In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging
Identifieur interne : 000961 ( Pmc/Curation ); précédent : 000960; suivant : 000962In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging
Auteurs : Chloé Chong [Suisse] ; Felix Scholkmann [Suisse] ; Samia B. Bachmann [Suisse] ; Paola Luciani [Suisse] ; Jean-Christophe Leroux [Suisse] ; Michael Detmar [Suisse] ; Steven T. Proulx [Suisse]Source :
- Scientific Reports [ 2045-2322 ] ; 2016.
Abstract
Techniques to image lymphatic vessel function in either animal models or in the clinic are limited. In particular, imaging methods that can provide robust outcome measures for collecting lymphatic vessel function are sorely needed. In this study, we aimed to develop a method to visualize and quantify collecting lymphatic vessel function in mice, and to establish an
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DOI: 10.1038/srep22930
PubMed: 26960708
PubMed Central: 4785392
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging</title><author><name sortKey="Chong, Chloe" sort="Chong, Chloe" uniqKey="Chong C" first="Chloé" last="Chong">Chloé Chong</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Scholkmann, Felix" sort="Scholkmann, Felix" uniqKey="Scholkmann F" first="Felix" last="Scholkmann">Felix Scholkmann</name><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich</institution>, 8091 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Bachmann, Samia B" sort="Bachmann, Samia B" uniqKey="Bachmann S" first="Samia B." last="Bachmann">Samia B. Bachmann</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Luciani, Paola" sort="Luciani, Paola" uniqKey="Luciani P" first="Paola" last="Luciani">Paola Luciani</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Leroux, Jean Christophe" sort="Leroux, Jean Christophe" uniqKey="Leroux J" first="Jean-Christophe" last="Leroux">Jean-Christophe Leroux</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Detmar, Michael" sort="Detmar, Michael" uniqKey="Detmar M" first="Michael" last="Detmar">Michael Detmar</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Proulx, Steven T" sort="Proulx, Steven T" uniqKey="Proulx S" first="Steven T." last="Proulx">Steven T. Proulx</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">26960708</idno><idno type="pmc">4785392</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4785392</idno><idno type="RBID">PMC:4785392</idno><idno type="doi">10.1038/srep22930</idno><date when="2016">2016</date><idno type="wicri:Area/Pmc/Corpus">000961</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000961</idno><idno type="wicri:Area/Pmc/Curation">000961</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000961</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging</title><author><name sortKey="Chong, Chloe" sort="Chong, Chloe" uniqKey="Chong C" first="Chloé" last="Chong">Chloé Chong</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Scholkmann, Felix" sort="Scholkmann, Felix" uniqKey="Scholkmann F" first="Felix" last="Scholkmann">Felix Scholkmann</name><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich</institution>, 8091 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Bachmann, Samia B" sort="Bachmann, Samia B" uniqKey="Bachmann S" first="Samia B." last="Bachmann">Samia B. Bachmann</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Luciani, Paola" sort="Luciani, Paola" uniqKey="Luciani P" first="Paola" last="Luciani">Paola Luciani</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Leroux, Jean Christophe" sort="Leroux, Jean Christophe" uniqKey="Leroux J" first="Jean-Christophe" last="Leroux">Jean-Christophe Leroux</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Detmar, Michael" sort="Detmar, Michael" uniqKey="Detmar M" first="Michael" last="Detmar">Michael Detmar</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Proulx, Steven T" sort="Proulx, Steven T" uniqKey="Proulx S" first="Steven T." last="Proulx">Steven T. Proulx</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></analytic><series><title level="j">Scientific Reports</title><idno type="eISSN">2045-2322</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Techniques to image lymphatic vessel function in either animal models or in the clinic are limited. In particular, imaging methods that can provide robust outcome measures for collecting lymphatic vessel function are sorely needed. In this study, we aimed to develop a method to visualize and quantify collecting lymphatic vessel function in mice, and to establish an <italic>in vivo</italic> system for evaluation of contractile agonists and antagonists using near-infrared fluorescence imaging. The flank collecting lymphatic vessel in mice was exposed using a surgical technique and a near-infrared tracer was infused into the inguinal lymph node. Collecting lymphatic vessel contractility and valve function could be easily visualized after the infusion. A diameter tracking method was established and the diameter of the vessel was found to closely correlate to near-infrared fluorescence signal. Phasic contractility measures of frequency and amplitude were established using an automated algorithm. The methods were validated by tracking the vessel response to topical application of a contractile agonist, prostaglandin F2α, and by demonstrating the potential of the technique for non-invasive evaluation of modifiers of lymphatic function. These new methods will enable high-resolution imaging and quantification of collecting lymphatic vessel function in animal models and may have future clinical applications.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Yang, Y" uniqKey="Yang Y">Y. Yang</name></author><author><name sortKey="Oliver, G" uniqKey="Oliver G">G. Oliver</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Alitalo, K" uniqKey="Alitalo K">K. Alitalo</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zawieja, D C" uniqKey="Zawieja D">D. C. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Sci Rep</journal-id><journal-id journal-id-type="iso-abbrev">Sci Rep</journal-id><journal-title-group><journal-title>Scientific Reports</journal-title></journal-title-group><issn pub-type="epub">2045-2322</issn><publisher><publisher-name>Nature Publishing Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">26960708</article-id><article-id pub-id-type="pmc">4785392</article-id><article-id pub-id-type="pii">srep22930</article-id><article-id pub-id-type="doi">10.1038/srep22930</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Chong</surname><given-names>Chloé</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="author-notes" rid="n1">*</xref></contrib><contrib contrib-type="author"><name><surname>Scholkmann</surname><given-names>Felix</given-names></name><xref ref-type="aff" rid="a2">2</xref><xref ref-type="author-notes" rid="n1">*</xref></contrib><contrib contrib-type="author"><name><surname>Bachmann</surname><given-names>Samia B.</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Luciani</surname><given-names>Paola</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Leroux</surname><given-names>Jean-Christophe</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Detmar</surname><given-names>Michael</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Proulx</surname><given-names>Steven T.</given-names></name><xref ref-type="corresp" rid="c1">a</xref><xref ref-type="aff" rid="a1">1</xref></contrib><aff id="a1"><label>1</label><institution>Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology, ETH Zurich</institution>, 8093 Zurich,<country>Switzerland</country></aff><aff id="a2"><label>2</label><institution>Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich</institution>, 8091 Zurich,<country>Switzerland</country></aff></contrib-group><author-notes><corresp id="c1"><label>a</label><email>steven.proulx@pharma.ethz.ch</email></corresp><fn id="n1"><label>*</label><p>These authors contributed equally to this work.</p></fn></author-notes><pub-date pub-type="epub"><day>10</day><month>03</month><year>2016</year></pub-date><pub-date pub-type="collection"><year>2016</year></pub-date><volume>6</volume><elocation-id>22930</elocation-id><history><date date-type="received"><day>02</day><month>11</month><year>2015</year></date><date date-type="accepted"><day>24</day><month>02</month><year>2016</year></date></history><permissions><copyright-statement>Copyright © 2016, Macmillan Publishers Limited</copyright-statement><copyright-year>2016</copyright-year><copyright-holder>Macmillan Publishers Limited</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/"><pmc-comment>author-paid</pmc-comment>
<license-p>This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><abstract><p>Techniques to image lymphatic vessel function in either animal models or in the clinic are limited. In particular, imaging methods that can provide robust outcome measures for collecting lymphatic vessel function are sorely needed. In this study, we aimed to develop a method to visualize and quantify collecting lymphatic vessel function in mice, and to establish an <italic>in vivo</italic> system for evaluation of contractile agonists and antagonists using near-infrared fluorescence imaging. The flank collecting lymphatic vessel in mice was exposed using a surgical technique and a near-infrared tracer was infused into the inguinal lymph node. Collecting lymphatic vessel contractility and valve function could be easily visualized after the infusion. A diameter tracking method was established and the diameter of the vessel was found to closely correlate to near-infrared fluorescence signal. Phasic contractility measures of frequency and amplitude were established using an automated algorithm. The methods were validated by tracking the vessel response to topical application of a contractile agonist, prostaglandin F2α, and by demonstrating the potential of the technique for non-invasive evaluation of modifiers of lymphatic function. These new methods will enable high-resolution imaging and quantification of collecting lymphatic vessel function in animal models and may have future clinical applications.</p></abstract></article-meta></front><floats-group><fig id="f1"><label>Figure 1</label><caption><title>Visualization of a contractile CLV in mice after inguinal lymph node infusion of P20D680.</title><p>(<bold>a</bold>) Schematic of setup for inguinal lymph node infusion. (<bold>b</bold>) Prox1-GFP image of inguinal lymph node and efferent CLV. (<bold>c</bold>) NIR image after lymph node infusion with efferent lymphatic vessel perfused with P20D680. (<bold>d</bold>) Prox1-GFP signal of stages of contraction cycle of CLV at 63× magnification. (<bold>e</bold>) NIR signal of stages of contraction cycle at 63×.</p></caption><graphic xlink:href="srep22930-f1"></graphic></fig><fig id="f2"><label>Figure 2</label><caption><title>Diameter tracking of CLVs.</title><p>(<bold>a</bold>) Signal profile of line bisecting a Prox1-GFP CLV. (<bold>b</bold>) Signal profile of line bisecting a P20D680 perfused CLV. (<bold>c</bold>) ROI analysis to determine appropriate threshold for CLV diameter tracking using NIR signals. (<bold>d</bold>) Contractility plot demonstrating results from diameter tracking using NIR signals of a CLV for a 3-min movie. (<bold>e</bold>) Corresponding contractility plot demonstrating fluorescent signal from region of interest over vessel.</p></caption><graphic xlink:href="srep22930-f2"></graphic></fig><fig id="f3"><label>Figure 3</label><caption><title>Automated assessments of frequency and amplitude from contractility plots of diameter or fluorescence data.</title><p>(<bold>a</bold>) Visual output of Matlab algorithm using diameter tracking data to determine peaks and troughs (red circles), instantaneous mean (blue line in left plot) and instantaneous amplitude (blue line in right plot). Shaded regions represent data that are excluded from the quantification but are necessary for the algorithm to calibrate. (<bold>b</bold>) Visual output of Matlab algorithm using NIR signal data. (<bold>c</bold>) Quantification of frequency in contractions per min. (<bold>d</bold>) Quantification of amplitude expressed as percent of instantaneous mean. n = 15 mice, ***represents P < 0.001 (two-tailed Student’s <italic>t</italic>-test). Data are mean ± SD.</p></caption><graphic xlink:href="srep22930-f3"></graphic></fig><fig id="f4"><label>Figure 4</label><caption><title>Representative NIR signal contractility plots of CLV response to topical treatment of PGF2α.</title><p>Eight-min movies were acquired with administration of 40 μL of either 0.1% DMSO vehicle control or 1 μmol/L, 10 μmol/L or 60 μmol/L PGF2α at t = 2 min. (<bold>a</bold>) Response to 0.1% DMSO. (<bold>b</bold>) Response to 1 μmol/L PGF2α. (<bold>c</bold>) Response to 10 μmol/L PGF2α. (<bold>d</bold>) Response to 60 μmol/L PGF2α.</p></caption><graphic xlink:href="srep22930-f4"></graphic></fig><fig id="f5"><label>Figure 5</label><caption><title>Quantifications from NIR signal contractility plots of CLV response to topical treatment of PGF2α.</title><p>Quantifications from contractility plots from the post treatment period of t = 3 to 6 min were normalized to the baseline data from t = 0 to 2 min and expressed as a % of baseline. (<bold>a</bold>) Frequency of contractions. (<bold>b</bold>) Percent amplitude of contractions. (<bold>c</bold>) Pumping score (frequency x % amplitude). (<bold>d</bold>) Vessel tone. Number of vessels analyzed: n = 14 DMSO, n = 12 1 μmol/L PGF2α, n = 14 10 μmol/L PGF2α, n = 15 60 μmol/L PGF2α. *P < 0.05, **P < 0.01, ***P < 0.001 (one-way ANOVA with Dunnett’s multiple comparison test).</p></caption><graphic xlink:href="srep22930-f5"></graphic></fig><fig id="f6"><label>Figure 6</label><caption><title>Non-invasive imaging of CLV contractility response to skin treatment of NO donor.</title><p>(<bold>a</bold>) Schematic indicating experimental design and a representative picture from non-invasive imaging of CLVs. Each mouse served as its own control with the NO donor (Rectogesic) treatment applied to the left leg and then the control (Linola fett) treatment applied to the right leg. Contractility was assessed in two vessels per leg (yellow ROIs). (<bold>b</bold>) Representative contractility plots from pre- and post-control treatment conditions. (<bold>c</bold>) Representative contractility plots from pre- and post-NO donor treatment conditions. The Y-axis scale is adjusted in each case such that the mean fluorescent intensity values fall in the center of the axis, in order to better visualize differences in percent amplitude. Quantifications from contractility plots from the post-treatment period were normalized to the pre-treatment data and expressed as a % of baseline. Raw values can be found in <xref ref-type="table" rid="t1">Table 1</xref>. (<bold>d</bold>) Frequency of contractions (<bold>e</bold>) Percent amplitude of contractions. (<bold>f</bold>) Pumping score (frequency x % amplitude). n = 6 C57BL/6J-<italic>Tyr</italic><sup><italic>c-J</italic></sup> albino mice were analyzed. *P < 0.05, **P < 0.01, ***P < 0.001 (two-tailed Student’s <italic>t</italic>-test).</p></caption><graphic xlink:href="srep22930-f6"></graphic></fig><table-wrap position="float" id="t1"><label>Table 1</label><caption><title>Non-invasive CLV contractility assessments from control ointment and NO donor groups during pre- and post-treatment conditions.</title></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="bottom"><tr><th rowspan="2" align="left" valign="top" charoff="50"> </th><th colspan="3" align="center" valign="top" charoff="50">Pre-treatment<hr></hr></th><th colspan="3" align="center" valign="top" charoff="50">Post-treatment<hr></hr></th></tr><tr><th align="center" valign="top" charoff="50">Frequency(min<sup>−1</sup>)</th><th align="center" valign="top" charoff="50">Amplitude(% of MFI)</th><th align="center" valign="bottom" charoff="50">Pumping Score</th><th align="center" valign="top" charoff="50">Frequency(min<sup>−1</sup>)</th><th align="center" valign="top" charoff="50">Amplitude(% of MFI)</th><th align="center" valign="bottom" charoff="50">Pumping Score</th></tr></thead><tbody valign="top"><tr><td align="left" valign="top" charoff="50">Control</td><td align="center" valign="top" charoff="50">12.58 ± 1.30</td><td align="center" valign="top" charoff="50">28.32 ± 13.46</td><td align="center" valign="top" charoff="50">336.67 ± 123.21</td><td align="center" valign="top" charoff="50">12.39 ± 1.72</td><td align="center" valign="top" charoff="50">22.90 ± 6.70</td><td align="center" valign="top" charoff="50">272.53 ± 68.90</td></tr><tr><td align="left" valign="top" charoff="50">NO donor</td><td align="center" valign="top" charoff="50">14.36 ± 1.46</td><td align="center" valign="top" charoff="50">26.13 ± 8.15</td><td align="center" valign="top" charoff="50">362.65 ± 90.40</td><td align="center" valign="top" charoff="50">8.47 ± 3.95</td><td align="center" valign="top" charoff="50">40.61 ± 8.54</td><td align="center" valign="top" charoff="50">313.73 ± 78.50</td></tr></tbody></table><table-wrap-foot><fn id="t1-fn1"><p>Values are reported as mean +/− standard deviation.</p></fn></table-wrap-foot></table-wrap></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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