ArticleLaboratory investigation; a journal of technical methods and pathology2010
Spectral cytopathology of cervical samples: detecting cellular abnormalities in cytologically normal cells.
Article in Laboratory investigation; a journal of technical methods and pathology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 64 citations in OpenAlex.
- Automated detection of dual p16/Ki67 nuclear immunoreactivity in liquid-based Pap tests for improved cervical cancer risk stratification.Annals of biomedical engineering · 2012Trial
- Biopolymer-based oral films integrated with probiotic active compounds for improved health applications.Archives of microbiology · 2024Article
- Infrared Spectroscopy in Gynecological Oncology: A Comprehensive Review of Diagnostic Potentials and Challenges.International journal of molecular sciences · 2024Review
- Simultaneous bioremediation of Disperse orange-2RL Azo dye and fatty acids production by Scenedesmus obliquus cultured under mixotrophic and heterotrophic conditions.Scientific reports · 2022Article
- Raman spectral cytopathology for cancer diagnostic applications.Nature protocols · 2021Article
- Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice.Materials (Basel, Switzerland) · 2019Review
- Raman spectroscopic detection of high-grade cervical cytology: Using morphologically normal appearing cells.Scientific reports · 2018Article
- Automated cytological detection of Barrett's neoplasia with infrared spectroscopy.Journal of gastroenterology · 2018Article
- Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP).Laboratory investigation; a journal of technical methods and pathology · 2015Article
- Raman difference spectroscopy: a non-invasive method for identification of oral squamous cell carcinoma.Biomedical optics express · 2014Article
- Infrared metrics for fixation-free liver tumor detection.The journal of physical chemistry. B · 2013Article
- Evaluating different fixation protocols for spectral cytopathology, part 2: cultured cells.Analytical chemistry · 2012Article
- Evaluating different fixation protocols for spectral cytopathology, part 1.Analytical chemistry · 2012Article
- Single point vs. mapping approach for spectral cytopathology (SCP).Journal of biophotonics · 2010Article
- Cytopathology by optical methods: spectral cytopathology of the oral mucosa.Laboratory investigation; a journal of technical methods and pathology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
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 shows SCP's potential as an enhancing tool for cytopathologists by aiding in the accurate and reproducible diagnosis of cells in all states of disease. 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. 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. SCP discriminated cytopathological diagnoses amongst 12 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 because of 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. 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 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.