Type B aortic dissection (TBAD) carries a high risk of complications, particularly with a partially thrombosed or patent false lumen (FL). Therefore, uncovering the risk factors leading to FL thrombosis is crucial to identify high-risk patients. Although studies have shown that morphological parameters of the dissected aorta are related to FL thrombosis, often conflicting results have been reported. We show that recent models of thrombus evolution in combination with sensitivity analysis methods can provide valuable insights into how combinations of morphological parameters affect the prospect of FL thrombosis. Based on clinical data, an idealized geometry of a TBAD is generated and parameterized. After implementing the thrombus model in computational fluid dynamics simulations, a global sensitivity analysis for selected morphological parameters is performed. We then introduce dimensionless morphological parameters to scale the results to individual patients. The sensitivity analysis demonstrates that the most sensitive parameters influencing FL thrombosis are the FL diameter and the size and location of intimal tears. A higher risk of partial thrombosis is observed when the FL diameter is larger than the true lumen diameter. Reducing the ratio of the distal to proximal tear size increases the risk of FL patency. In summary, these parameters play a dominant role in classifying morphologies into patent, partially thrombosed, and fully thrombosed FL. In this study, we point out the predictive role of morphological parameters for FL thrombosis in TBAD and show that the results are in good agreement with available clinical studies.

Background: Type B aortic dissection (TBAD) is a dangerous pathological condition with a high mortality rate. TBAD is initiated by an intimal tear that allows blood to flow between the aortic wall layers, causing them to separate. As a result, alongside the original aorta (true lumen), a false lumen (FL) develops. TBAD compromises the whole cardiovascular system, in the worst case resulting in complete aortic rupture. Clinical studies have shown that dilation and rupture of the FL are related to the failure of the FL to thrombose. Complete FL thrombosis has been found to improve the clinical outcomes of patients with chronic TBAD and is the desired outcome of any treatment. Partial FL thrombosis has been associated with late dissection-related deaths and the requirement for re-intervention, thus the level of FL thrombosis is dominant in classifying the risk of TBAD patients. Therefore, it is important to investigate and understand under which conditions complete thrombosis of the FL occurs.Method: Local FL hemodynamics play an essential role in thrombus formation and growth. In this study, we developed a simplified phenomenological model to predict FL thrombosis in TBAD under physiological flow conditions. Based on an existing shear-driven thrombosis model, a comprehensive model reduction study was performed to improve computational efficiency. The reduced model has been implemented in Ansys CFX and applied to a TBAD case following thoracic endovascular aortic repair (TEVAR) to test the model. Predicted thrombus formation based on post-TEVAR geometry at 1-month was compared to actual thrombus formation observed on a 3-year follow-up CT scan.Results: The predicted FL status is in excellent agreement with the 3-year follow-up scan, both in terms of thrombus location and total volume, thus validating the new model. The computational cost of the new model is significantly lower than the previous thrombus model, with an approximate 65% reduction in computational time. Such improvement means the new model is a significant step towards clinical applicability.Conclusion: The thrombosis model developed in this study is accurate and efficient at predicting FL thrombosis based on patient-specific data, and may assist clinicians in choosing individualized treatments in the future.

Volume 7, Issue 1 published for JBEB Journal.

Cardiovascular diseases are a leading global cause of mortality. The current standard diagnostic methods, such as imaging and invasive procedures, are relatively expensive and partly connected with risks to the patient. Bioimpedance measurements hold the promise to offer rapid, safe, and low-cost alternative diagnostic methods. In the realm of cardiovascular diseases, bioimpedance methods rely on the changing electrical conductivity of blood, which depends on the local hemodynamics. However, the exact dependence of blood conductivity on the hemodynamic parameters is not yet fully understood, and the existing models for this dependence are limited to rather academic flow fields in straight pipes or channels. In this work, we suggest two closely connected anisotropic electrical conductivity models for blood in general three-dimensional flows, which consider the orientation and alignment of red blood cells (RBCs) in shear flows. In shear flows, RBCs adopt preferred orientations through a rotation of their membrane known as tank-treading motion. The two models are built on two different assumptions as to which hemodynamic characteristic determines the preferred orientation. The models are evaluated in two example simulations of blood flow. In a straight rigid vessel, the models coincide and are in accordance with experimental observations. In a simplified aorta geometry, the models yield different results. These differences are analyzed quantitatively, but a validation of the models with experiments is yet outstanding.

Objectives: Early detection of cardiovascular diseases and their pre-existing conditions, arteriosclerosis and atherosclerosis, is crucial to increasing a patient’s chance of survival. While imaging technologies and invasive procedures provide a reliable diagnosis, they carry high costs and risks for patients. This study aims to explore impedance plethysmography (IPG) as a non-invasive and affordable alternative for diagnosis. Methods: To address the current lack of large-scale, high-quality impedance data, we introduce arterioscope.sim, a simulation platform that models arterial blood flow and computes the electrical conductivity of blood. The platform simulates bioimpedance measurements on specific body segments using patient-specific parameters. The study investigates how introducing arterial diseases into the simulation affects the bioimpedance signals. Results: The simulation results demonstrate that introducing atherosclerosis and arteriosclerosis leads to significant changes in the computed signals compared to simulations of healthy arteries. Furthermore, simulation of a patient-specific healthy artery strongly correlates with measured signals from a healthy volunteer. Conclusions and significance: arterioscope.sim effectively simulates bioimpedance signals in healthy and diseased arteries and highlights the potential of using these signals for early diagnosis of arterial diseases, offering a non-invasive and cost-effective alternative to traditional diagnostic methods.