. The main question it aims to answer is: • Can, in a single acquisition, CTTA coupled with AI produce good predictive performance of stenosis and FFR ? If it can it will allow us to avoid the need for invasive FFR. For patients who will be included in the retrospective part: only their data from their medical records will be used. Patients who will be included in the prospective part will additionally complete the EQ5D5L questionnaire before coronary angiography and at the end of the patient's participation (4 months after the CCTA). There is a no comparison group, the predictive FFR from CTTA of a patient will be compared with angiography FFR from the same patient, same vessel.