Automated Algorithm Detecting Physiologic Major Stenosis and Its Relationship With Post-PCI Clinical Outcomes

The presence of myocardial ischemia is the most important prognostic indicator in patients with coronary artery disease. Therefore, the purpose of percutaneous coronary intervention (PCI) is to relieve myocardial ischemia caused by the target stenosis. Fractional flow reserve (FFR) is an invasive physiologic index used to define functionally significant coronary stenosis, and its prognostic implications are supported by numerous studies. Contrary to the clear cutoff value and the benefit of FFR in pre-PCI evaluation, there have been various results regarding optimal cut-off values for post-PCI FFR. Nevertheless, the positive association between post-PCI FFR and the risk of future events has been reproduced by several studies. PCI with stent implantation is basically a local treatment and post-PCI FFR reflects both residual stenosis in the stented segment and remaining disease beyond the stented segment in the target vessel(s). Therefore, post-PCI FFR alone cannot fully discriminate the degree of contribution of each component. The relative increase of FFR with PCI is determined by the interaction of baseline severity of a target lesion, baseline disease burden of a target vessel, adequacy of PCI and residual disease burden in a target vessel. However, the most important problem in stratifying patients with better expected post-PCI physiologic results and following clinical outcome would be that there has been no clear method to identify these patients in pre-PCI phase. In this regard, we hypothesized that the amount of FFR step-up in pre-PCI pullback recording would determine the physiologic nature of target stenosis. For example, stenosis with sufficient step-up of FFR would deserve local treatment with PCI and these lesions would result in higher percent FFR increase, post-PCI FFR, and better clinical outcome than those without sufficient amount of FFR step-up. For this, we sought to develop automated algorithm to define physiologic major stenosis versus mino