Intraoperative detection of human meningioma using a handheld visible resonance Raman analyzer

Area of Science:

• Biomedical Optics
• Raman Spectroscopy
• Surgical Oncology

Background:

• Intraoperative identification of human meningioma grades and margins is crucial for effective surgical treatment.
• Current methods can be time-consuming or lack the precision needed for real-time surgical guidance.
• Visible Resonance Raman (VRR) spectroscopy offers a potential label-free approach for molecular tissue analysis.

Purpose of the Study:

• To evaluate the preliminary results of a novel VRR-LRR™ analyzer for intraoperative human meningioma grading and margin identification.
• To assess the capability of VRR spectroscopy in distinguishing between different meningioma grades and normal tissues.
• To explore the potential of VRR-LRR™ for rapid, objective, and label-free tumor detection during surgery.

Main Methods:

• Collected unprocessed primary and recurrent solid human meningeal tissues from 33 patients during surgery.
• Acquired 1180 VRR spectra from fresh tissues using the VRR-LRR™ analyzer.
• Compared VRR data with confocal Raman spectroscopy on ex vivo samples and analyzed spectral features using Support Vector Machines (SVMs) and Principal Component Analysis (PCA).

Main Results:

• Intensity ratios of specific protein and fatty acid VRR peaks (I2934/I2888) decreased with increasing meningioma grade.
• Ratios of phosphorylated protein to Amide I peaks (I1588/I1639) also decreased in higher-grade meningiomas.
• Significant changes in VRR peak intensities related to oxy-hemeprotein, amide B, and amide A proteins were observed in tumor tissues compared to normal tissue. Carotenoid VRR modes showed changes at the meningioma boundary.

Conclusions:

• The VRR-LRR™ analyzer shows potential as a novel tool for label-free, rapid, and objective intraoperative identification of human meningioma.
• Spectral analysis using SVMs achieved over 70% accuracy, while PCA reached 100% accuracy in detecting meningioma tissues.
• VRR spectroscopy can effectively differentiate meningioma grades and identify tumor margins based on key biomolecular vibrations.