Publication: Research - peer-review › Journal article – Annual report year: 2011
The identification of normal and cancer breast tissue of rats was investigated using high-frequency (HF) FT-Raman spectroscopy with a near-infrared excitation source on in vivo and ex vivo measurements. Significant differences in the Raman intensities of prominent Raman bands of lipids and proteins structures (2,800-3,100 cm(-1)) as well as in the broad band of water (3,100-3,550 cm(-1)) were observed in mean normal and cancer tissue spectra. The multivariate statistical analysis methods of principal components analysis (PCA) and linear discriminant analysis (LDA) were performed on all high-frequency Raman spectra of normal and cancer tissues. LDA results with the leave-one-out cross-validation option yielded a discrimination accuracy of 77.2, 83.3, and 100% for in vivo transcutaneous, in vivo skin-removed, and ex vivo biopsy HF Raman spectra. Despite the lower discrimination value for the in vivo transcutaneous measurements, which could be explained by the breathing movement and skin influences, our results showed good accuracy in discriminating between normal and cancer breast tissue samples. To support this, the calculated integration areas from the receiver-operating characteristic (ROC) curve yielded 0.86, 0.94, and 1.0 for in vivo transcutaneous, in vivo skin-removed, and ex vivo biopsy measurements, respectively. The feasibility of using HF Raman spectroscopy as a clinical diagnostic tool for breast cancer detection and monitoring is due to no interfering contribution from the optical fiber in the HF Raman region, the shorter acquisition time due to a more intense signal in the HF Raman region, and the ability to distinguish between normal and cancerous tissues.
|Citations||Web of Science® Times Cited: 15|
- Linear discriminant analysis, Raman spectroscopy, Principal components analysis, Multivariate statistical analysis, Breast cancer detection, High frequency Raman