Evidence map›Paper›PMID 40169495›Full record

ArticleKorean journal of radiology2025

Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI.

Xue-Han Wu, Yu-Tao Que, Xin-Yue Yang, Zi-Qiang Wen, Yu-Ru Ma, Zhi-Wen Zhang, Quan-Meng Liu, Wen-Jie Fan, Li Ding, Yue-Jiao Lang and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Korean journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

15 authors.

Xue-Han Wu *Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0009-0002-8662-1563
Yu-Tao Que *Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-0018-6154
Xin-Yue YangDepartment of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0002-3175-1363
Zi-Qiang WenDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0001-9648-3761
Yu-Ru MaDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0001-7357-6180
Zhi-Wen ZhangDepartment of Radiology, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, China.ORCID https://orcid.org/0000-0003-4610-8378
Quan-Meng LiuDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0009-0000-0927-8656
Wen-Jie FanDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0009-0009-0117-9165
Li DingDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-8094-4137
Yue-Jiao LangDepartment of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0009-0002-4007-834X
Yun-Zhu WuInstitute for AI in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China.ORCID https://orcid.org/0000-0002-4511-762X
Jian-Peng YuanDepartment of Radiology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.ORCID https://orcid.org/0000-0002-6363-0152
Shen-Ping YuDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-5988-781X
Yi-Yan LiuDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. liuyy398@mail.sysu.edu.cn.ORCID https://orcid.org/0000-0003-2234-3357
Yan ChenDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. cheny866@mail.sysu.edu.cn.ORCID https://orcid.org/0000-0003-4051-9045

Funding

Guangdong Medical Research Foundation A2024110National Natural Science Foundation of China 82302128
6 · The paper itself

Abstract

objectiveTo evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. MATERIALS AND

methodsA retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (

resultsAll morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all

conclusionThe combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Indexed as

Contrast MediaImage EnhancementLymphatic MetastasisLymph NodesMagnetic Resonance ImagingRectal NeoplasmsAdultAgedAged, 80 and overDiagnosis, DifferentialFeasibility StudiesFemaleHumansMaleMiddle AgedPilot ProjectsContrast MediaLymph nodeMagnetic resonance imagingPerfusion imagingRectal neoplasmsTumor deposits

Identifiers

PMID40169495
PMCPMC12055262

What OpenQuestion holds

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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.