Removing physiological motion from intravital and clinical functional imaging data

Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime...

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Vydáno v:eLife Ročník 7
Hlavní autoři: Warren, Sean C, Nobis, Max, Magenau, Astrid, Mohammed, Yousuf H, Herrmann, David, Moran, Imogen, Vennin, Claire, Conway, James RW, Mélénec, Pauline, Cox, Thomas R, Wang, Yingxiao, Morton, Jennifer P, Welch, Heidi CE, Strathdee, Douglas, Anderson, Kurt I, Phan, Tri Giang, Roberts, Michael S, Timpson, Paul
Médium: Journal Article
Jazyk:angličtina
Vydáno: England eLife Sciences Publications, Ltd 09.07.2018
eLife Sciences Publications Ltd
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ISSN:2050-084X, 2050-084X
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Abstract Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark Galene, a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that Galene is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, Galene can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data. Understanding how molecules and cells behave in living animals can give researchers key insights into what goes wrong in diseases such as cancer, and how well potential treatments for these diseases work. A number of tools help us to see these processes. For example, fluorescent ‘biosensors’ change colour to tell us how active a particular protein is. This can indicate how well a drug works in different parts of a tumour. High resolution microscopy makes it possible to image events happening in single cells, or even specific parts of a cell. However, small movements like those due to the heartbeat or breathing can blur the images, making it difficult to study living animals. This is particularly problematic for images that take several minutes to capture. Warren et al. have now developed a new open source software tool called Galene. The tool can correct for small movements in images collected by a technique called fluorescence lifetime imaging microscopy (FLIM). As a result, clear images can be captured in situations that were not previously possible. For example, Warren et al. watched cancer cells migrating to the liver of a mouse from the spleen over 24 hours, and, using a fluorescent biosensor, showed that a repurposed drug interferes with how well the cells can attach to the liver. In addition, Warren et al. used the software to take steady 3D images of human skin in a volunteer’s arm, which could be used to study drug penetration. Galene could help researchers to study a wide range of biological processes in living animals. The software can also be applied to existing data to clean up blurred images. In the future Galene could be further developed to work with the imaging techniques used during surgery. For example, surgeons could use it to help them find the edges of tumours.
AbstractList Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark Galene, a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that Galene is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, Galene can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data.
Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark Galene, a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that Galene is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, Galene can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data. Understanding how molecules and cells behave in living animals can give researchers key insights into what goes wrong in diseases such as cancer, and how well potential treatments for these diseases work. A number of tools help us to see these processes. For example, fluorescent ‘biosensors’ change colour to tell us how active a particular protein is. This can indicate how well a drug works in different parts of a tumour. High resolution microscopy makes it possible to image events happening in single cells, or even specific parts of a cell. However, small movements like those due to the heartbeat or breathing can blur the images, making it difficult to study living animals. This is particularly problematic for images that take several minutes to capture. Warren et al. have now developed a new open source software tool called Galene. The tool can correct for small movements in images collected by a technique called fluorescence lifetime imaging microscopy (FLIM). As a result, clear images can be captured in situations that were not previously possible. For example, Warren et al. watched cancer cells migrating to the liver of a mouse from the spleen over 24 hours, and, using a fluorescent biosensor, showed that a repurposed drug interferes with how well the cells can attach to the liver. In addition, Warren et al. used the software to take steady 3D images of human skin in a volunteer’s arm, which could be used to study drug penetration. Galene could help researchers to study a wide range of biological processes in living animals. The software can also be applied to existing data to clean up blurred images. In the future Galene could be further developed to work with the imaging techniques used during surgery. For example, surgeons could use it to help them find the edges of tumours.
Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark Galene, a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that Galene is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, Galene can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data.Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark Galene, a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that Galene is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, Galene can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data.
Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark Galene, a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that Galene is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, Galene can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data. Understanding how molecules and cells behave in living animals can give researchers key insights into what goes wrong in diseases such as cancer, and how well potential treatments for these diseases work. A number of tools help us to see these processes. For example, fluorescent ‘biosensors’ change colour to tell us how active a particular protein is. This can indicate how well a drug works in different parts of a tumour. High resolution microscopy makes it possible to image events happening in single cells, or even specific parts of a cell. However, small movements like those due to the heartbeat or breathing can blur the images, making it difficult to study living animals. This is particularly problematic for images that take several minutes to capture. Warren et al. have now developed a new open source software tool called Galene. The tool can correct for small movements in images collected by a technique called fluorescence lifetime imaging microscopy (FLIM). As a result, clear images can be captured in situations that were not previously possible. For example, Warren et al. watched cancer cells migrating to the liver of a mouse from the spleen over 24 hours, and, using a fluorescent biosensor, showed that a repurposed drug interferes with how well the cells can attach to the liver. In addition, Warren et al. used the software to take steady 3D images of human skin in a volunteer’s arm, which could be used to study drug penetration. Galene could help researchers to study a wide range of biological processes in living animals. The software can also be applied to existing data to clean up blurred images. In the future Galene could be further developed to work with the imaging techniques used during surgery. For example, surgeons could use it to help them find the edges of tumours.
Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark , a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data.
Author Welch, Heidi CE
Nobis, Max
Cox, Thomas R
Wang, Yingxiao
Strathdee, Douglas
Magenau, Astrid
Phan, Tri Giang
Herrmann, David
Morton, Jennifer P
Anderson, Kurt I
Vennin, Claire
Mélénec, Pauline
Conway, James RW
Mohammed, Yousuf H
Moran, Imogen
Warren, Sean C
Roberts, Michael S
Timpson, Paul
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Keywords computational biology
systems biology
mouse
cell biology
intravital microscopy
multiphoton
FLIM
FRET
motion correction
human
Language English
License http://creativecommons.org/licenses/by/4.0
2018, Warren et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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  text: 2018-07-09
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PublicationTitle eLife
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eLife Sciences Publications Ltd
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SSID ssj0000748819
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Snippet Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by...
SourceID doaj
pubmedcentral
proquest
pubmed
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
Enrichment Source
SubjectTerms Algorithms
Animals
Biosensing Techniques
Cell Adhesion
Cell Biology
Computational and Systems Biology
Computer Simulation
FLIM
Fluorescence Resonance Energy Transfer
FRET
Guanosine Triphosphate - metabolism
Humans
Imaging, Three-Dimensional
Intestines - physiology
Intravital Microscopy
Mice
Microscopy, Fluorescence
Models, Biological
Motion
motion correction
multiphoton
Neoplasm Metastasis
Neuropeptides - metabolism
Pancreatic Neoplasms - pathology
rac1 GTP-Binding Protein - metabolism
Skin - anatomy & histology
Software
src-Family Kinases - metabolism
Tools and Resources
Title Removing physiological motion from intravital and clinical functional imaging data
URI https://www.ncbi.nlm.nih.gov/pubmed/29985127
https://www.proquest.com/docview/2067139953
https://pubmed.ncbi.nlm.nih.gov/PMC6037484
https://doaj.org/article/b19ab0cf001841f7a2cef5cafceef00f
Volume 7
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