Location of Reentry Tears Affects False Lumen Thrombosis in Aortic Dissection Following TEVAR.

Purpose: To report a study that assesses the influence of the distance between the distal end of a thoracic stent-graft and the first reentry tear (SG-FRT) on the progression of false lumen (FL) thrombosis in patients who underwent thoracic endovascular aortic repair (TEVAR). Materials and Methods: Three patient-specific geometrical models were reconstructed from postoperative computed tomography scans. Two additional models were created by artificially changing the SG-FRT distance in patients 1 and 2. In all 5 models, computational fluid dynamics simulations coupled with thrombus formation modeling were performed at physiological flow conditions. Predicted FL thrombosis was compared to follow-up scans. Results: There was reduced false lumen flow and low time-averaged wall shear stress (TAWSS) in patients with large SG-FRT distances. Predicted thrombus formation and growth were consistent with follow-up scans for all patients. Reducing the SG-FRT distance by 30 mm in patient 1 increased the flow and time-averaged wall shear stress in the upper abdominal FL, reducing the thrombus volume by 9.6%. Increasing the SG-FRT distance in patient 2 resulted in faster thoracic thrombosis and increased total thrombus volume. Conclusion: The location of reentry tears can influence the progression of FL thrombosis following TEVAR. The more distal the reentry tear in the aorta the more likely it is that FL thrombosis will occur. Hence, the distal landing zone of the stent-graft should be chosen carefully to ensure a sufficient SG-FRT distance.

Dissection Level Within Aortic Wall Layers is Associated with Propagation of Type B Aortic Dissection: A Swine Model Study.

OBJECTIVE: Haemodynamic and geometric factors play pivotal roles in the propagation of acute type B aortic dissection (TBAD). The aim of this study was to evaluate the association between dissection level within all aortic layers and the propagation of acute TBAD in porcine aorta. METHODS: In twelve pigs, two models of TBAD were created. In model A (n = 6), the aortic wall tear was superficial and close to the intima (thin intimal flap), whereas in model B (n = 6) it was deep and close to the adventitia (thick intimal flap). Dissection propagation was evaluated using angiography or computed tomography scans, and the haemodynamic measurements were acquired using Doppler wires. Most pigs were followed up at 1, 3, 6, 12, 18, and up to 24 months; four animals were euthanised at three and six months, respectively (two from each group). RESULTS: Both models were successfully created. No statistical difference was observed for the median antegrade propagation distance intra-operatively between the two models (p = .092). At 24 months, the longitudinal propagation distance was significantly greater in model B than in model A (p = .016). No statistical difference in retrograde propagation was noted (p = .691). Over time, aortic wall dissection progressed most notably over the first three months in model A, whereas it continued over the first 12 months in model B. Flow velocity was significantly greater in the true lumen than in false lumen at the level of the primary tear (p = .001) and in the middle of the dissection (p = .004). The histopathological images at three and six months demonstrated the fibres were stretched linearly at the outside wall of false lumen in both models, while the depth of intimal tears developed to be superficial and similar at the distal dissection. CONCLUSION: In this swine model of TBAD, a deeper intimal tear resulted in greater dissection propagation.

High Wall Stress May Predict the Formation of Stent-Graft-Induced New Entries After Thoracic Endovascular Aortic Repair.

PURPOSE: To explore the potential role of morphological factors and wall stress in the formation of stent-graft-induced new entries (SINE) based on computed tomography (CT) images after thoracic endovascular aortic repair (TEVAR). CASE REPORT: Two female patients aged 59 years (patient 1) and 44 years (patient 2) underwent TEVAR for type B dissection in the chronic (patient 1) or subacute (patient 2) phase. CT scans at 3-month follow-up showed varying degrees of false lumen thrombosis in both patients. At 14-month follow-up, a SINE was observed in patient 1 while the dissected aorta in the other patient remained stable. Morphological and finite element analyses were performed based on the first follow-up CT images. The computational results showed that the SINE patient had higher stent-graft tortuosity than the non-SINE patient and much higher wall stress in the region close to the distal SINE. CONCLUSION: This case study suggests that high stent-graft tortuosity can lead to high wall stress, which is potentially linked to the formation of SINE. Further large population-based studies are needed to confirm this preliminary finding.

Mathematical modeling of thrombus formation in idealized models of aortic dissection: initial findings and potential applications.

Aortic dissection is a major aortic catastrophe with a high morbidity and mortality risk caused by the formation of a tear in the aortic wall. The development of a second blood filled region defined as the "false lumen" causes highly disturbed flow patterns and creates local hemodynamic conditions likely to promote the formation of thrombus in the false lumen. Previous research has shown that patient prognosis is influenced by the level of thrombosis in the false lumen, with false lumen patency and partial thrombosis being associated with late complications and complete thrombosis of the false lumen having beneficial effects on patient outcomes. In this paper, a new hemodynamics-based model is proposed to predict the formation of thrombus in Type B dissection. Shear rates, fluid residence time, and platelet distribution are employed to evaluate the likelihood for thrombosis and to simulate the growth of thrombus and its effects on blood flow over time. The model is applied to different idealized aortic dissections to investigate the effect of geometric features on thrombus formation. Our results are in qualitative agreement with in-vivo observations, and show the potential applicability of such a modeling approach to predict the progression of aortic dissection in anatomically realistic geometries.

Computational modeling of low-density lipoprotein accumulation at the carotid artery bifurcation after stenting.

Restenosis typically occurs in regions of low and oscillating wall shear stress, which also favor the accumulation of atherogenic macromolecules such as low-density lipoprotein (LDL). This study aims to evaluate LDL transport and accumulation at the carotid artery bifurcation following carotid artery stenting (CAS) by means of computational simulation. The computational model consists of coupled blood flow and LDL transport, with the latter being modeled as a dilute substance dissolved in the blood and transported by the flow through a convection-diffusion transport equation. The endothelial layer was assumed to be permeable to LDL, and the hydraulic conductivity of LDL was shear-dependent. Anatomically realistic geometric models of the carotid bifurcation were built based on pre- and post-stent computed tomography (CT) scans. The influence of stent design was investigated by virtually deploying two different types of stents (open- and closed-cell stents) into the same carotid bifurcation model. Predicted LDL concentrations were compared between the post-stent carotid models and the relatively normal contralateral model reconstructed from patient-specific CT images. Our results show elevated LDL concentration in the distal section of the stent in all post-stent models, where LDL concentration is 20 times higher than that in the contralateral carotid. Compared with the open-cell stents, the closed-cell stents have larger areas exposed to high LDL concentration, suggesting an increased risk of stent restenosis. This computational approach is readily applicable to multiple patient studies and, once fully validated against follow-up data, it can help elucidate the role of stent strut design in the development of in-stent restenosis after CAS.

Qualitative and Quantitative Assessments of Blood Flow on Tears in Type B Aortic Dissection With Different Morphologies.

Objective: The interactions between aortic morphology and hemodynamics play a key role in determining type B aortic dissection (TBAD) progression and remodeling. The study aimed to provide qualitative and quantitative hemodynamic assessment in four different TBAD morphologies based on 4D flow MRI analysis. Materials and Methods: Four patients with different TBAD morphologies underwent CT and 4D flow MRI scans. Qualitative blood flow evaluation was performed by visualizing velocity streamlines and flow directionality near the tears. Quantitative analysis included flow rate, velocity and reverse flow index (RFI) measurements. Statistical analysis was performed to evaluate hemodynamic differences between the true lumen (TL) and false lumen (FL) of patients. Results: Qualitative analysis revealed blood flow splitting near the primary entry tears (PETs), often causing the formation of vortices in the FL. All patients exhibited clear hemodynamic differences between TL and FL, with the TL generally showing higher velocities and flow rates, and lower RFIs. Average velocity magnitude measurements were significantly different for Patient 1 (t = 5.61, p = 0.001), Patient 2 (t = 3.09, p = 0.02) and Patient 4 (t = 2.81, p = 0.03). At follow-up, Patient three suffered from left renal ischemia because of FL collapse. This patient presented a complex morphology with two FLs and marked flow differences between TL and FLs. In Patient 4, left renal artery malperfusion was observed at the 32-months follow-up, due to FL thrombosis growing after PET repair. Conclusion: The study demonstrates the clinical feasibility of using 4D flow MRI in the context of TBAD. Detailed patient-specific hemodynamics assessment before treatment may provide useful insights to better understand this pathology in the future.

4-D Flow MRI-Based Computational Analysis of Blood Flow in Patient-Specific Aortic Dissection.

OBJECTIVE: 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. METHODS: 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. RESULTS AND CONCLUSION: 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.

A computational model for false lumen thrombosis in type B aortic dissection following thoracic endovascular repair.

Thoracic endovascular repair (TEVAR) has recently been established as the preferred treatment option for complicated type B dissection. This procedure involves covering the primary entry tear to stimulate aortic remodelling and promote false lumen thrombosis thereby restoring true lumen flow. However, complications associated with incomplete false lumen thrombosis, such as aortic dilatation and stent graft induced new entry tears, can arise after TEVAR. This study presents the application and validation of a recently developed mathematical model for patient-specific prediction of thrombus formation and growth under physiologically realistic flow conditions. The model predicts thrombosis through the evaluation of shear rates, fluid residence time and platelet distribution, based on convection-diffusion-reaction transport equations. The model was applied to 3 type B aortic dissection patients: two TEVAR cases showing complete and incomplete false lumen thrombosis respectively, and one medically treated dissection with no signs of thrombosis. Predicted thrombus growth over time was validated against follow-up CT scans, showing good agreement with in vivo data in all cases with a maximum difference between predicted and measured false lumen reduction below 8%. Our results demonstrate that TEVAR-induced thrombus formation in type B aortic dissection can be predicted based on patient-specific anatomy and physiologically realistic boundary conditions. Our model can be used to identify anatomical or stent graft related factors that are associated with incomplete false lumen thrombosis following TEVAR, which may help clinicians develop personalised treatment plans for dissection patients in the future.

Predicting false lumen thrombosis in patient-specific models of aortic dissection.

Aortic dissection causes splitting of the aortic wall layers, allowing blood to enter a 'false lumen' (FL). For type B dissection, a significant predictor of patient outcomes is patency or thrombosis of the FL. Yet, no methods are currently available to assess the chances of FL thrombosis. In this study, we present a new computational model that is capable of predicting thrombus formation, growth and its effects on blood flow under physiological conditions. Predictions of thrombus formation and growth are based on fluid shear rate, residence time and platelet distribution, which are evaluated through convection-diffusion-reaction transport equations. The model is applied to a patient-specific type B dissection for which multiple follow-up scans are available. The predicted thrombus formation and growth patterns are in good qualitative agreement with clinical data, demonstrating the potential applicability of the model in predicting FL thrombosis for individual patients. Our results show that the extent and location of thrombosis are strongly influenced by aortic dissection geometry that may change over time. The high computational efficiency of our model makes it feasible for clinical applications. By predicting which aortic dissection patient is more likely to develop FL thrombosis, the model has great potential to be used as part of a clinical decision-making tool to assess the need for early endovascular intervention for individual dissection patients.