Raman microspectroscopy for the early detection of pre-malignant changes in cervical tissue (original) (raw)
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Cervical cancer detection based on serum sample Raman spectroscopy
Lasers in medical science, 2013
The use of Raman spectroscopy to analyze the biochemical composition of serum samples and hence distinguish between normal and cervical cancer serum samples was investigated. The serum samples were obtained from 19 patients who were clinically diagnosed with cervical cancer, 3 precancer, and 20 healthy volunteer controls. The imprint was put under an Olympus microscope, and around points were chosen for Raman measurement.All spectra were collected at a Horiba Jobin-Yvon LabRAM HR800 Raman Spectrometer with a laser of 830-nm wavelength and 17-mW power irradiation. Raw spectra were processed by carrying out baseline correction, smoothing, andnormalization to remove noise, florescence, and shot noise and then analyzed using principal component analysis (PCA). The control serum spectrum showed the presence of higher amounts of carotenoids indicated by peaks at 1,002, 1,160, and 1,523 cm−1and intense peaks associated with protein components at 754, 853, 938, 1,002, 1,300–1,345, 1,447, 1,523, 1,550, 1,620, and 1,654 cm−1. The Raman bands assigned to glutathione (446, 828, and 1,404 cm−1) and tryptophan (509, 1,208, 1,556, 1,603, and 1,620 cm−1) in cervical cancer were higher than those of control samples, suggesting that their presence may also play a role in cervical cancer. Furthermore, weak bands in the control samples attributed to tryptophan (545, 760, and 1,174 cm−1) and amide III (1,234–1,290 cm−1) seem to disappear and decrease in the cervical cancer samples, respectively. It is shown that the serum samples from patients with cervical cancer and from the control group can be discriminated with high sensitivity and specificity when the multivariate statistical methods of PCA is applied to Raman spectra. PCA allowed us to define the wavelength differences between the spectral bands of the control and cervical cancer groups by confirming that the main molecular differences among the control and cervical cancer samples were glutathione, tryptophan, β carotene, and amide III. The preliminary results suggest that Raman spectroscopy could be a highly effective technique with a strong potential of support for current techniques as Papanicolaou smear by reducing the number of these tests; nevertheless, with the construction of a data library integrated with a large number of cervical cancer and control Raman spectra obtained from a wide range of healthy and cervical cancer population, Raman–PCA technique could be converted into a new technique for noninvasive real-time diagnosis of cervical cancer from serum samples.
In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques
The Analyst, 2011
This study aimed to evaluate the clinical utility of applying near-infrared (NIR) Raman spectroscopy and genetic algorithm-partial least squares-discriminant analysis (GA-PLS-DA) to identify biomolecular changes of cervical tissues associated with dysplastic transformation during colposcopic examination. A total of 105 in vivo Raman spectra were measured from 57 cervical sites (35 normal and 22 precancer sites) of 29 patients recruited, in which 65 spectra were from normal sites, while 40 spectra were from cervical precancerous lesions (i.e., 7 low-grade CIN and 33 high-grade CIN). The GA feature selection technique incorporated with PLS was utilized to study the significant biochemical Raman bands for differentiation between normal and precancer cervical tissues. The GA-PLS-DA algorithm with double cross-validation (dCV) identified seven diagnostically significant Raman bands in the ranges of 925related to proteins, nucleic acids and lipids in tissue, and yielded a diagnostic accuracy of 82.9% (sensitivity of 72.5% (29/40) and specificity of 89.2% (58/65)) for precancer detection. The results of this exploratory study suggest that Raman spectroscopy in conjunction with GA-PLS-DA and dCV methods has the potential to provide clinically significant discrimination between normal and precancer cervical tissues at the molecular level.
Raman spectroscopic study on classification of cervical cell specimens
Cervix-cancer is the third most common female cancer worldwide. Papanicolaou (Pap) test, a wellrecognized screening tool, is labor intensive, time consuming and prone to subjective interpretations. Optical spectroscopic methods, sensitive to molecular changes are being pursued as potential diagnostics tool. In this study we have explored Raman spectroscopic approach to differentiate exfoliated cell pellets using 94 cervical cell specimens (45-normal and 49-abnormal specimens). Study was carried out by two approaches. In the first approach, spectral data from 37 cell specimens were acquired and analyzed by Principal Component-Linear Discriminant Analysis (PC-LDA), which yielded classification efficiencies of 86% and 84% for normal and abnormal specimens, respectively. Mean and difference spectra suggest presence of blood in abnormal specimen as a major cause of discrimination. However, as tumor is vascular, bleeding was observed during abnormal sample collection. Hence, spectra of abnormal specimens show heme and fibrin features, and this can lead to false interpretations, as bleeding also occur in several non-cancerous conditions. Therefore, remaining 57 specimens were treated with Red Blood Corpuscles (RBC) lysis buffer in order to remove the RBC influence. PC-LDA resulted classification efficiency of about 79% and 78% for normal and abnormal smear, respectively -comparable to Pap test. Thus finding of the study suggests feasibility of Raman spectroscopic classification of normal and cancerous exfoliated cervical cell specimens.
Processing ThinPrep cervical cytological samples for Raman spectroscopic analysis
Anal. Methods, 2014
Raman microspectroscopy has been proven to be a promising technique for diagnosis and early detection of pathologies. The data collected delivers a chemical fingerprint allowing the identification of specific biomarkers indicating the presence of abnormalities. Label free, fast and cost effective, Raman spectroscopy has already been proposed as the new generation of diagnostic tool with a strong potential but has not emerged in the medical field as yet. Notably, it is crucial to improve and adapt the protocols used to reach suitable reproducibility for screening large cohorts of patients. In this study, it is demonstrated that the variability existing in the data sets collected can be limiting. Notably, when working on cervical ThinPrep samples, the presence of blood residue can be detected by Raman spectroscopy swamping the cellular signal. However, combining a washing of the slides using H 2 O 2 and alcohols (70% ethanol and 100% Industrial Methylated Spirits), the blood features are removed from the data without altering either the cell morphology or the spectral features. Ultimately, this work demonstrates the improved potential of Raman spectroscopy for ThinPrep analysis based on improved protocols for sample preparation. Therefore, the screening of cervical cells for the detection of abnormalities and identification of patients with Cervical Intraepithelial Neoplasia (CIN) is achievable.
Raman Spectroscopy of Individual Cervical Exfoliated Cells in Premalignant and Malignant Lesions
Applied Sciences, 2022
Cervical cancer is frequent neoplasia. Currently, the diagnostic approach includes cervical cytology, colposcopy, and histopathology studies; combining detection techniques increases the sensitivity and specificity of the tests. Raman spectroscopy is a high-resolution technique that supports the diagnosis of malignancies. This study aimed to evaluate the Raman spectroscopy technique discriminating between healthy and premalignant/malignant cervical cells. We included 81 exfoliative cytology samples, 29 in the “healthy group” (negative cytology), and 52 in the “CIN group” (premalignant/malignant lesions). We obtained the nucleus and cytoplasm Raman spectra of individual cells. We tested the spectral differences between groups using Permutational Multivariate Analysis of Variance (PERMANOVA) and Canonical Analysis of Principal Coordinates (CAP). We found that Raman spectra have increased intensity in premalignant/malignant cells compared with healthy cells. The characteristic Raman ba...
Raman spectroscopy for screening and diagnosis of cervical cancer
Analytical and Bioanalytical Chemistry, 2015
Cervical cancer is the fourth most common cancer in women worldwide and mainly affects younger women. The mortality associated with cervical cancer can be reduced if this disease is detected at the pre-cancer stage. Current gold standard methods include cytopathology, HPV testing and histopathology but these methods are limited in terms of subjectivity, cost and time. There is an unmet clinical need for new methods to aid clinicians in the early detection of cervical pre-cancer. These methods should be objective, rapid and require minimal sample preparation. Raman spectroscopy is a vibrational spectroscopic technique by which incident radiation is used to induce vibrations in the molecules of a sample and the scattered radiation may be used to characterise the sample in a rapid and nondestructive manner. Raman spectroscopy is sensitive to subtle biochemical changes occurring at the molecular level allowing spectral variations corresponding to disease onset to be detected. Over the past 15 years, there have been numerous reports showing the potential of Raman spectroscopy together with multivariate statistical analysis for the detection of a variety of cancers. This paper discusses the recent advances and issues for cervical cancer screening and diagnosis and offers some perspectives for the future.
Near-Infrared Micro-Raman Spectroscopy for in Vitro Detection of Cervical Cancer
Applied Spectroscopy, 2010
Near-infrared Raman spectroscopy is a powerful analytical tool for detecting critical differences in biological samples with minimum interference in the Raman spectra from the native fluorescence of the samples. The technique is often suggested as a potential screening tool for cancer. In this article we report in vitro Raman spectra of squamous cells in normal and cancerous cervical human tissue from seven patients, which have good signal-to-noise ratio and which were found to be reproducible. These preliminary results show that several Raman features in these spectra could be used to distinguish cancerous cervical squamous cells from normal cervical squamous cells. In general, the Raman spectra of cervical cancer cells show intensity differences compared to those of normal squamous cell spectra. For example, several well-defined Raman peaks of collagen in the 775 to 975 cm −1 region are observed in the case of normal squamous cells, but these are below the detection limit of normal Raman spectroscopy in the spectra of invasive cervical cancer cells. In the high frequency 2800 to 3100 cm −1 region, it is found that the peak area under the CH stretching band is lower by a factor of approximately six in the spectra of cervical cancer cells as compared with that of the normal cells. The Raman chemical maps of regions of cancer and normal cells in the cervical epithelium made from the spectral features in the 775 to 975 cm −1 and 2800 to 3100 cm −1 regions are also found to show good correlation with each other.
Optics in Health Care and Biomedical Optics III, 2007
Near-infrared (NIR) Raman spectroscopy has shown promise to detect cancer and precancer in human through measuring the biomolecular and biochemical changes of tissue associated with diseases transformation. Most of studies of NIR Raman spectroscopy on tissue diagnosis are concentrated on the so-called fingerprint region (800-1800 cm -1 ), there are only very limited work for tissue diagnosis using the high wavenumber (2800-3700 cm -1 ) spectral features. The purpose of this study is to explore the ability of NIR Raman spectroscopy in high wavenumber region for the in vivo detection of cervical precancer. A rapid NIR Raman spectroscopy system associated with a fiber-optic Raman probe was used for the in vivo spectroscopic measurements. Multivariate statistical techniques including principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop the diagnostic algorithm based on the spectral data from 2800-3700 cm -1 . Classification result based on PCA-LDA showed that high wavenumber NIR Raman spectroscopy can achieve the diagnostic sensitivity of 93.5% and specificity of 95.7% for precancer classification.
Raman spectroscopy studies for diagnosis of cancer in human uterine cervix
Cancer of uterine cervix is one of the leading cancers among women in both developed and developing countries. Optical spectroscopy methods mostly Fourier transform infrared (FTIR) and fluorescence have widely been used to diagnose cervix cancer using cells as well as tissues. Raman spectra of normal and malignant tissues were recorded in fingerprint region. Normal cervix tissues are characterized by strong, broad amide I, broader amide III and strong peaks at 853 and 938 cm À1 which can be attributed to structural proteins such as collagen. Prominent features of malignant tissue spectra with respect to normal tissue are-relatively weaker and sharper amide I, minor red shift in DCH 2 and sharper amide III which indicate the presence of Deoxyribonucleic acid (DNA), lipids and non-collagenous proteins. In order to develop highly objective discrimination methods, very elaborate data analysis was carried out using Principal Components Analysis (PCA). Standard sets for normal and malignant were prepared and tested retrospectively and prospectively. Several parameters such as (scores of factor, Mahalanobis distance and spectral residuals) were explored for discrimination and very clean clustering of normal and malignant spectra was achieved. A multiparametric approach (limit test) combining all the above discrimination parameters was also considered, in order to develop unambiguous discrimination. This analysis has produced very high, 99.5%, sensitivity and specificity. Results obtained in this study thus validate Raman spectroscopy methods for discrimination of normal and malignant tissues in cervical cancers. #
Raman spectroscopy studies for diagnosis of cancers in human uterine cervix
Vibrational …, 2006
Cancer of uterine cervix is one of the leading cancers among women in both developed and developing countries. Optical spectroscopy methods mostly Fourier transform infrared (FTIR) and fluorescence have widely been used to diagnose cervix cancer using cells as well as tissues. Raman spectra of normal and malignant tissues were recorded in fingerprint region. Normal cervix tissues are characterized by strong, broad amide I, broader amide III and strong peaks at 853 and 938 cm À1 which can be attributed to structural proteins such as collagen. Prominent features of malignant tissue spectra with respect to normal tissue are-relatively weaker and sharper amide I, minor red shift in DCH 2 and sharper amide III which indicate the presence of Deoxyribonucleic acid (DNA), lipids and non-collagenous proteins. In order to develop highly objective discrimination methods, very elaborate data analysis was carried out using Principal Components Analysis (PCA). Standard sets for normal and malignant were prepared and tested retrospectively and prospectively. Several parameters such as (scores of factor, Mahalanobis distance and spectral residuals) were explored for discrimination and very clean clustering of normal and malignant spectra was achieved. A multiparametric approach (limit test) combining all the above discrimination parameters was also considered, in order to develop unambiguous discrimination. This analysis has produced very high, 99.5%, sensitivity and specificity. Results obtained in this study thus validate Raman spectroscopy methods for discrimination of normal and malignant tissues in cervical cancers.