Deep Learning for Automated Analysis of Cellular and Extracellular Components of the Foreign Body Response in Multiphoton Microscopy Images
The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, lo...
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| Published in | Frontiers in bioengineering and biotechnology Vol. 9; p. 797555 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
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Switzerland
Frontiers Media S.A
25.01.2022
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| Online Access | Get full text |
| ISSN | 2296-4185 2296-4185 |
| DOI | 10.3389/fbioe.2021.797555 |
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| Abstract | The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is maintained across different objectives without impairing accuracy. This software for automatically detecting the elements of the FBR shows promise to unravel the complexity of this pathophysiological process. |
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| AbstractList | The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is maintained across different objectives without impairing accuracy. This software for automatically detecting the elements of the FBR shows promise to unravel the complexity of this pathophysiological process. The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is maintained across different objectives without impairing accuracy. This software for automatically detecting the elements of the FBR shows promise to unravel the complexity of this pathophysiological process.The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is maintained across different objectives without impairing accuracy. This software for automatically detecting the elements of the FBR shows promise to unravel the complexity of this pathophysiological process. |
| Author | Cerveri, Pietro Sarti, Mattia Dondossola, Eleonora Diaz-Gomez, Luis Mikos, Antonios G. Parlani, Maria Casarin, Stefano |
| AuthorAffiliation | 2 David H. Koch Center for Applied Research of Genitourinary Cancers and Genitourinary Medical Oncology Department , The University of Texas MD Anderson Cancer Center , Houston , TX , United States 5 Center for Computational Surgery , Houston Methodist Research Institute , Houston , TX , United States 7 Houston Methodist Academic Institute , Houston , TX , United States 6 Department of Surgery , Houston Methodist Hospital , Houston , TX , United States 1 Department of Electronics , Information and Bioengineering , Politecnico di Milano University , Milan , Italy 3 Department of Cell Biology , Radboud University Medical Center , Nijmegen , Netherlands 4 Rice University , Dept. of Bioengineering , Houston , TX , United States |
| AuthorAffiliation_xml | – name: 1 Department of Electronics , Information and Bioengineering , Politecnico di Milano University , Milan , Italy – name: 6 Department of Surgery , Houston Methodist Hospital , Houston , TX , United States – name: 7 Houston Methodist Academic Institute , Houston , TX , United States – name: 3 Department of Cell Biology , Radboud University Medical Center , Nijmegen , Netherlands – name: 2 David H. Koch Center for Applied Research of Genitourinary Cancers and Genitourinary Medical Oncology Department , The University of Texas MD Anderson Cancer Center , Houston , TX , United States – name: 4 Rice University , Dept. of Bioengineering , Houston , TX , United States – name: 5 Center for Computational Surgery , Houston Methodist Research Institute , Houston , TX , United States |
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| Cites_doi | 10.1038/nmeth.2075 10.1364/oe.22.022561 10.1038/nmeth.2089 10.1038/nmat4290 10.1073/pnas.1321139110 10.1002/adhm.201700370 10.1186/s12859-018-2375-z 10.1007/978-1-4939-7113-8_28 10.1016/j.addr.2019.08.010 10.1145/357994.358023 10.1063/1.118442 10.1016/j.media.2020.101841 10.1021/acsbiomaterials.6b00760 10.1016/j.jconrel.2015.07.021 10.1109/ISBI.2019.8759329 10.1016/j.biomaterials.2004.04.017 10.1016/s0146-664x(77)80024-5 10.3390/ma8095269 10.1016/j.actbio.2018.05.051 10.1109/ISCID.2016.1100 10.1038/s41467-020-19851-1 10.1242/jcs.236075 10.1016/j.biomaterials.2006.07.010 10.3390/jfb8040044 10.1016/0022-1759(94)90012-4 10.1038/nbt.3462 10.1109/cvpr.2019.00075 10.1007/s10237-011-0325-z 10.1038/s41578-021-00369-x 10.1208/s12248-010-9175-3 10.1371/journal.pone.0130386 10.1038/nm.2989 10.3389/fbioe.2020.00198 10.1007/978-3-319-24574-4_28 10.1016/j.biomaterials.2016.02.036 10.1208/aapsj070122 10.1038/s41592-020-01008-z 10.1002/adfm.202170040 10.1371/journal.pcbi.1009451 10.1109/tmi.2018.2806086 10.1038/nmeth.2019 10.1016/j.smim.2007.11.004 10.1038/s41551-016-0007 10.1038/nbt.2580 10.21037/qims-19-1090 10.1016/j.media.2021.102039 10.1016/j.media.2020.101786 |
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| Copyright | Copyright © 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola. Copyright © 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola. 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola |
| Copyright_xml | – notice: Copyright © 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola. – notice: Copyright © 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola. 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola |
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| Keywords | deep learning intravital multiphoton microscopy foreign body response image analysis U-Net |
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| License | Copyright © 2022 Sarti, Parlani, Diaz-Gomez, Mikos, Cerveri, Casarin and Dondossola. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: David Grainger, The University of Utah, United States These authors have contributed equally to this work and share senior authorship These authors have contributed equally to this work and share first authorship Stefan G. Stanciu, Politehnica University of Bucharest, Romania Edited by: Bryan Brown, University of Pittsburgh, United States This article was submitted to Tissue Engineering and Regenerative Medicine, a section of the journal Frontiers in Bioengineering and Biotechnology |
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| References | Kingma (B21) 2014 Dondossola (B11) 2022; 7 Morris (B30) 2017; 6 Vegas (B44) 2016; 34 Bancelin (B5) 2014; 22 Prakasam (B32) 2017; 8 Dumoulin (B13) 2016 Ronneberger (B36) 2015 de Vos (B9) 2006; 27 Veiseh (B46) 2019; 144 Moore (B28) 2016; 89 Schneider (B38) 2012; 9 Al-Kofahi (B3) 2018; 19 Anderson (B4) 2008; 20 Abraham (B1) 2019 Gurevich (B16) 2020; 133 Dondossola (B10) 2016; 1 Van Rooijen (B43) 1994; 174 Zhang (B49) 2021; 31 Ulku (B42) 2019 Liu (B25) 2017 Shayan (B39) 2018; 75 Zhang (B50) 2013; 31 Zhang (B51) 1984; 27 Masters (B26) 2018 Isensee (B19) 2021; 18 Kose (B23) 2021; 67 Dondossola (B12) 2013; 110 Kastellorizios (B20) 2015; 214 Fan (B14) 2020; 11 Novikov (B31) 2018; 37 Shen (B41) 2018 Veiseh (B45) 2015; 14 Galeska (B15) 2005; 7 Klueh (B22) 2005; 26 Rezatofighi (B34) 2019 Mihelic (B27) 2021; 17 Akilbekova (B2) 2015; 10 Barad (B6) 1997; 70 Robinson (B35) 1977; 6 Zhao (B52) 2020; 65 Liu (B24) 2020; 8 de Chaumont (B8) 2012; 9 LeBleu (B53) 2013; 19 Schindelin (B37) 2012; 9 Morais (B29) 2010; 12 Rezakhaniha (B33) 2012; 11 Yao (B48) 2016 Ioffe (B18) 2015 Cai (B7) 2020; 10 Sheikh (B40) 2015; 8 He (B17) 2021; 71 Witherel (B47) 2018; 4 |
| References_xml | – volume: 9 start-page: 690 year: 2012 ident: B8 article-title: Icy: an Open Bioimage Informatics Platform for Extended Reproducible Research publication-title: Nat. Methods doi: 10.1038/nmeth.2075 – volume: 22 start-page: 22561 year: 2014 ident: B5 article-title: Determination of Collagen Fiber Orientation in Histological Slides Using Mueller Microscopy and Validation by Second Harmonic Generation Imaging publication-title: Opt. Express doi: 10.1364/oe.22.022561 – volume: 9 start-page: 671 year: 2012 ident: B38 article-title: NIH Image to ImageJ: 25 Years of Image Analysis publication-title: Nat. Methods doi: 10.1038/nmeth.2089 – volume-title: On the Influence of Dice Loss Function in Multi-Class Organ Segmentation of Abdominal CT Using 3D Fully Convolutional Networks year: 2018 ident: B41 – volume: 14 start-page: 643 year: 2015 ident: B45 article-title: Size- and Shape-dependent Foreign Body Immune Response to Materials Implanted in Rodents and Non-human Primates publication-title: Nat. Mater doi: 10.1038/nmat4290 – volume-title: Adam: A Method for Stochastic Optimization year: 2014 ident: B21 – volume: 110 start-page: 20717 year: 2013 ident: B12 article-title: CD13-positive Bone Marrow-Derived Myeloid Cells Promote Angiogenesis, Tumor Growth, and Metastasis publication-title: Proc. Natl. Acad. Sci. doi: 10.1073/pnas.1321139110 – volume: 6 start-page: 1700370 year: 2017 ident: B30 article-title: Multicompartment Drug Release System for Dynamic Modulation of Tissue Responses publication-title: Adv. Healthc. Mater. doi: 10.1002/adhm.201700370 – volume: 19 start-page: 365 year: 2018 ident: B3 article-title: A Deep Learning-Based Algorithm for 2-D Cell Segmentation in Microscopy Images publication-title: BMC Bioinformatics doi: 10.1186/s12859-018-2375-z – start-page: 429 volume-title: Fibrosis: Methods and Protocols year: 2017 ident: B25 article-title: Methods for Quantifying Fibrillar Collagen Alignment doi: 10.1007/978-1-4939-7113-8_28 – volume: 144 start-page: 148 year: 2019 ident: B46 article-title: Domesticating the Foreign Body Response: Recent Advances and Applications publication-title: Adv. Drug Deliv. Rev. doi: 10.1016/j.addr.2019.08.010 – volume: 27 start-page: 236 year: 1984 ident: B51 article-title: A Fast Parallel Algorithm for Thinning Digital Patterns publication-title: Commun. ACM doi: 10.1145/357994.358023 – volume: 70 start-page: 922 year: 1997 ident: B6 article-title: Nonlinear Scanning Laser Microscopy by Third Harmonic Generation publication-title: Appl. Phys. Lett. doi: 10.1063/1.118442 – volume: 67 start-page: 101841 year: 2021 ident: B23 article-title: Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions In Vivo via a Multiscale Encoder-Decoder Network (MED-Net) publication-title: Med. Image Anal. doi: 10.1016/j.media.2020.101841 – volume: 4 start-page: 1233 year: 2018 ident: B47 article-title: Host-Biomaterial Interactions in Zebrafish publication-title: ACS Biomater. Sci. Eng. doi: 10.1021/acsbiomaterials.6b00760 – volume: 214 start-page: 103 year: 2015 ident: B20 article-title: Multiple Tissue Response Modifiers to Promote Angiogenesis and Prevent the Foreign Body Reaction Around Subcutaneous Implants publication-title: J. Controlled Release doi: 10.1016/j.jconrel.2015.07.021 – year: 2019 ident: B1 article-title: A Novel Focal Tversky Loss Function with Improved Attention U-Net for Lesion Segmentation doi: 10.1109/ISBI.2019.8759329 – volume: 26 start-page: 1155 year: 2005 ident: B22 article-title: Enhancement of Implantable Glucose Sensor Function In Vivo Using Gene Transfer-Induced Neovascularization publication-title: Biomaterials doi: 10.1016/j.biomaterials.2004.04.017 – volume: 6 start-page: 492 year: 1977 ident: B35 article-title: Edge Detection by Compass Gradient Masks publication-title: Comput. Graphics Image Process. doi: 10.1016/s0146-664x(77)80024-5 – volume: 8 start-page: 5671 year: 2015 ident: B40 article-title: Macrophages, Foreign Body Giant Cells and Their Response to Implantable Biomaterials publication-title: Materials doi: 10.3390/ma8095269 – volume: 75 start-page: 427 year: 2018 ident: B39 article-title: Nanopatterned Bulk Metallic Glass-Based Biomaterials Modulate Macrophage Polarization publication-title: Acta Biomater. doi: 10.1016/j.actbio.2018.05.051 – year: 2016 ident: B48 article-title: Convolutional Neural Network for Retinal Blood Vessel Segmentation doi: 10.1109/ISCID.2016.1100 – volume: 11 start-page: 6020 year: 2020 ident: B14 article-title: High-speed Volumetric Two-Photon Fluorescence Imaging of Neurovascular Dynamics publication-title: Nat. Commun. doi: 10.1038/s41467-020-19851-1 – volume: 133 start-page: jcs236075 year: 2020 ident: B16 article-title: Live Imaging the Foreign Body Response in Zebrafish Reveals How Dampening Inflammation Reduces Fibrosis publication-title: J. Cel Sci doi: 10.1242/jcs.236075 – volume-title: Revisiting Small Batch Training for Deep Neural Networks year: 2018 ident: B26 – volume: 27 start-page: 5603 year: 2006 ident: B9 article-title: Alginate-based Microcapsules for Immunoisolation of Pancreatic Islets publication-title: Biomaterials doi: 10.1016/j.biomaterials.2006.07.010 – volume: 8 start-page: 44-58 year: 2017 ident: B32 article-title: Biodegradable Materials and Metallic Implants-A Review publication-title: J. Funct. Biomater. doi: 10.3390/jfb8040044 – volume: 174 start-page: 83 year: 1994 ident: B43 article-title: Liposome Mediated Depletion of Macrophages: Mechanism of Action, Preparation of Liposomes and Applications publication-title: J. Immunol. Methods doi: 10.1016/0022-1759(94)90012-4 – volume: 34 start-page: 345 year: 2016 ident: B44 article-title: Combinatorial Hydrogel Library Enables Identification of Materials that Mitigate the Foreign Body Response in Primates publication-title: Nat. Biotechnol. doi: 10.1038/nbt.3462 – year: 2019 ident: B34 article-title: Generalized Intersection over Union: A Metric and a Loss for Bounding Box Regression doi: 10.1109/cvpr.2019.00075 – volume: 11 start-page: 461 year: 2012 ident: B33 article-title: Experimental Investigation of Collagen Waviness and Orientation in the Arterial Adventitia Using Confocal Laser Scanning Microscopy publication-title: Biomech. Model. Mechanobiol doi: 10.1007/s10237-011-0325-z – volume: 7 start-page: 6-22 year: 2022 ident: B11 article-title: Host Responses to Implants Revealed by Intravital Microscopy publication-title: Nat. Rev. Mater doi: 10.1038/s41578-021-00369-x – volume: 12 start-page: 188 year: 2010 ident: B29 article-title: Biomaterials/tissue Interactions: Possible Solutions to Overcome Foreign Body Response publication-title: AAPS J. doi: 10.1208/s12248-010-9175-3 – volume: 10 start-page: e0130386 year: 2015 ident: B2 article-title: Quantitative Characterization of Collagen in the Fibrotic Capsule Surrounding Implanted Polymeric Microparticles through Second Harmonic Generation Imaging publication-title: PLoS One doi: 10.1371/journal.pone.0130386 – volume: 19 start-page: 227 year: 2013 ident: B53 article-title: Identification of human epididymis protein-4 as a fibroblast-derived mediator of fibrosis publication-title: Nature Medicine doi: 10.1038/nm.2989 – volume: 8 start-page: 198 year: 2020 ident: B24 article-title: Fibrillar Collagen Quantification with Curvelet Transform Based Computational Methods publication-title: Front. Bioeng. Biotechnol. doi: 10.3389/fbioe.2020.00198 – volume-title: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 year: 2015 ident: B36 article-title: Convolutional Networks for Biomedical Image Segmentation doi: 10.1007/978-3-319-24574-4_28 – volume: 89 start-page: 127 year: 2016 ident: B28 article-title: Nanoparticle Delivery of miR-223 to Attenuate Macrophage Fusion publication-title: Biomaterials doi: 10.1016/j.biomaterials.2016.02.036 – volume: 7 start-page: E231 year: 2005 ident: B15 article-title: Controlled Release of Dexamethasone from PLGA Microspheres Embedded within Polyacid-Containing PVA Hydrogels publication-title: Aaps J. doi: 10.1208/aapsj070122 – volume: 18 start-page: 203 year: 2021 ident: B19 article-title: nnU-Net: a Self-Configuring Method for Deep Learning-Based Biomedical Image Segmentation publication-title: Nat. Methods doi: 10.1038/s41592-020-01008-z – volume-title: A Survey on Deep Learning-Based Architectures for Semantic Segmentation on 2D Images year: 2019 ident: B42 – volume: 31 start-page: 2170040 year: 2021 ident: B49 article-title: Dealing with the Foreign-Body Response to Implanted Biomaterials: Strategies and Applications of New Materials publication-title: Adv. Funct. Mater. doi: 10.1002/adfm.202170040 – volume: 17 start-page: e1009451 year: 2021 ident: B27 article-title: Segmentation-Less, Automated, Vascular Vectorization publication-title: Plos Comput. Biol. doi: 10.1371/journal.pcbi.1009451 – volume: 37 start-page: 1865 year: 2018 ident: B31 article-title: Fully Convolutional Architectures for Multiclass Segmentation in Chest Radiographs publication-title: IEEE Trans. Med. Imaging doi: 10.1109/tmi.2018.2806086 – volume: 9 start-page: 676 year: 2012 ident: B37 article-title: Fiji: an Open-Source Platform for Biological-Image Analysis publication-title: Nat. Methods doi: 10.1038/nmeth.2019 – start-page: 448 year: 2015 ident: B18 article-title: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift – volume: 20 start-page: 86 year: 2008 ident: B4 article-title: Foreign Body Reaction to Biomaterials publication-title: Semin. Immunol. doi: 10.1016/j.smim.2007.11.004 – volume: 1 start-page: 0007 year: 2016 ident: B10 article-title: Examination of the Foreign Body Response to Biomaterials by Nonlinear Intravital Microscopy publication-title: Nat. Biomed. Eng. doi: 10.1038/s41551-016-0007 – volume: 31 start-page: 553 year: 2013 ident: B50 article-title: Zwitterionic Hydrogels Implanted in Mice Resist the Foreign-Body Reaction publication-title: Nat. Biotechnol. doi: 10.1038/nbt.2580 – volume: 10 start-page: 1275 year: 2020 ident: B7 article-title: Dense-UNet: a Novel Multiphoton In Vivo Cellular Image Segmentation Model Based on a Convolutional Neural Network publication-title: Quant Imaging Med. Surg. doi: 10.21037/qims-19-1090 – volume-title: A Guide to Convolution Arithmetic for Deep Learning year: 2016 ident: B13 – volume: 71 start-page: 102039 year: 2021 ident: B17 article-title: MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise Prostate Segmentation via Online Sampling publication-title: Med. Image Anal. doi: 10.1016/j.media.2021.102039 – volume: 65 start-page: 101786 year: 2020 ident: B52 article-title: Triple U-Net: Hematoxylin-Aware Nuclei Segmentation with Progressive Dense Feature Aggregation publication-title: Med. Image Anal. doi: 10.1016/j.media.2020.101786 |
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| SubjectTerms | Bioengineering and Biotechnology deep learning foreign body response image analysis intravital multiphoton microscopy U-Net |
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| Title | Deep Learning for Automated Analysis of Cellular and Extracellular Components of the Foreign Body Response in Multiphoton Microscopy Images |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/35145962 https://www.proquest.com/docview/2628294514 https://pubmed.ncbi.nlm.nih.gov/PMC8822221 https://doaj.org/article/2153f7cff54c4b5caf7958e207a54b97 |
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