Histomechanical Modeling of the Wall of Abdominal Aortic Aneurysm

  • T. Christian GasserEmail author


Vascular diseases are already the leading cause of death in the industrialized countries and many of the associated risk factors are increasing. A multi-disciplinary approach including biomechanics is needed to better understand and more effectively treat these diseases. Specifically, constitutive modeling is critical in understanding the biomechanics of the vascular wall and to uncover pathologies like Abdominal Aortic Aneurysms (AAAs), i.e. local dilatations of the infrarenal aorta. Aneurysms are formed through irreversible pathological remodeling of the vascular wall and integrating this biological process in the constitutive description could improve our current understanding of aneurysm disease. It might also increase the predictability of biomechanical simulations towards augmenting clinical decisions. The present chapter develops histomechanical constitutive models for the AAA wall according to Lanir’s pioneering approach. Consequently, macroscopic properties were derived through an integration of distributed fibers, where collagen was regarded as the most important protein of the aneurysmatic Extra Cellular Matrix (ECM). Collagen organization was quantified through Polarized Light Microscopy (PLM) of picrosirius red stained histological slices from tissue samples harvested during elective open AAA repair. This histological information was either directly integrated in the constitutive description or used to qualitatively validate the predicted remodeling of the AAA wall. Specifically, two descriptions for the AAA wall were used, where collagen was regarded either as a purely passive entity of the ECM or as an active entity. The suggested constitutive models were able to successfully capture salient features of the AAA wall, but a rigorous validation against detailed experimental data was beyond the scope of this chapter.


Collagen Fiber Abdominal Aortic Aneurysm Collagen Fibril Extra Cellular Matrix Polarize Light Microscopy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work has been financially supported by the Project Grant No. 2010-4446 provided by the Swedish Research Council, and the EC Seventh Framework Programme, Fighting Aneurysmal Disease (FAD-200647).


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Authors and Affiliations

  1. 1.Department of Solid MechanicsSchool of Engineering Sciences, KTH Royal Institute of TechnologyStockholmSweden

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