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Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells

AIM: Spectral Cytopathology (SCP) is a novel spectroscopic method for objective and unsupervised classification of individual exfoliated cells. The limitations of conventional cytopathology are well-recognized within the pathology community. In SCP, cellular differentiation is made by observing mole...

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Autores principales: Schubert, Jennifer M., Bird, Benjamin, Papamarkakis, Kostas, Miljković, Miloš, Bedrossian, Kristi, Laver, Nora, Diem, Max
Formato: Texto
Lenguaje:English
Publicado: 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2894285/
https://www.ncbi.nlm.nih.gov/pubmed/20368702
http://dx.doi.org/10.1038/labinvest.2010.72
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author Schubert, Jennifer M.
Bird, Benjamin
Papamarkakis, Kostas
Miljković, Miloš
Bedrossian, Kristi
Laver, Nora
Diem, Max
author_facet Schubert, Jennifer M.
Bird, Benjamin
Papamarkakis, Kostas
Miljković, Miloš
Bedrossian, Kristi
Laver, Nora
Diem, Max
author_sort Schubert, Jennifer M.
collection PubMed
description AIM: Spectral Cytopathology (SCP) is a novel spectroscopic method for objective and unsupervised classification of individual exfoliated cells. The limitations of conventional cytopathology are well-recognized within the pathology community. In SCP, cellular differentiation is made by observing molecular changes in the nucleus and the cytoplasm, which may or may not produce morphological changes detectable by conventional cytopathology. This proof of concept study demonstrates SCP’s potential as an enhancing tool for cytopathologists by aiding in the accurate and reproducible diagnosis of cells in all states of disease. METHOD: Infrared spectra are collected from cervical cells deposited onto reflectively coated glass slides. Each cell has a corresponding infrared spectrum that describes its unique biochemical composition. Spectral data are processed and analyzed by an unsupervised chemometric algorithm, Principal Component Analysis (PCA). RESULTS: In this blind study, cervical samples are classified by analyzing the spectra of morphologically normal looking squamous cells from normal samples and samples diagnosed by conventional cytopathology with low grade squamous intraepithelial lesions (LSIL). SCP discriminated cytopathological diagnoses amongst twelve different cervical samples with a high degree of specificity and sensitivity. SCP also correlated two samples with abnormal spectral changes: these samples had a normal cytopathological diagnosis but had a history of abnormal cervical cytology. The spectral changes observed in the morphologically normal looking cells are most likely due to an infection with human papillomavirus, HPV. HPV DNA testing was conducted on five additional samples, and SCP accurately differentiated these samples by their HPV status. CONCLUSIONS: SCP tracks biochemical variations in cells that are consistent with the onset of disease. HPV has been implicated as the cause of these changes detected spectroscopically. SCP does not depend on identifying the sparse number of morphologically abnormal cells within a large sample in order to make an accurate classification, as does conventional cytopathology. These findings suggest that the detection of cellular biochemical variations by SCP can serve as a new enhancing screening method that can identify earlier stages of disease.
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spelling pubmed-28942852011-01-01 Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells Schubert, Jennifer M. Bird, Benjamin Papamarkakis, Kostas Miljković, Miloš Bedrossian, Kristi Laver, Nora Diem, Max Lab Invest Article AIM: Spectral Cytopathology (SCP) is a novel spectroscopic method for objective and unsupervised classification of individual exfoliated cells. The limitations of conventional cytopathology are well-recognized within the pathology community. In SCP, cellular differentiation is made by observing molecular changes in the nucleus and the cytoplasm, which may or may not produce morphological changes detectable by conventional cytopathology. This proof of concept study demonstrates SCP’s potential as an enhancing tool for cytopathologists by aiding in the accurate and reproducible diagnosis of cells in all states of disease. METHOD: Infrared spectra are collected from cervical cells deposited onto reflectively coated glass slides. Each cell has a corresponding infrared spectrum that describes its unique biochemical composition. Spectral data are processed and analyzed by an unsupervised chemometric algorithm, Principal Component Analysis (PCA). RESULTS: In this blind study, cervical samples are classified by analyzing the spectra of morphologically normal looking squamous cells from normal samples and samples diagnosed by conventional cytopathology with low grade squamous intraepithelial lesions (LSIL). SCP discriminated cytopathological diagnoses amongst twelve different cervical samples with a high degree of specificity and sensitivity. SCP also correlated two samples with abnormal spectral changes: these samples had a normal cytopathological diagnosis but had a history of abnormal cervical cytology. The spectral changes observed in the morphologically normal looking cells are most likely due to an infection with human papillomavirus, HPV. HPV DNA testing was conducted on five additional samples, and SCP accurately differentiated these samples by their HPV status. CONCLUSIONS: SCP tracks biochemical variations in cells that are consistent with the onset of disease. HPV has been implicated as the cause of these changes detected spectroscopically. SCP does not depend on identifying the sparse number of morphologically abnormal cells within a large sample in order to make an accurate classification, as does conventional cytopathology. These findings suggest that the detection of cellular biochemical variations by SCP can serve as a new enhancing screening method that can identify earlier stages of disease. 2010-04-05 2010-07 /pmc/articles/PMC2894285/ /pubmed/20368702 http://dx.doi.org/10.1038/labinvest.2010.72 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Schubert, Jennifer M.
Bird, Benjamin
Papamarkakis, Kostas
Miljković, Miloš
Bedrossian, Kristi
Laver, Nora
Diem, Max
Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells
title Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells
title_full Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells
title_fullStr Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells
title_full_unstemmed Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells
title_short Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells
title_sort spectral cytopathology of cervical samples: detecting cellular abnormalities in cytologically normal cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2894285/
https://www.ncbi.nlm.nih.gov/pubmed/20368702
http://dx.doi.org/10.1038/labinvest.2010.72
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