Computational Fluid Dynamics and Aortic Dissections: Panacea or Panic?

Abstract

This paper reviews the methodology, benefits and limitations associated with computational flow dynamics (CFD) in the field of vascular surgery. Combined with traditional imaging of the vasculature, CFD simulation enables accurate characterisation of real-time physiological and haemodynamic parameters such as wall shear stress. This enables vascular surgeons to understand haemodynamic changes in true and false lumens, and exit and re-entry tears. This crucial information may facilitate triaging decisions. Furthermore, CFD can be used to assess the impact of stent graft treatment, as it provides a haemodynamic account of what may cause procedure-related complications. Efforts to integrate conventional imaging, individual patient data and CFD are paramount to its success, given its potential to replace traditional registry-based, population-averaged data. Nonetheless, methodological limitations must be addressed before clinical implementation. This must be accompanied by further research with large sample sizes, to establish the association between haemodynamic patterns as observed by CFD and progression of aortic dissection.

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

“…The influence of WSS on the onset and progression of a multitude of cardiovascular diseases has been widely demonstrated (Mazzi et al, 2020). For example, specific WSS distribution characteristics have been identified as markers of aneurysm development (Chung and Cebral, 2015), and regions of low WSS have been associated with numerous adverse effects, including endothelial dysfunction and the formation of atherosclerotic regions (Wee et al, 2018). Due to the strong prognostic value of WSS, our results highlight the importance of compliance modelling.…”

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

“…The influence of WSS on the onset and progression of a multitude of cardiovascular diseases has been widely demonstrated ( Mazzi et al, 2020 ). For example, specific WSS distribution characteristics have been identified as markers of aneurysm development ( Chung and Cebral, 2015 ), and regions of low WSS have been associated with numerous adverse effects, including endothelial dysfunction and the formation of atherosclerotic regions ( Wee et al, 2018 ). Due to the strong prognostic value of WSS, our results highlight the importance of compliance modelling.…”

Patient-specific compliant simulation framework informed by 4DMRI-extracted Pulse Wave Velocity: Application post-TEVAR

“…TAWSS distributions obtained with S1 and S2 are qualitatively similar. In S2, the highest TAWSS values were found at the AA, arch and especially Vao (13.35Pa), where high velocities occur (Chen et al, 2013a;Wee et al, 2018). The OSI distributions differ broadly between S2 and S1, indicating mean relative errors >20% downstream of the arch, promoted by substantially different flow conditions predicted therein.…”