Brain cancer diagnosis requires histological, molecular, and genomic tumor analyses. Since conventional imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) don’t provide molecular characterisation, tumor sampling is often achieved using a targeted needle biopsy approach. Targeting errors and cancer heterogeneity are important limitations of this technique, causing inaccurate sampling resulting in non-diagnostic or poor quality samples leading and the need for repeated biopsies, which poses an elevated patient risk because of infections and potential hemorrhages. Previously, we presented the design of an optically-guided brain biopsy needle using high wavenumber Raman spectroscopy (RS) to characterize tissue prior to sample collection with demonstrated efficacy in a live animal. Using an intraoperative probe we further demonstrated in vivo high wavenumber or fingerprint RS can distinguish cancer and normal brain tissue with >90% accuracy. Here we report on the design, development, and validation of a new intraoperative cancer detection optical needle system based on the combination of fingerprint and high wavenumber RS for highly accurate brain biopsy targeting based on molecular tissue features. This optical cancer detection device was engineered into the internal cannula of a widely used commercially available biopsy needle allowing tumor analysis prior to tissue harvesting with minimal workflow disruption. First in-human results are presented setting the stage for the clinical translation of this optical molecular imaging method for high yield and safe targeted brain biopsy.
Joannie Desroches, Michael Jermyn, Eric Marple, Kirk Urmey, Gilles Soulez, Marie-Christine Guiot, Brian C. Wilson, Kevin Petrecca, and Frédéric Leblond, "Integrated Raman biopsy probe for high yield targeted brain cancer biopsies
(Conference Presentation)," Proc. SPIE 10484, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVI, 104840E (Presented at SPIE BiOS: January 28, 2018; Published: 5 April 2018); https://doi.org/10.1117/12.2290189.5751448989001.
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