12 research outputs found

    Improved Removal of Blood Contamination From ThinPrep Cervical Cytology Camples for Raman Spectroscopic Analysis

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    There is an unmet need for methods to help in the early detection of cervical precancer. Optical spectroscopy-based techniques, such as Raman spectroscopy, have shown great potential for diagnosis of different cancers, including cervical cancer. However, relatively few studies have been carried out on liquid-based cytology (LBC) pap test specimens and confounding factors, such as blood contamination, have been identified. Previous work reported a method to remove blood contamination before Raman spectroscopy by pretreatment of the slides with hydrogen peroxide. The aim of the present study was to extend this work to excessively bloody samples to see if these could be rendered suitable for Raman spectroscopy. LBC ThinPrep specimens were treated by adding hydrogen peroxide directly to the vial before slide preparation. Good quality Raman spectra were recorded from negative and high grade (HG) cytology samples with no blood contamination and with heavy blood contamination. Good classification between negative and HG cytology could be achieved for samples with no blood contamination (sensitivity 92%, specificity 93%) and heavy blood contamination (sensitivity 89%, specificity 88%) with poorer classification when samples were combined (sensitivity 82%, specificity 87%). This study demonstrates for the first time the improved potential of Raman spectroscopy for analysis of ThinPrep specimens regardless of blood contamination

    Comparability of Raman Spectroscopic Configurations: A LargeScale Cross-Laboratory Study

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    The variable configuration of Raman spectroscopic platforms is one ofthe major obstacles in establishing Raman spectroscopy as a valuable physicochemicalmethod within real-world scenarios such as clinical diagnostics. For such real worldapplications like diagnostic classification, the models should ideally be usable to predictdata from different setups. Whether it is done by training a rugged model with data frommany setups or by a primary-replica strategy where models are developed on a‘primary’setup and the test data are generated on‘replicate’setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable.However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if thesame samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumentalconfiguration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correctfor them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST(European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allowsvarious instrumental configurations ranging from highly confocal setups tofibre-optic based systems with different excitationwavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts,intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improvethe inter-laboratory studie

    Raman Spectroscopic Detection of High-Grade Cervical Cytology: Using Morphologically Normal Appearing Cells

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    This study aims to detect high grade squamous intraepithelial cells (HSIL) by investigating HSIL associated biochemical changes in morphologically normal appearing intermediate and superficial cells using Raman spectroscopy. Raman spectra (n = 755) were measured from intermediate and superficial cells from negative cytology ThinPrep specimens (n = 18) and from morphologically normal appearing intermediate and superficial cells from HSIL cytology ThinPrep specimens (n = 17). The Raman data was subjected to multivariate algorithms including the standard principal component analysis (PCA)-linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) together with random subsets cross-validation for discriminating negative cytology from HSIL. The PCA-LDA method yielded sensitivities of 74.9%, 72.8%, and 75.6% and specificities of 89.9%, 81.9%, and 84.5%, for HSIL diagnosis based on the dataset obtained from intermediate, superficial and mixed intermediate/superficial cells, respectively. The PLS-DA method provided improved sensitivities of 95.5%, 95.2% and 96.1% and specificities of 92.7%, 94.7% and 93.5% compared to the PCA-LDA method. The results demonstrate that the biochemical signatures of morphologically normal appearing cells can be used to discriminate between negative and HSIL cytology. In addition, it was found that mixed intermediate and superficial cells could be used for HSIL diagnosis as the biochemical differences between negative and HSIL cytology were greater than the biochemical differences between intermediate and superficial cell types

    Development and Validation of a Raman Spectroscopic Classification Model for Cervical Intraepithelial Neoplasia (CIN)

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    The mortality associated with cervical cancer can be reduced if detected at the precancer stage, but current methods are limited in terms of subjectivity, cost and time. Optical spectroscopic methods such as Raman spectroscopy can provide a rapid, label-free and nondestructive measurement of the biochemical fingerprint of a cell, tissue or biofluid. Previous studies have shown the potential of Raman spectroscopy for cervical cancer diagnosis, but most were pilot studies with small sample sizes. The aim of this study is to show the clinical utility of Raman spectroscopy for identifying cervical precancer in a large sample set with validation in an independent test set. Liquid-based cervical cytology samples (n = 662) (326 negative, 200 cervical intraepithelial neoplasia (CIN)1 and 136 CIN2+) were obtained as a training set. Raman spectra were recorded from single-cell nuclei and subjected to a partial least squares discriminant analysis (PLSDA). In addition, the PLSDA classification model was validated using a blinded independent test set (n = 69). A classification accuracy of 91.3% was achieved with only six of the blinded samples misclassified. This study showed the potential clinical utility of Raman spectroscopy with a good classification of negative, CIN1 and CIN2+ achieved in an independent test set

    Field remote Stokes/anti-Stokes Raman characterization of sulfur in hydrothermal vents

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    To study the dynamics of active volcanic environments, minerals involved in fresh lava flows are a nice probe and Raman spectroscopy is an excellent tool for their characterization. Because of the highly hostile environment linked to volcanic activity, studying lava cooling and weathering needs remote setups and specific procedures dedicated to medium‐high temperature targets. In this paper, we present the remote Raman characterization of sulfur produce by the fumarolic activity at Solfatara crater (Phlegraean Fields, Italy). Two medium temperature sites (280–380 K) were probed with two different Raman setups. For both, β‐sulfur is the prominent type in the entire temperature range and the absolute local temperature of the sulfur was remotely estimated by mean of a Stokes/anti‐Stokes procedure with ±10 K uncertainty. These results represent a good starting point for the development of new setups and protocols aimed to an increase of both measurement distance and temperature range.Published1385-13944V. Processi pre-eruttivi1TR. GeorisorseJCR Journa

    Raman spectroscopic detection of high-grade cervical cytology: Using morphologically normal appearing cells

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    Abstract This study aims to detect high grade squamous intraepithelial cells (HSIL) by investigating HSIL associated biochemical changes in morphologically normal appearing intermediate and superficial cells using Raman spectroscopy. Raman spectra (n = 755) were measured from intermediate and superficial cells from negative cytology ThinPrep specimens (n = 18) and from morphologically normal appearing intermediate and superficial cells from HSIL cytology ThinPrep specimens (n = 17). The Raman data was subjected to multivariate algorithms including the standard principal component analysis (PCA)-linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) together with random subsets cross-validation for discriminating negative cytology from HSIL. The PCA-LDA method yielded sensitivities of 74.9%, 72.8%, and 75.6% and specificities of 89.9%, 81.9%, and 84.5%, for HSIL diagnosis based on the dataset obtained from intermediate, superficial and mixed intermediate/superficial cells, respectively. The PLS-DA method provided improved sensitivities of 95.5%, 95.2% and 96.1% and specificities of 92.7%, 94.7% and 93.5% compared to the PCA-LDA method. The results demonstrate that the biochemical signatures of morphologically normal appearing cells can be used to discriminate between negative and HSIL cytology. In addition, it was found that mixed intermediate and superficial cells could be used for HSIL diagnosis as the biochemical differences between negative and HSIL cytology were greater than the biochemical differences between intermediate and superficial cell types

    Development and Validation of a Raman Spectroscopic Classification Model for Cervical Intraepithelial Neoplasia (CIN)

    No full text
    The mortality associated with cervical cancer can be reduced if detected at the precancer stage, but current methods are limited in terms of subjectivity, cost and time. Optical spectroscopic methods such as Raman spectroscopy can provide a rapid, label-free and nondestructive measurement of the biochemical fingerprint of a cell, tissue or biofluid. Previous studies have shown the potential of Raman spectroscopy for cervical cancer diagnosis, but most were pilot studies with small sample sizes. The aim of this study is to show the clinical utility of Raman spectroscopy for identifying cervical precancer in a large sample set with validation in an independent test set. Liquid-based cervical cytology samples (n = 662) (326 negative, 200 cervical intraepithelial neoplasia (CIN)1 and 136 CIN2+) were obtained as a training set. Raman spectra were recorded from single-cell nuclei and subjected to a partial least squares discriminant analysis (PLSDA). In addition, the PLSDA classification model was validated using a blinded independent test set (n = 69). A classification accuracy of 91.3% was achieved with only six of the blinded samples misclassified. This study showed the potential clinical utility of Raman spectroscopy with a good classification of negative, CIN1 and CIN2+ achieved in an independent test set
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