Evidence map›Paper›PMID 20441233›Full record

ArticleTechnology in cancer research & treatment2010

Automated analysis of fluorescent in situ hybridization (FISH) labeled genetic biomarkers in assisting cervical cancer diagnosis.

Xingwei Wang, Bin Zheng, Roy R Zhang, Shibo Li, Xiaodong Chen, John J Mulvihill, Xianglan Lu, Hui Pang, Hong Liu

Abstract read
In one paragraph

Article in Technology in cancer research & treatment, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Quantitative analysis of centromeric FISH spots during the cell cycle by image cytometry.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2013
    Article
  6. 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

9 authors at 4 institutions in 1 country.

Xingwei WangDepartment of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, 15213, USA.
Bin Zheng
Roy R Zhang
Shibo Li
Xiaodong Chen
John J Mulvihill
Xianglan Lu
Hui Pang
Hong Liu
University of Oklahoma Health Sciences Center · USUniversity of Oklahoma · USUniversity of Pittsburgh · USUniversity of Pittsburgh Medical Center · US

Funding

Automated FISH Imaging and Analysis for Screening Cervical CancerR01CA136700 · NCI · UNIVERSITY OF OKLAHOMA · PI LIU, HONG · 2009 to 2010
$825k
NCI NIH HHS CA136700NCI NIH HHS R01 CA136700
6 · The paper itself

Abstract

The numerical and/or structural deviation of some chromosomes (i.e., monosomy and _polysomy of chromosomes 3 and X) are routinely used as positive genetic biomarkers to diagnose cervical cancer and predict the disease progression. Among the available diagnostic methods to analyze the aneusomy of chromosomes 3 and X, fluorescence in situ hybridization (FISH) technology has demonstrated significant advantages in assisting clinicians to more accurately detect and diagnose cervical carcinoma at an early stage, in particular for the women at a high risk for progression of low-grade and high-grade squamous intra-epithelium lesions (LSIL and HSIL). In order to increase the diagnostic accuracy, consistency, and efficiency from that of manual FISH analysis, this study aims to develop and test an automated FISH analysis method that includes a two-stage scheme. In the first stage, an interactive multiple-threshold algorithm is utilized to segment potential interphase nuclei candidates distributed in different intensity levels and a rule-based classifier is implemented to identify analyzable interphase cells. In the second stage, FISH labeled biomarker spots of chromosomes 3 and X are segmented by a top-hat transform. The independent FISH spots are then detected by a knowledge-based classifier, which enables recognition of the splitting and stringy FISH signals. Finally, the ratio of abnormal interphase cells with numerical changes of chromosomes 3 and X is calculated to detect positive cases. The experimental results of four test cases showed high agreement of FISH analysis results between the automated scheme and the cytogeneticist's analysis including 92.7% to 98.7% agreement in cell segmentation and 4.4% to 11.0% difference in cell classification. This preliminary study demonstrates the feasibility of potentially applying the automatic FISH analysis method to expedite the screening and detecting cervical cancer at an early stage.

Indexed as

AutomationBiomarkers, TumorFemaleHumansIn Situ Hybridization, FluorescenceUterine Cervical DysplasiaUterine Cervical NeoplasmsVaginal SmearsBiomarkers, Tumor

Identifiers

PMID20441233
PMCPMC2916642
OpenAlexW2070057204

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.