Abstract
Brain tissue is not only one of the most important but also the most complex and compliant tissue in the human body. While long underestimated, increasing evidence confirms that mechanics plays a critical role in modulating brain function and dysfunction. Computational simulations–based on the field equations of nonlinear continuum mechanics–can provide important insights into the underlying mechanisms of brain injury and disease that go beyond the possibilities of traditional diagnostic tools. Realistic numerical predictions, however, require mechanical models that are capable of capturing the complex and unique characteristics of this ultrasoft, heterogeneous, and active tissue. In recent years, contradictory experimental results have caused confusion and hindered rapid progress. In this review, we carefully assess the challenges associated with brain tissue testing and modeling, and work out the most important characteristics of brain tissue behavior on different length and time scales. Depending on the application of interest, we propose appropriate mechanical modeling approaches that are as complex as necessary but as simple as possible. This comprehensive review will, on the one hand, stimulate the design of new experiments and, on the other hand, guide the selection of appropriate constitutive models for specific applications. Mechanical models that capture the complex behavior of nervous tissues and are accurately calibrated with reliable and comprehensive experimental data are key to performing reliable predictive simulations. Ultimately, mathematical modeling and computational simulations of the brain are useful for both biomedical and clinical communities, and cover a wide range of applications ranging from predicting disease progression and estimating injury risk to planning surgical procedures.
Highlights
Brain tissue is one of the most complex tissues in the human body
Due to controversies regarding previous results in the literature, where some suggested that brain tissue was isotropic [22, 22, 91, 120, 137], but others showed that there were significant directional trends [52, 53, 85, 134, 165], we combined biomechanical testing of the same specimen in three orthogonal loading directions with antecedent diffusion tensor imaging to carefully analyze to which extent the fibrous microstructure of axonal networks in white matter results in an anisotropic macroscopic mechanical response [22]
We have proposed a finite viscoelastic model that combines the hyperelastic Ogden model with two viscoelastic elements and can, in addition to the experimentally observed compression-tension asymmetry and nonlinearity, capture timedependent effects including hysteresis according to Sect. 3.3, and the successive softening for stepwise loading according to Sect. 3.5
Summary
Brain tissue is one of the most complex tissues in the human body. Neurological disorders, including stroke, encephalitis, dementias, and epilepsy, have been identified as one of the major public health concerns by the world health organization. Computational modeling and personalized simulations can provide fundamental insights into the underlying mechanisms during injury and disease. Such predictive models reduce the necessity of experiments on humans and animals, and allow for the development of novel treatment strategies or the detailed planning of surgical procedures [171]. While great efforts have been made to mechanically model the behavior of brain tissue in health and disease [68], contradictory experimental results have constantly hindered progress [29] and caused confusion and delay [7]. After addressing the challenges associated with brain tissue testing and modeling, we review experimental observations based on different testing techniques to work out the diverse characteristics of brain tissue behavior under different loading conditions in Sect.
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