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In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality

Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates in situ tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displaye...

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Autores principales: Woolman, Michael, Qiu, Jimmy, Kuzan-Fischer, Claudia M., Ferry, Isabelle, Dara, Delaram, Katz, Lauren, Daud, Fowad, Wu, Megan, Ventura, Manuela, Bernards, Nicholas, Chan, Harley, Fricke, Inga, Zaidi, Mark, Wouters, Brad G., Rutka, James T., Das, Sunit, Irish, Jonathan, Weersink, Robert, Ginsberg, Howard J., Jaffray, David A., Zarrine-Afsar, Arash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163395/
https://www.ncbi.nlm.nih.gov/pubmed/34123126
http://dx.doi.org/10.1039/d0sc02241a
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author Woolman, Michael
Qiu, Jimmy
Kuzan-Fischer, Claudia M.
Ferry, Isabelle
Dara, Delaram
Katz, Lauren
Daud, Fowad
Wu, Megan
Ventura, Manuela
Bernards, Nicholas
Chan, Harley
Fricke, Inga
Zaidi, Mark
Wouters, Brad G.
Rutka, James T.
Das, Sunit
Irish, Jonathan
Weersink, Robert
Ginsberg, Howard J.
Jaffray, David A.
Zarrine-Afsar, Arash
author_facet Woolman, Michael
Qiu, Jimmy
Kuzan-Fischer, Claudia M.
Ferry, Isabelle
Dara, Delaram
Katz, Lauren
Daud, Fowad
Wu, Megan
Ventura, Manuela
Bernards, Nicholas
Chan, Harley
Fricke, Inga
Zaidi, Mark
Wouters, Brad G.
Rutka, James T.
Das, Sunit
Irish, Jonathan
Weersink, Robert
Ginsberg, Howard J.
Jaffray, David A.
Zarrine-Afsar, Arash
author_sort Woolman, Michael
collection PubMed
description Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates in situ tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displayed at the site of laser sampling as color-coded pixels in an augmented reality video feed of the surgical field of view. This is enabled by two-way communication between surgical navigation and mass spectrometry data analysis platforms through a custom-built interface. Performance of the system was evaluated using murine models of human cancers sampled in situ in the presence of body fluids with a technical pixel error of 1.0 ± 0.2 mm, suggesting a 84% or 92% (excluding one outlier) cancer type classification rate across different molecular models that distinguish cell-lines of each class of breast, brain, head and neck murine models. Further, through end-point immunohistochemical staining for DNA damage, cell death and neuronal viability, spatially encoded PIRL-MS sampling is shown to produce classifiable mass spectral data from living murine brain tissue, with levels of neuronal damage that are comparable to those induced by a surgical scalpel. This highlights the potential of spatially encoded PIRL-MS analysis for in vivo use during neurosurgical applications of cancer type determination or point-sampling in vivo tissue during tumor bed examination to assess cancer removal. The interface developed herein for the analysis and the display of spatially encoded PIRL-MS data can be adapted to other hand-held mass spectrometry analysis probes currently available.
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spelling pubmed-81633952021-06-11 In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality Woolman, Michael Qiu, Jimmy Kuzan-Fischer, Claudia M. Ferry, Isabelle Dara, Delaram Katz, Lauren Daud, Fowad Wu, Megan Ventura, Manuela Bernards, Nicholas Chan, Harley Fricke, Inga Zaidi, Mark Wouters, Brad G. Rutka, James T. Das, Sunit Irish, Jonathan Weersink, Robert Ginsberg, Howard J. Jaffray, David A. Zarrine-Afsar, Arash Chem Sci Chemistry Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates in situ tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displayed at the site of laser sampling as color-coded pixels in an augmented reality video feed of the surgical field of view. This is enabled by two-way communication between surgical navigation and mass spectrometry data analysis platforms through a custom-built interface. Performance of the system was evaluated using murine models of human cancers sampled in situ in the presence of body fluids with a technical pixel error of 1.0 ± 0.2 mm, suggesting a 84% or 92% (excluding one outlier) cancer type classification rate across different molecular models that distinguish cell-lines of each class of breast, brain, head and neck murine models. Further, through end-point immunohistochemical staining for DNA damage, cell death and neuronal viability, spatially encoded PIRL-MS sampling is shown to produce classifiable mass spectral data from living murine brain tissue, with levels of neuronal damage that are comparable to those induced by a surgical scalpel. This highlights the potential of spatially encoded PIRL-MS analysis for in vivo use during neurosurgical applications of cancer type determination or point-sampling in vivo tissue during tumor bed examination to assess cancer removal. The interface developed herein for the analysis and the display of spatially encoded PIRL-MS data can be adapted to other hand-held mass spectrometry analysis probes currently available. The Royal Society of Chemistry 2020-07-23 /pmc/articles/PMC8163395/ /pubmed/34123126 http://dx.doi.org/10.1039/d0sc02241a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Woolman, Michael
Qiu, Jimmy
Kuzan-Fischer, Claudia M.
Ferry, Isabelle
Dara, Delaram
Katz, Lauren
Daud, Fowad
Wu, Megan
Ventura, Manuela
Bernards, Nicholas
Chan, Harley
Fricke, Inga
Zaidi, Mark
Wouters, Brad G.
Rutka, James T.
Das, Sunit
Irish, Jonathan
Weersink, Robert
Ginsberg, Howard J.
Jaffray, David A.
Zarrine-Afsar, Arash
In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
title In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
title_full In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
title_fullStr In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
title_full_unstemmed In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
title_short In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
title_sort in situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163395/
https://www.ncbi.nlm.nih.gov/pubmed/34123126
http://dx.doi.org/10.1039/d0sc02241a
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