Detecting brain cancer with Raman spectroscopy

by Michael Jermyn

Gliomas are a type of brain cancer with a poor prognosis; grade 4 glioblastomas have a median survival of 14 months1,2. Cancer can be difficult to differentiate from normal brain tissue during surgery for tumor removal. This leads to cancer remaining after surgery, which can cause recurrence and thereby negatively affect patient survival. Most recurrences occur due to residual cancer which has been left behind in the resection cavity3. Standard imaging technologies are unable to detect all of these cancer cells, and so there is a need for highly accurate invasive cancer detection during surgery. The removal of normal brain tissue, which can lead to impairments in cognitive function for patients further motivates the need to be able to distinguish cancer from normal brain.

Raman spectroscopy measures optical interactions with tissue based on inelastic scattering associated with the vibrational modes of molecules. We have developed a Raman spectroscopy system using a hand-held probe for rapid detection of invasive brain cancer. Raman spectra offer a unique fingerprint based on the molecular constituents of tissue. Using developed machine-learning algorithms that use the molecular information from Raman spectra we can distinguish between cancer and normal tissue. These algorithms exploit all of the available spectral information, rather than just individual bands, resulting in improved classification performance. We were able to detect cancer in 17 patients with grade 2-4 gliomas with an accuracy of 92%, sensitivity of 93%, and specificity of 91%4. More than half of the cancer measurements were taken from areas of low-density cancer invasion. It is often difficult to identify cancer in these areas at the periphery of the tumor, and so the ability to rapidly detect this cancer invasion using Raman spectroscopy may have a substantial impact on the effectiveness of surgery for gliomas. Our novel Raman spectroscopy probe gives neurosurgeons a convenient hand-held guide for rapid tissue characterization during surgery. The ability to detect invasive cancer during surgery may reduce the amount of residual cancer in the resection cavity, and consequently lengthen patient survival.

References

1. Brandes, A. A. et al. Glioblastoma in adults. Crit. Rev. Oncol. Hematol. 67, 139–152 (2008).
2. Goodenberger, M. L. & Jenkins, R. B. Genetics of adult glioma. Cancer Genet. 205, 613–621 (2012).
3. Petrecca, K., Guiot, M.-C., Panet-Raymond, V. & Souhami, L. Failure pattern following complete resection plus radiotherapy and temozolomide is at the resection margin in patients with glioblastoma. J. Neurooncol. 111, 19–23 (2013).
4. Jermyn, M. et al. Intraoperative brain cancer detection with Raman spectroscopy in humans. Sci. Transl. Med. 7, 274ra19–274ra19 (2015).

Michael Jermyn is a postdoctoral fellow working with Dr. F. Leblond from the Dept of Engineering Physics, Plolytechnique Montreal and Dr. K. Petrecca a neurosurgeon at the Montreal Neuro and Assistant Professor of Neurology and Neurosurgery at McGill.