Shear-driven modelling of thrombus formation in type B aortic dissection.
Shear-driven modelling of thrombus formation in type B aortic dissection.
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DOI：
10.3389/fbioe.2022.1033450
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发表时间：
2022
影响因子：
5.7
通讯作者：
Hochrainer T
中科院分区：
文献类型：
--
作者：
Jafarinia A;Armour CH;Gibbs RGJ;Xu XY;Hochrainer T
背景：B型主动脉夹层（TBAD）是一种危险的病理状态，死亡率高。TBAD由内膜撕裂引发，允许血液在主动脉壁层之间流动，导致它们分离。结果，在原始主动脉（真腔）旁边，形成假腔（FL）。TBAD损害整个心血管系统，在最坏的情况下导致主动脉完全破裂。临床研究表明，FL的扩张和破裂与FL未能形成血栓有关。已发现完全FL血栓形成可改善慢性TBAD患者的临床结局，并且是任何治疗的预期结局。部分FL血栓形成与晚期解剖相关死亡和需要再次介入相关，因此FL血栓形成水平在TBAD患者风险分类中占主导地位。因此，重要的是调查和了解在何种条件下发生FL完全血栓形成。 方法：局部FL血流动力学在血栓形成和生长中起重要作用。在这项研究中，我们开发了一个简化的现象学模型来预测生理流量条件下TBAD的FL血栓形成。基于现有的剪切驱动血栓模型，进行了全面的模型降阶研究，以提高计算效率。简化模型已在Ansys CFX中实现，并应用于胸主动脉腔内修复术（TEVAR）后的TBAD病例以测试模型。将1个月时基于TEVAR后几何形状的预测血栓形成与3年随访CT扫描观察到的实际血栓形成进行比较。 结果如下：在血栓位置和总体积方面，预测的FL状态与3年随访扫描非常一致，从而验证了新模型。新模型的计算成本显著低于以前的血栓模型，计算时间减少约65%。这种改进意味着新模型是迈向临床应用的重要一步。 结论：本研究中开发的血栓形成模型在基于患者特定数据预测FL血栓形成方面是准确和有效的，并且可以帮助临床医生在未来选择个性化治疗。
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.
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