ArticleEuropean radiology2016
Predictive features of CT for risk stratifications in patients with primary gastrointestinal stromal tumour.
Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.
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Who cites it
62 citing papers in PubMed, 1 synthesis or guideline pooled it, 91 citations in OpenAlex.
- Prognostic value of tumor necrosis in gastrointestinal stromal tumor: A meta-analysis.Medicine · 2019Pooled it
- Prediction of the mitotic index and preoperative risk stratification of gastrointestinal stromal tumors with CT radiomic features.La Radiologia medica · 2023Trial
- Integrating CT radiomics and morphologic features for preoperative risk stratification of gastrointestinal stromal tumours.Scientific reports · 2026Article
- Development and validation of CT-based nomograms for predicting recurrence and prognosis in gastrointestinal stromal tumor.Abdominal radiology (New York) · 2026Article
- Imaging Strategies and Research Advances in Gastrointestinal Stromal Tumors.Current treatment options in oncology · 2026Review
- 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
- Novel risk predictor of spontaneous rupture and hemorrhage of renal cell carcinoma based on clinical and radiographic characteristics.World journal of urology · 2025Article
- CT features of gastric calcifying fibrous tumors: differentiation from gastrointestinal stromal tumors.Abdominal radiology (New York) · 2025Article
- Correlation of preoperative CT features with intra- and postoperative parameters of endoscopic resection in patients with gastric submucosal tumor (1~3 cm).Surgical endoscopy · 2025Article
- Deep learning model combined with computed tomography features to preoperatively predicting the risk stratification of gastrointestinal stromal tumors.World journal of gastrointestinal oncology · 2024Article
- Different radiomics models in predicting the malignant potential of small intestinal stromal tumors.European journal of radiology open · 2024Article
- Clinical outcomes of endoscopic resection for the treatment of intermediate- or high-risk gastric small gastrointestinal stromal tumors: a multicenter retrospective study.Surgical endoscopy · 2024Article
- Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor.World journal of gastrointestinal oncology · 2024Article
- Predicting the risk stratification of gastrointestinal stromal tumors using machine learning-based ultrasound radiomics.Journal of medical ultrasonics (2001) · 2024Article
- Preoperative differentiation of gastric schwannomas and gastrointestinal stromal tumors based on computed tomography: a retrospective multicenter observational study.Frontiers in oncology · 2024Article
- Article
- Multi-Slice CT Features Predict Pathological Risk Classification in Gastric Stromal Tumors Larger Than 2 cm: A Retrospective Study.Diagnostics (Basel, Switzerland) · 2023Article
- Radiomics signatures based on contrast-enhanced CT for preoperative prediction of the Ki-67 proliferation state in gastrointestinal stromal tumors.Japanese journal of radiology · 2023Article
- Relationship between multi-slice computed tomography features and pathological risk stratification assessment in gastric gastrointestinal stromal tumors.World journal of gastrointestinal oncology · 2023Article
2 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo determine the predictive CT imaging features for risk stratifications in patients with primary gastrointestinal stromal tumours (GISTs). MATERIALS AND
methodsOne hundred and twenty-nine patients with histologically confirmed primary GISTs (diameter >2 cm) were enrolled. CT imaging features were reviewed. Tumour risk stratifications were determined according to the 2008 NIH criteria where GISTs were classified into four categories according to the tumour size, location, mitosis count, and tumour rupture. The association between risk stratifications and CT features was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis.
resultsCT imaging features including tumour margin, size, shape, tumour growth pattern, direct organ invasion, necrosis, enlarged vessels feeding or draining the mass (EVFDM), lymphadenopathy, and contrast enhancement pattern were associated with the risk stratifications, as determined by univariate analysis (P < 0.05). Only lesion size, growth pattern and EVFDM remained independent risk factors in multinomial logistic regression analysis (OR = 3.480-100.384). ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.806 (95 % CI: 0.727-0.885).
conclusionCT features including lesion size, tumour growth pattern, and EVFDM were predictors of the risk stratifications for GIST. KEY POINTS: • CT features were of predictive value for risk stratification of GISTs. • Tumour size, growth patterns, and EVFDM were risk predictors of GISTs. • Large size, mixed growth pattern, or EVFDM indicated high risk GIST.
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