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A computational fluid dynamics approach to determine white matter permeability

Glioblastomas represent a challenging problem with an extremely poor survival rate. Since these tumour cells have a highly invasive character, an effective surgical resection as well as chemotherapy and radiotherapy is very difficult. Convection-enhanced delivery (CED), a technique that consists in...

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Autores principales: Vidotto, Marco, Botnariuc, Daniela, De Momi, Elena, Dini, Daniele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685924/
https://www.ncbi.nlm.nih.gov/pubmed/30783834
http://dx.doi.org/10.1007/s10237-019-01131-7
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author Vidotto, Marco
Botnariuc, Daniela
De Momi, Elena
Dini, Daniele
author_facet Vidotto, Marco
Botnariuc, Daniela
De Momi, Elena
Dini, Daniele
author_sort Vidotto, Marco
collection PubMed
description Glioblastomas represent a challenging problem with an extremely poor survival rate. Since these tumour cells have a highly invasive character, an effective surgical resection as well as chemotherapy and radiotherapy is very difficult. Convection-enhanced delivery (CED), a technique that consists in the injection of a therapeutic agent directly into the parenchyma, has shown encouraging results. Its efficacy depends on the ability to predict, in the pre-operative phase, the distribution of the drug inside the tumour. This paper proposes a method to compute a fundamental parameter for CED modelling outcomes, the hydraulic permeability, in three brain structures. Therefore, a bidimensional brain-like structure was built out of the main geometrical features of the white matter: axon diameter distribution extrapolated from electron microscopy images, extracellular space (ECS) volume fraction and ECS width. The axons were randomly allocated inside a defined border, and the ECS volume fraction as well as the ECS width maintained in a physiological range. To achieve this result, an outward packing method coupled with a disc shrinking technique was implemented. The fluid flow through the axons was computed by solving Navier–Stokes equations within the computational fluid dynamics solver ANSYS. From the fluid and pressure fields, an homogenisation technique allowed establishing the optimal representative volume element (RVE) size. The hydraulic permeability computed on the RVE was found in good agreement with experimental data from the literature.
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spelling pubmed-66859242019-08-23 A computational fluid dynamics approach to determine white matter permeability Vidotto, Marco Botnariuc, Daniela De Momi, Elena Dini, Daniele Biomech Model Mechanobiol Original Paper Glioblastomas represent a challenging problem with an extremely poor survival rate. Since these tumour cells have a highly invasive character, an effective surgical resection as well as chemotherapy and radiotherapy is very difficult. Convection-enhanced delivery (CED), a technique that consists in the injection of a therapeutic agent directly into the parenchyma, has shown encouraging results. Its efficacy depends on the ability to predict, in the pre-operative phase, the distribution of the drug inside the tumour. This paper proposes a method to compute a fundamental parameter for CED modelling outcomes, the hydraulic permeability, in three brain structures. Therefore, a bidimensional brain-like structure was built out of the main geometrical features of the white matter: axon diameter distribution extrapolated from electron microscopy images, extracellular space (ECS) volume fraction and ECS width. The axons were randomly allocated inside a defined border, and the ECS volume fraction as well as the ECS width maintained in a physiological range. To achieve this result, an outward packing method coupled with a disc shrinking technique was implemented. The fluid flow through the axons was computed by solving Navier–Stokes equations within the computational fluid dynamics solver ANSYS. From the fluid and pressure fields, an homogenisation technique allowed establishing the optimal representative volume element (RVE) size. The hydraulic permeability computed on the RVE was found in good agreement with experimental data from the literature. Springer Berlin Heidelberg 2019-02-20 2019 /pmc/articles/PMC6685924/ /pubmed/30783834 http://dx.doi.org/10.1007/s10237-019-01131-7 Text en © The Author(s) 2019, corrected publication 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits any noncommercial use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, a link is provided to the Creative Commons license and any changes made are indicated.
spellingShingle Original Paper
Vidotto, Marco
Botnariuc, Daniela
De Momi, Elena
Dini, Daniele
A computational fluid dynamics approach to determine white matter permeability
title A computational fluid dynamics approach to determine white matter permeability
title_full A computational fluid dynamics approach to determine white matter permeability
title_fullStr A computational fluid dynamics approach to determine white matter permeability
title_full_unstemmed A computational fluid dynamics approach to determine white matter permeability
title_short A computational fluid dynamics approach to determine white matter permeability
title_sort computational fluid dynamics approach to determine white matter permeability
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685924/
https://www.ncbi.nlm.nih.gov/pubmed/30783834
http://dx.doi.org/10.1007/s10237-019-01131-7
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