Evidence map›Paper›PMID 41462129›Full record

ArticleBMC cancer2025

Continuous-time random walk diffusion MRI facilitates assessment of Ki-67 expression in endometrial cancer: a comparative study with diffusion kurtosis imaging.

Wangyi Liu, Jipeng Ren, Zhong Li, Wenling Liu, Shuaina Wang, Yiwen Ba, Baiyan Jiang, Dongming Han, Ruifang Yan

Abstract readComparative Study
In one paragraph

Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Wangyi LiuDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China.
Jipeng RenDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China.
Zhong LiDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China.
Wenling LiuDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China.
Shuaina WangDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China.
Yiwen BaDepartment of Orthopedics, the First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Baiyan JiangCT&S Philips Healthcare, Beijing, China.
Dongming HanDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China. 625492590@qq.com.
Ruifang YanDepartment of MR, the First Affiliated Hospital, Xinxiang Medical University, 88 Jiankang Road, Weihui, PR , 453100, China. yrf718@163.com.

Funding

The Key Research Projects of Higher Education Institutions in Henan Province 24B320017the Medical and Health Career Research and Development Fund Program - Röntgen Imaging Research Specialization HN-20201017-002
6 · The paper itself

Abstract

objectivesThis study aimed to evaluate the performance of continuous-time random walk (CTRW), diffusion kurtosis imaging (DKI), and diffusion-weighted imaging (DWI) in predicting the proliferative state of endometrial cancer (EC).

methodsA cohort of 81 EC patients was recruited. The parameters obtained from CTRW (α, β, and D

resultsK

conclusionThe combination of CTRW-derived parameter α, DKI-derived parameter K

Indexed as

Diffusion Magnetic Resonance ImagingEndometrial NeoplasmsKi-67 AntigenAdultAgedFemaleHumansMiddle AgedROC CurveKi-67 AntigenContinuous-time random walkDiffusion kurtosis imagingEndometrial cancerProliferation status

Identifiers

PMID41462129
PMCPMC12752295

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.