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In vivo measurement of human brain material properties under quasi-static loading

Computational modelling of the brain requires accurate representation of the tissues concerned. Mechanical testing has numerous challenges, in particular for low strain rates, like neurosurgery, where redistribution of fluid is biomechanically important. A finite-element (FE) model was generated in...

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Autores principales: Bennion, Nicholas J., Zappalá, Stefano, Potts, Matthew, Woolley, Max, Marshall, David, Evans, Sam L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748497/
https://www.ncbi.nlm.nih.gov/pubmed/36514891
http://dx.doi.org/10.1098/rsif.2022.0557
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author Bennion, Nicholas J.
Zappalá, Stefano
Potts, Matthew
Woolley, Max
Marshall, David
Evans, Sam L.
author_facet Bennion, Nicholas J.
Zappalá, Stefano
Potts, Matthew
Woolley, Max
Marshall, David
Evans, Sam L.
author_sort Bennion, Nicholas J.
collection PubMed
description Computational modelling of the brain requires accurate representation of the tissues concerned. Mechanical testing has numerous challenges, in particular for low strain rates, like neurosurgery, where redistribution of fluid is biomechanically important. A finite-element (FE) model was generated in FEBio, incorporating a spring element/fluid–structure interaction representation of the pia–arachnoid complex (PAC). The model was loaded to represent gravity in prone and supine positions. Material parameter identification and sensitivity analysis were performed using statistical software, comparing the FE results to human in vivo measurements. Results for the brain Ogden parameters µ, α and k yielded values of 670 Pa, −19 and 148 kPa, supporting values reported in the literature. Values of the order of 1.2 MPa and 7.7 kPa were obtained for stiffness of the pia mater and out-of-plane tensile stiffness of the PAC, respectively. Positional brain shift was found to be non-rigid and largely driven by redistribution of fluid within the tissue. To the best of our knowledge, this is the first study using in vivo human data and gravitational loading in order to estimate the material properties of intracranial tissues. This model could now be applied to reduce the impact of positional brain shift in stereotactic neurosurgery.
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spelling pubmed-97484972022-12-15 In vivo measurement of human brain material properties under quasi-static loading Bennion, Nicholas J. Zappalá, Stefano Potts, Matthew Woolley, Max Marshall, David Evans, Sam L. J R Soc Interface Life Sciences–Engineering interface Computational modelling of the brain requires accurate representation of the tissues concerned. Mechanical testing has numerous challenges, in particular for low strain rates, like neurosurgery, where redistribution of fluid is biomechanically important. A finite-element (FE) model was generated in FEBio, incorporating a spring element/fluid–structure interaction representation of the pia–arachnoid complex (PAC). The model was loaded to represent gravity in prone and supine positions. Material parameter identification and sensitivity analysis were performed using statistical software, comparing the FE results to human in vivo measurements. Results for the brain Ogden parameters µ, α and k yielded values of 670 Pa, −19 and 148 kPa, supporting values reported in the literature. Values of the order of 1.2 MPa and 7.7 kPa were obtained for stiffness of the pia mater and out-of-plane tensile stiffness of the PAC, respectively. Positional brain shift was found to be non-rigid and largely driven by redistribution of fluid within the tissue. To the best of our knowledge, this is the first study using in vivo human data and gravitational loading in order to estimate the material properties of intracranial tissues. This model could now be applied to reduce the impact of positional brain shift in stereotactic neurosurgery. The Royal Society 2022-12-14 /pmc/articles/PMC9748497/ /pubmed/36514891 http://dx.doi.org/10.1098/rsif.2022.0557 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Engineering interface
Bennion, Nicholas J.
Zappalá, Stefano
Potts, Matthew
Woolley, Max
Marshall, David
Evans, Sam L.
In vivo measurement of human brain material properties under quasi-static loading
title In vivo measurement of human brain material properties under quasi-static loading
title_full In vivo measurement of human brain material properties under quasi-static loading
title_fullStr In vivo measurement of human brain material properties under quasi-static loading
title_full_unstemmed In vivo measurement of human brain material properties under quasi-static loading
title_short In vivo measurement of human brain material properties under quasi-static loading
title_sort in vivo measurement of human brain material properties under quasi-static loading
topic Life Sciences–Engineering interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748497/
https://www.ncbi.nlm.nih.gov/pubmed/36514891
http://dx.doi.org/10.1098/rsif.2022.0557
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