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

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 developing in silico trials for assessing the safety and efficacy of cardiovascular devices, focusing on bioprostheses designed for transcatheter aortic valve implantation (TAVI).

Methods: A statistical shape model (SSM) was employed to extract uncorrelated shape features from TAVI patients, enabling the augmentation of the original patient population into a clinically validated synthetic cohort.

Computational fluid dynamics in cardiac surgery and perfusion: A review.

Cardiovascular diseases persist as a leading cause of mortality and morbidity, despite significant advances in diagnostic and surgical approaches. Computational Fluid Dynamics (CFD) represents a branch of fluid mechanics widely used in industrial engineering but is increasingly applied to the cardiovascular system. This review delves into the transformative potential for simulating cardiac surgery procedures and perfusion systems, providing an in-depth examination of the state-of-the-art in cardiovascular CFD modeling.

Parametric analysis of transcatheter aortic valve replacement in transcatheter aortic valve replacement: evaluation of coronary flow obstruction.

Transcatheter aortic valve replacement (TAVR) is increasingly being considered for use in younger patients having longer life expectancy than those who were initially treated. The TAVR-in-TAVR procedure represents an appealing strategy to treat failed transcatheter heart valves (THV) likely occurring in young patients. However, the permanent displacement of first THV can potentially compromise the coronary access and ultimately inhibit the blood flow circulation.

A custom-built planar biaxial system for soft tissue material testing.

Accurate material characterization of soft tissues is crucial for understanding the physiopathology of cardiovascular diseases. However, commercial biaxial testing systems are expensive, prompting the need for affordable custom solutions. This study aimed to develop a low-cost custom biaxial system capable of accurately characterizing the mechanical behavior of soft tissues.