Dynamic mechanical characterization and viscoelastic modeling of bovine brain tissue

Li, Weiqi; Shepherd, Duncan E.T.; Espino, Daniel M.

doi:10.1016/j.jmbbm.2020.104204

Cited by 19 publications

(15 citation statements)

References 76 publications

(110 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bovine brain tissue has also been examined under compression (Cheng & Bilston, 2007; Eskandari et al., 2021b; Li et al., 2021; Eskandari et al., 2021; Hosseini‐Farid, 2019; Pervin & Chen, 2009; Pervin & Chen, 2011; Shafiee et al., 2016; Shafieian et al., 2012; van Oosten et al., 2019), tension (Eskandari et al., 2021b; Eskandari et al., 2021a), shear (Bilston, Liu, & Phan‐Thien, 2001; Bilston, Liu, & Phan‐Thien, 1997; Darvish & Crandall, 2001; Li et al., 2021; Peters, Meulman, & Sauren, 1997; Takhounts et al., 2003; van Oosten et al., 2019), and indentation (Budday et al., 2015; Samadi‐Dooki et al., 2017; Weickenmeier et al., 2016; Weickenmeier et al., 2017). An early study found that human brain tissue is 40% stiffer than bovine brain tissue obtained from stress relaxation experiments (Takhounts et al., 2003).…”

Section: Challenges In Brain Tissue Testingmentioning

confidence: 99%

“…Regarding the diameter of cylindrical or ring-shaped samples, either intermediate (5 mm -9 mm) (Calhoun et al, 2019;Distler et al, 2020;Franceschini et al, 2006;Greiner et al, 2021;Haslach et al, 2014;Hrapko et al, 2006;Hrapko et al, 2008a;Li et al, 2015;Li et al, 2021;Li et al, 2019;Mihai et al, 2015;Mijailovic et al, 2021;Pogoda et al, 2014;Reiter et al, 2021;Zhao et al, 2016), relatively large (10 mm -19.05 mm) (Arbogast & Margulies, 1997;Arbogast & Margulies, 1998;Brands et al, 2000;Brands et al, 1999;Calhoun et al, 2019;Darvish & Crandall, 2001;Tamura et al, 2007;van Oosten et al, 2019;Vappou et al, 2007;Yue et al, 2017), or extremely large (50 mm) (Shen et al, 2006) samples have been prepared. For cubic and symmetric cruciform-shaped samples, one can differentiate between intermediate (5 mm -7 mm) (Budday et al, 2017a;Budday et al, 2017b;Budday et al, 2017c;Budday et al, 2020a;Felfelian et al, 2019;Labus & Puttlitz, 2016b;Labus & Puttlitz, 2016a;Zhang et al, 2016a;Zhang et al, 2016c;Zhang et al, 2018), relatively large (10 mm -19 mm) (Destrade et al, 2015;Falland-Cheung et al, 2018;…”

Section: Sample Preparationmentioning

confidence: 99%

See 1 more Smart Citation

Tissue‐Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

et al. 2022

View full text Add to dashboard Cite

Brain tissue is one of the most complex and softest tissues in the human body. Due to its ultrasoft and biphasic nature, it is difficult to control the deformation state during biomechanical testing and to quantify the highly nonlinear, time‐dependent tissue response. In numerous experimental studies that have investigated the mechanical properties of brain tissue over the last decades, stiffness values have varied significantly. One reason for the observed discrepancies is the lack of standardized testing protocols and corresponding data analyses. The tissue properties have been tested on different length and time scales depending on the testing technique, and the corresponding data have been analyzed based on simplifying assumptions. In this review, we highlight the advantage of using nonlinear continuum mechanics based modeling and finite element simulations to carefully design experimental setups and protocols as well as to comprehensively analyze the corresponding experimental data. We review testing techniques and protocols that have been used to calibrate material model parameters and discuss artifacts that might falsify the measured properties. The aim of this work is to provide standardized procedures to reliably quantify the mechanical properties of brain tissue and to more accurately calibrate appropriate constitutive models for computational simulations of brain development, injury and disease. Computational models can not only be used to predictively understand brain tissue behavior, but can also serve as valuable tools to assist diagnosis and treatment of diseases or to plan neurosurgical procedures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. This article was corrected on 16 April 2022. See the end of the full text for details.

show abstract

Section: Challenges In Brain Tissue Testingmentioning

confidence: 99%

Section: Sample Preparationmentioning

confidence: 99%

Tissue‐Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

et al. 2022

View full text Add to dashboard Cite

show abstract

“…A vibratome, on the other hand, can directly cut soft tissues thanks to its vibrating blade that applies oscillating shear cutting force to the sample. Because soft tissues are viscoelastic materials, their dynamic moduli increase as the vibrating blade exerts dynamic force on the material, leading the tissue to be “hardened” temporarily and locally by the vibration of the blade 25,26 . A vibratome is suitable for generating thicker slices (100 µm – several millimeters) and it requires much less tissue pretreatment.…”

Section: Resultsmentioning

confidence: 99%

Integrated platform for multi-scale molecular imaging and phenotyping of the human brain

Park

Wang

Guan

et al. 2022

Preprint

View full text Add to dashboard Cite

A detailed understanding of the anatomical and molecular architectures of brain cells and their brain-wide organization is essential for interrogating human brain function and dysfunction. Extensive efforts have been made toward mapping brain cells through various lenses, and have established invaluable databases yielding new insights. However, we still lack technologies that allow us to capture multi-scale multi-omic properties of individual brain cells in a holistic and scalable manner. To address this challenge, we developed a fully integrated technology platform for scalable three-dimensional (3D) mapping of human brain cells at subcellular resolution by simultaneously extracting brain-wide structure and high-dimensional features (e.g., spatial, molecular, morphological, and connectivity information) of individual cells from the same brain. We accomplished this by seamlessly integrating new chemical, mechanical, and computational tools to enable highly multiplexed multi-scale 3D proteomic imaging of human brain tissues with minimal information loss. We developed a novel microtome, termed MEGAtome, that enables ultra-precision slicing of a whole-mount intact human brain hemisphere and large arrays of animal organs with minimal loss of intra- and inter-slice information. To preserve structural and molecular information within intact human brain slabs and to enable highly multiplexed multiscale imaging, we developed a tissue-gel technology, termed mELAST, that transforms human brain tissues into an elastic, thermochemically stable, and reversibly expandable tissue-hydrogel. To reconstruct the intact brain to preserve the 3D connectivity information of neural fibers, we developed a semi-automatic tissue reconstruction computational pipeline termed HuBRIS. We demonstrated the utility and scalability of the technology platform by processing whole human brain hemispheres, investigating Alzheimer Disease (AD) pathology, and demonstrating the feasibility of projectome mapping.

show abstract

“…Eight whole bovine brains were obtained from animals under 12 months of age collected from a supplier (Samples for Schools, Portsmouth, UK), and all of the specimens were free from imperfections. 27 On arrival in the laboratory, the brains were stored at – 40 °C wrapped in tissue paper soaked in Ringer’ solution (Oxoid Ltd, Basingstoke, UK) following the standard procedure. 28 , 52 Prior to the mechanical tests, brain samples were thawed in Ringer’ solution for 12 h before dissection.…”

Section: Methodsmentioning

confidence: 99%

“…Based on the equivalent mathematical equations including integral and differential theory with shared linear viscoelastic material parameters, it should be possible to link between time dependent and frequency dependent viscoelastic properties. 47 Even though frequency dependent properties and corresponding viscoelastic models of brain tissue have been recently studied, 27 it remains unclear whether such data can be used in computational models to predict mechanical behavior under various loading conditions such as under time-dependent loading. In order to understand the mechanical properties of brain tissue under different testing impact conditions, the frequency-dependent and time-dependent relaxation behavior of brains were studied with the same physical conditions through compressive mechanical testing.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Compressive Viscoelastic Properties of Brain Tissue Under Time and Frequency Dependent Loading Conditions

Shepherd

Espino

2021

Ann Biomed Eng

Self Cite

View full text Add to dashboard Cite

The mechanical characterization of brain tissue has been generally analyzed in the frequency and time domain. It is crucial to understand the mechanics of the brain under realistic, dynamic conditions and convert it to enable mathematical modelling in a time domain. In this study, the compressive viscoelastic properties of brain tissue were investigated under time and frequency domains with the same physical conditions and the theory of viscoelasticity was applied to estimate the prediction of viscoelastic response in the time domain based on frequency-dependent mechanical moduli through Finite Element models. Storage and loss modulus were obtained from white and grey matter, of bovine brains, using dynamic mechanical analysis and time domain material functions were derived based on a Prony series representation. The material models were evaluated using brain testing data from stress relaxation and hysteresis in the time dependent analysis. The Finite Element models were able to represent the trend of viscoelastic characterization of brain tissue under both testing domains. The outcomes of this study contribute to a better understanding of brain tissue mechanical behaviour and demonstrate the feasibility of deriving time-domain viscoelastic parameters from frequency-dependent compressive data for biological tissue, as validated by comparing experimental tests with computational simulations.

show abstract

Dynamic mechanical characterization and viscoelastic modeling of bovine brain tissue

Cited by 19 publications

References 76 publications

Tissue‐Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

Tissue‐Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

Integrated platform for multi-scale molecular imaging and phenotyping of the human brain

Investigation of the Compressive Viscoelastic Properties of Brain Tissue Under Time and Frequency Dependent Loading Conditions

Contact Info

Product

Resources

About