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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Bibliographic Details
Published in:Chemical science (Cambridge) 2020-09, Vol.11 (33), p.8723-8735
Main Authors: 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
Format: Article
Language:English
Subjects:
Augmented reality
Body fluids
Brain damage
Cancer
Cell death
Chemistry
Computational fluid dynamics
Data analysis
Field of view
In vivo methods and tests
Infrared lasers
Infrared tracking
Ions
Mass spectrometry
Outliers (statistics)
Pathology
Pixels
Sampling
Scientific imaging
Spectroscopy
Tracking systems
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Summary: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.
ISSN:2041-6520
2041-6539
DOI:10.1039/d0sc02241a