Numerical modeling of hemodynamics scenarios of patient-specific coronary artery bypass grafts

Francesco Ballarin*, Faggiano Elena, Manzoni Andrea, Quarteroni Alfio, Rozza Gianluigi, Ippolito Sonia, Antona Carlo, Scrofani Roberto

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo

18 Citazioni (Scopus)

Abstract

A fast computational framework is devised to the study of several configurations of patient-specific coronary artery bypass grafts. This is especially useful to perform a sensitivity analysis of the hemodynamics for different flow conditions occurring in native coronary arteries and bypass grafts, the investigation of the progression of the coronary artery disease and the choice of the most appropriate surgical procedure. A complete pipeline, from the acquisition of patient-specific medical images to fast parameterized computational simulations, is proposed. Complex surgical configurations employed in the clinical practice, such as Y-grafts and sequential grafts, are studied. A virtual surgery platform based on model reduction of unsteady Navier–Stokes equations for blood dynamics is proposed to carry out sensitivity analyses in a very rapid and reliable way. A specialized geometrical parameterization is employed to compare the effect of stenosis and anastomosis variation on the outcome of the surgery in several relevant cases.
Lingua originaleInglese
pagine (da-a)1373-1399
Numero di pagine27
RivistaBiomechanics and Modeling in Mechanobiology
Volume16
Numero di pubblicazione4
DOI
Stato di pubblicazionePubblicato - 2017

All Science Journal Classification (ASJC) codes

  • Biotecnologia
  • Modellazione e Simulazione
  • Ingegneria Meccanica

Keywords

  • Cardiovascular
  • Cardiovascular simulations
  • Computational reduction strategies
  • Computer Simulation
  • Coronary Artery Bypass
  • Coronary Artery Disease
  • Coronary Vessels
  • Coronary bypass grafts
  • Data assimilation
  • Geometrical parameterization
  • Hemodynamics
  • Humans
  • Models
  • Patient-specific computing

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