Shiyamala Duraipandian

Simultaneous fingerprint and high-wavenumber confocal Raman spectroscopy enhances early detection of cervical precancer in vivo.

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.

Real-time Raman spectroscopy for in vivo, online gastric cancer diagnosis during clinical endoscopic examination.

Optical spectroscopic techniques including reflectance, fluorescence and Raman spectroscopy have shown promising potential for in vivo precancer and cancer diagnostics in a variety of organs. However, data-analysis has mostly been limited to post-processing and off-line algorithm development. In this work, we develop a fully automated on-line Raman spectral diagnostics framework integrated with a multimodal image-guided Raman technique for real-time in vivo cancer detection at endoscopy. A total of 2748 in vivo gastric tissue spectra (2465 normal and 283 cancer) were acquired from 305 patients recruited to construct a spectral database for diagnostic algorithms development. The novel diagnostic scheme developed implements on-line preprocessing, outlier detection based on principal component analysis statistics (i.e., Hotellings T2 and Q-residuals) for tissue Raman spectra verification as well as for organ specific probabilistic diagnostics using different diagnostic algorithms. Free-running optical diagnosis and processing time of < 0.5 s can be achieved, which is critical to realizing real-time in vivo tissue diagnostics during clinical endoscopic examination. The optimized partial least squares-discriminant analysis (PLS-DA) models based on the randomly resampled training database (80% for learning and 20% for testing) provide the diagnostic accuracy of 85.6% [95% confidence interval (CI): 82.9% to 88.2%] [sensitivity of 80.5% (95% CI: 71.4% to 89.6%) and specificity of 86.2% (95% CI: 83.6% to 88.7%)] for the detection of gastric cancer. The PLS-DA algorithms are further applied prospectively on 10 gastric patients at gastroscopy, achieving the predictive accuracy of 80.0% (60/75) [sensitivity of 90.0% (27/30) and specificity of 73.3% (33/45)] for in vivo diagnosis of gastric cancer. The receiver operating characteristics curves further confirmed the efficacy of Raman endoscopy together with PLS-DA algorithms for in vivo prospective diagnosis of gastric cancer. This work successfully moves biomedical Raman spectroscopic technique into real-time, on-line clinical cancer diagnosis, especially in routine endoscopic diagnostic applications.

In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques

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 925-935, 979-999, 1080-1090, 1240-1260, 1320-1340, 1400-1420, and 1625-1645 cm(-1) related 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.

Near-infrared-excited confocal Raman spectroscopy advances in vivo diagnosis of cervical precancer

Abstract. 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=993), dysplasia (n=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., PC4, 0.0023%; PC5, 0.00095%; PC8, 0.00022%, (p<0.05)], representing the primary tissue Raman features (e.g., 854, 937, 1095, 1253, 1311, 1445, and 1654  cm−1). Confocal Raman spectroscopy coupled with PCA-LDA modeling yielded the diagnostic accuracy of 84.1% (a sensitivity of 81.0% and a specificity of 87.1%) for in vivo discrimination of dysplastic cervix. The receiver operating characteristic curves further confirmed that the best classification was achieved using confocal Raman spectroscopy compared to the composite NIR AF/Raman spectroscopy or NIR AF spectroscopy alone. This study illustrates that confocal Raman spectroscopy has great potential to improve early diagnosis of cervical precancer in vivo during clinical colposcopy.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

Effect of hormonal variation on in vivo high wavenumber Raman spectra improves cervical precancer detection

Raman spectroscopy is a unique analytical probe for molecular vibration and is capable of providing specific spectroscopic fingerprints of molecular compositions and structures of biological tissues. The aim of this study is to improve the classification accuracy of cervical precancer by characterizing the variations in the normal high wavenumber (HW - 2800-3700cm-1) Raman spectra arising from the menopausal status of the cervix. A rapidacquisition near-infrared (NIR) Raman spectroscopic system was used for in vivo tissue Raman measurements at 785 nm excitation. Individual HW Raman spectrum was measured with a 5s exposure time from both normal and precancer tissue sites of 15 patients recruited. The acquired Raman spectra were stratified based on the menopausal status of the cervix before the data analysis. Significant differences were noticed in Raman intensities of prominent band at 2924 cm-1 (CH3 stretching of proteins) and the broad water Raman band (in the 3100-3700 cm-1 range) with a peak at 3390 cm-1 in normal and dysplasia cervical tissue sites. Multivariate diagnostic decision algorithm based on principal component analysis (PCA) and linear discriminant analysis (LDA) was utilized to successfully differentiate the normal and precancer cervical tissue sites. By considering the variations in the Raman spectra of normal cervix due to the hormonal or menopausal status of women, the diagnostic accuracy was improved from 71 to 91%. By incorporating these variations prior to tissue classification, we can significantly improve the accuracy of cervical precancer detection using HW Raman spectroscopy.

Integrated fingerprint and high wavenumber confocal Raman spectroscopy for in vivo diagnosis of cervical precancer

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

Quantitative fiber-optic Raman spectroscopy for tissue Raman measurements

Molecular profiling of tissue using near-infrared (NIR) Raman spectroscopy has shown great promise for in vivo detection and prognostication of cancer. The Raman spectra measured from the tissue generally contain fundamental information about the absolute biomolecular concentrations in tissue and its changes associated with disease transformation. However, producing analogues tissue Raman spectra present a great technical challenge. In this preliminary study, we propose a method to ensure the reproducible tissue Raman measurements and validated with the in vivo Raman spectra (n=150) of inner lip acquired using different laser powers (i.e., 30 and 60 mW). A rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe was utilized for tissue Raman measurements. The investigational results showed that the variations between the spectra measured with different laser powers are almost negligible, facilitating the quantitative analysis of tissue Raman measurements in vivo.

Univariate and multivariate methods for chemical mapping of cervical cancer cells

Visualization of cells and subcellular organelles are currently carried out using available microscopy methods such as cryoelectron microscopy, and fluorescence microscopy. These methods require external labeling using fluorescent dyes and extensive sample preparations to access the subcellular structures. However, Raman micro-spectroscopy provides a non-invasive, label-free method for imaging the cells with chemical specificity at sub-micrometer spatial resolutions. The scope of this paper is to image the biochemical/molecular distributions in cells associated with cancerous changes. Raman map data sets were acquired from the human cervical carcinoma cell lines (HeLa) after fixation under 785 nm excitation wavelength. The individual spectrum was recorded by raster-scanning the laser beam over the sample with 1μm step size and 10s exposure time. Images revealing nucleic acids, lipids and proteins (phenylalanine, amide I) were reconstructed using univariate methods. In near future, the small pixel to pixel variations will also be imaged using different multivariate methods (PCA, clustering (HCA, K-means, FCM)) to determine the main cellular constitutions. The hyper-spectral image of cell was reconstructed utilizing the spectral contrast at different pixels of the cell (due to the variation in the biochemical distribution) without using fluorescent dyes. Normal cervical squamous cells will also be imaged in order to differentiate normal and cancer cells of cervix using the biochemical changes in different grades of cancer. Based on the information obtained from the pseudo-color maps, constructed from the hyper-spectral cubes, the primary cellular constituents of normal and cervical cancer cells were identified.