Role of mechanical heterogeneity in cerebral aneurysm growth and rupture

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.

Grant Number: 5R01NS126762-04
NIH Institute/Center: NIH
Principal Investigator: PATRICK ALFORD