Free Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy
Traction Force Microscopy (TFM) is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV) is commonly used to quantify the substrate's deformations, due to its simplicity and efficiency. Howeve...
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creator | Jorge-Peñas, Alvaro Izquierdo-Alvarez, Alicia Aguilar-Cuenca, Rocio Vicente-Manzanares, Miguel Garcia-Aznar, José Manuel Van Oosterwyck, Hans de-Juan-Pardo, Elena M Ortiz-de-Solorzano, Carlos Muñoz-Barrutia, Arrate |
description | Traction Force Microscopy (TFM) is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV) is commonly used to quantify the substrate's deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell's adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD) algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated) data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery. |
doi_str_mv | 10.1371/journal.pone.0144184 |
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Particle Image Velocimetry (PIV) is commonly used to quantify the substrate's deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell's adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD) algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated) data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0144184</identifier><identifier>PMID: 26641883</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Biomechanics ; Computer simulation ; Deformation ; Deformation mechanisms ; Endothelial cells ; Extracellular matrix ; Finite element method ; Formability ; Free form ; Image registration ; Imaging, Three-Dimensional - methods ; Mechanical engineering ; Microscopy ; Microscopy, Atomic Force - methods ; Models, Theoretical ; Particle image velocimetry ; Pathological physiology ; Recovery ; Registration ; Substrates ; Traction ; Traction force ; Velocity measurement</subject><ispartof>PloS one, 2015-12, Vol.10 (12), p.e0144184-e0144184</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Jorge-Peñas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Jorge-Peñas et al 2015 Jorge-Peñas et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c720t-a5a369fa9885487e11adadc83d5de14a06359f6534a6da22188adf52c315ec4a3</citedby><cites>FETCH-LOGICAL-c720t-a5a369fa9885487e11adadc83d5de14a06359f6534a6da22188adf52c315ec4a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4671587/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4671587/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26641883$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jorge-Peñas, Alvaro</creatorcontrib><creatorcontrib>Izquierdo-Alvarez, Alicia</creatorcontrib><creatorcontrib>Aguilar-Cuenca, Rocio</creatorcontrib><creatorcontrib>Vicente-Manzanares, Miguel</creatorcontrib><creatorcontrib>Garcia-Aznar, José Manuel</creatorcontrib><creatorcontrib>Van Oosterwyck, Hans</creatorcontrib><creatorcontrib>de-Juan-Pardo, Elena M</creatorcontrib><creatorcontrib>Ortiz-de-Solorzano, Carlos</creatorcontrib><creatorcontrib>Muñoz-Barrutia, Arrate</creatorcontrib><title>Free Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Traction Force Microscopy (TFM) is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV) is commonly used to quantify the substrate's deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell's adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD) algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated) data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Biomechanics</subject><subject>Computer simulation</subject><subject>Deformation</subject><subject>Deformation mechanisms</subject><subject>Endothelial cells</subject><subject>Extracellular matrix</subject><subject>Finite element method</subject><subject>Formability</subject><subject>Free form</subject><subject>Image registration</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Mechanical engineering</subject><subject>Microscopy</subject><subject>Microscopy, Atomic Force - methods</subject><subject>Models, Theoretical</subject><subject>Particle image velocimetry</subject><subject>Pathological physiology</subject><subject>Recovery</subject><subject>Registration</subject><subject>Substrates</subject><subject>Traction</subject><subject>Traction 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Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy</title><author>Jorge-Peñas, Alvaro ; Izquierdo-Alvarez, Alicia ; Aguilar-Cuenca, Rocio ; Vicente-Manzanares, Miguel ; Garcia-Aznar, José Manuel ; Van Oosterwyck, Hans ; de-Juan-Pardo, Elena M ; Ortiz-de-Solorzano, Carlos ; Muñoz-Barrutia, Arrate</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c720t-a5a369fa9885487e11adadc83d5de14a06359f6534a6da22188adf52c315ec4a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Biomechanics</topic><topic>Computer simulation</topic><topic>Deformation</topic><topic>Deformation mechanisms</topic><topic>Endothelial cells</topic><topic>Extracellular matrix</topic><topic>Finite element method</topic><topic>Formability</topic><topic>Free form</topic><topic>Image registration</topic><topic>Imaging, 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Hans</au><au>de-Juan-Pardo, Elena M</au><au>Ortiz-de-Solorzano, Carlos</au><au>Muñoz-Barrutia, Arrate</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Free Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-12-07</date><risdate>2015</risdate><volume>10</volume><issue>12</issue><spage>e0144184</spage><epage>e0144184</epage><pages>e0144184-e0144184</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Traction Force Microscopy (TFM) is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV) is commonly used to quantify the substrate's deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell's adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD) algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated) data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26641883</pmid><doi>10.1371/journal.pone.0144184</doi><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Analysis Biomechanics Computer simulation Deformation Deformation mechanisms Endothelial cells Extracellular matrix Finite element method Formability Free form Image registration Imaging, Three-Dimensional - methods Mechanical engineering Microscopy Microscopy, Atomic Force - methods Models, Theoretical Particle image velocimetry Pathological physiology Recovery Registration Substrates Traction Traction force Velocity measurement |
title | Free Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy |
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