Applications of Raman spectroscopy in cancer diagnosis.

Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.

Intraoperative Raman Spectroscopy.

Surgical excision of brain tumors provides a means of cytoreduction and diagnosis while minimizing neurologic deficit and improving overall survival. Despite advances in functional and three-dimensional stereotactic navigation and intraoperative MRI, delineating tissue in real time with physiologic confirmation is challenging. Raman spectroscopy has potential to be an important modality in the intraoperative evaluation of tissue during surgical resection. In vitro experimental studies have shown that this technique can be used to differentiate normal brain tissue from tissue with infiltrating cancer cells and dense cancerous masses with high specificity, indicating the feasibility of this method for in vivo application.

Shining light on neurosurgery diagnostics using Raman spectroscopy.

Surgical excision of brain tumors provides a means of cytoreduction and diagnosis while minimizing neurologic deficit and improving overall survival. Despite advances in functional and three-dimensional stereotactic navigation and intraoperative magnetic resonance imaging, delineating tissue in real time with physiological confirmation is challenging. Raman spectroscopy is a promising investigative and diagnostic tool for neurosurgery, which provides rapid, non-destructive molecular characterization in vivo or in vitro for biopsy, margin assessment, or laboratory uses. The Raman Effect occurs when light temporarily changes a bond's polarizability, causing change in the vibrational frequency, with a corresponding change in energy/wavelength of the scattered photon. The recorded inelastic scattering results in a "fingerprint" or Raman spectrum of the constituent under investigation. The amount, location, and intensity of peaks in the fingerprint vary based on the amount of vibrational bonds in a molecule and their ensemble interactions with each other. Distinct differences between various pathologic conditions are shown as different intensities of the same peak, or shifting of a peak based on the binding conformation. Raman spectroscopy has potential for integration into clinical practice, particularly in distinguishing normal and diseased tissue as an adjunct to standard pathologic diagnosis. Further, development of fiber-optic Raman probes that fit through the instrument port of a standard endoscope now allows researchers and clinicians to utilize spectroscopic information for evaluation of in vivo tissue. This review highlights the need for such an instrument, summarizes neurosurgical Raman work performed to date, and discusses the future applications of neurosurgical Raman spectroscopy.

Identification of regions of normal grey matter and white matter from pathologic glioblastoma and necrosis in frozen sections using Raman imaging.

In neurosurgical applications, a tool capable of distinguishing grey matter, white matter, and areas of tumor and/or necrosis in near-real time could greatly aid in tumor resection decision making. Raman spectroscopy is a non-destructive spectroscopic technique which provides molecular information about the tissue under examination based on the vibrational properties of the constituent molecules. With careful measurement and data processing, a spatial step and repeat acquisition of Raman spectra can be used to create Raman images. Forty frozen brain tissue sections were imaged in their entirety using a 300-µm-square measurement grid, and two or more regions of interest within each tissue were also imaged using a 25 µm-square step size. Molecular correlates for histologic features of interest were identified within the Raman spectra, and novel imaging algorithms were developed to compare molecular features across multiple tissues. In previous work, the relative concentration of individual biomolecules was imaged. Here, the relative concentrations of 1004, 1300:1344, and 1660 cm(-1), which correspond primarily to protein and lipid content, were simultaneously imaged across all tissues. This provided simple interpretation of boundaries between grey matter, white matter, and diseased tissue, and corresponded with findings from adjacent hematoxylin and eosin-stained sections. This novel, yet simple, multi-channel imaging technique allows clinically-relevant resolution with straightforward molecular interpretation of Raman images not possible by imaging any single peak. This method can be applied to either surgical or laboratory tools for rapid, non-destructive imaging of grey and white matter.