Trial reportLa Radiologia medica2023
Prediction of the mitotic index and preoperative risk stratification of gastrointestinal stromal tumors with CT radiomic features.
Trial report in La Radiologia medica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Delta radiomics: an updated systematic review.La Radiologia medica · 2024Pooled it
- Case Report: Coexistence of a giant borderline phyllodes tumor of the breast and a contralateral fibroadenoma: a challenging case with clinical manifestations and PET-CT imaging mimicking advanced cancer.Frontiers in oncology · 2026Article
- A CT-based radiomics model for preoperative risk stratification of gastrointestinal stromal tumors.Frontiers in oncology · 2026Article
- Insights into radiomics: a comprehensive review for beginners.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- Review
- CT assessed morphological features can predict higher mitotic index in gastric gastrointestinal stromal tumors.European radiology · 2025Article
- Study on the predictive value of preoperative CT features for the mitotic index of GIST based on the nomogram.Scientific reports · 2025Article
- Subregional CT radiomics for preoperative prediction of mitotic index and risk stratification in 2-5 cm gastrointestinal stromal tumors of the stomach: a dual-center study.Frontiers in oncology · 2025Article
- Radiomics in radiology: What the radiologist needs to know about technical aspects and clinical impact.La Radiologia medica · 2024Review
- Identification and validation of protein biomarkers for predicting gastrointestinal stromal tumor recurrence.Computational and structural biotechnology journal · 2024Article
- Evaluating nomogram models for predicting survival outcomes in gastric gastrointestinal stromal tumors with SEER database analysis.Scientific reports · 2024Article
- Development and validation of a computed tomography-based radiomics signature to predict "highest-risk" from patients with high-risk gastrointestinal stromal tumor.Journal of gastrointestinal oncology · 2024Article
- Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics.Diagnostics (Basel, Switzerland) · 2023Review
- Risk stratification system of gastrointestinal stromal tumors under EUS elastography based on artificial intelligence.Endoscopic ultrasoundArticle
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
objectiveThe objective is to develop a mitotic prediction model and preoperative risk stratification nomogram for gastrointestinal stromal tumor (GIST) based on computed tomography (CT) radiomic features.
methodsA total of 267 GIST patients from 2009.07 to 2015.09 were retrospectively collected and randomly divided into (6:4) training cohort and validation cohort. The 2D-tumor region of interest was delineated from the portal-phase images on contrast-enhanced (CE)-CT, and radiomic features were extracted. Lasso regression method was used to select valuable features to establish a radiomic model for predicting mitotic index in GIST. Finally, the nomogram of preoperative risk stratification was constructed by combining the radiomic features and clinical risk factors.
resultsFour radiomic features closely related to the level of mitosis were obtained, and a mitotic radiomic model was constructed. The area under the curve (AUC) of the radiomics signature model used to predict mitotic levels in training and validation cohorts (training cohort AUC = 0.752; 95% confidence interval [95%CI] 0.674-0.829; validation cohort AUC = 0.764; 95% CI 0.667-0.862). Finally, the preoperative risk stratification nomogram combining radiomic features was equivalent to the clinically recognized gold standard AUC (0.965 vs. 0.983) (p = 0.117). The Cox regression analysis found that the nomogram score was one of the independent risk factors for the long-term prognosis of the patients.
conclusionPreoperative CT radiomic features can effectively predict the level of mitosis in GIST, and combined with preoperative tumor size, accurate preoperative risk stratification can be performed to guide clinical decision-making and individualized treatment.
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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.