Role of mechanical heterogeneity in cerebral aneurysm growth and rupture

脑动脉瘤(CA)是由于局部血管壁变薄和血管扩张而导致的脑血管外袋扩张。 适应不良的重塑。虽然破裂相对罕见，但破裂后存活率较低，原因是 血管痉挛和中风等并发症。由于大多数脑动脉瘤都是稳定的，因此有能力 预测破裂既可以进行早期干预，又可以避免不必要的手术治疗 动脉瘤。已经开发了许多计算模型，目的是基于以下因素来预测破裂 与临床可测量因素的相关性，如动脉瘤形状或血流动力学。但是，这些 模型还不够准确，无法在临床上使用。当前的一个主要缺点是 方法是，它不考虑破裂的复杂机制，而是试图从形状中跳跃 和/或流体动力学直接导致破裂风险。相反，我们将建立在对机械的理解基础上 异质性及其在组织生长、重塑和失败中的作用。通过将异质性融入到 关于CA的描述，我们将通知未来的模型，并使更准确的CA破裂风险评估。 我们假设脑动脉瘤在力学上是异质性的，并且这种异质性是可预测的。 动脉瘤破裂的可能性。我们进一步假设，物质的非均质性可以是 根据(I)动脉瘤中的血液流动引起的壁切应力场和(Ii)动脉瘤的几何形状确定 动脉瘤，这两种情况都可以在临床上确定。 我们提出了一系列新的实验和计算模型，旨在阐明组织的作用 脑动脉瘤生长、重塑和破裂的异质性。使用新切除的人体动脉瘤 组织，我们将测量局部组织尺度的力学性能、ECM结构和组成、细胞 组织，以及动脉瘤的破裂应力。接下来，我们将开发和使用计算模型来 阐明组织特性与动脉瘤破裂之间的生物物理机制。最后，我们将使用 动脉瘤内结构和血流力学的计算分析将它们联系起来 临床可测量的材料特性的临床不可测量的度量。这项研究的发现将 提供推进脑动脉瘤破裂预测模型所需的关键机制洞察。

Cerebral aneurysms (CAs) are out-pouching dilations of cerebral arteries caused by local wall weakening and maladaptive remodeling. Though rupture is relatively rare, the post-rupture survival rate is low, due to complications such as vasospasm and stroke. Since the majority of cerebral aneurysms are stable, the ability to predict rupture would both allow early intervention and eliminate unnecessary surgical procedures for stable aneurysms. Many computational models have been developed with the aim of predicting rupture based on correlation with clinically measurable factors, such as aneurysm shape or blood flow dynamics. But, these models are not yet accurate enough for them to have been used in the clinic. A major shortcoming of the current approach is that it does not consider the complex mechanics of rupture but instead tries to leap from shape and/or fluid dynamics directly to rupture risk. In contrast, we will build on our understanding of mechanical heterogeneity and its role in tissue growth, remodeling, and failure. By incorporating heterogeneity into the description of the CA, we will inform future models and enable more accurate assessment of CA rupture risk. We hypothesize that cerebral aneurysms are mechanically heterogeneous, and this heterogeneity is predictive of the rupture potential of the aneurysm. We further hypothesize that the material heterogeneity can be determined from (i) the wall shear stress field caused by blood flow in the aneurysm and (ii) the geometry of aneurysm, both of which can be determined in a clinical setting. We propose a series of novel experiments and computational models aimed at elucidating the role of tissue heterogeneity on cerebral aneurysm growth, remodeling, and rupture. Using freshly excised human aneurysm tissue, we will measure regional tissue-scale mechanical properties, ECM structure and composition, cell organization, and the rupture stress of the aneurysm. Next, we will develop and use computational models to elucidate the biophysical mechanisms that connect tissue properties to aneurysm rupture. Finally, we will use computational analyses of the architecture and blood flow mechanics within the aneurysm to connect these clinically-measurable metrics to clinically non-measurable material properties. The findings from this study will provide key mechanistic insights needed to advance cerebral aneurysm rupture prediction models.