Evidence map›Paper›PMID 37843576›Full record

ArticleAbdominal radiology (New York)2024

Computed tomography radiomics identification of T1-2 and T3-4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?

Yang Li, Li Yang, Xiaolong Gu, Qi Wang, Gaofeng Shi, Andu Zhang, Meng Yue, Mingbo Wang, Jialiang Ren

Abstract read
In one paragraph

Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Prediction of lymphovascular invasion in esophageal squamous cell carcinoma by computed tomography-based radiomics analysis: 2D or 3D ?Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Yang LiDepartment of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Li YangDepartment of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Xiaolong GuDepartment of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China. 1016799543@qq.com.ORCID 0000-0001-8549-342X
Qi WangDepartment of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Gaofeng ShiDepartment of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Andu ZhangDepartment of Radiotherapy, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Meng YueDepartment of Pathology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Mingbo WangDepartment of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei Province, People's Republic of China.
Jialiang RenGE Healthcare China, Beijing, 100176, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo evaluate two-dimensional (2D) and three-dimensional (3D) computed tomography (CT) radiomics analysis for the T stage of esophageal squamous cell carcinoma (ESCC).

methods398 patients with pathologically confirmed ESCC were divided into training and testing sets. All patients underwent chest CT scans preoperatively. For each tumor, based on CT images, a 2D region of interest (ROI) was outlined on the largest cross-sectional area, and a 3D ROI was outlined layer by layer on each section of the tumor. The radiomics platform was used for feature extraction. For feature selection, stepwise logistic regression was used. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of the 2D radiomics model versus the 3D radiomics model. The differences were compared using the DeLong test. The value of the clinical utility of the two radiomics models was evaluated.

results1595 radiomics features were extracted. After screening, two radiomics models were constructed. In the training set, the difference between the area under the curve (AUC) of the 2D radiomics model (AUC = 0.831) and the 3D radiomics model (AUC = 0.830) was not statistically significant (p = 0.973). In the testing set, the difference between the AUC of the 2D radiomics model (AUC = 0.807) and the 3D radiomics model (AUC = 0.797) was also not statistically significant (p = 0.748). A 2D model was equally useful as a 3D model in clinical situations.

conclusionThe performance of 2D radiomics model is comparable to that of 3D radiomics model in distinguishing between the T1-2 and T3-4 stages of ESCC. In addition, 2D radiomics model may be a more feasible option due to the shorter time required for segmenting the ROI.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaHumansRadiomicsRetrospective StudiesTomography, X-Ray ComputedComputed tomographyEsophageal squamous cell carcinomaRadiomicsTumor stage

Identifiers

PMID37843576
PMCPMC10789855

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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.