Literature DB >> 28553722

Uncertainty propagation of phase contrast-MRI derived inlet boundary conditions in computational hemodynamics models of thoracic aorta.

Silvia Bozzi1, Umberto Morbiducci2, Diego Gallo2, Raffaele Ponzini3, Giovanna Rizzo4, Cristina Bignardi2, Giuseppe Passoni1.   

Abstract

This study investigates the impact that uncertainty in phase contrast-MRI derived inlet boundary conditions has on patient-specific computational hemodynamics models of the healthy human thoracic aorta. By means of Monte Carlo simulations, we provide advice on where, when and how, it is important to account for this source of uncertainty. The study shows that the uncertainty propagates not only to the intravascular flow, but also to the shear stress distribution at the vessel wall. More specifically, the results show an increase in the uncertainty of the predicted output variables, with respect to the input uncertainty, more marked for blood pressure and wall shear stress. The methodological approach proposed here can be easily extended to study uncertainty propagation in both healthy and pathological computational hemodynamic models.

Entities:  

Keywords:  Phase contrast MRI; boundary conditions; computational hemodynamics; thoracic aorta; uncertainty propagation; wall shear stress

Mesh:

Year:  2017        PMID: 28553722     DOI: 10.1080/10255842.2017.1334770

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  4 in total

1.  Computational study of aortic hemodynamics for patients with an abnormal aortic valve: The importance of secondary flow at the ascending aorta inlet.

Authors:  S Pirola; O A Jarral; D P O'Regan; G Asimakopoulos; J R Anderson; J R Pepper; T Athanasiou; X Y Xu
Journal:  APL Bioeng       Date:  2018-03-16

Review 2.  Computational Modeling of Blood Flow Hemodynamics for Biomechanical Investigation of Cardiac Development and Disease.

Authors:  Huseyin Enes Salman; Huseyin Cagatay Yalcin
Journal:  J Cardiovasc Dev Dis       Date:  2021-01-31

3.  A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics.

Authors:  Catriona Stokes; Mirko Bonfanti; Zeyan Li; Jiang Xiong; Duanduan Chen; Stavroula Balabani; Vanessa Díaz-Zuccarini
Journal:  J Biomech       Date:  2021-10-09       Impact factor: 2.712

4.  On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses.

Authors:  Simona Celi; Emanuele Vignali; Katia Capellini; Emanuele Gasparotti
Journal:  Front Med Technol       Date:  2021-12-01
  4 in total

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