Non-invasive Evaluation of Glioblastoma Multiforme (GBM) Using Graphene Monitored Via Raman Mapping. (16th November 2020)

• Record Type: Journal Article
• Authors: Behbahani, Mandana; Keisham, Bijentimala; Fernandes, Deisy; Berry, Vikas; Mehta, Ankit Indravadan
• Is Part Of: Neurosurgery. Volume 67(2010)Supplement 1
• Publication Date: 2020-11-16
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1093/neuros/nyaa447_915
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: INTRODUCTION: Imaging modalities aimed at distinguishing Glioblastoma multiforme (GBM) tumor margins can be potentially applied intraoperatively towards maximal tumor resection and improve overall survival. METHODS: An ultrasensitive monolayer graphene sheet was interfaced with 14 GBM tissue samples, to study the resultant change in shift of Raman signal and doping, in relation to various H&E confirmed heterogenous regions. RESULTS: We showed that the second-order overtone of in-plane phonon vibration energies (2D) of graphene can sensitively differentiate various heterogenous regions within GBM tissue, as confirmed on H&E stain. Graphene interfaced with tumor tissue was significantly n-doped with a Raman shift of ∼5 cm −1 in the 2D peak. This is attributed to the distinct surface chemistries of the heterogeneous tissue, which sensitively modified the phonon vibration energies of the interfaced graphene. Further, the molecular dipole moment arising from the different tissue sections coupled with the high quantum capacitance of graphene resulted in a doping density of ∼9.40 × 10 12 cm −2 for tumor interfaced graphene. CONCLUSION: Raman based graphene platform is capable of identifying heterogeneity within GBM tissue. This can be applied to design ultrasensitive diagnostic, therapeutic and monitoring technology in GBM patients. Intraoperatively, not only can this technology be applied towards identification of tumor margins for maximal safe resection, but also, the characteristic signal can enhance or replace frozen histopathologic diagnosis. This research can open new avenues for studying various cancer tissues via a simple Raman based graphene platform.