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Proceedings Paper

Neural networks improve brain cancer detection with Raman spectroscopy in the presence of light artifacts
Author(s): Michael Jermyn; Joannie Desroches; Jeanne Mercier; Karl St-Arnaud; Marie-Christine Guiot; Kevin Petrecca; Frederic Leblond
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Paper Abstract

It is often difficult to identify cancer tissue during brain cancer (glioma) surgery. Gliomas invade into areas of normal brain, and this cancer invasion is frequently not detected using standard preoperative magnetic resonance imaging (MRI). This results in enduring invasive cancer following surgery and leads to recurrence. A hand-held Raman spectroscopy is able to rapidly detect cancer invasion in patients with grade 2-4 gliomas. However, ambient light sources can produce spectral artifacts which inhibit the ability to distinguish between cancer and normal tissue using the spectral information available. To address this issue, we have demonstrated that artificial neural networks (ANN) can accurately classify invasive cancer versus normal brain tissue, even when including measurements with significant spectral artifacts from external light sources. The non-parametric and adaptive model used by ANN makes it suitable for detecting complex non-linear spectral characteristics associated with different tissues and the confounding presence of light artifacts. The use of ANN for brain cancer detection with Raman spectroscopy, in the presence of light artifacts, improves the robustness and clinical translation potential for intraoperative use. Integration with the neurosurgical workflow is facilitated by accounting for the effect of light artifacts which may occur, due to operating room lights, neuronavigation systems, windows, or other light sources. The ability to rapidly detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery, and thereby improve patient survival.

Paper Details

Date Published: 9 March 2016
PDF: 6 pages
Proc. SPIE 9690, Clinical and Translational Neurophotonics; Neural Imaging and Sensing; and Optogenetics and Optical Manipulation, 96900B (9 March 2016); doi: 10.1117/12.2208892
Show Author Affiliations
Michael Jermyn, McGill Univ. (Canada)
Polytechnique Montreal (Canada)
Joannie Desroches, Polytechnique Montreal (Canada)
Jeanne Mercier, Polytechnique Montreal (Canada)
Karl St-Arnaud, Polytechnique Montreal (Canada)
Marie-Christine Guiot, McGill Univ. (Canada)
Kevin Petrecca, McGill Univ. (Canada)
Frederic Leblond, Polytechnique Montreal (Canada)


Published in SPIE Proceedings Vol. 9690:
Clinical and Translational Neurophotonics; Neural Imaging and Sensing; and Optogenetics and Optical Manipulation
Steen J. Madsen; E. Duco Jansen; Samarendra K. Mohanty; Nitish V. Thakor; Qingming Luo; Victor X. D. Yang, Editor(s)

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