Toward noncontact macroscopic imaging of multiple cancers using multi-spectral inelastic scattering detection

Sandryne David, Nassim Ksantini, Frédérick Dallaire, Katherine Ember, François Daoust, Guillaume Sheehy, Costas G. Hadjipanayis, Kevin Petrecca, Brian C. Wilson, Frédéric Leblond

Research output: Contribution to journalLetterpeer-review

Abstract

Here we introduce a Raman spectroscopy approach combining multi-spectral imaging and a new fluorescence background subtraction technique to image individual Raman peaks in less than 5 seconds over a square field-of-view of 1-centimeter sides with 350 micrometers resolution. First, human data is presented supporting the feasibility of achieving cancer detection with high sensitivity and specificity – in brain, breast, lung, and ovarian/endometrium tissue – using no more than three biochemically interpretable biomarkers associated with the inelastic scattering signal from specific Raman peaks. Second, a proof-of-principle study in biological tissue is presented demonstrating the feasibility of detecting a single Raman band – here the CH2/CH3 deformation bands from proteins and lipids – using a conventional multi-spectral imaging system in combination with the new background removal method. This study paves the way for the development of a new Raman imaging technique that is rapid, label-free, and wide field.

Original languageEnglish
Article numbere202400087
JournalJournal of Biophotonics
Volume17
Issue number9
DOIs
StatePublished - Sep 2024

Keywords

  • Raman spectroscopy
  • cancer biomarkers
  • fluorescence
  • machine learning
  • multi-spectral imaging
  • surgery
  • tissue optics

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