Micro-Raman spectroscopy is widely used for non-invasive tissue diagnosis and detection, as it provides detailed information about biomolecular composition, structure, and interaction of tissue. In this work, micro-Raman spectroscopy was used to investigate non-cancerous and cancerous nasopharyngeal tissues. The obtained nasopharyngeal tissue samples in vitro are divided into two groups: cancerous (n=12, undifferentiated non-keratinizing carcinomas) and non-cancerous (n=10, 7 chronic inflammations, 2 lymphomas and 1 lymphocytosis). Firstly, we analyzed the Raman spectra in the fingerprint (FP, 400-1800cm-1) region acquired. Preliminary results showed that there are some spectral differences in different pathological conditions. Furthermore, Raman spectra from cancerous and non-cancerous nasopharyngeal tissue in the high wavenumber region (HW, 2800-3100cm-1) were also reported for the first time. After detailed analysis, we achieved significant differences in Raman bands at 2854, 2874, 2934, and 3067cm-1 between cancerous and non-cancerous nasopharyngeal tissues. This study demonstrates that both fingerprint and high wavenumber regions of micro-Raman spectroscopy have the potential for the early detection of nasopharyngeal carcinomas.
KEYWORDS: Raman spectroscopy, Diagnostics, Remote sensing, Statistical analysis, Principal component analysis, Control systems, Analytical research, Medical research, Signal detection, Medicine
Raman spectroscopy is a rapidly non-invasive technique with great potential for biomedical research. The aim of this
study was to evaluate the feasibility of using Raman spectroscopy of human saliva for acute myocardial infarction (AMI)
detection. Raman spectroscopy measurements were performed on two groups of saliva samples: one group from patients
(n=30) with confirmed AMI and the other group from healthy controls (n=31). The diagnostic performance for
differentiating AMI saliva from normal saliva was evaluated by multivariate statistical analysis. The combination of
principal component analysis (PCA) and linear discriminate analysis (LDA) of the measured Raman spectra separated
the spectral features of the two groups into two distinct clusters with little overlaps, rendering the sensitivity of 80.0%
and specificity of 80.6%. The results from this exploratory study demonstrated that Raman spectroscopy of human saliva
can serve as a potentially clinical tool for rapid AMI detection and screening.
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