In order for computational fluid dynamics to provide quantitative parameters to aid in the clinical assessment of type B aortic dissection, the results must accurately mimic the hemodynamic environment within the aorta. The choice of inlet velocity profile (IVP) therefore is crucial; however, idealised profiles are often adopted, and the effect of IVP on hemodynamics in a dissected aorta is unclear. This study examined two scenarios with respect to the influence of IVP—using (a) patient-specific data in the form of a three-directional (3D), through-plane (TP) or flat IVP; and (b) non-patient-specific flow waveform. The results obtained from nine simulations using patient-specific data showed that all forms of IVP were able to reproduce global flow patterns as observed with 4D flow magnetic resonance imaging. Differences in maximum velocity and time-averaged wall shear stress near the primary entry tear were up to 3% and 6%, respectively, while pressure differences across the true and false lumen differed by up to 6%. More notable variations were found in regions of low wall shear stress when the primary entry tear was close to the left subclavian artery. The results obtained with non-patient-specific waveforms were markedly different. Throughout the aorta, a 25% reduction in stroke volume resulted in up to 28% and 35% reduction in velocity and wall shear stress, respectively, while the shape of flow waveform had a profound influence on the predicted pressure. The results of this study suggest that 3D, TP and flat IVPs all yield reasonably similar velocity and time-averaged wall shear stress results, but TP IVPs should be used where possible for better prediction of pressure. In the absence of patient-specific velocity data, effort should be made to acquire patient’s stroke volume and adjust the applied IVP accordingly.

Computational hemodynamic studies of aortic dissections usually combine patient-specific geometries with idealized or generic boundary conditions. In this study, we present a comprehensive methodology for the simulation of hemodynamics in type B aortic dissection (TBAD), based on fully patient-specific boundary conditions. Pre-operative four-dimensional (4-D) flow magnetic resonance imaging (MRI) and Doppler-wire pressure measurements (pre- and post-operative) were acquired from a TBAD patient. These data were used to derive boundary conditions for computational modeling of flow before and after thoracic endovascular repair (TEVAR). Validations of the computational results were performed by comparing predicted flow patterns with pre-TEVAR 4-D flow MRI, as well as pressures with in vivo measurements. Comparison of instantaneous velocity streamlines showed a good qualitative agreement with 4-D flow MRI. Quantitative comparison of predicted pressures with pressure measurements revealed a maximum difference of 11 mmHg (-9.7%). Furthermore, our model correctly predicted the reduction of true lumen pressure from 74/115 mmHg pre-TEVAR to 64/107 mmHg post-TEVAR (diastolic/systolic pressures at entry tear level), compared to the corresponding measurements of 72/118 mmHg and 64/114 mmHg. This demonstrates that pre-TEVAR 4D flow MRI can be used to tune boundary conditions for post-TEVAR hemodynamic analyses.

Thoracic endovascular aortic repair (TEVAR) has been accepted as the mainstream treatment for type B aortic dissection, but post-TEVAR biomechanical-related complications are still a major drawback. Unfortunately, the stent-graft (SG) configuration after implantation and biomechanical interactions between the SG and local aorta are usually unknown prior to a TEVAR procedure. The ability to obtain such information via personalised computational simulation would greatly assist clinicians in pre-surgical planning. In this study, a virtual SG deployment simulation framework was developed for the treatment for a complicated aortic dissection case. It incorporates patient-specific anatomical information based on pre-TEVAR CT angiographic images, details of the SG design and the mechanical properties of the stent wire, graft and dissected aorta. Hyperelastic material parameters for the aortic wall were determined based on uniaxial tensile testing performed on aortic tissue samples taken from type B aortic dissection patients. Pre-stress conditions of the aortic wall and the action of blood pressure were also accounted for. The simulated post-TEVAR configuration was compared with follow-up CT scans, demonstrating good agreement with mean deviations of 5.8% in local open area and 4.6 mm in stent strut position. Deployment of the SG increased the maximum principal stress by 24.30 kPa in the narrowed true lumen but reduced the stress by 31.38 kPa in the entry tear region where there was an aneurysmal expansion. Comparisons of simulation results with different levels of model complexity suggested that pre-stress of the aortic wall and blood pressure inside the SG should be included in order to accurately predict the deformation of the deployed SG.

Background: Inflammation plays an important role in the progression of sporadic aortic dissection (AD). Immune cells, especially macrophages, infiltrate the aorta and secrete inflammatory cytokines and matrix metalloproteinases to cause degradation of the extracellular matrix, thereby contributing to the pathogenesis of AD. However, the cellular heterogeneity within these immune cells has not been fully characterized.Methods: We used single-cell RNA sequencing to profile the transcriptomes of all immune cells in AD tissue and normal aorta. Using magnetic-activated cell sorting gating on CD45, we obtained a higher resolution identification of the immune cell subsets in the aorta.Results: We observed significant differences in the proportion of major immune cell subpopulations between AD and normal aorta tissues. Macrophages accounted for a higher percentage in the normal aorta, while the proportions of T cells, B cells and natural killer (NK) cells were all increased in AD tissues. Macrophage clusters that expanded in AD tissues originated primarily from circulating monocytes and expressed genes encoding proinflammatory cytokines and molecules involved in tissue repair. T and NK cells in AD tissues exhibited enhanced cytotoxic properties. A cluster of CD4⁺ T cells that had expanded in AD tissues was Th17-like and might contribute to the pathogenesis of AD. Cell–cell interaction analysis highlighted the increased communication between macrophages and T cells, which primarily regulated the costimulation of T cells.Conclusions: Our study provides a comprehensive characterization of immune cells in the dissected aorta with an emphasis on the role of macrophages and T cells. The information from our study improves our understanding of immune mechanisms in AD formation and helps to identify additional useful targets for early diagnosis or therapy of AD.