Mechanical properties of the spinal cord and brain: Comparison with clinical-grade biomaterials for tissue engineering and regenerative medicine

Bartlett, Richard D.; Eleftheriadou, Despoina; Evans, RA; Choi, David; Phillips, James B.

doi:10.1016/j.biomaterials.2020.120303

Cited by 50 publications

(35 citation statements)

References 57 publications

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“…6 Comparisons between the frequency response corresponding to the 1st-, 2nd-, and 3rd-order Prony series. G 1 is the storage modulus, G 2 is the loss modulus, |G * | is the amplitude of G * (iw) , and is the phase angle Our results are consistent with the dynamic compressive mechanical test, where the frequency response was observable only in a frequency range larger than 30 Hz [45]. This also implies that the dynamic response of viscoelastic materials can be predicted using a ramp-hold indentation test.…”

Section: Phantom Testsupporting

confidence: 84%

Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties

Chen

Qiu

et al. 2021

Acta Mech. Sin.

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Measurement the viscoelastic properties is important for studying the developmental and pathological behavior of soft biological tissues. Magnetic resonance elastography (MRE) is a non-invasive method for in vivo measurement of tissue viscoelasticity. As a flexible method capable of testing small samples, indentation has been widely used for characterizing soft tissues. Using 2nd-order Prony series and dimensional analysis, we analyzed and compared the model parameters estimated from both indentation and MRE. Conversions of the model parameters estimated from the two methods were established. We found that the indention test is better at capturing the dynamic response of tissues at a frequency less than 10 Hz, while MRE is better for describing the frequency responses at a relatively higher range. The results provided helpful information for testing soft tissues using indentation and MRE. The models analyzed are also helpful for quantifying the frequency response of viscoelastic tissues. Graphic Abstract

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Section: Phantom Testsupporting

confidence: 84%

Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties

Chen

Qiu

et al. 2021

Acta Mech. Sin.

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“…This approach has been previously used to test many biological and synthetical materials. 2 , 4 , 23 The brain specimens were placed in the sample container; force and displacement values were adjusted to be a zero. Prior to the data collection procedure, an upper flat indenter was lowered onto the specimen until a preload of 10 mN was observed using the WinTest DMA software (Bose Corporation, ElectroForce Systems Group, Minnesota, USA).…”

Section: Methodsmentioning

confidence: 99%

“…Dynamic mechanical analysis (DMA) has been considered as an effective technique for measuring the bulk mechanical properties of viscoelastic materials. 4 This method is flexible and powerful to map frequency-dependent viscoelastic properties of biological tissue over a range of frequencies covering physiological and injury loading conditions. The storage modulus in viscoelastic materials characterizes the ability of the material to store energy in the elastic phase and the loss modulus characterizes the ability of the material to dissipate energy, for instance as heat, in the viscous phase.…”

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

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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.

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“…Structural and compositional heterogeneity, alongside hierarchical patterning, is responsible for guiding cellular processes and dynamic non-linear mechanical behaviour of living tissue [32,65]. Hydrogels are an ideal biomaterial for CNS modelling due to their high water content and porous structure enabling diffusion of metabolites, with the solid-phase polymer network providing relevant mechanical and spatial cues, tuneable mechanics and versatile chemical modification [17,34,[65][66][67].…”

Section: Biomaterialsmentioning

confidence: 99%

“…The concept of mechanical control of cell behaviour becomes increasingly relevant when we observe abnormal mechanical features (i.e. increased stiffness) in neurodevelopmental disorders, neurodegenerative disease and CNS injury [ 28 , 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Modelling the central nervous system: tissue engineering of the cellular microenvironment

Walczak

Esteban

Bassett

et al. 2021

Emerging Topics in Life Sciences

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With the increasing prevalence of neurodegenerative diseases, improved models of the central nervous system (CNS) will improve our understanding of neurophysiology and pathogenesis, whilst enabling exploration of novel therapeutics. Studies of brain physiology have largely been carried out using in vivo models, ex vivo brain slices or primary cell culture from rodents. Whilst these models have provided great insight into complex interactions between brain cell types, key differences remain between human and rodent brains, such as degree of cortical complexity. Unfortunately, comparative models of human brain tissue are lacking. The development of induced Pluripotent Stem Cells (iPSCs) has accelerated advancement within the field of in vitro tissue modelling. However, despite generating accurate cellular representations of cortical development and disease, two-dimensional (2D) iPSC-derived cultures lack an entire dimension of environmental information on structure, migration, polarity, neuronal circuitry and spatiotemporal organisation of cells. As such, researchers look to tissue engineering in order to develop advanced biomaterials and culture systems capable of providing necessary cues for guiding cell fates, to construct in vitro model systems with increased biological relevance. This review highlights experimental methods for engineering of in vitro culture systems to recapitulate the complexity of the CNS with consideration given to previously unexploited biophysical cues within the cellular microenvironment.

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Mechanical properties of the spinal cord and brain: Comparison with clinical-grade biomaterials for tissue engineering and regenerative medicine

Cited by 50 publications

References 57 publications

Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties

Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties

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

Modelling the central nervous system: tissue engineering of the cellular microenvironment

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