Computational modeling of bicuspid aortopathy: Towards personalized risk strategies

Francesco Scardulla, Federica Cosentino, Leonardo D'Acquisto, Salvatore Pasta, Valentina Agnese, Michele Pilato, Diego Bellavia, Giuseppe Raffa, Giovanni Gentile, Salvatore Pasta, Valentina Agnese, Federica Cosentino, Giovanni Domenico Gentile

Risultato della ricerca: Article

Abstract

This paper describes current advances on the application of in-silico for the understanding of bicuspid aortopathy and future perspectives of this technology on routine clinical care. This includes the impact that artificial intelligence can provide to develop computer-based clinical decision support system and that wearable sensors can offer to remotely monitor high-risk bicuspid aortic valve (BAV) patients. First, we discussed the benefit of computational modeling by providing tangible examples of in-silico software products based on computational fluid-dynamic (CFD) and finite-element method (FEM) that are currently transforming the way we diagnose and treat cardiovascular diseases. Then, we presented recent findings on computational hemodynamic and structural mechanics of BAV to highlight the potentiality of patient-specific metrics (not-based on aortic size) to support the clinical-decision making process of BAV-associated aneurysms. Examples of BAV-related personalized healthcare solutions are illustrated.
Lingua originaleEnglish
pagine (da-a)122-131
Numero di pagine10
RivistaJournal of Molecular and Cellular Cardiology
Volume131
Stato di pubblicazionePublished - 2019

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Bicuspid
Computer Simulation
Clinical Decision Support Systems
Artificial Intelligence
Mechanics
Aneurysm
Cardiovascular Diseases
Software
Hemodynamics
Technology
Delivery of Health Care
Bicuspid Aortic Valve

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Cardiology and Cardiovascular Medicine

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Computational modeling of bicuspid aortopathy: Towards personalized risk strategies. / Scardulla, Francesco; Cosentino, Federica; D'Acquisto, Leonardo; Pasta, Salvatore; Agnese, Valentina; Pilato, Michele; Bellavia, Diego; Raffa, Giuseppe; Gentile, Giovanni; Pasta, Salvatore; Agnese, Valentina; Cosentino, Federica; Gentile, Giovanni Domenico.

In: Journal of Molecular and Cellular Cardiology, Vol. 131, 2019, pag. 122-131.

Risultato della ricerca: Article

Scardulla, F, Cosentino, F, D'Acquisto, L, Pasta, S, Agnese, V, Pilato, M, Bellavia, D, Raffa, G, Gentile, G, Pasta, S, Agnese, V, Cosentino, F & Gentile, GD 2019, 'Computational modeling of bicuspid aortopathy: Towards personalized risk strategies', Journal of Molecular and Cellular Cardiology, vol. 131, pagg. 122-131.
Scardulla, Francesco ; Cosentino, Federica ; D'Acquisto, Leonardo ; Pasta, Salvatore ; Agnese, Valentina ; Pilato, Michele ; Bellavia, Diego ; Raffa, Giuseppe ; Gentile, Giovanni ; Pasta, Salvatore ; Agnese, Valentina ; Cosentino, Federica ; Gentile, Giovanni Domenico. / Computational modeling of bicuspid aortopathy: Towards personalized risk strategies. In: Journal of Molecular and Cellular Cardiology. 2019 ; Vol. 131. pagg. 122-131.
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AU - Agnese, Valentina

AU - Pilato, Michele

AU - Bellavia, Diego

AU - Raffa, Giuseppe

AU - Gentile, Giovanni

AU - Pasta, Salvatore

AU - Agnese, Valentina

AU - Cosentino, Federica

AU - Gentile, Giovanni Domenico

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