ArticleAbdominal radiology (New York)2020
Gastrointestinal stromal tumors (GIST): a proposal of a "CT-based predictive model of Miettinen index" in predicting the risk of malignancy.
Article in Abdominal radiology (New York), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 52 citations in OpenAlex.
- Machine learning for predicting the risk stratification of 1-5 cm gastric gastrointestinal stromal tumors based on CT.BMC medical imaging · 2023Trial
- Radiomics analysis of multiphase contrast-enhanced CT imaging for differentiating primary gastric lymphoma and Borrmann type IV gastric cancer.European journal of radiology open · 2026Article
- Preoperative Prediction of High Mitotic Count in Gastrointestinal Stromal Tumors Using CT Features and Serologic Indicators: An Interpretable Model with Multicenter External Validation.Journal of inflammation research · 2026Article
- Preoperatively Predicting Risk Stratification for GISTs ≤2 cm by Radiomics Model: A Dual-center StudyCurrent medical imaging · 2026Article
- 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
- Prediction of Ki-67 expression and malignant potential in gastrointestinal stromal tumors: novel models based on CE-CT and serological indicators.BMC cancer · 2024Article
- A New Online Dynamic Nomogram: Construction and Validation of a Predictive Model for Distant Metastasis Risk and Prognosis in Patients with Gastrointestinal Stromal Tumors.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023Review
- Relationship between multi-slice computed tomography features and pathological risk stratification assessment in gastric gastrointestinal stromal tumors.World journal of gastrointestinal oncology · 2023Article
- Imaging of Gastrointestinal Tract Ailments.Journal of imaging · 2023Review
- Clinical-radiomics-based treatment decision support for KIT Exon 11 deletion in gastrointestinal stromal tumors: a multi-institutional retrospective study.Frontiers in oncology · 2023Article
- Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Application of radiomics in predicting the preoperative risk stratification of gastric stromal tumors.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Article
- Gastrointestinal stromal tumors: a comprehensive radiological review.Japanese journal of radiology · 2022Review
- Multi-slice spiral computed tomography in differential diagnosis of gastric stromal tumors and benign gastric polyps, and gastric stromal tumor risk stratification assessment.World journal of gastrointestinal oncology · 2022Article
- Preoperative prediction of malignant potential of 2-5 cm gastric gastrointestinal stromal tumors by computerized tomography-based radiomics.World journal of gastrointestinal oncology · 2022Article
- Structured and shared CT radiological report of gastric cancer: a consensus proposal by the Italian Research Group for Gastric Cancer (GIRCG) and the Italian Society of Medical and Interventional Radiology (SIRM).European radiology · 2022Article
- Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study.Frontiers in oncology · 2022Article
- Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study.Frontiers in oncology · 2022Article
- Assessment of morphological CT imaging features for the prediction of risk stratification, mutations, and prognosis of gastrointestinal stromal tumors.European radiology · 2021Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo identify the predictors of malignancy on CT for the evaluation of gastrointestinal stromal tumors (GIST) by correlating CT findings with the mitotic index in order to propose a "CT-based predictive model of Miettinen index."
methodsOne radiologist and one resident in radiology with 14- and 4-year experience in oncological field reviewed the CT findings of 42 patients by consensus, with respect to lesion site, size, contour, tumor growth pattern, enhancing pattern, degree of enhancement of tumor, percentage of tumor necrosis, mesenteric fat infiltration, ulceration, calcification, regional lymphadenopathy, direct invasion to adjacent organs, and distant metastasis. All parameters were correlated with the mitotic index evaluated at histopathological analysis following surgery. Normality of variables was evaluated using Shapiro-Wilk test. Pearson's correlation test was used to assess the interaction between variables. The diagnostic accuracy percentage of tumor necrosis was measured by receiver operating characteristic (ROC) analysis for detecting whether the number of mitosis per 50 high-power fields was > 5.
resultsA significant statistical correlation was found between percentage of tumor necrosis and the mitotic index (p < 0.005), dimension, and location of the tumor.
conclusionCT could be an accurate technique in the prediction of malignancy of GIST in a CT risk assessment system, based on the location of the tumor, its size, and the percentage of tumor necrosis.
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