FORCETRACKER: A versatile tool for standardized assessment of tissue contractile properties in 3D Heart-on-Chip platforms
Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease mo...
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| Published in | PloS one Vol. 20; no. 2; p. e0314985 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
13.02.2025
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0314985 |
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| Abstract | Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease modelling, and fundamental research. The tissues' contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. However, existing optical tracking algorithms which focus on calculating the contractile force are customized and platform-specific, often not available to the broad research community, and thus hamper head-to-head comparison of the model output. Therefore, there is the need for robust, standardized and platform-independent software for tissues' force assessment. To meet this need, we developed ForceTracker: a standalone and computationally efficient software for analyzing contractile properties of tissues in different EHT platforms. The software uses a shape-detection algorithm to single out and track the movement of pillars' tips for the most common shapes of EHT platforms. In this way, we can obtain information about tissues' contractile performance. ForceTracker is coded in Python and uses a multi-threading approach for time-efficient analysis of large data sets in multiple formats. The software efficiency to analyze circular and rectangular pillar shapes is successfully tested by analyzing different format videos from two EHT platforms, developed by different research groups. We demonstrate robust and reproducible performance of the software in the analysis of tissues over time and in various conditions. ForceTracker's detection and tracking shows low sensitivity to common incidental defects, such as alteration of tissue shape or air bubbles. Detection accuracy is determined via comparison with manual measurements using the software ImageJ. We developed ForceTracker as a tool for standardized analysis of contractile performance in EHT platforms to facilitate research on disease modeling and drug discovery in academia and industry. |
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| AbstractList | Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease modelling, and fundamental research. The tissues’ contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. However, existing optical tracking algorithms which focus on calculating the contractile force are customized and platform-specific, often not available to the broad research community, and thus hamper head-to-head comparison of the model output. Therefore, there is the need for robust, standardized and platform-independent software for tissues’ force assessment. To meet this need, we developed ForceTracker: a standalone and computationally efficient software for analyzing contractile properties of tissues in different EHT platforms. The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. In this way, we can obtain information about tissues’ contractile performance. ForceTracker is coded in Python and uses a multi-threading approach for time-efficient analysis of large data sets in multiple formats. The software efficiency to analyze circular and rectangular pillar shapes is successfully tested by analyzing different format videos from two EHT platforms, developed by different research groups. We demonstrate robust and reproducible performance of the software in the analysis of tissues over time and in various conditions. ForceTracker’s detection and tracking shows low sensitivity to common incidental defects, such as alteration of tissue shape or air bubbles. Detection accuracy is determined via comparison with manual measurements using the software ImageJ. We developed ForceTracker as a tool for standardized analysis of contractile performance in EHT platforms to facilitate research on disease modeling and drug discovery in academia and industry. Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease modelling, and fundamental research. The tissues' contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. However, existing optical tracking algorithms which focus on calculating the contractile force are customized and platform-specific, often not available to the broad research community, and thus hamper head-to-head comparison of the model output. Therefore, there is the need for robust, standardized and platform-independent software for tissues' force assessment. To meet this need, we developed ForceTracker: a standalone and computationally efficient software for analyzing contractile properties of tissues in different EHT platforms. The software uses a shape-detection algorithm to single out and track the movement of pillars' tips for the most common shapes of EHT platforms. In this way, we can obtain information about tissues' contractile performance. ForceTracker is coded in Python and uses a multi-threading approach for time-efficient analysis of large data sets in multiple formats. The software efficiency to analyze circular and rectangular pillar shapes is successfully tested by analyzing different format videos from two EHT platforms, developed by different research groups. We demonstrate robust and reproducible performance of the software in the analysis of tissues over time and in various conditions. ForceTracker's detection and tracking shows low sensitivity to common incidental defects, such as alteration of tissue shape or air bubbles. Detection accuracy is determined via comparison with manual measurements using the software ImageJ. We developed ForceTracker as a tool for standardized analysis of contractile performance in EHT platforms to facilitate research on disease modeling and drug discovery in academia and industry.Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease modelling, and fundamental research. The tissues' contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. However, existing optical tracking algorithms which focus on calculating the contractile force are customized and platform-specific, often not available to the broad research community, and thus hamper head-to-head comparison of the model output. Therefore, there is the need for robust, standardized and platform-independent software for tissues' force assessment. To meet this need, we developed ForceTracker: a standalone and computationally efficient software for analyzing contractile properties of tissues in different EHT platforms. The software uses a shape-detection algorithm to single out and track the movement of pillars' tips for the most common shapes of EHT platforms. In this way, we can obtain information about tissues' contractile performance. ForceTracker is coded in Python and uses a multi-threading approach for time-efficient analysis of large data sets in multiple formats. The software efficiency to analyze circular and rectangular pillar shapes is successfully tested by analyzing different format videos from two EHT platforms, developed by different research groups. We demonstrate robust and reproducible performance of the software in the analysis of tissues over time and in various conditions. ForceTracker's detection and tracking shows low sensitivity to common incidental defects, such as alteration of tissue shape or air bubbles. Detection accuracy is determined via comparison with manual measurements using the software ImageJ. We developed ForceTracker as a tool for standardized analysis of contractile performance in EHT platforms to facilitate research on disease modeling and drug discovery in academia and industry. |
| Audience | Academic |
| Author | Segerink, Loes I Windt, Laura M Rivera-Arbeláez, José M Ribeiro, Marcelo C Sarro, Pasqualina M Stein, Jeroen M Boonen, Tom van Meer, Berend J Wiendels, Maury Passier, Robert Cofiño-Fabres, Carla van den Berg, Albert Mastrangeli, Massimo Mummery, Christine L Dostanić, Milica |
| AuthorAffiliation | 2 Department of Bioengineering Technologies, Applied Stem Cell Technologies Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands 4 Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands Purdue University, UNITED STATES OF AMERICA 5 River BioMedics, Enschede, The Netherlands 1 MESA+Institute for Nanotechnology, BIOS Lab on a Chip Group, Technical Medical Centre, Max Planck Center for Com-plex Fluid Dynamics, University of Twente, Enschede, The Netherlands 3 Microelectronics, Delft University of Technology, Delft, The Netherlands |
| AuthorAffiliation_xml | – name: 1 MESA+Institute for Nanotechnology, BIOS Lab on a Chip Group, Technical Medical Centre, Max Planck Center for Com-plex Fluid Dynamics, University of Twente, Enschede, The Netherlands – name: 2 Department of Bioengineering Technologies, Applied Stem Cell Technologies Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands – name: 4 Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands – name: 3 Microelectronics, Delft University of Technology, Delft, The Netherlands – name: 5 River BioMedics, Enschede, The Netherlands – name: Purdue University, UNITED STATES OF AMERICA |
| Author_xml | – sequence: 1 givenname: José M orcidid: 0000-0002-0075-6006 surname: Rivera-Arbeláez fullname: Rivera-Arbeláez, José M organization: Department of Bioengineering Technologies, Applied Stem Cell Technologies Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands – sequence: 2 givenname: Milica surname: Dostanić fullname: Dostanić, Milica organization: Microelectronics, Delft University of Technology, Delft, The Netherlands – sequence: 3 givenname: Laura M surname: Windt fullname: Windt, Laura M organization: Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands – sequence: 4 givenname: Jeroen M surname: Stein fullname: Stein, Jeroen M organization: Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands – sequence: 5 givenname: Carla surname: Cofiño-Fabres fullname: Cofiño-Fabres, Carla organization: Department of Bioengineering Technologies, Applied Stem Cell Technologies Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands – sequence: 6 givenname: Tom surname: Boonen fullname: Boonen, Tom organization: River BioMedics, Enschede, The Netherlands – sequence: 7 givenname: Maury surname: Wiendels fullname: Wiendels, Maury organization: Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands – sequence: 8 givenname: Albert surname: van den Berg fullname: van den Berg, Albert organization: MESA+Institute for Nanotechnology, BIOS Lab on a Chip Group, Technical Medical Centre, Max Planck Center for Com-plex Fluid Dynamics, University of Twente, Enschede, The Netherlands – sequence: 9 givenname: Loes I orcidid: 0000-0001-6943-8156 surname: Segerink fullname: Segerink, Loes I organization: MESA+Institute for Nanotechnology, BIOS Lab on a Chip Group, Technical Medical Centre, Max Planck Center for Com-plex Fluid Dynamics, University of Twente, Enschede, The Netherlands – sequence: 10 givenname: Christine L surname: Mummery fullname: Mummery, Christine L organization: Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands – sequence: 11 givenname: Pasqualina M surname: Sarro fullname: Sarro, Pasqualina M organization: Microelectronics, Delft University of Technology, Delft, The Netherlands – sequence: 12 givenname: Berend J surname: van Meer fullname: van Meer, Berend J organization: Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands – sequence: 13 givenname: Marcelo C surname: Ribeiro fullname: Ribeiro, Marcelo C organization: River BioMedics, Enschede, The Netherlands – sequence: 14 givenname: Massimo orcidid: 0000-0003-3265-5768 surname: Mastrangeli fullname: Mastrangeli, Massimo organization: Microelectronics, Delft University of Technology, Delft, The Netherlands – sequence: 15 givenname: Robert orcidid: 0000-0003-4312-9296 surname: Passier fullname: Passier, Robert organization: Department of Anatomy and Embryology, Leiden University Medical Centre, Leiden, The Netherlands |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39946364$$D View this record in MEDLINE/PubMed |
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| Copyright | Copyright: © 2025 Rivera-Arbeláez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2025 Public Library of Science 2025 Rivera-Arbeláez 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. 2025 Rivera-Arbeláez et al 2025 Rivera-Arbeláez et al 2025 Rivera-Arbeláez 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. |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: R.P. is a co-founder of Pluriomics (Ncardia) and River BioMed-ics BV. M.C.R. is a co-founder of River BioMedics BV. A.v.d.B. is a scientific advisor of River BioMedics BV. C.L.M. is co-founder of Pluriomics (Ncardia). The other authors report no conflicts. |
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| Snippet | Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in... |
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| SubjectTerms | 3D printing Air bubbles Algorithms Analysis Animals Aprotinin Biology and Life Sciences Biomechanics Cardiomyocytes Cell interactions Computer and Information Sciences Contractility (Biology) Drug development Drug discovery Engineering and Technology Fibroblasts Heart - physiology Heart muscle Human motion Humans Industrial development Lab-On-A-Chip Devices Medical research Medicine and Health Sciences Medicine, Experimental Methods Motion perception Muscle contraction Myocardial Contraction - physiology Myocytes, Cardiac - cytology Myocytes, Cardiac - physiology Optical tracking Physical Sciences Physiological aspects Platforms Python Real property Research and Analysis Methods Robustness Software Tissue analysis Tissue engineering Tissue Engineering - methods Valuation |
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| Title | FORCETRACKER: A versatile tool for standardized assessment of tissue contractile properties in 3D Heart-on-Chip platforms |
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