In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques (original) (raw)
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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.
Advanced Biomedical and Clinical Diagnostic Systems XI, 2013
Raman spectroscopy is a vibrational spectroscopic technique capable of optically probing the compositional, conformational, and structural changes in the tissue associated with disease progression. The main goal of this work is to develop an integrated fingerprint (FP) and high wavenumber (HW) in vivo confocal Raman spectroscopy for simultaneous FP/HW tissue Raman spectral measurements. This work further explores the potential of integrated FP/HW Raman spectroscopy developed as a diagnostic tool for in vivo detection of cervical precancer. A total of 473 in vivo integrated FP/HW Raman spectra (340 normal and 133 precancer) were acquired from 35 patients within 1 s during clinical colposcopy. The major tissue Raman peaks are noticed around 854, 937, 1001, 1095, 1253, 1313, 1445, 1654, 2946 and 3400 cm -1 , related to the molecular changes (e.g., proteins, lipids, glycogen, nucleic acids, water, etc.) that accompany the dysplastic transformation of tissue. The FP (800 -1800 cm -1 ), HW (2800 -3800 cm -1 ) and the integrated FP/HW Raman spectra were analyzed using partial least squares-discriminant analysis (PLS-DA) together with the leave-one patient-out, cross-validation. The developed PLS-DA classification models and receiver operating characteristics (ROC) curves for the FP, HW and integrated FP/HW spectroscopy further discloses that the performance of integrated FP/HW Raman spectroscopy is superior to that of all others in discriminating the dysplastic cervix. The results of this work indicate that the co-contributions of underlying rich biochemical information revealed by the complementary spectral modalities (FP and HW Raman) can improve the in vivo early diagnosis of cervical precancer at clinical colposcopy
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.
Analytical Chemistry, 2012
Raman spectroscopy is a vibrational spectroscopic technique capable of nondestructively probing endogenous biomolecules and their changes associated with dysplastic transformation in the tissue. The main objectives of this study are (i) to develop a simultaneous fingerprint (FP) and high-wavenumber (HW) confocal Raman spectroscopy and (ii) to investigate its diagnostic utility for improving in vivo diagnosis of cervical precancer (dysplasia). We have successfully developed an integrated FP/HW confocal Raman diagnostic system with a ball-lens Raman probe for simultaneous acquistion of FP/HW Raman signals of the cervix in vivo within 1 s. A total of 476 in vivo FP/HW Raman spectra (356 normal and 120 precancer) are acquired from 44 patients at clinical colposcopy. The distinctive Raman spectral differences between normal and dysplastic cervical tissue are observed at ∼854, 937, 1001, 1095, 1253, 1313, 1445, 1654, 2946, and 3400 cm −1 mainly related to proteins, lipids, glycogen, nucleic acids and water content in tissue. Multivariate diagnostic algorithms developed based on partial least-squares-discriminant analysis (PLS-DA) together with the leave-one-patient-out, cross-validation yield the diagnostic sensitivities of 84.2%, 76.7%, and 85.0%, respectively; specificities of 78.9%, 73.3%, and 81.7%, respectively; and overall diagnostic accuracies of 80.3%, 74.2%, and 82.6%, respectively, using FP, HW, and integrated FP/HW Raman spectroscopic techniques for in vivo diagnosis of cervical precancer. Receiver operating characteristic (ROC) analysis further confirms the best performance of the integrated FP/HW confocal Raman technique, compared to FP or HW Raman spectroscopy alone. This work demonstrates, for the first time, that the simultaneous FP/HW confocal Raman spectroscopy has the potential to be a clinically powerful tool for improving early diagnosis and detection of cervical precancer in vivo during clinical colposcopic examination.
Near-infrared-excited confocal Raman spectroscopy advances in vivo diagnosis of cervical precancer
Journal of Biomedical Optics, 2013
Raman spectroscopy is a unique optical technique that can probe the changes of vibrational modes of biomolecules associated with tissue premalignant transformation. This study evaluates the clinical utility of confocal Raman spectroscopy over near-infrared (NIR) autofluorescence (AF) spectroscopy and composite NIR AF/ Raman spectroscopy for improving early diagnosis of cervical precancer in vivo at colposcopy. A rapid NIR Raman system coupled with a ball-lens fiber-optic confocal Raman probe was utilized for in vivo NIR AF/ Raman spectral measurements of the cervix. A total of 1240 in vivo Raman spectra [normal (n ¼ 993), dysplasia (n ¼ 247)] were acquired from 84 cervical patients. Principal components analysis (PCA) and linear discriminant analysis (LDA) together with a leave-one-patient-out, cross-validation method were used to extract the diagnostic information associated with distinctive spectroscopic modalities. The diagnostic ability of confocal Raman spectroscopy was evaluated using the PCA-LDA model developed from the significant principal components (PCs) [i.e.
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.
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.
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 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...
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2017
The molecular level changes associated with oncogenesis precede the morphological changes in cells and tissues. Hence molecular level diagnosis would promote early diagnosis of the disease. Raman spectroscopy is capable of providing specific spectral signature of various biomolecules present in the cells and tissues under various pathological conditions. The aim of this work is to develop a non-linear multi-class statistical methodology for discrimination of normal, neoplastic and malignant cells/tissues. The tissues were classified as normal, premalignant and malignant by employing Principal Component Analysis followed by Artificial Neural Network (PC-ANN). The overall accuracy achieved was 99%. Further, to get an insight into the quantitative biochemical composition of the normal, neoplastic and malignant tissues, a linear combination of the major biochemicals by non-negative least squares technique was fit to the measured Raman spectra of the tissues. This technique confirms the changes in the major biomolecules such as lipids, nucleic acids, actin, glycogen and collagen associated with the different pathological conditions. To study the efficacy of this technique in comparison with histopathology, we have utilized Principal Component followed by Linear Discriminant Analysis (PC-LDA) to discriminate the well differentiated, moderately differentiated and poorly differentiated squamous cell carcinoma with an accuracy of 94.0%. And the results demonstrated that Raman spectroscopy has the potential to complement the good old technique of histopathology.