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Transcatheter Aortic Valve Replacement

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A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement.

Cardiovascular revascularization medicine : including molecular interventions
BACKGROUND: Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatment of aortic stenosis. Computed tomography (CT) analysis is essential for pre-procedural planning. Currently available software packages for TAVR plann...

Transcatheter Aortic Valve Replacement and Coronary Protection Guided by Deep Learning and 3-Dimensional Printing.

Surgical innovation
OBJECTIVE: In this case report, the auxiliary role of deep learning and 3-dimensional printing technology in the perioperative period was discussed to guide transcatheter aortic valve replacement and coronary stent implantation simultaneously.

Machine-learning approaches for risk prediction in transcatheter aortic valve implantation: Systematic review and meta-analysis.

The Journal of thoracic and cardiovascular surgery
OBJECTIVES: With the expanding integration of artificial intelligence (AI) and machine learning (ML) into the structural heart domain, numerous ML models have emerged for the prediction of adverse outcomes after transcatheter aortic valve implantatio...

Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.

Scientific reports
Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss of valve function which requires the substitution by surgical aortic valve replacement (SAVR) or transcatheter aortic valve intervention (TAVI). These ...

Low muscle quality on a procedural computed tomography scan assessed with deep learning as a practical useful predictor of mortality in patients with severe aortic valve stenosis.

Clinical nutrition ESPEN
BACKGROUND & AIMS: Accurate diagnosis of sarcopenia requires evaluation of muscle quality, which refers to the amount of fat infiltration in muscle tissue. In this study, we aim to investigate whether we can independently predict mortality risk in tr...

Machine Learning of Cardiac Anatomy and the Risk of New-Onset Atrial Fibrillation After TAVR.

JACC. Clinical electrophysiology
BACKGROUND: New-onset atrial fibrillation (NOAF) occurs in 5% to 15% of patients who undergo transfemoral transcatheter aortic valve replacement (TAVR). Cardiac imaging has been underutilized to predict NOAF following TAVR.

Generation of a virtual cohort of TAVI patients for in silico trials: a statistical shape and machine learning analysis.

Medical & biological engineering & computing
PURPOSE: In silico trials using computational modeling and simulations can complement clinical trials to improve the time-to-market of complex cardiovascular devices in humans. This study aims to investigate the significance of synthetic data in deve...