Role of mechanical heterogeneity in cerebral aneurysm growth and rupture

脑动脉瘤（CA）是由局部壁弱化引起的脑动脉外囊扩张， 适应不良性重塑虽然破裂是相对罕见的，但破裂后的存活率很低，因为 血管痉挛和中风等并发症。由于大多数脑动脉瘤是稳定的， 预测破裂既允许早期干预，又可以消除不必要的外科手术， 动脉瘤已经开发了许多计算模型，其目的是基于 与临床可测量因素的相关性，例如动脉瘤形状或血流动力学。但是这些 模型还不够精确，不能用于临床。目前的一个主要缺点是， 方法是它不考虑复杂的断裂力学，而是试图从形状飞跃 和/或流体动力学直接影响破裂风险。相反，我们将建立在我们对机械的理解上， 异质性及其在组织生长、重塑和衰竭中的作用。通过将异质性纳入 通过对CA的描述，我们将为未来的模型提供信息，并能够更准确地评估CA破裂风险。 我们假设脑动脉瘤是机械异质性的，这种异质性是预测性的， 动脉瘤破裂的可能性我们进一步假设，材料的异质性可以是 由（i）动脉瘤中血流引起的壁剪切应力场和（ii）动脉瘤的几何形状确定 动脉瘤，两者都可以在临床环境中确定。 我们提出了一系列新颖的实验和计算模型，旨在阐明组织的作用 脑动脉瘤生长、重塑和破裂的异质性。使用新鲜切除的人类动脉瘤 组织，我们将测量区域组织规模的机械性能，ECM结构和组成，细胞 组织和动脉瘤的破裂应力。接下来，我们将开发和使用计算模型， 阐明将组织特性与动脉瘤破裂联系起来的生物物理机制。最后，我们将使用 动脉瘤内的结构和血流力学的计算分析，以连接这些 从临床可测量的指标到临床不可测量的材料特性。这项研究的结果将 提供推进脑动脉瘤破裂预测模型所需的关键机制见解。

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.