Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry. (March 2022)

• Record Type: Journal Article
• Authors: Franzetti, Gaia; Bonfanti, Mirko; Homer-Vanniasinkam, Shervanthi; Diaz-Zuccarini, Vanessa; Balabani, Stavroula
• Is Part Of: Journal of biomechanics. Volume 134(2022)
• Publication Date: 2022-03
• Subjects: Aortic Dissection -- Particle Image Velocimetry -- Haemodynamics -- Patient-specific; Animal mechanics -- Periodicals; Biomechanics -- Periodicals; Biomechanics -- Periodicals; Mécanique animale -- Périodiques; Biomécanique -- Périodiques; Electronic journals; 571.4305
• DOI: 10.1016/j.jbiomech.2022.110963
• Languages: English
• ISSNs: 0021-9290

Abstract

Abstract: Aortic Dissection (AD) is a complex pathology that affects the aorta. Diagnosis, management and treatment remain a challenge as it is a highly patient-specific pathology and there is still a limited understanding of the fluid-mechanics phenomena underlying clinical outcomes. Although in vitro models can allow the accurate study of AD flow fields in physical phantoms, they are currently scarce and almost exclusively rely on over simplifying assumptions. In this work, we present the first experimental study of a patient-specific case of AD. An anatomically correct phantom was produced and combined with a state-of-the-art in vitro platform, informed by clinical data, employed to accurately reproduce personalised conditions. The complex AD haemodynamics reproduced by the platform was characterised by flow rate and pressure acquisitions as well as Particle Image Velocimetry (PIV) derived velocity fields. Clinically relevant haemodynamic indices, that can be correlated with AD prognosis – such as velocity, shear rate, turbulent kinetic energy distributions – were extracted in two regions of interest in the aortic domain. The acquired data highlighted the complex nature of the flow (e.g. recirculation regions, low shear rate in the false lumen) and was in very good agreement with the available clinical data and the CFD results of a study conducted alongside, demonstrating the accuracy of the findings. These results demonstrate that the described platform constitutes a powerful, unique tool to reproduce in vitro personalised haemodynamic conditions, which can be used to support the evaluation of surgical procedures, medical devices testing and to validate state-of-the-art numerical models.