Dr. Katherine J. Ember Profile

Dr. Katherine J. Ember

at CRCHUM

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Publications (5)

SPIE Journal Paper | 24 January 2025 Open Access

Quantitative assessment of the generalizability of a brain tumor Raman spectroscopy machine learning model to various tumor types including astrocytoma and oligodendroglioma

Frédéric Leblond, Frédérick Dallaire, Katherine Ember, Alice Le Moël, Victor Blanquez-Yeste, Hugo Tavera, Guillaume Sheehy, Trang Tran, Marie-Christine Guiot, Alexander Weil, Roy Dudley, Costas Hadjipanayis, Kevin Petrecca

JBO, Vol. 30, Issue 01, 010501, (January 2025) https://doi.org/10.1117/12.10.1117/1.JBO.30.1.010501

KEYWORDS: Tumors, Brain, Raman spectroscopy, Cancer detection, Data modeling, Machine learning, Brain tissue, Education and training, Signal to noise ratio, Surgery

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SignificanceMaximal safe resection of brain tumors can be performed by neurosurgeons through the use of accurate and practical guidance tools that provide real-time information during surgery. Current established adjuvant intraoperative technologies include neuronavigation guidance, intraoperative imaging (MRI and ultrasound), and 5-ALA for fluorescence-guided surgery.AimWe have developed intraoperative Raman spectroscopy as a real-time decision support system for neurosurgical guidance in brain tumors. Using a machine learning model, trained on data from a multicenter clinical study involving 67 patients, the device achieved diagnostic accuracies of 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas. Here, the aim is to assess the generalizability of a predictive model trained with data from this study to other types of brain tumors.ApproachA method was developed to assess the generalizability of the model, quantifying performance for tumors including astrocytoma, oligodendroglioma and ependymoma, pediatric glioblastoma, and classification of glioblastoma data acquired in the presence of 5-ALA induced fluorescence. Statistical analyses were conducted to assess the impact of vibrational bands beyond contributors identified in our previous research.ResultsA machine learning brain tumor detection model showed a positive predictive value (PPV) of 70% for astrocytoma, 74% for oligodendroglioma, and 100% for ependymoma. Furthermore, the PPV was 100% in classifying spectra from a pediatric glioblastoma and 90% for detecting adult glioblastoma labeled with 5-ALA-induced fluorescence. Univariate statistical analyses applied to individual vibrational bands demonstrated that the inclusion of Raman biomarkers unexploited to date had the potential to improve detectability, setting the stage for future advances.ConclusionsDeveloping predictive models relying on the inelastic scattering contrast from a wider pool of Raman bands may improve detection accuracy for astrocytoma and oligodendroglioma. To do so, larger tumor datasets and a higher Raman photon signal-to-noise ratio may be required.

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Proceedings Article | 13 March 2024 Presentation

Rapid detection of COVID-19 in liquid saliva using reagent-free Raman spectroscopy

Katherine Ember, Nassim Ksantini, Frédéric Dallaire, Guillaume Sheehy, Antoine Noé, Trang Tran, Madeleine Durand, Dominique Trudel, Frederic Leblond

Proceedings Volume PC12850, PC1285005 (2024) https://doi.org/10.1117/12.3001877

KEYWORDS: COVID 19, Artificial intelligence, Portability, Statistical modeling, Statistical analysis, Raman spectroscopy, Spectroscopy, Receivers, Point-of-care devices, Machine learning

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SPIE Journal Paper | 21 February 2023 Open Access

Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids

Guillaume Sheehy, Fabien Picot, Frédérick Dallaire, Katherine Ember, Tien Nguyen, Kevin Petrecca, Dominique Trudel, Frédéric Leblond

JBO, Vol. 28, Issue 02, 025002, (February 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.2.025002

KEYWORDS: Raman spectroscopy, Data processing, Tissues, Equipment, Bubbles, Biological samples, Raman scattering, Fluorescence, Aluminum, Spectroscopy

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SPIE Journal Paper | 9 February 2022 Open Access

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Katherine Ember, François Daoust, Myriam Mahfoud, Frédérick Dallaire, Esmat Zamani, Trang Tran, Arthur Plante, Mame-Kany Diop, Tien Nguyen, Amélie St-Georges-Robillard, Nassim Ksantini, Julie Lanthier, Antoine Filiatrault, Guillaume Sheehy, Gabriel Beaudoin, Caroline Quach, Dominique Trudel, Frédéric Leblond

JBO, Vol. 27, Issue 02, 025002, (February 2022) https://doi.org/10.1117/12.10.1117/1.JBO.27.2.025002

KEYWORDS: Raman spectroscopy, Crystals, Proteins, Statistical modeling, Spectroscopy, Data modeling, Molecules, Statistical analysis, Feature selection, Aluminum

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SPIE Journal Paper | 1 May 2020 Open Access

Rise of Raman spectroscopy in neurosurgery: a review

Damon DePaoli, Émile Lemoine, Katherine Ember, Martin Parent, Michel Prud’homme, Léo Cantin, Kevin Petrecca, Frédéric Leblond, Daniel Côté

JBO, Vol. 25, Issue 05, 050901, (May 2020) https://doi.org/10.1117/12.10.1117/1.JBO.25.5.050901

KEYWORDS: Raman spectroscopy, Tissues, Brain, Tissue optics, Remote sensing, Imaging systems, Chromium, Tumors, Signal processing, Biopsy

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