A comprehensive experimental study on material properties of human brain tissue

Jin, Xin; Zhu, Feng; Mao, Haojie; Shen, Ming; Yang, King H.

doi:10.1016/j.jbiomech.2013.09.001

Cited by 188 publications

(171 citation statements)

References 20 publications

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“…This suggests the importance of the loading direction on the mechanical properties of brain tissue. It is also consistent with Karimi et al 7 and Jin et al 31 who demonstrated that brain tissue has an elastic modulus of 26.67 kPa in the longitudinal direction. Therefore, as there is no significant variance in the elastic modulus either in the longitudinal or circumferential directions at the linear part of the stress-strain diagram, the isotropic material model could be an acceptable assumption for material modeling.…”

Section: Resultssupporting

confidence: 91%

RETRACTED: Experimental and numerical study on the mechanical behavior of rat brain tissue

et al. 2014

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Brain tissue is a very soft tissue in which the mechanical properties depend on the loading direction. While few studies have characterized these biomechanical properties, it is worth knowing that accurate characterization of the mechanical properties of brain tissue at different loading directions is a key asset for neuronavigation and surgery simulation through haptic devices. In this study, the hyperelastic mechanical properties of rat brain tissue were measured experimentally and computationally. Prepared cylindrical samples were excised from the parietal lobes of rats' brains and experimentally tested by a tensile testing machine. The effects of loading direction on the mechanical properties of brain tissue were measured by applying load on both longitudinal and circumferential directions. The general prediction ability of the proposed hyperelastic model was verified using finite element (FE) simulations of brain tissue tension experiments. The uniaxial experimental results compared well with those predicted by the FE models. The results revealed the influence of loading direction on the mechanical properties of brain tissue. The Ogden hyperelastic material model was suitably represented by the non-linear behavior of the brain tissue, which can be used in future biomechanical simulations. The hyperelastic properties of brain tissue provided here have interest to the medical research community as there are several applications where accurate characterization of these properties are crucial for an accurate outcome, such as neurosurgery, robotic surgery, haptic device design or car manufacturing to evaluate possible trauma due to an impact.

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Section: Resultssupporting

confidence: 91%

RETRACTED: Experimental and numerical study on the mechanical behavior of rat brain tissue

et al. 2014

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“…Achieved on human cadavers, with an average age of 66 years after autopsy, these authors study the human brain elasticity and viscoelasticity in vitro in various location such as the corpus callosum, the corona radiata but not immediately below the cortex, that is in the sub-plate. For various loading conditions: tension, compression and shear, they conclude that the cortex always appears stiffer than the white matter, in opposition with other results [33]. Clearly the question of the comparison of the stiffness of both layers: the cortex and the white matter, so important for the modeling, is matter of debate.…”

Section: The Brain Convolutions the Gyrification Index And Associatementioning

confidence: 93%

“…Experimental results showed that the white matter is stiffer than the gray matter for adults and fetuses [64,33,5]. In Table 1, recent data measurements are reported for mammals, showing a noticeable dispersion on experimental values which are strongly dependent on the technique, the data analysis, the regional variation but also on the age of the brain and the strain intensity.…”

Section: The Brain Convolutions the Gyrification Index And Associatementioning

confidence: 96%

“…However, if one must be cautious about cerebellum and cerebrum data comparisons, it is important to recall that most of rodents do not have gyri. For human brain, this consensus is based on experimental biomechanical measurements [64,33,5] and on analytical works on wrinkling [64,55]. However, during the final revision of this work, an extensive experimental study concerning mechanical tests in static and dynamics [14] announces opposite conclusions concerning the stiffness of the cortex and of the white matter.…”

Section: The Brain Convolutions the Gyrification Index And Associatementioning

confidence: 99%

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Mimicking Cortex Convolutions Through the Wrinkling of Growing Soft Bilayers

Amar

Bordner

2017

J Elast

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Brain convolutions are a specificity of mammals. Varying in intensity according to the animal species, it is measured by an index called the gyrification index, ratio between the effective surface of the cortex compared to its apparent surface. Its value is close to 1 for rodents (smooth brain), 2.6 for newborns and 5 for dolphins. For humans, any significant deviation is a signature of a pathology occurring in fetal life, which can be detected now by magnetic resonance imaging (MRI). We propose a simple model of growth for a bilayer made of the grey and white matter, the grey matter being in cortical position. We analytically solved the neo-Hookean approximation in the short and large wavelength limits. When the upper layer is softer than the bottom layer, the selection mechanism is shown to be dominated by the physical properties of the upper layer. When the anisotropy favors the growth tangentially as for the human brain, it decreases the threshold value for gyri formation. The gyrification index is predicted by a post-buckling analysis and compared with experimental data. We also discuss some pathologies in the model framework.

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“…Brain tissue is generally considered anisotropic, but the significance of this anisotropy is still an open question. Some researchers have found considerable directional dependence of material properties [54], while others have found the opposite [55]. For the purpose of our study, we take brain tissue to be isotropic as it somewhat simplifies the constitutive model form and therefore reduces the number of model parameters that have to be estimated.…”

Section: (A) Experimental Datamentioning

confidence: 99%