Close

Search

Search Menu
Photonics Media Photonics Buyers' Guide Photonics Spectra BioPhotonics EuroPhotonics Vision Spectra Photonics Showcase Photonics ProdSpec Photonics Handbook
More News

Visible Resonance Raman Spectroscopy Could Advance Tumor Identification

Facebook Twitter LinkedIn Email Comments
NEW YORK, Oct. 30, 2019 — A team of researchers from the U.S. and China, led by Robert Alfano from City University of New York, has used visible resonance Raman (VRR) spectroscopy to identify and grade gliomas, a common tumor of the central nervous system. The researchers used in situ spectral biomarkers to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. Analyses of the VRR spectra revealed that the major molecular biomarkers are involved in metabolic processes in human brain tissues and can be used to create an optical molecular pathology method.

The VRR approach to identifying and grading tumors is a continuation of the Alfano group’s work in the area of optical biopsy, a field that the group has pioneered since 1987.

“To our best knowledge we are the first to apply VRR on gliomas and use it for distinguishing normal and cancerous human brain tissues and margin detection. Moreover, this optical biopsy approach can be used for breast cancer.”
Professor Robert Alfano, 
City College of New York 
The objective of this study was to use VRR as a new Raman technique to evaluate the biomarkers for glioma margins and the correlation between the levels of biomarkers and tumor grades. The researchers used 532-nm Raman spectroscopy on human tissue ex vivo. After collecting the spectra from glioma tissues at different grades, they applied Principal Control Analysis-Support Vector Machine (PCA-SVM) machine learning methods to classify the samples. They compared the results with those from traditional histopathology.

A set of criteria for differentiating normal human brain tissues from normal control tissues was created and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71% for distinguishing the negative cancer margins from normal tissues when compared with the regular pathologically examined results by chemical reagents (the “gold standard”). The results could be used to develop a new fiber optic navigator for in vivo diagnosis of brain cancers and cancer margins that combines all VRR molecular spectral biomarkers. This Raman method and other optical spectroscopy approaches will add to medical armamentarium, Alfano said.

While the survival of a brain glioma patient is affected by multiple factors, the accuracy of tumor boundary identification and the degree of resection of the tumor are two essential factors. The VRR spectroscopy-based technique for glioma diagnosis and margin detection developed by the group could provide a rapid, in situ approach to locating and determining cancer margins and the tumor grade at the molecular level. The researchers believe that their study demonstrates the potential of VRR as a label-free, optical molecular histopathology method for in situ boundary line judgment for brain surgery in the margins.

Visible resonance Raman spectroscopy for identifying and grading gliomas, Robert Alfano, et al., City University of New York.

Typical experimental VRR spectral data plots: the ratios of (a) I1588 cm−1/I1440 cm−1 and (b) I2934 cm−1/I2885 cm−1 from normal human brain tissues and glioma tissues with increasing malignancy. G0-N, normal human brain tissues; GI, grade I; GII, grade II; GIII, grade III; and GIV, grade IV. Courtesy of Robert R. Alfano, et al./
Journal of Biomedical Optics.

According to the researchers, the method is fast, accurate, and local. VRR uses the magic laser wavelength near 532 nm to enhance the Raman signal intensity by > 100× to 1000×, making the method very fast. The VRR method has a high signal-to-noise ratio, provides visually intuitive results for inspection, and takes only seconds for data acquisition. The VRR system also uses less power and a shorter integration time to collect signals; thus, VRR could provide a safer and more suitable method for in vivo and real-time in situ brain cancer diagnosis compared with NIR or FT-Raman methods.

“Optical spectroscopy, in particular, resonance Raman and stimulated Raman gain/loss methods, will be at the heart of future medical armamentarium along with current standard medical tools such as blood tests, x-rays, CAT scans, and MRI and PET imaging,” said Alfano, Distinguished Professor of Physics and Electrical Engineering, Science, and Engineering. “Light will spearhead the use of these tools by giving molecular information. My current and future efforts are to improve these methods, making them more compact and cheaper, and more importantly, to combine diagnosis with treatment.” 

A U.S. patent, 10 426 349, was issued to RR Alfano and CH Liu Oct. 1, 2019.

The research was published in the Journal of Biomedical Optics, a publication of SPIE, the international society for optics and photonics (https://doi.org/10.1117/1.JBO.24.9.095001).

Photonics.com
Dec 2019
GLOSSARY
raman spectroscopy
That branch of spectroscopy concerned with Raman spectra and used to provide a means of studying pure rotational, pure vibrational and rotation-vibration energy changes in the ground level of molecules. Raman spectroscopy is dependent on the collision of incident light quanta with the molecule, inducing the molecule to undergo the change.
Research & TechnologyeducationAsia-PacificAmericasCity University of New Yorkrobert alfanoimaginglight sourcesopticsoptical spectroscopyRaman spectroscopyvisible resonance RamanBiophotonicscancermedicalbrain tumorgliomasoptical biopsy

Comments
back to top
Facebook Twitter Instagram LinkedIn YouTube RSS
©2019 Photonics Media, 100 West St., Pittsfield, MA, 01201 USA, info@photonics.com

Photonics Media, Laurin Publishing
x We deliver – right to your inbox. Subscribe FREE to our newsletters.
We use cookies to improve user experience and analyze our website traffic as stated in our Privacy Policy. By using this website, you agree to the use of cookies unless you have disabled them.