In vivo detection of murine glioblastoma through Raman and reflectance fiber-probe spectroscopies.
Enrico BariaEnrico PracucciVinoshene PillaiFrancesco Saverio PavoneGian M RattoRiccardo CicchiPublished in: Neurophotonics (2020)
Significance: Glioblastoma (GBM) is the most common and aggressive malignant brain tumor in adults. With a worldwide incidence rate of 2 to 3 per 100,000 people, it accounts for more than 60% of all brain cancers; currently, its 5-year survival rate is < 5 % . GBM treatment relies mainly on surgical resection. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumor detection and guiding the removal of diseased tissues. Aim: Discriminating healthy brain from GBM tissues in an animal model through the combination of Raman and reflectance spectroscopies. Approach: EGFP-GL261 cells were injected into the brains of eight laboratory mice for inducing murine GBM in these animals. A multimodal optical fiber probe combining fluorescence, Raman, and reflectance spectroscopy was used to localize in vivo healthy and tumor brain areas and to collect their spectral information. Results: Tumor areas were localized through the detection of EGFP fluorescence emission. Then, Raman and reflectance spectra were collected from healthy and tumor tissues, and later analyzed through principal component analysis and linear discriminant analysis in order to develop a classification algorithm. Raman and reflectance spectra resulted in 92% and 93% classification accuracy, respectively. Combining together these techniques allowed improving the discrimination between healthy and tumor tissues up to 97%. Conclusions: These preliminary results demonstrate the potential of multimodal fiber-probe spectroscopy for in vivo label-free detection and delineation of brain tumors, and thus represent an additional, encouraging step toward clinical translation and deployment of fiber-probe spectroscopy.
Keyphrases
- label free
- single molecule
- high resolution
- gene expression
- machine learning
- living cells
- quantum dots
- deep learning
- white matter
- pain management
- resting state
- loop mediated isothermal amplification
- computed tomography
- healthcare
- type diabetes
- metabolic syndrome
- chronic pain
- magnetic resonance
- blood brain barrier
- risk assessment
- skeletal muscle
- climate change
- density functional theory
- human health
- sensitive detection
- molecular dynamics
- contrast enhanced