In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality. Issue 33 (12th August 2020)

• Record Type: Journal Article
• 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
• Is Part Of: Chemical science. Volume 11:Issue 33(2020)
• Page Start: 8723
• Page End: 8735
• Publication Date: 2020-08-12
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d0sc02241a
• Languages: English
• ISSNs: 2041-6520

Abstract

Abstract : 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. Abstract : 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.