Evidence map›Paper›PMID 20368702›Full record

ArticleLaboratory investigation; a journal of technical methods and pathology2010

Spectral cytopathology of cervical samples: detecting cellular abnormalities in cytologically normal cells.

Jennifer M Schubert, Benjamin Bird, Kostas Papamarkakis, Milos Miljković, Kristi Bedrossian, Nora Laver, Max Diem

Open access · greenAbstract readEvaluation Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
8.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 64 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP).Laboratory investigation; a journal of technical methods and pathology · 2015
    Article
  10. Article
  11. Infrared metrics for fixation-free liver tumor detection.The journal of physical chemistry. B · 2013
    Article
  12. Article
  13. Article
  14. Article
  15. Cytopathology by optical methods: spectral cytopathology of the oral mucosa.Laboratory investigation; a journal of technical methods and pathology · 2010
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Jennifer M SchubertLaboratory for Spectral Diagnosis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA. jmschubert@gmail.com
Benjamin Bird
Kostas Papamarkakis
Milos Miljković
Kristi Bedrossian
Nora Laver
Max Diem
Northeastern University · USTufts Medical Center · US

Funding

Micro-Spectroscopy for Cytological Screening, and Staging of DiseaseR01CA090346 · NCI · NORTHEASTERN UNIVERSITY · PI DIEM, MAX · 2003 to 2010
$3.2M
Oral Cancer Screening via Spectral CytopathologyR21CA153148 · NCI · NORTHEASTERN UNIVERSITY · PI DIEM, MAX · 2010 to 2011
$367k
NCI NIH HHS CA090346NCI NIH HHS R01 CA090346NCI NIH HHS R21 CA153148
6 · The paper itself

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

Cervix UteriFemaleHumansPathologySpectrophotometry, InfraredUterine Cervical DysplasiaUterine Cervical Neoplasms

Identifiers

PMID20368702
PMCPMC2894285
OpenAlexW1999866141

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.