Special Series on Translational Biophotonics

Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts

[+] Author Affiliations
Michael Jermyn

McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, 3801 University Street, Montreal, Quebec H3A 2B4, Canada

Polytechnique Montreal, Department of Engineering Physics, CP 6079, Succ. Centre-Ville, Montreal, Quebec H3C 3A7, Canada

Joannie Desroches, Jeanne Mercier, Marie-Andrée Tremblay, Karl St-Arnaud

Polytechnique Montreal, Department of Engineering Physics, CP 6079, Succ. Centre-Ville, Montreal, Quebec H3C 3A7, Canada

Marie-Christine Guiot

McGill University, Division of Neuropathology, Department of Pathology, 3801 University Street, Montreal, Quebec H3A 2B4, Canada

Kevin Petrecca

McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, 3801 University Street, Montreal, Quebec H3A 2B4, Canada

Frederic Leblond

Polytechnique Montreal, Department of Engineering Physics, CP 6079, Succ. Centre-Ville, Montreal, Quebec H3C 3A7, Canada

Centre de Recherche du Centre Hospitalier de l’Université de Montréal, 900 rue Saint-Denis, H2X 0A9 Quebec, Canada

J. Biomed. Opt. 21(9), 094002 (Sep 08, 2016). doi:10.1117/1.JBO.21.9.094002
History: Received March 29, 2016; Accepted August 18, 2016
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Abstract.  Invasive brain cancer cells cannot be visualized during surgery and so they are often not removed. These residual cancer cells give rise to recurrences. In vivo Raman spectroscopy can detect these invasive cancer cells in patients with grade 2 to 4 gliomas. The robustness of this Raman signal can be dampened by spectral artifacts generated by lights in the operating room. We found that artificial neural networks (ANNs) can overcome these spectral artifacts using nonparametric and adaptive models to detect complex nonlinear spectral characteristics. Coupling ANN with Raman spectroscopy simplifies the intraoperative use of Raman spectroscopy by limiting changes required to the standard neurosurgical workflow. The ability to detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery and improve patient survival.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Michael Jermyn ; Joannie Desroches ; Jeanne Mercier ; Marie-Andrée Tremblay ; Karl St-Arnaud, et al.
"Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts", J. Biomed. Opt. 21(9), 094002 (Sep 08, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.9.094002


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