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

Journal: Medical & biological engineering & computing
PMID: 39388030

Abstract

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).

Authors

  • Roberta Scuoppo
    Department of Engineering, Università degli Studi di Palermo, Viale Delle Scienze Ed.8, Palermo, Italy.
  • Salvatore Castelbuono
    Department of Electronics, Informatics and Bioengineering, Politecnico di Milano, Milan, Italy.
  • Stefano Cannata
    Interventional Cardiology Unit, IRCCS ISMETT, via Tricomi, 5, Palermo, Italy.
  • Giovanni Gentile
    Radiology Unit, Department of Diagnostic and Therapeutic Services, IRCCS ISMETT, Via Tricomi, 5, Palermo, Italy.
  • Valentina Agnese
    Department of Research, IRCCS ISMETT, via Tricomi, 5, Palermo, Italy.
  • Diego Bellavia
    Department of Research, IRCCS ISMETT, via Tricomi, 5, Palermo, Italy.
  • Caterina Gandolfo
    Interventional Cardiology Unit, IRCCS ISMETT, via Tricomi, 5, Palermo, Italy.
  • Salvatore Pasta
    Department of Engineering, Università degli Studi di Palermo, Viale Delle Scienze Ed.8, Palermo, Italy. salvatore.pasta@unipa.it.

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