Classification of normal and malignant human gastric mucosa tissue with confocal Raman microspectroscopy and wavelet analysis

Near-Infrared Multichannel Raman Spectroscopy with a 1064 nm Excitation Wavelength for Ex Vivo Diagnosis of Gastric Cancer

“…With regard to gastric cancer, RAS had only been applied in vitro until our previous study [29,30]. Recently, a couple of groups have reported the usefulness of near-infrared Raman spectroscopy for gastric cancer diagnosis using biopsy specimens [30,31]. However, there are currently no studies that have focused on optical diagnosis by RAS of the whole stomach.…”

“…To evaluate whether RAS can also distinguish cancer lesions and non-neoplastic areas in the whole stomach, we applied RAS ex vivo to the resected stomach with whole layers that are more likely to reflect the in vivo setting. In addition, most previous studies on gastric cancer have utilized a shorter excitation wavelength, such as 785 nm, than our 1064 nm excitation wavelength [30][31][32]. The excitation wavelength of 1064 nm in our RAS system was expected to exclude any effect of fluorescence, which is known to be emitted from the gastric mucosal tissues [33][34][35].…”

Optical diagnosis of gastric cancer using near-infrared multichannel Raman spectroscopy with a 1064-nm excitation wavelength

“…6,7 Although RAS methods remain to be standardized with regard to not only the preparation of specimens but also the excitation wavelength, RAS has previously been used for various malignancies, including those of the breast, [8][9][10][11][12][13][14] skin, 15 lung, [16][17][18] oral cavity, 19,20 cervix, 21-24 esophagus, [25][26][27][28] colorectum, 29,30 gynecological tract, 31 bladder, 32 prostate gland, 32,33 and other. 6,25 Among these malignancies, RAS of breast cancer was reported to have high specifi city and sensitivity in an ex vivo study, and the usefulness of its clinical application at mastectomy was recently reported.…”

Clinical SERS: are we there yet?

“…RS has been widely used, since the 70's or 80's, for the characterisation of bio-samples obtained from suspected subjects. Combined with pattern recognition algorithm or neural network [23], many authors have repeatedly shown the potential of Raman for disease classification [31,79]. While the data has been promising, the low efficiency of Raman scattering often restricts detection sensitivity and/or specificity [80].…”