Comparison of hemodynamic and structural indices of ascending thoracic aortic aneurysm as predicted by 2-way FSI, CFD rigid wall simulation and patient-specific displacement-based FEA

Salvatore Pasta, Marzio Di Giuseppe, Salvatore Pasta, Marzio Di Giuseppe, Vincent Mendez

Risultato della ricerca: Articlepeer review

11 Citazioni (Scopus)

Abstract

Patient-specific computational modeling is increasingly being used to predict structural and hemodynamic parameters, especially when current clinical tools are not accessible. Indeed, pathophysiology of ascending thoracic aortic aneurysm (ATAA) has been simulated to quantify the risk of complications by novel prognostic parameters and thus to improve the clinical decision-making process related to the intervention of ATAAs. In this study, the relevance of aneurysmal wall elasticity in determining parameters of clinical importance, such as the wall shear stress (WSS), is discussed together with the significance of applying realistic boundary conditions to consider the aortic stretch and twist transmitted by the heart motion. Results from both finite element analysis (FEA) and computational fluid-dynamic (CFD) were compared to those of 2-way fluid-solid interaction analyses (FSI), which were carried out on ATAAs with either bicuspid aortic valve (BAV) or tricuspid aortic valve (TAV). Although both the shear and intramural stress spatial distributions were found different for a given ATAA, correlation analysis and Bland-Altman plots demonstrated that CFD-related WSS and FEA-related IMS predictions were comparable with those derived by the more sophisticated 2-way FSI modeling. This is likely caused by the stiff aneurysmal wall showing reduced diameter changes over the cardiac beating (ie, 4.2 +/- 2.4%). Therefore, with the fact that there is no gold-standard for the assessment of hemodynamic and structural mechanics of ATAAs and with accepted limitations of our approach, computational technique has to be verified before applications in routine clinical practice as demonstrated in this study.
Lingua originaleEnglish
pagine (da-a)221-229
Numero di pagine9
RivistaComputers in Biology and Medicine
Volume100
Stato di pubblicazionePublished - 2018

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Health Informatics

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