Ex vivo and in vivo diagnosis of C6 glioblastoma development by Raman spectroscopy coupled to a microprobe

Abstract

The potential of Raman spectroscopy for ex vivo and in vivo classification of normal and glioblastoma brain tumor development was investigated. High-quality spectra of normal and tumor tissues were obtained using a portable Raman spectrometer coupled to a microprobe with a signal integration time of 5 s. Ex vivo results demonstrated that by using the biochemical information contained in the spectra, we were able to distinguish between normal brain features (white and gray matter), invasion, and tumor tissues with a classification accuracy of 100%. Differences between these features resulted from variations in their lipid signal contributions, which probably reflect differences in the level of myelinization. This finding supports the ability of in vivo Raman spectroscopy to delineate tumor margins during surgery. After implanting C6 cells in rat brain, we monitored, in vivo, the development of glioblastoma tumor from days 0 to 20 post-implantation (PI). The classification exhibited a clear separation of the data into two clusters: one cluster was associated with normal brain tissues (cortex), and the second was related to data measured from tumor evolution. The second cluster could be divided into two subclusters, one associated with tumor tissue from 4 to 13 days PI and the second related to tumor tissue from 15 to 20 days PI. Histological analysis reveals that the differences between these two subclusters are: the presence of a massive infiltration zone in the brain tissue from 4 to 13 days PI, and; a maturation of the tumor characterized by the appearance of edematous and necrotic zones, as well as a diminution in the proliferative and invasive area, from 15 days. This work demonstrates the potential of Raman spectroscopy to provide diagnostic information for the early detection of tumors in vivo.

Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

“…In fact, projection of spectra from molecular species on a tissue spectrum is very sensitive to noise in the data. Typically, molecular characterization and quantification is performed with spectra acquired with integration times of ∼1 to 10 seconds, which can be challenging for clinical implementation [29][30][31]. Also, distinguishing between different tumor grades, which potentially relies on subtle spectral differences, might be achievable with higher SNR levels.…”

Highly Accurate Detection of Cancer In Situ with Intraoperative, Label-Free, Multimodal Optical Spectroscopy

“…Cancer detection system performance RS peaks were identified for lipids, nucleic acids, and cholesterol, as well as the three amide bands associated with the secondary structure of proteins (33,(37)(38)(39)(40)(41)(42)(43). The most significant biochemical differences between cancer and normal tissue were found, based on univariate statistical hypothesis testing of the individual RS peaks and tissue bands, as either increases (þ) or decreases (À) in cancer.…”

Raman spectroscopy as a promising noninvasive tool in brain cancer detection

“…A glioblastoma Wistar rat model was used in this study, obtained after injecting a C6 glioma cell suspension into brain cortex, and sequential progression was monitored at days 4, 6, 8, 11, 13, 15, and 20 post tumor injection. 21 Tanahashi et al compared spectra obtained from mouse models of avian sarcoma-based in¯ltrative glioma cells and tissues to spectra from normal mouse astrocytes and normal tissues and could distinguish the in¯l-trative tumors using RS. 22 …”