New experimental results on collagen fibre dispersion in human arterial layers have shown that the dispersion in the tangential plane is more significant than that out of plane. A rotationally symmetric dispersion model is not able to capture this distinction. For this reason, we introduce a new non-symmetric dispersion model, based on the bivariate von Mises distribution, which is used to construct a new structure tensor. The latter is incorporated in a strain-energy function that accommodates both the mechanical and structural features of the material, extending our rotationally symmetric dispersion model (Gasser et al. 2006 J. R. Soc. Interface 3 , 15–35. ( doi:10.1098/rsif.2005.0073 )). We provide specific ranges for the dispersion parameters and show how previous models can be deduced as special cases. We also provide explicit expressions for the stress and elasticity tensors in the Lagrangian description that are needed for a finite-element implementation. Material and structural parameters were obtained by fitting predictions of the model to experimental data obtained from human abdominal aortic adventitia. In a finite-element example, we analyse the influence of the fibre dispersion on the homogeneous biaxial mechanical response of aortic strips, and in a final example the non-homogeneous stress distribution is obtained for circumferential and axial strips under fixed extension. It has recently become apparent that this more general model is needed for describing the mechanical behaviour of a variety of fibrous tissues.

Soft biological tissues such as aortic walls can be viewed as fibrous composites assembled by a ground matrix and embedded families of collagen fibres. Changes in the structural components of aortic walls such as the ground matrix and the embedded families of collagen fibres have been shown to play a significant role in the pathogenesis of aortic degeneration. Hence, there is a need to develop a deeper understanding of the microstructure and the related mechanics of aortic walls. In this study, tissue samples from 17 human abdominal aortas (AA) and from 11 abdominal aortic aneurysms (AAA) are systematically analysed and compared with respect to their structural and mechanical differences. The collagen microstructure is examined by analysing data from second-harmonic generation imaging after optical clearing. Samples from the intact AA wall, their individual layers and the AAA wall are mechanically investigated using biaxial stretching tests. A bivariate von Mises distribution was used to represent the continuous fibre dispersion throughout the entire thickness, and to provide two independent dispersion parameters to be used in a recently proposed material model. Remarkable differences were found between healthy and diseased tissues. The out-of-plane dispersion was significantly higher in AAA when compared with AA tissues, and with the exception of one AAA sample, the characteristic wall structure, as visible in healthy AAs with three distinct layers, could not be identified in AAA samples. The collagen fibres in the abluminal layer of AAAs lost their waviness and exhibited rather straight and thick struts of collagen. A novel set of three structural and three material parameters is provided. With the structural parameters fixed, the material model was fitted to the mechanical experimental data, giving a very satisfying fit although there are only three material parameters involved. The results highlight the need to incorporate the structural differences into finite-element simulations as otherwise simulations of AAA tissues might not be good predictors for the actualin vivostress state.

Acute and chronic tendinopathies remain clinically challenging and tendons are predisposed to degeneration or injury with age. Despite the high prevalence of tendon disease in the elderly, our current understanding of the mechanisms underlying the age-dependent deterioration of tendon function remains very limited. Here, we show that Secreted protein acidic and rich in cysteine (Sparc) expression significantly decreases in healthy-aged mouse Achilles tendons. Loss of Sparc results in tendon collagen fibrillogenesis defects and Sparc−/− tendons are less able to withstand force in comparison with their respective wild type counterparts. On the cellular level, Sparc-null and healthy-aged tendon-derived cells exhibited a more contracted phenotype and an altered actin cytoskeleton. Additionally, an elevated expression of the adipogenic marker genes PPARγ and Cebpα with a concomitant increase in lipid deposits in aged and Sparc−/− tendons was observed. In summary, we propose that Sparc levels in tendons are critical for proper collagen fibril maturation and its age-related decrease, together with a change in ECM properties favors lipid accretion in tendons.

Collagen plays a key role in the strength of aortic walls, so studying micro-structural changes during disease development is critical to better understand collagen reorganization. Second-harmonic generation microscopy is used to obtain images of human aortic collagen in both healthy and diseased states. Methods are being developed in order to efficiently determine the waviness, that is, tortuosity and amplitude, as well as the diameter, orientation, and dispersion of collagen fibers, and bundles in healthy and aneurysmal tissues. The results show layer-specific differences in the collagen of healthy tissues, which decrease in samples of aneurysmal aortic walls. In healthy tissues, the thick collagen bundles of the adventitia are characterized by greater waviness, both in the tortuosity and in the amplitude, compared to the relatively thin and straighter collagen fibers of the media. In contrast, most aneurysmal tissues tend to have a more uniform structure of the aortic wall with no significant difference in collagen diameter between the luminal and abluminal layers. An increase in collagen tortuosity compared to the healthy media is also observed in the aneurysmal luminal layer. The data set provided can help improve related material and multiscale models of aortic walls and aneurysm formation.

Cardiac growth and remodeling (G&R) refers to structural changes in myocardial tissue in response to chronic alterations in loading conditions. One such condition is pressure overload where elevated wall stresses stimulate the growth in cardiomyocyte thickness, associated with a phenotype of concentric hypertrophy at the organ scale, and promote fibrosis. The initial hypertrophic response can be considered adaptive and beneficial by favoring myocyte survival, but over time if pressure overload conditions persist, maladaptive mechanisms favoring cell death and fibrosis start to dominate, ultimately mediating the transition towards an overt heart failure phenotype. The underlying mechanisms linking biological factors at the myocyte level to biomechanical factors at the systemic and organ level remain poorly understood. Computational models of G&R show high promise as a unique framework for providing a quantitative link between myocardial stresses and strains at the organ scale to biological regulatory processes at the cellular level which govern the hypertrophic response. However, microstructurally motivated, rigorously validated computational models of G&R are still in their infancy. This article provides an overview of the current state-of-the-art of computational models to study cardiac G&R. The microstructure and mechanosensing/mechanotransduction within cells of the myocardium is discussed and quantitative data from previous experimental and clinical studies is summarized. We conclude with a discussion of major challenges and possible directions of future research that can advance the current state of cardiac G&R computational modeling. STATEMENT OF SIGNIFICANCE: The mechanistic links between organ-scale biomechanics and biological factors at the cellular size scale remain poorly understood as these are largely elusive to investigations using experimental methodology alone. Computational G&R models show high promise to establish quantitative links which allow more mechanistic insight into adaptation mechanisms and may be used as a tool for stratifying the state and predict the progression of disease in the clinic. This review provides a comprehensive overview of research in this domain including a summary of experimental data. Thus, this study may serve as a basis for the further development of more advanced G&R models which are suitable for making clinical predictions on disease progression or for testing hypotheses on pathogenic mechanisms using in-silico models.