Characterisation of spatiotemporal aortic flow and aortic wall biomechanics in coarctation

The thoracic aorta performs sophisticated functions which depends largely on its almost unique structure1. Coarctation of the aorta is a relatively common congenital anomaly, which causes a heavy burden of morbidity and mortality worldwide. As emphasized by Suradi and Hijazy in this issue of the journal, the long-term results can be very variable due to many factors. There is now a growing realization that the condition is associated with different forms of aortopathy, which are either a direct result of, or associated with, the narrowing2–4. These changes of the aorta can interfere with the long-term results of surgical correction of the anomaly and, therefore, need to be thoroughly defined and understood. Advances in modern imaging techniques, coupled with detailed computerized analysis, offer new opportunities to evaluate in vivo the mechano-biology of the arterial wall and the factors which could influence it, such as the spatiotemporal pattern of flow.Computational fluid dynamics (CFD) offers an opportunity to study both the fluid dynamics as well as its potential impact on the (patho-) physiology of the aortic wall5,6, (see Figure 1 and Figure Figure2).2). It allows quantification of flow, vortex formation, pressure gradients, wall shear stress (WSS) and other relevant parameters starting from the aortic valve through the coarcted area downstream towards the distal descending aorta, based on patient-specific 3D anatomical models of the aorta and magnetic resonance imaging (MRI) flow acquisition. Briefly, CFD analysis of a patient-specific vasculature involves the following steps: (1) reconstruction of vascular anatomy from medical images such as CT and MRI, (2) setting inflow and outflow conditions as well as properties of the blood, (3) running computations, and (4) post-processing to visualise and/or quantify the variables of interest.Figure 1.a) Flow patterns in a hypoplastic aortic arch ((left) systole, (right) diastole). The flow pathways are visualised by traces of virtual particles released in the aorta based on the CFD. High velocity flow through the hypoplastic arch leads to a hemodynamic ...Figure 2.Flow patterns (left) and endothelial shear stress (right) of a patient with calcified bicuspid aortic valve (BAV) and thoracic aortic aneurysm. The impact of the hemodynamic jet coming out through the BAV elevates the shear stress level on the endothelium ...Goubergrits et al.7 developed a CFD model to calculate peak systolic pressure drops in coarctation patients pre- and post-treatment. This is particularly relevant due to the fact that pre-operative geometries vary considerably, (Figure 3). The model demonstrated a strong correlation with catheter-based measurements in the aorta as well as flow patterns captured using 4D velocity CMR imaging. Another interesting study on the use of CFD to calculate cardiac workload and hemodynamic behaviour in different types of aortic arch obstruction was presented by Coogan et al.8. The above examples demonstrate the potential of CFD as a functional imaging tool, by adding additional visualisation and quantification power to conventional diagnostic measurements such as CT and MRI.Figure 3.Anatomical models of different reconstructed cases representing aortic coarctation geometries7.More recently, 4D velocity CMR imaging (4D Flow) has been used in looking at fluid dynamics over the cardiac cycle. Using 4D Flow acquisition sequence and post-processing software, the propagation of blood – velocity and flow – through an arterial segment can be calculated over the cardiac cycle (Figure 4).Figure 4.Post-processing results of 4D velocity CMR images in a patient with aortic coarctation and poststenotic dilatation. Systolic 3D streamlines in the entire thoratic aorta and a magnified region encompassing the pathological site14.4D velocity CMR imaging and quantification of cardiovascular hemodynamics are contributing to the understanding of cardiovascular pathologies: the combination of 3D spatial encoding, three-directional velocity encoding and cine acquisition provides data for the measurement and visualization of the temporal evolution of complex flow patterns throughout a 3D-volume9. Hope et al.10 showed that 4D velocity CMR imaging can help to evaluate collateral blood flow as a potential measure of hemodynamic significance in patients with aortic coarctation. Additionally, 4D Flow analysis showed distorted flow patterns in the descending aorta after coarctation repair. Considerable helical and vortical flow in regions of post-stenotic dilation were identified. The utility of 4D Flow to analyse and understand vascular geometry and systolic flow characteristics in a patient with restenosis in aortic coarctation, after surgical repair, is presented by Markl et al.11 (Figure 4). An early study by Kilner et al. 12 was published, describing helical and retrograde flows in normal aortic arch using three-directional cine velocity mapping (predecessor to 4D Flow). The development of flow through the two coronary cusp sinuses, the arch and the descending aorta was demonstrated at selected velocity mapping planes.Image acquisition as well as post-processing of 4D flow datasets require time and multi-disciplinary skills. Efficient synchronization considering cardiac and respiratory movements has a significant impact on image quality13,14. 4D Flow is not yet a part of the clinical routine of CMR examination, but its use should increase in specialized centres in the near future.