Evidence map›Paper›PMID 36052224›Full record

ArticleFrontiers in oncology2022

Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study.

Yun Wang, Yurui Wang, Jialiang Ren, Linyi Jia, Luyao Ma, Xiaoping Yin, Fei Yang, Bu-Lang Gao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. 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
2.3field-weighted citation impact, top 12% of its field
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, 14 citations in OpenAlex.

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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

8 authors at 5 institutions in 1 country.

Yun WangAffiliated Hospital of Hebei University/Hebei University (Clinical Medical College), Baoding, China.
Yurui WangTangshan Gongren Hospital, Tangshan, China.
Jialiang RenGeneral Electric Pharmaceutical Co., Ltd, Shanghai, China.
Linyi JiaXingtai People's Hospital, Xingtai, China.
Luyao MaAffiliated Hospital of Hebei University/Hebei University (Clinical Medical College), Baoding, China.
Xiaoping YinAffiliated Hospital of Hebei University/Hebei University (Clinical Medical College), Baoding, China.
Fei YangMedical Imaging Department, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China.
Bu-Lang GaoAffiliated Hospital of Hebei University/Hebei University (Clinical Medical College), Baoding, China.
Affiliated Hospital of Hebei University · CNTangshan Gongren Hospital · CNHebei Medical University · CNHebei North University · CNShanghai Electric (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study was to investigate the diagnostic efficacy of radiomics models based on the enhanced CT images in differentiating the malignant risk of gastrointestinal stromal tumors (GIST) in comparison with the clinical indicators model and traditional CT diagnostic criteria. Materials and methods: A total of 342 patients with GISTs confirmed histopathologically were enrolled from five medical centers. Data of patients wrom two centers comprised the training group (n=196), and data from the remaining three centers constituted the validation group (n=146). After CT image segmentation and feature extraction and selection, the arterial phase model and venous phase model were established. The maximum diameter of the tumor and internal necrosis were used to establish a clinical indicators model. The traditional CT diagnostic criteria were established for the classification of malignant potential of tumor. The performance of the four models was assessed using the receiver operating characteristics curve. Reuslts: In the training group, the area under the curves(AUCs) of the arterial phase model, venous phase model, clinical indicators model, and traditional CT diagnostic criteria were 0.930 [95% confidence interval (CI): 0.895-0.965), 0.933 (95%CI 0.898-0.967), 0.917 (95%CI 0.872-0.961) and 0.782 (95%CI 0.717-0.848), respectively. In the validation group, the AUCs of the models were 0.960 (95%CI 0.930-0.990), 0.961 (95% CI 0.930-0.992), 0.922 (95%CI 0.884-0.960) and 0.768 (95%CI 0.692-0.844), respectively. No significant difference was detected in the AUC between the arterial phase model, venous phase model, and clinical indicators model by the DeLong test, whereas a significant difference was observed between the traditional CT diagnostic criteria and the other three models. Conclusion: The radiomics model using the morphological features of GISTs play a significant role in tumor risk stratification and can provide a reference for clinical diagnosis and treatment plan.

Indexed as

enhance different periodsgastrointestinal stromal tumorsmultiple centersradiomicstraditional CT diagnosis

Identifiers

PMID36052224
PMCPMC9425090
OpenAlexW4291926489

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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.