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.
KEYWORDS: Tissues, Raman spectroscopy, Spectroscopy, In vivo imaging, Diffuse reflectance spectroscopy, Fluorescence spectroscopy, Brain, Principal component analysis, Surgery
Glioblastoma (GBM) is the most common and aggressive malignant brain tumour in adults, and the survival rate of patients affected by this disease is strongly dependent on the successful resection of the tumour. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumour detection and guiding the surgical removal of diseased tissues. In this study, we used an optical fibre-probe system combining multiple spectroscopic techniques for in vivo examination of normal and GBM tissues in mouse brain. Spectroscopic measurements based on fluorescence, Raman, and diffuse reflectance spectroscopy were performed on anesthetized animals through two optical windows implanted on the head of each mouse. Then, the recorded data were analysed using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for obtaining an automated classification of the examined tissues based on the intrinsic spectral information provided by Raman and reflectance spectroscopy. These techniques provided 77% and 97% classification accuracy, respectively, by taking advantage of the intrinsic molecular content of the examined tissues. In particular, the high sensitivity and specificity achieved by means of reflectance spectroscopy indicate that such technique is the most suited for in vivo detection of GBM. The presented results demonstrate the potential of our method for improving the diagnosis of suspicious brain areas during surgery through a very fast spectroscopic inspection, thus helping the surgeon in removing all tumour tissues and reducing the probability of GBM recurrence.
Glioblastoma (GBM) is the most common and aggressive malignant brain tumour in adults. Patient survival rates are strongly dependent on the successfully resection of the tumour. In this framework, multimodal optical spectroscopy could provide a fast and label-free tool for improving tumour detection and guiding the removal of diseased tissue. In this study, we used an optical fibre-probe system combining multiple spectroscopic techniques for in vivo examination of normal and GBM tissues in mouse brain. Specifically, the probe – based on a fibre-bundle with optical fibres of various size and properties – allowed performing spectroscopic measurements based on fluorescence, Raman, and diffuse reflectance spectroscopy though two optical windows implanted on the head of each animal. Two visible laser diodes were used for fluorescence spectroscopy, a laser diode emitting in the NIR was used for Raman spectroscopy, and a fibre-coupled halogen lamp for diffuse reflectance. All spectral recordings were done when the animals were anesthetized; optical inspection required less than 4 minutes for each animal. The recorded data were analysed using Principal Component Analysis (PCA) for obtaining an automated classification of the examined tissues based on the intrinsic spectral information provided by Raman and reflectance spectroscopy. The presented method demonstrated high sensitivity and specificity in discriminating GBM from normal brain. Furthermore, we found that the multimodal approach is crucial for improving diagnostic capabilities beyond what can be achieved from individual techniques.
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