Evidence map›Paper›PMID 39349725›Full record

ArticleEuropean radiology2025

CT assessed morphological features can predict higher mitotic index in gastric gastrointestinal stromal tumors.

Xiaoxuan Jia, Youping Xiao, Hui Zhang, Jiazheng Li, Shiying Lv, Yinli Zhang, Fan Chai, Caizhen Feng, Yulu Liu, Haoquan Chen and 8 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

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 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

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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

3 citing papers in PubMed.

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4 · The record

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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

18 authors.

Xiaoxuan Jia *Department of Radiology, Peking University People's Hospital, Beijing, China.
Youping Xiao *Department of Radiology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, China.
Hui ZhangDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Jiazheng LiDepartment of Radiology, Peking University Cancer Hospital and Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing, China.
Shiying LvDepartment of Radiology, Shijiazhuang People's Hospital, Shijiazhuang, China.
Yinli ZhangDepartment of Pathology, Peking University People's Hospital, Beijing, China.
Fan ChaiDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Caizhen FengDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Yulu LiuDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Haoquan ChenDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Feiyu MaDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Shengcai WeiDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Jin ChengDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Sen ZhangDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Zhidong GaoDepartment of Gastrointestinal Surgery, Peking University People's Hospital, Beijing, China.
Nan HongDepartment of Radiology, Peking University People's Hospital, Beijing, China.
Lei TangDepartment of Radiology, Peking University Cancer Hospital and Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing, China. terrytang78@163.com.
Yi WangDepartment of Radiology, Peking University People's Hospital, Beijing, China. wang_yi@bjmu.edu.cn.ORCID http://orcid.org/0000-0002-7000-693X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the correlation of the mitotic index (MI) of 1-5 cm gastric gastrointestinal stromal tumors (gGISTs) with CT-identified morphological and first-order radiomics features, incorporating subgroup analysis based on tumor size.

methodsWe enrolled 344 patients across four institutions, each pathologically diagnosed with 1-5 cm gGISTs and undergoing preoperative contrast-enhanced CT scans. Univariate and multivariate analyses were performed to investigate the independent CT morphological high-risk features of MI. Lesions were categorized into four subgroups based on their pathological LD: 1-2 cm (n = 69), 2-3 cm (n = 96), 3-4 cm (n = 107), and 4-5 cm (n = 72). CT morphological high-risk features of MI were evaluated in each subgroup. In addition, first-order radiomics features were extracted on CT images of the venous phase, and the association between these features and MI was investigated.

resultsTumor size (p = 0.04, odds ratio, 1.41; 95% confidence interval: 1.01-1.96) and invasive margin (p < 0.01, odds ratio, 4.55; 95% confidence interval: 1.77-11.73) emerged as independent high-risk features for MI > 5 of 1-5 cm gGISTs from multivariate analysis. In the subgroup analysis, the invasive margin was correlated with MI > 5 in 3-4 cm and 4-5 cm gGISTs (p = 0.02, p = 0.03), and potentially correlated with MI > 5 in 2-3 cm gGISTs (p = 0.07). The energy was the sole first-order radiomics feature significantly correlated with gGISTs of MI > 5, displaying a strong correlation with CT-detected tumor size (Pearson's ρ = 0.85, p < 0.01).

conclusionsThe invasive margin stands out as the sole independent CT morphological high-risk feature for 1-5 cm gGISTs after tumor size-based subgroup analysis, overshadowing intratumoral morphological characteristics and first-order radiomics features. KEY POINTS: Question How can accurate preoperative risk stratification of gGISTs be achieved to support treatment decision-making? Findings Invasive margins may serve as a reliable marker for risk prediction in gGISTs up to 5 cm, rather than surface ulceration, irregular shape, necrosis, or heterogeneous enhancement. Clinical relevance For gGISTs measuring up to 5 cm, preoperative prediction of the metastatic risk could help select patients who could be treated by endoscopic resection, thereby avoiding overtreatment.

Indexed as

Gastrointestinal Stromal TumorsMitotic IndexStomach NeoplasmsTomography, X-Ray ComputedAdultAgedAged, 80 and overContrast MediaFemaleHumansMaleMiddle AgedRetrospective StudiesContrast MediaGastrointestinal stromal tumorsRisk assessmentX-ray computed (tomography)

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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.