Artificial intelligence in estimating fractional flow reserve: a systematic literature review of techniques.

BACKGROUND: Fractional Flow Reserve (FFR) is the gold standard for the functional evaluation of coronary arteries, which is effective in selecting patients for revascularization, avoiding unnecessary procedures, and reducing treatment costs. However, its use is limited due to invasiveness, high cost, and complexity. Therefore, the non-invasive estimation of FFR using artificial intelligence (AI) methods is crucial. OBJECTIVE: This study aimed to identify the AI techniques used for FFR estimation and to explore the features of the studies that applied AI techniques in FFR estimation. METHODS: The present systematic review was conducted by searching five databases, PubMed, Scopus, Web of Science, IEEE, and Science Direct, based on the search strategy of each database. RESULTS: Five hundred seventy-three articles were extracted, and by applying the inclusion and exclusion criteria, twenty-five were finally selected for review. The findings revealed that AI methods, including Machine Learning (ML) and Deep Learning (DL), have been used to estimate the FFR. CONCLUSION: This study shows that AI methods can be used non-invasively to estimate FFR, which can help physicians diagnose and treat coronary artery occlusion and provide significant clinical performance for patients.

Infective Left Atrial Dissecting Flap after Cardiac Surgery

Left atrial dissection (LatD), defined as the forced separation of the left atrial (LA) wall layers by blood, is a rare and severe complication of cardiac surgery. It is most frequently associated with atrioventricular junction injuries. We report a case of infected LatD after coronary artery bypass graft, mitral valve replacement, aortic valve replacement and ascending aortic root replacement. The patient was presented with septicemia and disseminated intravascular coagulation. To the best of our knowledge, this is the first case report of LA dissecting flap concomitant with attached infective vegetations identified by transesophageal echocardiography.