Issue 33, 2020

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

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.

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

Supplementary files

Article information

Article type
Edge Article
Submitted
20 Apr 2020
Accepted
22 Jul 2020
First published
23 Jul 2020
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2020,11, 8723-8735

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

M. Woolman, J. Qiu, C. M. Kuzan-Fischer, I. Ferry, D. Dara, L. Katz, F. Daud, M. Wu, M. Ventura, N. Bernards, H. Chan, I. Fricke, M. Zaidi, B. G. Wouters, J. T. Rutka, S. Das, J. Irish, R. Weersink, H. J. Ginsberg, D. A. Jaffray and A. Zarrine-Afsar, Chem. Sci., 2020, 11, 8723 DOI: 10.1039/D0SC02241A

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