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...
Gespeichert in:
Veröffentlicht in: | Biomechanics and modeling in mechanobiology 2019-08, Vol.18 (4), p.1111-1122 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1122 |
---|---|
container_issue | 4 |
container_start_page | 1111 |
container_title | Biomechanics and modeling in mechanobiology |
container_volume | 18 |
creator | Vidotto, Marco Botnariuc, Daniela De Momi, Elena Dini, Daniele |
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. |
doi_str_mv | 10.1007/s10237-019-01131-7 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6685924</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2184139462</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-6df36970a240dfd18ba1be72cf48d5869b73f76dff80d4f3b117507e371953183</originalsourceid><addsrcrecordid>eNp9kUFPHSEQx4mpUat-AQ8NSS-9bMsAu7AXE2OqbWLqRc-EXcCH2V22wGrety_16dN66IHMZOY3fxj-CJ0A-QqEiG8JCGWiItCWAwwqsYMOoAFRiZaTD9u8bvfRx5TuCaGESbaH9hkRsmT8AP06w30Y5yXr7MOkB-yGxRts1pMefZ-wnucYdL_COWBjs42jnyx-XPls8ahzKeC5FK3u_ODz-gjtOj0ke_wcD9Htxfeb8x_V1fXlz_Ozq6rngueqMY41rSCacmKcAdlp6KygvePS1LJpO8GcKJSTxHDHOgBRE2GZgLZmINkhOt3ozks3WtPbKUc9qDn6Uce1CtqrfzuTX6m78KCaRtYt5UXgy7NADL8Xm7IafertMOjJhiUpCpIDa3lDC_r5HXofllj-6olinFBZN4WiG6qPIaVo3fYxQNRfu9TGLlXsUk92KVGGPr1dYzvy4k8B2AZIpTXd2fh6939k_wC4kKEf</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2183402856</pqid></control><display><type>article</type><title>A computational fluid dynamics approach to determine white matter permeability</title><source>MEDLINE</source><source>SpringerLink Journals</source><creator>Vidotto, Marco ; Botnariuc, Daniela ; De Momi, Elena ; Dini, Daniele</creator><creatorcontrib>Vidotto, Marco ; Botnariuc, Daniela ; De Momi, Elena ; Dini, Daniele</creatorcontrib><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.</description><identifier>ISSN: 1617-7959</identifier><identifier>ISSN: 1617-7940</identifier><identifier>EISSN: 1617-7940</identifier><identifier>DOI: 10.1007/s10237-019-01131-7</identifier><identifier>PMID: 30783834</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Animals ; Axons ; Biological and Medical Physics ; Biomedical Engineering and Bioengineering ; Biophysics ; Brain ; CAD ; Chemical compounds ; Chemotherapy ; Computational fluid dynamics ; Computational neuroscience ; Computer aided design ; Convection ; Electron microscopy ; Engineering ; Extracellular matrix ; Extracellular Space - metabolism ; Fluid dynamics ; Fluid flow ; Haplorhini ; Humans ; Hydraulic permeability ; Hydrodynamics ; Mice ; Original Paper ; Parenchyma ; Permeability ; Pharmacology ; Pressure ; Radiation therapy ; Substantia alba ; Survival ; Theoretical and Applied Mechanics ; Tumors ; White Matter - physiology</subject><ispartof>Biomechanics and modeling in mechanobiology, 2019-08, Vol.18 (4), p.1111-1122</ispartof><rights>The Author(s) 2019. corrected publication 2019</rights><rights>Biomechanics and Modeling in Mechanobiology is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2019, corrected publication 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-6df36970a240dfd18ba1be72cf48d5869b73f76dff80d4f3b117507e371953183</citedby><cites>FETCH-LOGICAL-c474t-6df36970a240dfd18ba1be72cf48d5869b73f76dff80d4f3b117507e371953183</cites><orcidid>0000-0002-2327-0148</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10237-019-01131-7$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10237-019-01131-7$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27903,27904,41467,42536,51297</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30783834$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Vidotto, Marco</creatorcontrib><creatorcontrib>Botnariuc, Daniela</creatorcontrib><creatorcontrib>De Momi, Elena</creatorcontrib><creatorcontrib>Dini, Daniele</creatorcontrib><title>A computational fluid dynamics approach to determine white matter permeability</title><title>Biomechanics and modeling in mechanobiology</title><addtitle>Biomech Model Mechanobiol</addtitle><addtitle>Biomech Model Mechanobiol</addtitle><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.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Axons</subject><subject>Biological and Medical Physics</subject><subject>Biomedical Engineering and Bioengineering</subject><subject>Biophysics</subject><subject>Brain</subject><subject>CAD</subject><subject>Chemical compounds</subject><subject>Chemotherapy</subject><subject>Computational fluid dynamics</subject><subject>Computational neuroscience</subject><subject>Computer aided design</subject><subject>Convection</subject><subject>Electron microscopy</subject><subject>Engineering</subject><subject>Extracellular matrix</subject><subject>Extracellular Space - metabolism</subject><subject>Fluid dynamics</subject><subject>Fluid flow</subject><subject>Haplorhini</subject><subject>Humans</subject><subject>Hydraulic permeability</subject><subject>Hydrodynamics</subject><subject>Mice</subject><subject>Original Paper</subject><subject>Parenchyma</subject><subject>Permeability</subject><subject>Pharmacology</subject><subject>Pressure</subject><subject>Radiation therapy</subject><subject>Substantia alba</subject><subject>Survival</subject><subject>Theoretical and Applied Mechanics</subject><subject>Tumors</subject><subject>White Matter - physiology</subject><issn>1617-7959</issn><issn>1617-7940</issn><issn>1617-7940</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kUFPHSEQx4mpUat-AQ8NSS-9bMsAu7AXE2OqbWLqRc-EXcCH2V22wGrety_16dN66IHMZOY3fxj-CJ0A-QqEiG8JCGWiItCWAwwqsYMOoAFRiZaTD9u8bvfRx5TuCaGESbaH9hkRsmT8AP06w30Y5yXr7MOkB-yGxRts1pMefZ-wnucYdL_COWBjs42jnyx-XPls8ahzKeC5FK3u_ODz-gjtOj0ke_wcD9Htxfeb8x_V1fXlz_Ozq6rngueqMY41rSCacmKcAdlp6KygvePS1LJpO8GcKJSTxHDHOgBRE2GZgLZmINkhOt3ozks3WtPbKUc9qDn6Uce1CtqrfzuTX6m78KCaRtYt5UXgy7NADL8Xm7IafertMOjJhiUpCpIDa3lDC_r5HXofllj-6olinFBZN4WiG6qPIaVo3fYxQNRfu9TGLlXsUk92KVGGPr1dYzvy4k8B2AZIpTXd2fh6939k_wC4kKEf</recordid><startdate>20190801</startdate><enddate>20190801</enddate><creator>Vidotto, Marco</creator><creator>Botnariuc, Daniela</creator><creator>De Momi, Elena</creator><creator>Dini, Daniele</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TB</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>M7S</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-2327-0148</orcidid></search><sort><creationdate>20190801</creationdate><title>A computational fluid dynamics approach to determine white matter permeability</title><author>Vidotto, Marco ; Botnariuc, Daniela ; De Momi, Elena ; Dini, Daniele</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-6df36970a240dfd18ba1be72cf48d5869b73f76dff80d4f3b117507e371953183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Axons</topic><topic>Biological and Medical Physics</topic><topic>Biomedical Engineering and Bioengineering</topic><topic>Biophysics</topic><topic>Brain</topic><topic>CAD</topic><topic>Chemical compounds</topic><topic>Chemotherapy</topic><topic>Computational fluid dynamics</topic><topic>Computational neuroscience</topic><topic>Computer aided design</topic><topic>Convection</topic><topic>Electron microscopy</topic><topic>Engineering</topic><topic>Extracellular matrix</topic><topic>Extracellular Space - metabolism</topic><topic>Fluid dynamics</topic><topic>Fluid flow</topic><topic>Haplorhini</topic><topic>Humans</topic><topic>Hydraulic permeability</topic><topic>Hydrodynamics</topic><topic>Mice</topic><topic>Original Paper</topic><topic>Parenchyma</topic><topic>Permeability</topic><topic>Pharmacology</topic><topic>Pressure</topic><topic>Radiation therapy</topic><topic>Substantia alba</topic><topic>Survival</topic><topic>Theoretical and Applied Mechanics</topic><topic>Tumors</topic><topic>White Matter - physiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vidotto, Marco</creatorcontrib><creatorcontrib>Botnariuc, Daniela</creatorcontrib><creatorcontrib>De Momi, Elena</creatorcontrib><creatorcontrib>Dini, Daniele</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Biomechanics and modeling in mechanobiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vidotto, Marco</au><au>Botnariuc, Daniela</au><au>De Momi, Elena</au><au>Dini, Daniele</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A computational fluid dynamics approach to determine white matter permeability</atitle><jtitle>Biomechanics and modeling in mechanobiology</jtitle><stitle>Biomech Model Mechanobiol</stitle><addtitle>Biomech Model Mechanobiol</addtitle><date>2019-08-01</date><risdate>2019</risdate><volume>18</volume><issue>4</issue><spage>1111</spage><epage>1122</epage><pages>1111-1122</pages><issn>1617-7959</issn><issn>1617-7940</issn><eissn>1617-7940</eissn><abstract>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.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>30783834</pmid><doi>10.1007/s10237-019-01131-7</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-2327-0148</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1617-7959 |
ispartof | Biomechanics and modeling in mechanobiology, 2019-08, Vol.18 (4), p.1111-1122 |
issn | 1617-7959 1617-7940 1617-7940 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6685924 |
source | MEDLINE; SpringerLink Journals |
subjects | Algorithms Animals Axons Biological and Medical Physics Biomedical Engineering and Bioengineering Biophysics Brain CAD Chemical compounds Chemotherapy Computational fluid dynamics Computational neuroscience Computer aided design Convection Electron microscopy Engineering Extracellular matrix Extracellular Space - metabolism Fluid dynamics Fluid flow Haplorhini Humans Hydraulic permeability Hydrodynamics Mice Original Paper Parenchyma Permeability Pharmacology Pressure Radiation therapy Substantia alba Survival Theoretical and Applied Mechanics Tumors White Matter - physiology |
title | A computational fluid dynamics approach to determine white matter permeability |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T06%3A22%3A34IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20computational%20fluid%20dynamics%20approach%20to%20determine%20white%20matter%20permeability&rft.jtitle=Biomechanics%20and%20modeling%20in%20mechanobiology&rft.au=Vidotto,%20Marco&rft.date=2019-08-01&rft.volume=18&rft.issue=4&rft.spage=1111&rft.epage=1122&rft.pages=1111-1122&rft.issn=1617-7959&rft.eissn=1617-7940&rft_id=info:doi/10.1007/s10237-019-01131-7&rft_dat=%3Cproquest_pubme%3E2184139462%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2183402856&rft_id=info:pmid/30783834&rfr_iscdi=true |