Evidence map›Paper›PMID 27646154›Full record

ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2017

Transverse Relaxation Rate of Cyst Fluid Can Predict Malignant Transformation of Ovarian Endometriosis.

Chiharu Yoshimoto, Junko Takahama, Takuya Iwabuchi, Masato Uchikoshi, Hiroshi Shigetomi, Hiroshi Kobayashi

Open access · diamondAbstract read
In one paragraph

Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 27 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

6 authors at 2 institutions in 2 countries.

Chiharu YoshimotoDepartment of Obstetrics and Gynecology, Nara Medical University.
Junko Takahama
Takuya Iwabuchi
Masato Uchikoshi
Hiroshi Shigetomi
Hiroshi Kobayashi
Nara Medical University · JPSiemens (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHeme and iron accumulation due to repeated hemorrhage in endometriosis may contribute to a pivotal role in carcinogenesis. We evaluate the clinical application of MR relaxometry in a series of ovarian endometriosis (OE) and endometriosis-associated ovarian cancer (EAOC). MATERIALS AND

methodsA prospective study of diagnostic accuracy was conducted among 82 patients (67 OE and 15 EAOC) to compare MR relaxometry and biochemical measurement of cyst fluid total iron concentration. Transverse relaxation rate R2 value was determined using a single-voxel, multi-echo MR sequence (HISTO) by a 3T-MR system. Phantom experiments were also performed to assess the correlation between the ex vivo R2 values and total iron concentrations.

resultsBoth the results of phantom experiments and in vivo human data confirmed that in vivo R2 values were highly correlated with total iron concentrations. Compared to OE, EAOC exhibit decreased in vivo R2 values and total iron levels, regardless of their age, menopausal status and cyst size. The use of in vivo R2 values retained excellent accuracy in distinguishing EAOC versus OE (sensitivity and specificity: 86% and 94%).

conclusionsWe have demonstrated that MR relaxometry provides a noninvasive predictive tool to discriminate between EAOC and OE.

Indexed as

Magnetic Resonance ImagingAdultAgedCell Transformation, NeoplasticCohort StudiesCyst FluidEndometriosisFemaleHumansIronMiddle AgedOvarian NeoplasmsPredictive Value of TestsProspective StudiesReproducibility of ResultsSensitivity and SpecificityIron

Identifiers

PMID27646154
PMCPMC5600073
OpenAlexW2519434689

What OpenQuestion holds

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Registered trials

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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.