We have investigated a multiple label-free detection method based on Raman spectroscopy and multivariate curve resolution (MCR) analysis to classify breast cancer. Twenty breast tissues collected from five participants during breast surgery were used as biological samples. Ten samples were from malignant tumor mass (cancer core area) and the others were from the safety margin outside of the tumor mass (two sample groups). For each breast tissue sample, twenty Raman spectra were collected using a fiber-optics Raman system consisting of a fiber-optic Raman probe, a low dark current deep-depletion CCD connected to a Czerny-Turner spectrograph and 785-nm laser source. Using MCR analysis iteratively optimized by an alternative least squares (ALS) algorithm, biomarker-dominated spectral data can be obtained from the preprocessed Raman spectra. This allows a more accurate classification between the two sample groups (normal and cancer). We expect that the proposed method based on biomarker analysis using MCR-ALS will more accurately classify breast cancer.
A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification.
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.
This work reports that the laser fluence rate inside porcine skin varied notably with the change of tissue water content under the same laser irradiation conditions. The laser fluence rate inside skin tissue samples with varying water content was measured using an optical fiber sensor, while the target was irradiated either by a low-level 635 or 830 nm laser (50 mW/cm2). It was demonstrated that the distribution of laser fluence rate inside the target is strongly affected by tissue water content and its profile is determined by the water content dependency of optical properties at the laser wavelength.
This work reports that the ablation volume and rate of porcine skin changed significantly with the change of skin water content. Under the same laser irradiation conditions (532 nm Nd:YAG laser, pulse width=11.5 ns, pulse energy=1.54 J, beam radius=0.54 mm), the ablation volume dropped by a factor of 4 as the skin water content decreased from 40 wt. % (native) to 19 wt. % with a change in the ablation rate below and above around 25 wt. %. Based on the ablation characteristics observed by in situ shadowgraph images and the calculated tissue temperatures, it is considered that an explosive rupture by rapid volumetric vaporization of water is responsible for the ablation of the high water content of skin, whereas thermal disintegration of directly irradiated surface layer is responsible for the low water content of skin.