Raman Spectroscopy of Individual Cervical Exfoliated Cells in Premalignant and Malignant Lesions (original) (raw)
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FDVIBSPC16: Raman spectroscopy for cytopathology of exfoliated cervical cells
Faraday Discuss., 2015
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...
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.
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.
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.
In vivo Raman spectroscopy of cervix cancers
Optical Biopsy XII, 2014
In vivo Raman spectroscopy is being projected as a new, noninvasive method for cervical cancer diagnosis. In most of the reported studies, normal areas in the cancerous cervix were used as control. However, in the Indian subcontinent, the majority of cervical cancers are detected at advanced stages, leaving no normal sites for acquiring control spectra. Moreover, vagina and ectocervix are reported to have similar biochemical composition. Thus, in the present study, we have evaluated the feasibility of classifying normal and cancerous conditions in the Indian population and we have also explored the utility of the vagina as an internal control. A total of 228 normal and 181 tumor in vivo Raman spectra were acquired from 93 subjects under clinical supervision. The spectral features in normal conditions suggest the presence of collagen, while DNA and noncollagenous proteins were abundant in tumors. Principal-component linear discriminant analysis (PC-LDA) yielded 97% classification efficiency between normal and tumor groups. An analysis of a normal cervix and vaginal controls of cancerous and noncancerous subjects suggests similar spectral features between these groups. PC-LDA of tumor, normal cervix, and vaginal controls further support the utility of the vagina as an internal control. Overall, findings of the study corroborate with earlier studies and facilitate objective, noninvasive, and rapid Raman spectroscopic-based screening/diagnosis of cervical cancers.
RAMAN SPECTROSCOPIC STUDY ON PREDICTION OF TREATMENT RESPONSE IN CERVICAL CANCERS
Concurrent chemoradiotherapy (CCRT) is the choice of treatment for locally advanced cervical cancers; however, tumors exhibit diverse response to treatment. Early prediction of tumor response leads to individualizing treatment regimen. Response evaluation criteria in solid tumors (RECIST), the current modality of tumor response assessment, is often subjective and carried out at the¯rst visit after treatment, which is about four months. Hence, there is a need for better predictive tool for radioresponse. Optical spectroscopic techniques, sensitive to molecular alteration, are being pursued as potential diagnostic tools. Present pilot study aims to explore thē ber-optic-based Raman spectroscopy approach in prediction of tumor response to CCRT, before taking up extensive in vivo studies. Ex vivo Raman spectra were acquired from biopsies collected from 11 normal (148 spectra), 16 tumor (201 spectra) and 13 complete response (151 CR spectra), one partial response (8 PR spectra) and one nonresponder (8 NR spectra) subjects. Data was analyzed using principal component linear discriminant analysis (PC-LDA) followed by leaveone-out cross-validation (LOO-CV). Findings suggest that normal tissues can be e±ciently classi¯ed from both pre-and post-treated tumor biopsies, while there is an overlap between preand post-CCRT tumor tissues. Spectra of CR, PR and NR tissues were subjected to principal component analysis (PCA) and a tendency of classi¯cation was observed, corroborating previous studies. Thus, this study further supports the feasibility of Raman spectroscopy in prediction of tumor radioresponse and prospective noninvasive in vivo applications.
Raman microspectroscopy for the early detection of pre-malignant changes in cervical tissue
Cervical cancer is the third most common cancer affecting women worldwide. The mortality associatedwith cervical cancer can, however, be significantly reduced if the disease is detected at the pre-malignant stage. The aim of this studywas to evaluate the potential of Raman microspectroscopy for elucidation of the biochemical changes associated with the pre-malignant stages of cervical cancer. Formalin fixed paraffin preserved tissue sections from cervical biopsies classified as negative for intraepithelial lesion and malignancy (NILM), low grade squamous intraepithelial lesion (LSIL) or high grade squamous intraepithelial lesion (HSIL) were analysed by Raman spectral mapping. Raman mapping, with K-means cluster analysis (KMCA), was able to differentiate the NILM cervical tissue into three layers including stroma, basal/para-basal and superficial layers, characterized by spectral features of collagen, DNA bases and glycogen respectively. In the LSIL and HSIL samples, KMCA clustered regions of the superficial layer with the basal layer. Using principal components analysis (PCA), biochemical changes associatedwith diseasewere also observed in normal areas of the abnormal samples,wheremorphological changeswere not apparent. This study has shown that Raman microspectroscopy could be useful for the early detection of pre-malignant changes in cervical tissue.
Multiclass discrimination of cervical precancers using Raman spectroscopy
Journal of Raman Spectroscopy, 2009
Raman spectroscopy has the potential to differentiate among the various stages leading to high-grade cervical cancer such as normal, squamous metaplasia, and low-grade cancer. For Raman spectroscopy to successfully differentiate among the stages, an applicable statistical method must be developed. Algorithms like linear discriminant analysis (LDA) are incapable of differentiating among three or more types of tissues. We developed a novel statistical method combining the method of maximum representation and discrimination feature (MRDF) to extract diagnostic information with sparse multinomial logistic regression (SMLR) to classify spectra based on nonlinear features for multiclass analysis of Raman spectra. We found that high-grade spectra classified correctly 95% of the time; low-grade data classified correctly 74% of the time, improving sensitivity from 92 to 98% and specificity from 81 to 96% suggesting that MRDF with SMLR is a more appropriate technique for categorizing Raman spectra. SMLR also outputs a posterior probability to evaluate the algorithm's accuracy. This combined method holds promise to diagnose subtle changes leading to cervical cancer.
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.