Raman spectroscopy for cytopathology of exfoliated cervical cells

Cervical cancer is the fourth most common cancer affecting women worldwide but mortality can be decreased by early detection of pre-malignant lesions. The Pap smear test is the most commonly used method in cervical cancer screening programmes. Although specificity is high for this test, it is widely acknowledged that sensitivity can be poor mainly due to the subjective nature of the test. There is a need for new objective tests for the early detection of pre-malignant cervical lesions. Over the past two decades, Raman spectroscopy has emerged as a promising new technology for cancer screening and diagnosis. The aim of this study was to evaluate the potential of Raman spectroscopy for cervical cancer screening using both Cervical Intraepithelial Neoplasia (CIN) and Squamous Intraepithelial Lesion (SIL) classification terminology. ThinPrep® Pap samples were recruited from a cervical screening population. Raman spectra were recorded from single cell nuclei and subjected to multivariate statistical analysis. Normal and abnormal ThinPrep® samples were discriminated based on the biochemical fingerprint of the cells using Principal Component Analysis (PCA). Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA) was employed to build classification models based on either CIN or SIL terminology. This study has shown that Raman spectroscopy can be successfully applied to the study of routine cervical cytology samples from a cervical screening programme and that the use of CIN terminology resulted in improved sensitivity for high grade cases.

Competitive evaluation of data mining algorithms for use in classification of leukocyte subtypes with Raman microspectroscopy

In this study Raman spectral data from peripheral blood mononuclear cells (PBMCs) is used for the competitive evaluation of three data-mining models in discriminating a highly pure population of T-cell lymphocytes from other myeloid cells within the PBMCs fraction.

Vibrational spectroscopy for cervical cancer pathology, from biochemical analysis to diagnostic tool

Cervical cancer is the second most common cancer in women worldwide with 80% of cases arising in the developing world. The mortality associated with cervical cancer can be reduced if this disease is detected at the early stages of development or at the pre-malignant state (cervical intraepithelial neoplasia, CIN). The aim of this study was to investigate the potential of Raman spectroscopy as a diagnostic tool to detect biochemical changes accompanying cervical cancer progression. Raman spectra were acquired from proteins, nucleic acids, lipids and carbohydrates in order to gain an insight into the biochemical composition of cells and tissues. Spectra were also obtained from histological samples of normal, CIN and invasive carcinoma tissue from 40 patients. Multivariate analysis of the spectra was carried out to develop a classification model to discriminate normal from abnormal tissue. The results show that Raman spectroscopy displays a high sensitivity to biochemical changes in tissue during disease progression resulting in an exceptional prediction accuracy when discriminating between normal cervical tissue, invasive carcinoma and cervical intraepithelial neoplasia (CIN). Raman spectroscopy shows enormous clinical potential as a rapid non-invasive diagnostic tool for cervical and other cancers.