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Data-driven modelling of the FRC network for studying the fluid flow in the conduit system

Rostislav Savinkov, Alexey Kislitsyn, Daniel J. Watson, Raoul van Loon Orcid Logo, Igor Sazonov Orcid Logo, Mario Novkovic, Lucas Onder, Gennady Bocharov

Engineering Applications of Artificial Intelligence, Volume: 62, Pages: 341 - 349

Swansea University Authors: Raoul van Loon Orcid Logo, Igor Sazonov Orcid Logo

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DOI (Published version): 10.1016/j.engappai.2016.10.007

Abstract

The human immune system is characterized by enormous cellular and anatomical complexity. Lymph nodes are key centers of immune reactivity, organized into distinct structural and functional modules including the T-cell zone, fibroblastic reticular cell (FRC) network and the conduit system. A thorough...

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Published in: Engineering Applications of Artificial Intelligence
ISSN: 0952-1976
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa30588
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Lymph nodes are key centers of immune reactivity, organized into distinct structural and functional modules including the T-cell zone, fibroblastic reticular cell (FRC) network and the conduit system. A thorough understanding of the modular organization is a prerequisite for lymphoid organ tissue-engineering. Due to the biological complexity of lymphoid organs, the development of mathematical models capable of elaborating the lymph node architecture and functional organization, has remained a major challenge in computational biology. Here, we present a computational method to model the geometry of the FRC network and fluid flow in the conduit system. It differs from the blood vascular network image-based reconstruction approaches as it develops the parameterized geometric model using the real statistics of the node degree and the edge length distributions. The FRC network model is then used to analyze the fluid flow through the underlying conduit system. A first observation is that the pressure gradient is approximately linear, which suggests homogeneity of the network. Furthermore, calculated permeability values View the MathML source show the generated network is isotropic, while investigating random variations of pipe radii (with a given mean and standard deviation) shows a significant effect on the permeability. This framework can now be further explored to systematically correlate fundamental characteristics of the FRC conduit system to more global material properties such as permeability.</abstract><type>Journal Article</type><journal>Engineering Applications of Artificial Intelligence</journal><volume>62</volume><journalNumber/><paginationStart>341</paginationStart><paginationEnd>349</paginationEnd><publisher/><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0952-1976</issnPrint><issnElectronic/><keywords>Lymph node engineering; Fibroblastic reticular cell; Conduit system; Complex vascular network; Artificial networks; Fluid flow</keywords><publishedDay>1</publishedDay><publishedMonth>6</publishedMonth><publishedYear>2017</publishedYear><publishedDate>2017-06-01</publishedDate><doi>10.1016/j.engappai.2016.10.007</doi><url/><notes/><college>COLLEGE NANME</college><department>Biomedical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDE</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2021-01-14T12:56:50.3919366</lastEdited><Created>2016-10-14T15:01:38.2187079</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering</level></path><authors><author><firstname>Rostislav</firstname><surname>Savinkov</surname><order>1</order></author><author><firstname>Alexey</firstname><surname>Kislitsyn</surname><order>2</order></author><author><firstname>Daniel J.</firstname><surname>Watson</surname><order>3</order></author><author><firstname>Raoul</firstname><surname>van Loon</surname><orcid>0000-0003-3581-5827</orcid><order>4</order></author><author><firstname>Igor</firstname><surname>Sazonov</surname><orcid>0000-0001-6685-2351</orcid><order>5</order></author><author><firstname>Mario</firstname><surname>Novkovic</surname><order>6</order></author><author><firstname>Lucas</firstname><surname>Onder</surname><order>7</order></author><author><firstname>Gennady</firstname><surname>Bocharov</surname><order>8</order></author></authors><documents><document><filename>0030588-14102016150320.pdf</filename><originalFilename>savinkov2016.pdf</originalFilename><uploaded>2016-10-14T15:03:20.1500000</uploaded><type>Output</type><contentLength>3097458</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2017-10-28T00:00:00.0000000</embargoDate><documentNotes>Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND).</documentNotes><copyrightCorrect>true</copyrightCorrect><language>English</language></document></documents><OutputDurs/></rfc1807>
spelling 2021-01-14T12:56:50.3919366 v2 30588 2016-10-14 Data-driven modelling of the FRC network for studying the fluid flow in the conduit system 880b30f90841a022f1e5bac32fb12193 0000-0003-3581-5827 Raoul van Loon Raoul van Loon true false 05a507952e26462561085fb6f62c8897 0000-0001-6685-2351 Igor Sazonov Igor Sazonov true false 2016-10-14 MEDE The human immune system is characterized by enormous cellular and anatomical complexity. Lymph nodes are key centers of immune reactivity, organized into distinct structural and functional modules including the T-cell zone, fibroblastic reticular cell (FRC) network and the conduit system. A thorough understanding of the modular organization is a prerequisite for lymphoid organ tissue-engineering. Due to the biological complexity of lymphoid organs, the development of mathematical models capable of elaborating the lymph node architecture and functional organization, has remained a major challenge in computational biology. Here, we present a computational method to model the geometry of the FRC network and fluid flow in the conduit system. It differs from the blood vascular network image-based reconstruction approaches as it develops the parameterized geometric model using the real statistics of the node degree and the edge length distributions. The FRC network model is then used to analyze the fluid flow through the underlying conduit system. A first observation is that the pressure gradient is approximately linear, which suggests homogeneity of the network. Furthermore, calculated permeability values View the MathML source show the generated network is isotropic, while investigating random variations of pipe radii (with a given mean and standard deviation) shows a significant effect on the permeability. This framework can now be further explored to systematically correlate fundamental characteristics of the FRC conduit system to more global material properties such as permeability. Journal Article Engineering Applications of Artificial Intelligence 62 341 349 0952-1976 Lymph node engineering; Fibroblastic reticular cell; Conduit system; Complex vascular network; Artificial networks; Fluid flow 1 6 2017 2017-06-01 10.1016/j.engappai.2016.10.007 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2021-01-14T12:56:50.3919366 2016-10-14T15:01:38.2187079 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering Rostislav Savinkov 1 Alexey Kislitsyn 2 Daniel J. Watson 3 Raoul van Loon 0000-0003-3581-5827 4 Igor Sazonov 0000-0001-6685-2351 5 Mario Novkovic 6 Lucas Onder 7 Gennady Bocharov 8 0030588-14102016150320.pdf savinkov2016.pdf 2016-10-14T15:03:20.1500000 Output 3097458 application/pdf Accepted Manuscript true 2017-10-28T00:00:00.0000000 Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND). true English
title Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
spellingShingle Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
Raoul van Loon
Igor Sazonov
title_short Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
title_full Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
title_fullStr Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
title_full_unstemmed Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
title_sort Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
author_id_str_mv 880b30f90841a022f1e5bac32fb12193
05a507952e26462561085fb6f62c8897
author_id_fullname_str_mv 880b30f90841a022f1e5bac32fb12193_***_Raoul van Loon
05a507952e26462561085fb6f62c8897_***_Igor Sazonov
author Raoul van Loon
Igor Sazonov
author2 Rostislav Savinkov
Alexey Kislitsyn
Daniel J. Watson
Raoul van Loon
Igor Sazonov
Mario Novkovic
Lucas Onder
Gennady Bocharov
format Journal article
container_title Engineering Applications of Artificial Intelligence
container_volume 62
container_start_page 341
publishDate 2017
institution Swansea University
issn 0952-1976
doi_str_mv 10.1016/j.engappai.2016.10.007
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering
document_store_str 1
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description The human immune system is characterized by enormous cellular and anatomical complexity. Lymph nodes are key centers of immune reactivity, organized into distinct structural and functional modules including the T-cell zone, fibroblastic reticular cell (FRC) network and the conduit system. A thorough understanding of the modular organization is a prerequisite for lymphoid organ tissue-engineering. Due to the biological complexity of lymphoid organs, the development of mathematical models capable of elaborating the lymph node architecture and functional organization, has remained a major challenge in computational biology. Here, we present a computational method to model the geometry of the FRC network and fluid flow in the conduit system. It differs from the blood vascular network image-based reconstruction approaches as it develops the parameterized geometric model using the real statistics of the node degree and the edge length distributions. The FRC network model is then used to analyze the fluid flow through the underlying conduit system. A first observation is that the pressure gradient is approximately linear, which suggests homogeneity of the network. Furthermore, calculated permeability values View the MathML source show the generated network is isotropic, while investigating random variations of pipe radii (with a given mean and standard deviation) shows a significant effect on the permeability. This framework can now be further explored to systematically correlate fundamental characteristics of the FRC conduit system to more global material properties such as permeability.
published_date 2017-06-01T03:37:12Z
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score 11.013082

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