The diagnosis of lung cancer using 1064-nm excited near-infrared multichannel Raman spectroscopy.

PURPOSE: Raman spectroscopy is based on Raman scattering of light from molecules. Because the wavelength of Raman scattered light depends on molecular composition, Raman spectra provide highly useful information about molecular composition. It has already been shown that Raman spectroscopy is potentially useful for the clinical diagnosis of malignant tumors. However, this technique had never been applied to the diagnosis of lung cancers, primarily because of interference from the strong fluorescence emitted from lung tissues. Our purpose was to examine the effectiveness of near-infrared Raman spectroscopy for the diagnosis of lung cancers. METHODS: We constructed a new near-infrared multichannel Raman system that is capable of measuring high signal-to-noise ratio, fluorescence-free Raman spectra of lung tissues within a measurement time of 1 second. Using this system, we collected a total of 210 Raman spectra from cancerous and non-cancerous lung tissues and analyzed these spectra by a least-squares fitting procedure for cancer diagnosis. RESULTS: The resultant sensitivity of cancer prediction was as high as 91%, with 97% specificity and an error margin of p<0.0001 according to Fisher's exact test. CONCLUSIONS: A method of diagnosing lung cancer efficiently and objectively using Raman spectroscopy has thus been established.