Raman spectroscopy detects distant invasive brain cancer cells centimeters beyond MRI capability in humans.

  title={Raman spectroscopy detects distant invasive brain cancer cells centimeters beyond MRI capability in humans.},
  author={Michael Jermyn and Joannie Desroches and Jeanne Mercier and Karl St-Arnaud and Marie C. Guiot and Fr{\'e}d{\'e}ric Leblond and Kevin Petrecca},
  journal={Biomedical optics express},
  volume={7 12},
Surgical treatment of brain cancer is limited by the inability of current imaging capabilities such as magnetic resonance imaging (MRI) to detect the entirety of this locally invasive cancer. This results in residual cancer cells remaining following surgery, leading to recurrence and death. We demonstrate that intraoperative Raman spectroscopy can detect invasive cancer cells centimeters beyond pathological T1-contrast-enhanced and T2-weighted MRI signals. This intraoperative optical guide can… 

Figures and Tables from this paper

Raman spectroscopy as a promising noninvasive tool in brain cancer detection

RS is suggested as a promising tool which can aid in improving the accuracy of brain tumor surgery and further advancements in instrumentation, market-assessment, and clinical trials can facilitate translation of the technology as a noninvasive intraoperative guidance tool.

Fresh Brain Tissue Diagnostics Using Raman Spectroscopy in Humans

This paper pairs Raman spectroscopy with a supervised machine learning technique, support vector machine, to classify fresh tissue samples as solid tumor, infiltrating tumor, necrosis, or normal brain tissue, and results resulted in 89% accuracy of the 117 tissue samples while delivering real time results.

Rapid Label-Free Analysis of Brain Tumor Biopsies by Near Infrared Raman and Fluorescence Spectroscopy—A Study of 209 Patients

The results demonstrate the feasibility of rapid brain tumors recognition and extraction of diagnostic information by Raman spectroscopy, using a protocol that can be easily included in the routine surgical workflow.

Raman spectroscopy for cancer detection and cancer surgery guidance: translation to the clinics.

This review summarizes actual clinical needs in oncology that can be addressed by spontaneous Raman spectroscopy and it provides an overview over the results that have been published between 2007 and 2017.

The Use of Spectroscopy Handheld Tools in Brain Tumor Surgery: Current Evidence and Techniques

The current evidence and techniques for handheld spectroscopic tools in surgical neuro-oncology are explored here and have the potential for manual intraoperative adjustments to improve visualization of remaining tumor tissue that would otherwise be difficult to detect.

Label-free brain tumor imaging using Raman-based methods

These results demonstrate how label-free Raman-based imaging methods can be used to improve the management of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.

Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy

The HRMAS NMR technique can accurately perform this analysis in real-time and can analyze the full spectrum in an untargeted fashion using machine learning, and it is validated that known malignancy biomarkers such as creatine and 2-hydroxyglutarate play an important role in distinguish tumor and normal cells.

Diagnosis of Glioma Molecular Markers by Terahertz Technologies

This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis, as well as considering new metamaterial-based technologies for molecular marker detection at terahertz frequencies.

Use of Handheld Raman Spectroscopy for Intraoperative Differentiation of Normal Brain Tissue From Intracranial Neoplasms in Dogs

The Raman device was feasible to use intraoperatively with rapid interpretation of spectra to accurately detect neoplastic tissue from adjacent normal gray and white matter and may be useful for intraoperative guidance of tumor resection.



Intraoperative brain cancer detection with Raman spectroscopy in humans

A handheld Raman spectroscopy probe enabled detection of invasive brain cancer intraoperatively in patients with grade 2 to 4 gliomas and may be able to classify cell populations in real time, making it an ideal guide for surgical resection and decision-making.

Imaging of human brain tumor tissue by near-infrared laser coherence tomography

This feasibility study has demonstrated that OCT analysis of the tissue microstructure and light attenuation characteristics discriminate normal brain, areas of tumor infiltrated brain, solid tumor, and necrosis.

Imaging in the era of molecular oncology

Advances in experimental and clinical imaging are likely to improve how cancer is understood at a systems level and should enable doctors not only to locate tumours but also to assess the activity of the biological processes within these tumours and to provide 'on the spot' treatment.

Time‐domain and spectral‐domain optical coherence tomography in the analysis of brain tumor tissue

New technologies that may facilitate an intraoperative analysis of the tissue at the resection edge are of great interest to neurosurgeons.

Ultrasound-guided surgery of deep seated brain lesions.

Serial Intraoperative Magnetic Resonance Imaging of Brain Shift

Only serial intraoperative magnetic resonance imaging provides an accurate basis for the computational analysis of brain deformations, which might lead to an understanding and eventual simulation of brain shift for intraoperative guidance.


GTR was associated with a delay in tumor progression and malignant degeneration as well as improved OS independent of age, degree of disability, histological subtype, or revision versus primary resection.

Supratentorial low-grade glioma resectability: statistical predictive analysis based on anatomic MR features and tumor characteristics.

The main variables associated with incomplete tumor resection in 101 patients were identified by using statistical predictive analyses.