Evidence map›Paper›PMID 39257922›Full record

ArticlePolish journal of radiology2024

Mohamed Ibrahim Amin, A El-Aziz I Amin, Shimaa Elsayed Badr, Noha Yahia Ebaid

Abstract read
In one paragraph

Article in Polish journal of radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Mohamed Ibrahim AminDepartment of Diagnostic Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
A El-Aziz I AminDepartment of Gynecology and Obstetrics, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Shimaa Elsayed BadrDepartment of Diagnostic Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Noha Yahia EbaidDepartment of Diagnostic Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To evaluate the extent to which magnetic resonance spectroscopy (MRS) lipid metabolites are accurate in predicting high-grade cervical cancer. Material and methods: This prospective single-centre pilot study included 20 cases with pathologically proven cervical cancer. They underwent pelvic magnetic resonance imaging (MRI) with MRS. Two radiologists, blinded to the histopathological results, with 10 years of experience in gynaecological imaging, independently analysed the MRI images and MRS curves, and a third one resolved any disagreement. Using the histopathological results as a standard test, the receiver operating characteristics (ROC) curve was utilised to calculate the optimal lipid peak (1.3 ppm) cutoff for predicting high-grade cervical cancer. The difference in MRS metabolites between low- and high-grade cervical cancer groups was estimated using the Mann-Whitney test. Results: The study included 11 high-grade and nine low-grade cervical cancer cases based on the histopathological evaluation. A lipid (1.3 ppm) peak of 29.9 was the optimal cutoff for predicting high-grade cervical cancer with 100% sensitivity, 77.8%, specificity, and 90% accuracy. Moreover, there was a significant difference between low- and high-grade cervical cancer cases concerning lipid peak at 0.9 ppm, lipid peak at 1.3 ppm, and the peak of choline with ( Conclusions: MRS might be considered a useful imaging technique for assessing the grade of cervical cancer and improving the planning of treatment. It shows a good diagnostic accuracy. Therefore, it can be adopted in clinical practice for better patient outcome.

Indexed as

cervical cancercholinediagnostic accuracylipid

Identifiers

PMID39257922
PMCPMC11384214

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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.