Evidence map›Paper›PMID 38971944›Full record

ReviewInsights into imaging2024

How to update esophageal masses imaging using literature review (MRI and CT features).

Jinrong Qu, Zhaoqi Wang, Hongkai Zhang, Yanan Lu, Zhengyan Jia, Shuang Lu, Keke Zhao, Funing Chu, Bingmei Bai, Yan Zheng and 4 more

Abstract readReview
In one paragraph

Review in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

14 authors.

Jinrong QuDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China. qjryq@126.com.ORCID http://orcid.org/0000-0001-8751-9988
Zhaoqi WangDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Hongkai ZhangDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Yanan LuDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Zhengyan JiaDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Shuang LuDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Keke ZhaoDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Funing ChuDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Bingmei BaiDepartment of Radiology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Yan ZhengDepartment of Thoracic surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Qingxin XiaDepartment of Pathology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Xu LiDepartment of Pathology, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, 450008, China.
Shaoyu WangMR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China.
Ihab R KamelDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205-2196, USA.

Funding

Innovative Research Group Project of the National Natural Science Foundation of China No. 82271979the Henan Health Science and Technology Innovation Talent Project No. YXKC2020011the Projects of the General Programs of the National Natural Science Foundation of China No. 81972802
6 · The paper itself

Abstract

MRI offers new opportunities for detailed visualization of the different layers of the esophageal wall, as well as early detection and accurate characterization of esophageal lesions. Staging of esophageal tumors including extramural extent of disease, and status of the adjacent organ can also be performed by MRI with higher accuracy compared to other imaging modalities including CT and esophageal endoscopy. Although MDCT appears to be the primary imaging modality that is indicated for preoperative staging of esophageal cancer to assess tumor resectability, MDCT is considered less accurate in T staging. This review aims to update radiologists about emerging imaging techniques and the imaging features of various esophageal masses, emphasizing the imaging features that differentiate between esophageal masses, demonstrating the critical role of MRI in esophageal masses. CRITICAL RELEVANCE STATEMENT: MRI features may help differentiate mucosal high-grade neoplasia from early invasive squamous cell cancer of the esophagus, also esophageal GISTs from leiomyomas, and esophageal malignant melanoma has typical MR features. KEY POINTS: MRI can accurately visualize different layers of the esophagus potentially has a role in T staging. MR may accurately delineate esophageal fistulae, especially small mediastinal fistulae. MRI features of various esophageal masses are helpful in the differentiation.

Indexed as

Computed tomographyEsophageal neoplasmsMagnetic resonance imaging

Identifiers

PMID38971944
PMCPMC11227487

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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.