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3 March 2017 Dual modal endoscopic cancer detection based on optical pH sensing and Raman spectroscopy
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To discriminate between normal and cancerous tissue, a dual modal approach using Raman spectroscopy and pH sensor was designed and applied. Raman spectroscopy has demonstrated the possibility of using as diagnostic method for the early detection of precancerous and cancerous lesions in vivo. It also can be used in identifying markers associated with malignant change. However, Raman spectroscopy lacks sufficient sensitivity due to very weak Raman scattering signal or less distinctive spectral pattern. A dual modal approach could be one of the solutions to solve this issue. The level of extracellular pH in cancer tissue is lower than that in normal tissue due to increased lactic acid production, decreased interstitial fluid buffering and decreased perfusion. High sensitivity and specificity required for accurate cancer diagnosis could be achieved by combining the chemical information from Raman spectrum with metabolic information from pH level. Raman spectra were acquired by using a fiber optic Raman probe, a cooled CCD camera connected to a spectrograph and 785 nm laser source. Different transmission spectra depending on tissue pH were measured by a lossy-mode resonance sensor based on fiber optic. The discriminative capability of pH-Raman dual modal method was evaluated using principal component analysis (PCA). The obtained results showed that the pH-Raman dual modal approach can improve discriminative capability between normal and cancerous tissue, which can lead to very high sensitivity and specificity. The proposed method for cancer detection is expected to be used in endoscopic diagnosis later.
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Soogeun Kim, ByungHyun Kim, Won Bum Sohn, Kyung Min Byun, and Soo Yeol Lee "Dual modal endoscopic cancer detection based on optical pH sensing and Raman spectroscopy", Proc. SPIE 10058, Optical Fibers and Sensors for Medical Diagnostics and Treatment Applications XVII, 1005813 (3 March 2017); doi: 10.1117/12.2249622;

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