Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

中文翻译：

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主动脉夹层的机制：从病理变化到实验和计算机模型


主动脉夹层仍然是导致显着发病率和死亡率的原因，尽管最近医学数据同化以及实验和计算机模型的进展提高了我们对主动脉壁内血液积聚开始和进展的理解。因此，仍然迫切需要创新和增强的模型来更准确地描述相关的病理变化。早期，采用实验模型来揭示主动脉夹层的机制，例如血流动力学变化和壁微观结构的改变，并评估医疗植入物的疗效。虽然实验模型曾经是唯一可用的选项，但最近它们也被用于在计算机模型中进行验证。基于对主动脉壁恶化微观结构的更好理解，近几十年来提出了许多多尺度材料模型来研究夹层主动脉中的应力状态，包括与损伤和失效相关的变化。此外，当与可访问的患者来源的医学数据相结合时，计算机模拟模型被证明是识别血流动力学、室壁应力或恶化的主动脉壁血栓形成之间相关性的宝贵工具。它们还有利于医疗植入物的模型引导设计，目的是评估植入物在患者体内的部署和迁移。尽管如此，计算机模型的实用性在很大程度上取决于患者衍生的医学数据，例如选择的边界条件或组织特性。在这篇综述文章中，我们的目标是提供医学数据的全面总结，阐明与该疾病相关的病理改变。 同时，我们的目标是评估实验模型，以及以计算机模型为依据的多尺度材料和患者数据，以研究主动脉夹层的各个方面。总之，我们提出了关于未来前景的论述，包括疾病建模、数值挑战和临床应用的各个方面，特别关注主动脉夹层。我们的目标是激发未来的研究，加深我们对疾病的理解，并最终影响临床护理和治疗决策。