Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon
The frontiers of bioimaging are currently being pushed toward the integration and correlation of several modalities to tackle biomedical research questions holistically and across multiple scales. Correlated Multimodal Imaging (CMI) gathers information about exactly the same specimen with two or mor...
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Format: | Article |
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Frontiers Media S.A.
2020-04-01
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Series: | Frontiers in Physics |
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Online Access: | https://www.frontiersin.org/article/10.3389/fphy.2020.00047/full |
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doaj-b351d43f762e4b51bf0b5203308a8644 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Andreas Walter Perrine Paul-Gilloteaux Perrine Paul-Gilloteaux Birgit Plochberger Ludek Sefc Paul Verkade Julia G. Mannheim Julia G. Mannheim Julia G. Mannheim Paul Slezak Angelika Unterhuber Martina Marchetti-Deschmann Manfred Ogris Katja Bühler Dror Fixler Stefan H. Geyer Wolfgang J. Weninger Martin Glösmann Stephan Handschuh Thomas Wanek |
spellingShingle |
Andreas Walter Perrine Paul-Gilloteaux Perrine Paul-Gilloteaux Birgit Plochberger Ludek Sefc Paul Verkade Julia G. Mannheim Julia G. Mannheim Julia G. Mannheim Paul Slezak Angelika Unterhuber Martina Marchetti-Deschmann Manfred Ogris Katja Bühler Dror Fixler Stefan H. Geyer Wolfgang J. Weninger Martin Glösmann Stephan Handschuh Thomas Wanek Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon Frontiers in Physics bioimaging correlated multimodal imaging CMI COMULIS CLEM correlative microscopy |
author_facet |
Andreas Walter Perrine Paul-Gilloteaux Perrine Paul-Gilloteaux Birgit Plochberger Ludek Sefc Paul Verkade Julia G. Mannheim Julia G. Mannheim Julia G. Mannheim Paul Slezak Angelika Unterhuber Martina Marchetti-Deschmann Manfred Ogris Katja Bühler Dror Fixler Stefan H. Geyer Wolfgang J. Weninger Martin Glösmann Stephan Handschuh Thomas Wanek |
author_sort |
Andreas Walter |
title |
Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon |
title_short |
Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon |
title_full |
Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon |
title_fullStr |
Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon |
title_full_unstemmed |
Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon |
title_sort |
correlated multimodal imaging in life sciences: expanding the biomedical horizon |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Physics |
issn |
2296-424X |
publishDate |
2020-04-01 |
description |
The frontiers of bioimaging are currently being pushed toward the integration and correlation of several modalities to tackle biomedical research questions holistically and across multiple scales. Correlated Multimodal Imaging (CMI) gathers information about exactly the same specimen with two or more complementary modalities that—in combination—create a composite and complementary view of the sample (including insights into structure, function, dynamics and molecular composition). CMI allows to describe biomedical processes within their overall spatio-temporal context and gain a mechanistic understanding of cells, tissues, diseases or organisms by untangling their molecular mechanisms within their native environment. The two best-established CMI implementations for small animals and model organisms are hardware-fused platforms in preclinical imaging (Hybrid Imaging) and Correlated Light and Electron Microscopy (CLEM) in biological imaging. Although the merits of Preclinical Hybrid Imaging (PHI) and CLEM are well-established, both approaches would benefit from standardization of protocols, ontologies and data handling, and the development of optimized and advanced implementations. Specifically, CMI pipelines that aim at bridging preclinical and biological imaging beyond CLEM and PHI are rare but bear great potential to substantially advance both bioimaging and biomedical research. CMI faces three main challenges for its routine use in biomedical research: (1) Sample handling and preparation procedures that are compatible across modalities without compromising data quality, (2) soft- and hardware solutions to relocate the same region of interest (ROI) after transfer between imaging platforms including fiducial markers, and (3) automated software solutions to correlate complex, multiscale, multimodal and volumetric image data including reconstruction, segmentation and visualization. This review goes beyond preclinical imaging and puts accessible information into a broader imaging context. We present a comprehensive overview of the field of CMI from preclinical hybrid imaging to correlative microscopy, highlight requirements for optimization and standardization, present a synopsis of current solutions to challenges of the field and focus on current efforts to bridge the gap between preclinical and biological imaging (from small animals down to single cells and molecules). The review is in line with major European initiatives, such as COMULIS (CA17121), a COST Action to promote and foster Correlated Multimodal Imaging in Life Sciences. |
topic |
bioimaging correlated multimodal imaging CMI COMULIS CLEM correlative microscopy |
url |
https://www.frontiersin.org/article/10.3389/fphy.2020.00047/full |
work_keys_str_mv |
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doaj-b351d43f762e4b51bf0b5203308a86442020-11-25T02:04:51ZengFrontiers Media S.A.Frontiers in Physics2296-424X2020-04-01810.3389/fphy.2020.00047516154Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical HorizonAndreas Walter0Perrine Paul-Gilloteaux1Perrine Paul-Gilloteaux2Birgit Plochberger3Ludek Sefc4Paul Verkade5Julia G. Mannheim6Julia G. Mannheim7Julia G. Mannheim8Paul Slezak9Angelika Unterhuber10Martina Marchetti-Deschmann11Manfred Ogris12Katja Bühler13Dror Fixler14Stefan H. Geyer15Wolfgang J. Weninger16Martin Glösmann17Stephan Handschuh18Thomas Wanek19BioImaging Austria/CMI, Vienna BioCenter Core Facilities, Vienna, AustriaUniversité de Nantes, CNRS, INSERM, l'institut du thorax, Nantes, FranceNantes Université, CHU Nantes, Inserm, CNRS, SFR Santé, Inserm UMS 016, CNRS UMS 3556, Nantes, FranceUpper Austria University of Applied Sciences, Medical Engineering, BioImaging Austria/CMI, Linz, AustriaCenter for Advanced Preclinical Imaging (CAPI), First Faculty of Medicine, Charles University, Prague, CzechiaSchool of Biochemistry, University of Bristol, Bristol, United KingdomDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard-Karls University Tübingen, Tübingen, GermanyDepartment of Physics and Astronomy, University of British Columbia, Vancouver, BC, CanadaCluster of Excellence iFIT (EXC 2180) “Image Guided and Functionally Instructed Tumor Therapies”, University of Tuebingen, Tübingen, Germany0Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, BioImaging Austria/CMI, Vienna, Austria1Center for Medical Physics and Biomedical Engineering, BioImaging Austria/CMI, Medical University of Vienna, Vienna, Austria2Mass Spectrometric Bio- and Polymeranalysis, Institute of Chemical Technologies and Analytics, BioImaging Austria/CMI, TU Wien, Vienna, Austria3Laboratory of MacroMolecular Cancer Therapeutics (MMCT), Department of Pharmaceutical Chemistry, Center of Pharmaceutical Sciences, BioImaging Austria/CMI, University of Vienna, Vienna, Austria4VRVis Zentrum für Virtual Reality und Visualisierung Forschungs GmbH, BioImaging Austria/CMI, Vienna, Austria5Laboratory of Advance Microscopy LAB, Faculty of Engineering, Institute of Nanotechnology and Advanced Materials, Bar Ilan University, Ramat Gan, Israel6Division of Anatomy, Center for Anatomy and Cell Biology, BioImaging Austria/CMI, Medical University of Vienna, Vienna, Austria6Division of Anatomy, Center for Anatomy and Cell Biology, BioImaging Austria/CMI, Medical University of Vienna, Vienna, Austria7VetCore Facility for Research, Imaging Unit, BioImaging Austria/CMI, University of Veterinary Medicine Vienna, Vienna, Austria7VetCore Facility for Research, Imaging Unit, BioImaging Austria/CMI, University of Veterinary Medicine Vienna, Vienna, Austria8Preclinical Molecular Imaging, BioImaging Austria/CMI, AIT Austrian Institute of Technology GmbH, Seibersdorf, AustriaThe frontiers of bioimaging are currently being pushed toward the integration and correlation of several modalities to tackle biomedical research questions holistically and across multiple scales. Correlated Multimodal Imaging (CMI) gathers information about exactly the same specimen with two or more complementary modalities that—in combination—create a composite and complementary view of the sample (including insights into structure, function, dynamics and molecular composition). CMI allows to describe biomedical processes within their overall spatio-temporal context and gain a mechanistic understanding of cells, tissues, diseases or organisms by untangling their molecular mechanisms within their native environment. The two best-established CMI implementations for small animals and model organisms are hardware-fused platforms in preclinical imaging (Hybrid Imaging) and Correlated Light and Electron Microscopy (CLEM) in biological imaging. Although the merits of Preclinical Hybrid Imaging (PHI) and CLEM are well-established, both approaches would benefit from standardization of protocols, ontologies and data handling, and the development of optimized and advanced implementations. Specifically, CMI pipelines that aim at bridging preclinical and biological imaging beyond CLEM and PHI are rare but bear great potential to substantially advance both bioimaging and biomedical research. CMI faces three main challenges for its routine use in biomedical research: (1) Sample handling and preparation procedures that are compatible across modalities without compromising data quality, (2) soft- and hardware solutions to relocate the same region of interest (ROI) after transfer between imaging platforms including fiducial markers, and (3) automated software solutions to correlate complex, multiscale, multimodal and volumetric image data including reconstruction, segmentation and visualization. This review goes beyond preclinical imaging and puts accessible information into a broader imaging context. We present a comprehensive overview of the field of CMI from preclinical hybrid imaging to correlative microscopy, highlight requirements for optimization and standardization, present a synopsis of current solutions to challenges of the field and focus on current efforts to bridge the gap between preclinical and biological imaging (from small animals down to single cells and molecules). The review is in line with major European initiatives, such as COMULIS (CA17121), a COST Action to promote and foster Correlated Multimodal Imaging in Life Sciences.https://www.frontiersin.org/article/10.3389/fphy.2020.00047/fullbioimagingcorrelated multimodal imagingCMICOMULISCLEMcorrelative microscopy |