Evidence map›Paper›PMID 38992110›Full record

ArticleEuropean radiology2025

Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics.

Yongfei Hao, Jianyong Zheng, Wanqing Li, Wanting Zhao, Jianmin Zheng, Hong Wang, Jialiang Ren, Guangwen Zhang, Jinsong Zhang

Abstract read
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Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
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.

Yongfei Hao *Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Jianyong Zheng *Department of Gastrointestinal Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Wanqing LiDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Wanting ZhaoDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Jianmin ZhengDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Hong WangDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Jialiang RenDepartment of Pharmaceuticals Diagnostics, GE HealthCare, Beijing, China.
Guangwen ZhangDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China. divedeep@126.com.
Jinsong ZhangDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China. stspine@163.com.ORCID http://orcid.org/0000-0002-7099-4034

Funding

National Natural Science Foundation of China 82371918
6 · The paper itself

Abstract

objectivesThis study aims to evaluate image quality and regional lymph node metastasis (LNM) in patients with rectal cancer (RC) on multi-b-value diffusion-weighted imaging (DWI).

methodsThis retrospective study included 199 patients with RC who had undergone multi-b-value DWI. Subjective (five-point Likert scale) and objective assessments of quality images were performed on DWI

resultsThe mean signal intensity of the tumor (SI

conclusionDWI CLINICAL RELEVANCE STATEMENT: DWI KEY POINTS: Lymph node staging is required to determine the best treatment plan for rectal cancer. DWI

Indexed as

Diffusion Magnetic Resonance ImagingLymphatic MetastasisRectal NeoplasmsAdultAgedAged, 80 and overFemaleHumansLymph NodesMaleMiddle AgedRadiomicsRetrospective StudiesSignal-To-Noise RatioDiffusion magnetic resonance imagingLymphatic metastasisMachine learningRectal neoplasms

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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.