Evidence map›Paper›PMID 40084263›Full record

ArticleInternational journal of medical sciences2025

The Value of Texture Analysis of Multi-parameter MRI Images in Distinguishing Benign and Malignant Lesions of O-RADS MRI 4 Lesions.

Yan Lei, Hanzhou Tang, Lianlian Liu, Tingting Zheng, Yuan Zhang, Tong Chen, Junkang Shen, Bin Song

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. CT-based radiomics model to predict platinum sensitivity in epithelial ovarian carcinoma: a multicentre study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    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

8 authors.

Yan LeiDepartment of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, Shanghai, People's Republic of China.
Hanzhou TangDepartment of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, Shanghai, People's Republic of China.
Lianlian LiuDepartment of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, Shanghai, People's Republic of China.
Tingting ZhengDepartment of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, Shanghai, People's Republic of China.
Yuan ZhangDepartment of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, Shanghai, People's Republic of China.
Tong ChenDepartment of Radiology, The Second Affiliated Hospital of Soochow University, Soochow University, 1055 Sanxiang Road, Suzhou, 215004, Jiangsu, People's Republic of China.
Junkang ShenDepartment of Radiology, The Second Affiliated Hospital of Soochow University, Soochow University, 1055 Sanxiang Road, Suzhou, 215004, Jiangsu, People's Republic of China.
Bin SongDepartment of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Image Interpretation, Computer-AssistedMagnetic Resonance ImagingOvarian NeoplasmsAdultAgedAlgorithmsDiagnosis, DifferentialFemaleHumansMiddle AgedRetrospective StudiesROC CurveSensitivity and SpecificityYoung AdultBenign and malignant lesionsMagnetic resonance imagingOvarian-adnexal reporting and data system MRI (O-RADS MRI)Ovarian lesionTexture analysis

Identifiers

PMID40084263
PMCPMC11898845

What OpenQuestion holds

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LicenceCC BY
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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.