In vivo label-free measurement of lymph flow velocity and volumetric flow rates using Doppler optical coherence tomography
Identifieur interne : 008515 ( Ncbi/Merge ); précédent : 008514; suivant : 008516In vivo label-free measurement of lymph flow velocity and volumetric flow rates using Doppler optical coherence tomography
Auteurs : Cedric Blatter [États-Unis] ; Eelco F. J. Meijer [États-Unis] ; Ahhyun S. Nam [États-Unis] ; Dennis Jones [États-Unis] ; Brett E. Bouma [États-Unis] ; Timothy P. Padera [États-Unis] ; Benjamin J. Vakoc [États-Unis]Source :
- Scientific Reports [ 2045-2322 ] ; 2016.
Abstract
Direct
Url:
DOI: 10.1038/srep29035
PubMed: 27377852
PubMed Central: 4932526
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J." last="Meijer">Eelco F. J. Meijer</name><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a3"><institution>Edwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital Cancer Center</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Nam, Ahhyun S" sort="Nam, Ahhyun S" uniqKey="Nam A" first="Ahhyun S." last="Nam">Ahhyun S. 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J." last="Meijer">Eelco F. J. Meijer</name><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a3"><institution>Edwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital Cancer Center</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Nam, Ahhyun S" sort="Nam, Ahhyun S" uniqKey="Nam A" first="Ahhyun S." last="Nam">Ahhyun S. Nam</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Wellman Center for Photomedicine, Massachusetts General Hospital</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a4"><institution>Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue</institution>, Cambridge, Massachusetts 02139,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Jones, Dennis" sort="Jones, Dennis" uniqKey="Jones D" first="Dennis" last="Jones">Dennis Jones</name><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a3"><institution>Edwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital Cancer Center</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Bouma, Brett E" sort="Bouma, Brett E" uniqKey="Bouma B" first="Brett E." last="Bouma">Brett E. Bouma</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Wellman Center for Photomedicine, Massachusetts General Hospital</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Padera, Timothy P" sort="Padera, Timothy P" uniqKey="Padera T" first="Timothy P." last="Padera">Timothy P. Padera</name><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a3"><institution>Edwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital Cancer Center</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Vakoc, Benjamin J" sort="Vakoc, Benjamin J" uniqKey="Vakoc B" first="Benjamin J." last="Vakoc">Benjamin J. Vakoc</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Wellman Center for Photomedicine, Massachusetts General Hospital</institution>, Boston, Massachusetts 02114,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a2"><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></nlm:aff><country xml:lang="fr">États-Unis</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>Direct <italic>in vivo</italic> imaging of lymph flow is key to understanding lymphatic system function in normal and disease states. Optical microscopy techniques provide the resolution required for these measurements, but existing optical techniques for measuring lymph flow require complex protocols and provide limited temporal resolution. Here, we describe a Doppler optical coherence tomography platform that allows direct, label-free quantification of lymph velocity and volumetric flow rates. We overcome the challenge of very low scattering by employing a Doppler algorithm that operates on low signal-to-noise measurements. We show that this technique can measure lymph velocity at sufficiently high temporal resolution to resolve the dynamic pulsatile flow in collecting lymphatic vessels.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Pereira, E R" uniqKey="Pereira E">E. R. Pereira</name></author><author><name sortKey="Jones, D" uniqKey="Jones D">D. Jones</name></author><author><name sortKey="Jung, K" uniqKey="Jung K">K. 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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">27377852</article-id><article-id pub-id-type="pmc">4932526</article-id><article-id pub-id-type="pii">srep29035</article-id><article-id pub-id-type="doi">10.1038/srep29035</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title><italic>In vivo</italic> label-free measurement of lymph flow velocity and volumetric flow rates using Doppler optical coherence tomography</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Blatter</surname><given-names>Cedric</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a2">2</xref></contrib><contrib contrib-type="author"><name><surname>Meijer</surname><given-names>Eelco F. J.</given-names></name><xref ref-type="aff" rid="a2">2</xref><xref ref-type="aff" rid="a3">3</xref></contrib><contrib contrib-type="author"><name><surname>Nam</surname><given-names>Ahhyun S.</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a2">2</xref><xref ref-type="aff" rid="a4">4</xref></contrib><contrib contrib-type="author"><name><surname>Jones</surname><given-names>Dennis</given-names></name><xref ref-type="aff" rid="a2">2</xref><xref ref-type="aff" rid="a3">3</xref></contrib><contrib contrib-type="author"><name><surname>Bouma</surname><given-names>Brett E.</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a2">2</xref></contrib><contrib contrib-type="author"><name><surname>Padera</surname><given-names>Timothy P.</given-names></name><xref ref-type="aff" rid="a2">2</xref><xref ref-type="aff" rid="a3">3</xref><xref ref-type="author-notes" rid="n1">*</xref></contrib><contrib contrib-type="author"><name><surname>Vakoc</surname><given-names>Benjamin J.</given-names></name><xref ref-type="corresp" rid="c1">a</xref><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a2">2</xref><xref ref-type="author-notes" rid="n1">*</xref></contrib><aff id="a1"><label>1</label><institution>Wellman Center for Photomedicine, Massachusetts General Hospital</institution>, Boston, Massachusetts 02114,<country>USA</country></aff><aff id="a2"><label>2</label><institution>Harvard Medical School</institution>, Boston, Massachusetts 02115,<country>USA</country></aff><aff id="a3"><label>3</label><institution>Edwin L. Steele Laboratories for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital Cancer Center</institution>, Boston, Massachusetts 02114,<country>USA</country></aff><aff id="a4"><label>4</label><institution>Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue</institution>, Cambridge, Massachusetts 02139,<country>USA</country></aff></contrib-group><author-notes><corresp id="c1"><label>a</label><email>bvakoc@mgh.harvard.edu</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>05</day><month>07</month><year>2016</year></pub-date><pub-date pub-type="collection"><year>2016</year></pub-date><volume>6</volume><elocation-id>29035</elocation-id><history><date date-type="received"><day>25</day><month>02</month><year>2016</year></date><date date-type="accepted"><day>09</day><month>06</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>Direct <italic>in vivo</italic> imaging of lymph flow is key to understanding lymphatic system function in normal and disease states. Optical microscopy techniques provide the resolution required for these measurements, but existing optical techniques for measuring lymph flow require complex protocols and provide limited temporal resolution. Here, we describe a Doppler optical coherence tomography platform that allows direct, label-free quantification of lymph velocity and volumetric flow rates. We overcome the challenge of very low scattering by employing a Doppler algorithm that operates on low signal-to-noise measurements. We show that this technique can measure lymph velocity at sufficiently high temporal resolution to resolve the dynamic pulsatile flow in collecting lymphatic vessels.</p></abstract></article-meta></front><floats-group><fig id="f1"><label>Figure 1</label><caption><title>Illustration of the method to measure lymphatic flow velocity with DOCT under low SNR settings and in the presence of artifacts from neighboring static tissue signals.</title><p>(<bold>a</bold>) Three-dimensional OCT datasets viewed in <italic>en face</italic> (upper panel) and cross sectional (lower panel) presentations are used to identify lymphatic vessels and select the location for flow measurement. (<bold>b</bold>) The depth-resolved OCT signal at a fixed transverse (x,y) location is recorded for five minutes and used to generate an M-Mode intensity image to identify the lymphatic vessel upper and lower boundaries. Depths within the lymphatic vessel are analyzed using Doppler methods. (<bold>c</bold>) A spectrogram is obtained for each depth, here shown for the depth indicated by the dashed line in (<bold>b</bold>). (<bold>d</bold>) Spectra showing the static and lymph signals at times of small (upper panel, −55 Hz) and moderate (lower panel, −281 Hz) Doppler shifts. Each spectral curve (black trace) within the spectrogram (panel c) is fit to a parametric model comprising two Gaussians and a white noise background (red trace). One Gaussian represents the static component and is centered at 0 Hz (blue peak). The second Gaussian represents the component due to lymph flow and is a broad distribution centered on the Doppler frequency (grey peak). The sign of the Doppler frequency shift denotes the direction of flow relative to the imaging beam.</p></caption><graphic xlink:href="srep29035-f1"></graphic></fig><fig id="f2"><label>Figure 2</label><caption><title>Comparison of DOCT and fluorescence photobleaching measurements of lymph proxy flow in microfluidic phantoms and <italic>in vivo</italic>.</title><p>(<bold>a</bold>) Schematic of the experimental setup showing fluorescence widefield illumination (light green), focused and pulsed illumination for photobleaching (dark green) and DOCT (red). (<bold>b</bold>) Two cropped fluorescence frames taken from the video sequence acquired immediately after creation of a photobleached spot (in a microfluidic phantom). The translation of the spot is used to calculate flow velocity. (<bold>c</bold>) Comparison of simultaneous DOCT and fluorescence based flow velocity measurements in the microfluidic phantom and mouse ear. (<bold>d</bold>) The time-resolved velocity measurements from DOCT and fluorescence modalities in the microfluidic and <italic>in vivo</italic> experiments. Note that the larger discrepancies between the modalities in the <italic>in vivo</italic> measurements occur from 25 seconds to 65 seconds, immediately after creation of the flow bolus (arrow) when flow velocity is changing rapidly. (<bold>e</bold>,<bold>f</bold>) Bland-Altman plots, displaying the difference between DOCT and fluorescence flow measurements compared to the mean flow speed, show agreement between the two modalities in the microfluidic and <italic>in vivo</italic> experiments respectively.</p></caption><graphic xlink:href="srep29035-f2"></graphic></fig><fig id="f3"><label>Figure 3</label><caption><title>M-Mode DOCT measurement of pulsatile lymph flow velocity.</title><p>(<bold>a</bold>) Depth and time-resolved flow velocity in the lymphatic vessel lumen overlaid on the M-Mode intensity image. The measurement location is highlighted in <xref ref-type="fig" rid="f1">Fig. 1(a)</xref>. The positive velocity indicates flow proximally toward the body. The animal leg was lying lower than the abdomen. The flow direction was therefore against gravity. A velocity time trace was calculated by averaging the flow velocity in the vessel over the lymphatic vessel (LV) depth. The maximum amplitude of this velocity is smaller than in the image above because of this depth averaging. (<bold>b</bold>) An M-Mode measurement showing periods of backflow. (<bold>c</bold>) A measurement in another animal showing an oscillatory flow velocity at relatively higher frequency than pulsatile flow exemplified by panel (a). (d) The average pulse interval for 10 animals showing pronounced pulsatile flow dynamics. The box plot for each animal includes data obtained over multiple five minute duration measurements. The mean pulse interval is 19.8 seconds and is much longer than respiratory or cardiac cycles. (<bold>e</bold>) The mean flow velocity in the same animals as in (<bold>d</bold>) calculated as the average over individual five minute measurements. <inline-formula id="d33e759"><inline-graphic id="d33e760" xlink:href="srep29035-m2.jpg"></inline-graphic></inline-formula> and S.E.M. denote mean, median and standard error of the mean respectively.</p></caption><graphic xlink:href="srep29035-f3"></graphic></fig><fig id="f4"><label>Figure 4</label><caption><title>B-Mode DOCT measurement of spatially and temporally resolved lymph flow velocity, vessel cross-sectional area and volumetric flow rates.</title><p>(<bold>a</bold>) Three-dimensional OCT datasets viewed in <italic>en face</italic> (upper panel, lv: lymphatic vessel) and cross-sectional (lower panel) presentations are used to identify lymphatic vessels and select the flow measurement cross-section. Representative image of the time series (<xref ref-type="supplementary-material" rid="S1">Supplementary Video 1</xref>) showing the vessel cross-section (<bold>b</bold>), its segmentation result (<bold>c</bold>), yellow curve) and the calculated flow velocity spatial distribution (<bold>d</bold>). The velocity image was filtered with a two dimensional median filter and unwrapped. (<bold>e</bold>) The segmented cross-sectional area of the lymphatic vessel is reported over the five minutes measurement. (<bold>f</bold>) The mean velocity calculated over the vessel cross-sectional area is reported with its mean value indicated by the dashed line. (<bold>g</bold>) The lymphatic volumetric flow is calculated as the product of the cross-sectional area and the mean velocity (methods). The velocity measurement resolves the pulsatile flow, similar to previous measurements. Interestingly, the vessel cross-section profile shows changes in accordance with the flow pulses. (<bold>h</bold>) Seven spectra (black line) at a particular spatial location in the vessel during a flow pulse show high velocity frequency components being wrapped, i.e. appearing on the right side of the frequency scale. The fitting model in red operates on a circular coordinate system. The length of the black arrow pointing to the center of the broad Gaussian indicates the value of the frequency/velocity estimator after unwrapping.</p></caption><graphic xlink:href="srep29035-f4"></graphic></fig></floats-group></pmc><affiliations><list><country><li>États-Unis</li></country></list><tree><country name="États-Unis"><noRegion><name sortKey="Blatter, Cedric" sort="Blatter, Cedric" uniqKey="Blatter C" first="Cedric" last="Blatter">Cedric Blatter</name></noRegion><name sortKey="Blatter, Cedric" sort="Blatter, Cedric" uniqKey="Blatter C" first="Cedric" last="Blatter">Cedric Blatter</name><name sortKey="Bouma, Brett E" sort="Bouma, Brett E" uniqKey="Bouma B" first="Brett E." last="Bouma">Brett E. Bouma</name><name sortKey="Bouma, Brett E" sort="Bouma, Brett E" uniqKey="Bouma B" first="Brett E." last="Bouma">Brett E. Bouma</name><name sortKey="Jones, Dennis" sort="Jones, Dennis" uniqKey="Jones D" first="Dennis" last="Jones">Dennis Jones</name><name sortKey="Jones, Dennis" sort="Jones, Dennis" uniqKey="Jones D" first="Dennis" last="Jones">Dennis Jones</name><name sortKey="Meijer, Eelco F J" sort="Meijer, Eelco F J" uniqKey="Meijer E" first="Eelco F. J." last="Meijer">Eelco F. J. Meijer</name><name sortKey="Meijer, Eelco F J" sort="Meijer, Eelco F J" uniqKey="Meijer E" first="Eelco F. J." last="Meijer">Eelco F. J. Meijer</name><name sortKey="Nam, Ahhyun S" sort="Nam, Ahhyun S" uniqKey="Nam A" first="Ahhyun S." last="Nam">Ahhyun S. Nam</name><name sortKey="Nam, Ahhyun S" sort="Nam, Ahhyun S" uniqKey="Nam A" first="Ahhyun S." last="Nam">Ahhyun S. Nam</name><name sortKey="Nam, Ahhyun S" sort="Nam, Ahhyun S" uniqKey="Nam A" first="Ahhyun S." last="Nam">Ahhyun S. Nam</name><name sortKey="Padera, Timothy P" sort="Padera, Timothy P" uniqKey="Padera T" first="Timothy P." last="Padera">Timothy P. Padera</name><name sortKey="Padera, Timothy P" sort="Padera, Timothy P" uniqKey="Padera T" first="Timothy P." last="Padera">Timothy P. Padera</name><name sortKey="Vakoc, Benjamin J" sort="Vakoc, Benjamin J" uniqKey="Vakoc B" first="Benjamin J." last="Vakoc">Benjamin J. Vakoc</name><name sortKey="Vakoc, Benjamin J" sort="Vakoc, Benjamin J" uniqKey="Vakoc B" first="Benjamin J." last="Vakoc">Benjamin J. Vakoc</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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