Evidence map›Paper›PMID 40304002›Full record

ArticleFrontiers in oncology2025

The value of multi-sequence magnetic resonance imaging and whole-tumor apparent diffusion coefficient histogram analysis in differentiating p53 abnormal from non-p53 abnormal endometrial carcinoma.

Yuying Sun, Jieying Zhang, Yilin Wang, Xinxin Zhang, Yan Chen

Abstract read
In one paragraph

Article in Frontiers in oncology, 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

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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
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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.

Yuying SunRadiology Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jieying ZhangRadiology Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yilin WangRadiology Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xinxin ZhangRadiology Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yan ChenRadiology Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the utility of multi-sequence magnetic resonance imaging (MRI) and whole-tumor apparent diffusion coefficient (ADC) histogram metrics in preoperatively differentiating p53 abnormal (p53abn) from non-p53abn endometrial carcinoma (EC). Methods: This retrospective study included 146 EC patients (29 p53abn cases and 117 non-p53abn cases) who underwent preoperative MRI scans. MRI features were analyzed. Whole-tumor ADC histogram analysis was conducted by delineating regions of interest (ROIs) on diffusion-weighted imaging (DWI) scans. Receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC) was used for diagnostic performance evaluation. Results: Extrauterine extension (p=0.004) and lymphadenopathy (p=0.005) were more frequently observed in p53abn EC compared to non-p53abn EC. p53abn EC exhibited significantly lower value of minADC (p=0.001), meanADC (p=0.005), P10 (p=0.009), P50 (p=0.007), and P90 (p=0.013) ADC and higher value of kurtosis (p=0.008), compared to non-p53abn EC. MinADC demonstrated the highest discrimination ability in differentiating p53abn from non-p53abn EC [AUC 0.70(0.60;0.80)]. Conclusion: Preoperative multi-sequence MRI findings and whole-tumor ADC histogram metrics are conducive to differentiating p53abn from non-p53abn EC.

Indexed as

diffusion-weighted imagingendometrial cancerhistogram analysismagnetic resonance imagingp53

Identifiers

PMID40304002
PMCPMC12039310

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