Evidence map›Paper›PMID 21054125›Full record

ArticleJournal of biomedical optics

Clinical research device for ovarian cancer detection by optical spectroscopy in the ultraviolet C-visible.

Ronie George, Archana Chandrasekaran, Molly A Brewer, Kenneth D Hatch, Urs Utzinger

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Journal of biomedical optics. 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
1.9field-weighted citation impact, top 13% 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, 12 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Ronie GeorgeUniversity of Arizona, College of Optical Sciences, 1630 East University Boulevard, Tucson, Arizona 85724, USA.
Archana Chandrasekaran
Molly A Brewer
Kenneth D Hatch
Urs Utzinger
University of Arizona · USUniversity of Connecticut · US

Funding

Optical Spectroscopy of Ovarian CancerR01CA098341 · NCI · UNIVERSITY OF ARIZONA · PI UTZINGER, URS · 2003 to 2005
$915k
NCI NIH HHS CA098341NCI NIH HHS R01 CA098341
6 · The paper itself

Abstract

Early detection of ovarian cancer could greatly increase the likelihood of successful treatment. However, present detection techniques are not very effective, and symptoms are more commonly seen in later stage disease. Amino acids, structural proteins, and enzymatic cofactors have endogenous optical properties influenced by precancerous changes and tumor growth. We present the technical details of an optical spectroscopy system used to quantify these properties. A fiber optic probe excites the surface epithelium (origin of 90% of cases) over 270 to 580 nm and collects fluorescence and reflectance at 300 to 800 nm with four or greater orders of magnitude instrument to background suppression. Up to four sites per ovary are investigated on patients giving consent to oophorectomy and the system's in vivo optical evaluation. Data acquisition is completed within 20 s per site. We illustrate design, selection, and development of the components used in the system. Concerns relating to clinical use, performance, calibration, and quality control are addressed. In the future, spectroscopic data will be compared with histological biopsies from the corresponding tissue sites. If proven effective, this technique can be useful in screening women at high risk of developing ovarian cancer to determine whether oophorectomy is necessary.

Indexed as

Equipment DesignFemaleHumansLaparoscopyOptical FibersOptical PhenomenaOvarian NeoplasmsOvariectomySpectrophotometry, Ultraviolet

Identifiers

PMID21054125
PMCPMC2988829
OpenAlexW1976545792

What OpenQuestion holds

Textmetadata
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.