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Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans

C. D’Onofrio, R. van Loon, S. Rolland, R. Johnston, L. North, S. Brown, R. Phillips, J. Sienz, Johann Sienz Orcid Logo, Richard Johnston Orcid Logo, Raoul van Loon Orcid Logo, Sam Rolland Orcid Logo, Claudio D'Onofrio Orcid Logo

Medical Engineering & Physics

Swansea University Authors: Johann Sienz Orcid Logo, Richard Johnston Orcid Logo, Raoul van Loon Orcid Logo, Sam Rolland Orcid Logo, Claudio D'Onofrio Orcid Logo

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DOI (Published version): 10.1016/j.medengphy.2017.06.035

Abstract

Cardiopulmonary bypass procedures are one of the most common operations and blood oxygenators are the centre piece for the heart-lung machines. Blood oxygenators have been tested as entire devices but intricate details on the flow field inside the oxygenators remain unknown. In this study, a novel m...

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Published in: Medical Engineering & Physics
ISSN: 1350-4533
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa34491
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Blood oxygenators have been tested as entire devices but intricate details on the flow field inside the oxygenators remain unknown. In this study, a novel method is presented to analyse the flow field inside oxygenators based on micro Computed Tomography (&#x3BC;CT) scans. Two Hollow Fibre Membrane (HFM) oxygenator prototypes were scanned and three-dimensional full scale models that capture the device-specific fibre distributions are set up for computational fluid dynamics analysis. The blood flow through the oxygenator is modelled as a non-Newtonian fluid. The results were compared against the flow solution through an ideal fibre distribution and show the importance of a uniform distribution of fibres and that the oxygenators analysed are not susceptible to flow directionality as mass flow versus area remain the same. However the pressure drop across the oxygenator is dependent on flow rate and direction. By comparing residence time of blood against the time frame to fully saturate blood with oxygen we highlight the potential of this method as design optimisation tool.In conclusion, image-based reconstruction is found to be a feasible route to assess oxygenator performance through flow modelling. It offers the possibility to review a product as manufactured rather than as designed, which is a valuable insight as a precursor to the approval processes. Finally, the flow analysis presented may be extended, at computational cost, to include species transport in further studies.</abstract><type>Journal Article</type><journal>Medical Engineering &amp; Physics</journal><publisher/><issnPrint>1350-4533</issnPrint><keywords>ECMO; Hollow Fibre Membrane; Non-Newtonian; Blood; Micro-CT</keywords><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2017</publishedYear><publishedDate>2017-12-31</publishedDate><doi>10.1016/j.medengphy.2017.06.035</doi><url/><notes/><college>COLLEGE NANME</college><department>Science and Engineering - Faculty</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>FGSEN</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2017-09-04T16:31:46.2824348</lastEdited><Created>2017-06-27T10:36:39.0740181</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Engineering and Applied Sciences - Uncategorised</level></path><authors><author><firstname>C.</firstname><surname>D&#x2019;Onofrio</surname><order>1</order></author><author><firstname>R.</firstname><surname>van Loon</surname><order>2</order></author><author><firstname>S.</firstname><surname>Rolland</surname><order>3</order></author><author><firstname>R.</firstname><surname>Johnston</surname><order>4</order></author><author><firstname>L.</firstname><surname>North</surname><order>5</order></author><author><firstname>S.</firstname><surname>Brown</surname><order>6</order></author><author><firstname>R.</firstname><surname>Phillips</surname><order>7</order></author><author><firstname>J.</firstname><surname>Sienz</surname><order>8</order></author><author><firstname>Johann</firstname><surname>Sienz</surname><orcid>0000-0003-3136-5718</orcid><order>9</order></author><author><firstname>Richard</firstname><surname>Johnston</surname><orcid>0000-0003-1977-6418</orcid><order>10</order></author><author><firstname>Raoul</firstname><surname>van Loon</surname><orcid>0000-0003-3581-5827</orcid><order>11</order></author><author><firstname>Sam</firstname><surname>Rolland</surname><orcid>0000-0003-0455-5620</orcid><order>12</order></author><author><firstname>Claudio</firstname><surname>D'Onofrio</surname><orcid>0000-0002-1982-3889</orcid><order>13</order></author></authors><documents><document><filename>0034491-04092017162953.pdf</filename><originalFilename>ThreeDimensionalComputationalModel.pdf</originalFilename><uploaded>2017-09-04T16:29:53.6970000</uploaded><type>Output</type><contentLength>2382932</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2017-09-04T00:00:00.0000000</embargoDate><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 2017-09-04T16:31:46.2824348 v2 34491 2017-06-27 Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans 17bf1dd287bff2cb01b53d98ceb28a31 0000-0003-3136-5718 Johann Sienz Johann Sienz true false 23282e7acce87dd926b8a62ae410a393 0000-0003-1977-6418 Richard Johnston Richard Johnston true false 880b30f90841a022f1e5bac32fb12193 0000-0003-3581-5827 Raoul van Loon Raoul van Loon true false c14ac34a71e9c058d1d2a353b44a24cd 0000-0003-0455-5620 Sam Rolland Sam Rolland true false eb796674dfe9857999fe5394035f4868 0000-0002-1982-3889 Claudio D'Onofrio Claudio D'Onofrio true false 2017-06-27 FGSEN Cardiopulmonary bypass procedures are one of the most common operations and blood oxygenators are the centre piece for the heart-lung machines. Blood oxygenators have been tested as entire devices but intricate details on the flow field inside the oxygenators remain unknown. In this study, a novel method is presented to analyse the flow field inside oxygenators based on micro Computed Tomography (μCT) scans. Two Hollow Fibre Membrane (HFM) oxygenator prototypes were scanned and three-dimensional full scale models that capture the device-specific fibre distributions are set up for computational fluid dynamics analysis. The blood flow through the oxygenator is modelled as a non-Newtonian fluid. The results were compared against the flow solution through an ideal fibre distribution and show the importance of a uniform distribution of fibres and that the oxygenators analysed are not susceptible to flow directionality as mass flow versus area remain the same. However the pressure drop across the oxygenator is dependent on flow rate and direction. By comparing residence time of blood against the time frame to fully saturate blood with oxygen we highlight the potential of this method as design optimisation tool.In conclusion, image-based reconstruction is found to be a feasible route to assess oxygenator performance through flow modelling. It offers the possibility to review a product as manufactured rather than as designed, which is a valuable insight as a precursor to the approval processes. Finally, the flow analysis presented may be extended, at computational cost, to include species transport in further studies. Journal Article Medical Engineering & Physics 1350-4533 ECMO; Hollow Fibre Membrane; Non-Newtonian; Blood; Micro-CT 31 12 2017 2017-12-31 10.1016/j.medengphy.2017.06.035 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2017-09-04T16:31:46.2824348 2017-06-27T10:36:39.0740181 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised C. D’Onofrio 1 R. van Loon 2 S. Rolland 3 R. Johnston 4 L. North 5 S. Brown 6 R. Phillips 7 J. Sienz 8 Johann Sienz 0000-0003-3136-5718 9 Richard Johnston 0000-0003-1977-6418 10 Raoul van Loon 0000-0003-3581-5827 11 Sam Rolland 0000-0003-0455-5620 12 Claudio D'Onofrio 0000-0002-1982-3889 13 0034491-04092017162953.pdf ThreeDimensionalComputationalModel.pdf 2017-09-04T16:29:53.6970000 Output 2382932 application/pdf Version of Record true 2017-09-04T00:00:00.0000000 true eng
title Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
spellingShingle Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
Johann Sienz
Richard Johnston
Raoul van Loon
Sam Rolland
Claudio D'Onofrio
title_short Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
title_full Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
title_fullStr Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
title_full_unstemmed Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
title_sort Three-dimensional computational model of a blood oxygenator reconstructed from micro-CT scans
author_id_str_mv 17bf1dd287bff2cb01b53d98ceb28a31
23282e7acce87dd926b8a62ae410a393
880b30f90841a022f1e5bac32fb12193
c14ac34a71e9c058d1d2a353b44a24cd
eb796674dfe9857999fe5394035f4868
author_id_fullname_str_mv 17bf1dd287bff2cb01b53d98ceb28a31_***_Johann Sienz
23282e7acce87dd926b8a62ae410a393_***_Richard Johnston
880b30f90841a022f1e5bac32fb12193_***_Raoul van Loon
c14ac34a71e9c058d1d2a353b44a24cd_***_Sam Rolland
eb796674dfe9857999fe5394035f4868_***_Claudio D'Onofrio
author Johann Sienz
Richard Johnston
Raoul van Loon
Sam Rolland
Claudio D'Onofrio
author2 C. D’Onofrio
R. van Loon
S. Rolland
R. Johnston
L. North
S. Brown
R. Phillips
J. Sienz
Johann Sienz
Richard Johnston
Raoul van Loon
Sam Rolland
Claudio D'Onofrio
format Journal article
container_title Medical Engineering & Physics
publishDate 2017
institution Swansea University
issn 1350-4533
doi_str_mv 10.1016/j.medengphy.2017.06.035
college_str Faculty of Science and Engineering
hierarchytype
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 Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description Cardiopulmonary bypass procedures are one of the most common operations and blood oxygenators are the centre piece for the heart-lung machines. Blood oxygenators have been tested as entire devices but intricate details on the flow field inside the oxygenators remain unknown. In this study, a novel method is presented to analyse the flow field inside oxygenators based on micro Computed Tomography (μCT) scans. Two Hollow Fibre Membrane (HFM) oxygenator prototypes were scanned and three-dimensional full scale models that capture the device-specific fibre distributions are set up for computational fluid dynamics analysis. The blood flow through the oxygenator is modelled as a non-Newtonian fluid. The results were compared against the flow solution through an ideal fibre distribution and show the importance of a uniform distribution of fibres and that the oxygenators analysed are not susceptible to flow directionality as mass flow versus area remain the same. However the pressure drop across the oxygenator is dependent on flow rate and direction. By comparing residence time of blood against the time frame to fully saturate blood with oxygen we highlight the potential of this method as design optimisation tool.In conclusion, image-based reconstruction is found to be a feasible route to assess oxygenator performance through flow modelling. It offers the possibility to review a product as manufactured rather than as designed, which is a valuable insight as a precursor to the approval processes. Finally, the flow analysis presented may be extended, at computational cost, to include species transport in further studies.
published_date 2017-12-31T03:41:02Z
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score 10.9382515

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