ArticleEuropean radiology2021
Assessment of morphological CT imaging features for the prediction of risk stratification, mutations, and prognosis of gastrointestinal stromal tumors.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 31 citations in OpenAlex.
- Risk stratification for 1- to 2-cm gastric gastrointestinal stromal tumors: visual assessment of CT and EUS high-risk features versus CT radiomics analysis.European radiology · 2023Trial
- Machine learning based on preoperative CT for noninvasive prediction of recurrence-free survival in gastrointestinal stromal tumors.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- An interpretable machine learning model integrating [European journal of nuclear medicine and molecular imaging · 2026Article
- Development and validation of CT-based nomograms for predicting recurrence and prognosis in gastrointestinal stromal tumor.Abdominal radiology (New York) · 2026Article
- Predictive imaging in abdominal oncology: current trends and future directions.Japanese journal of radiology · 2026Review
- CT assessed morphological features can predict higher mitotic index in gastric gastrointestinal stromal tumors.European radiology · 2025Article
- Association between calcification and risk stratification in gastric gastrointestinal stromal tumors.Abdominal radiology (New York) · 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
- Advancing gastrointestinal stromal tumor management: The role of imagomics features in precision risk assessment.World journal of gastrointestinal surgery · 2024Article
- CT and MRI of abdominal cancers: current trends and perspectives in the era of radiomics and artificial intelligence.Japanese journal of radiology · 2024Review
- KIT/PDGFRA Variant Allele Frequency as Prognostic Factor in Gastrointestinal Stromal Tumors (GISTs): Results From a Multi-Institutional Cohort Study.The oncologist · 2024Article
- Preoperative differentiation of gastric schwannomas and gastrointestinal stromal tumors based on computed tomography: a retrospective multicenter observational study.Frontiers in oncology · 2024Article
- A mutation-based radiomics signature predicts response to imatinib in Gastrointestinal Stromal Tumors (GIST).European journal of radiology open · 2023Article
- Case report: a rare case of gastroduodenal intussusception caused by GIST in an elderly patient and literature review.Journal of surgical case reports · 2023Article
- The Neoplastic Side of the Abdominal Wall: A Comprehensive Pictorial Essay of Benign and Malignant Neoplasms.Diagnostics (Basel, Switzerland) · 2023Review
- Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors.Frontiers in oncology · 2023Article
- Exploring the Dynamic Crosstalk between the Immune System and Genetics in Gastrointestinal Stromal Tumors.Cancers · 2022Review
- Do you get the GIST? Successful resection of a giant 3.5 kg gastrointestinal stromal tumour.ANZ journal of surgery · 2022Article
- Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Article
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Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate the correlation between CT imaging features and risk stratification of gastrointestinal stromal tumors (GISTs), prediction of mutation status, and prognosis.
methodsThis retrospective dual-institution study included patients with pathologically proven GISTs meeting the following criteria: (i) preoperative contrast-enhanced CT performed between 2008 and 2019; (ii) no treatments before imaging; (iii) available pathological analysis. Tumor risk stratification was determined according to the National Institutes of Health (NIH) 2008 criteria. Two readers evaluated the CT features, including enhancement patterns and tumor characteristics in a blinded fashion. The differences in distribution of CT features were assessed using univariate and multivariate analyses. Survival analyses were performed by using the Cox proportional hazard model, Kaplan-Meier method, and log-rank test.
resultsThe final population included 88 patients (59 men and 29 women, mean age 60.5 ± 11.1 years) with 45 high-risk and 43 low-to-intermediate-risk GISTs (median size 6.3 cm). At multivariate analysis, lesion size ≥ 5 cm (OR: 10.52, p = 0.009) and enlarged feeding vessels (OR: 12.08, p = 0.040) were independently associated with the high-risk GISTs. Hyperenhancement was significantly more frequent in PDGFRα-mutated/wild-type GISTs compared to GISTs with KIT mutations (59.3% vs 23.0%, p = 0.004). Ill-defined margins were associated with shorter progression-free survival (HR 9.66) at multivariate analysis, while ill-defined margins and hemorrhage remained independently associated with shorter overall survival (HR 44.41 and HR 30.22). Inter-reader agreement ranged from fair to almost perfect (k: 0.32-0.93).
conclusionsMorphologic contrast-enhanced CT features are significantly different depending on the risk status or mutations and may help to predict prognosis. KEY POINTS: • Lesions size ≥ 5 cm (OR: 10.52, p = 0.009) and enlarged feeding vessels (OR: 12.08, p = 0.040) are independent predictors of high-risk GISTs. • PDGFRα-mutated/wild-type GISTs demonstrate more frequently hyperenhancement compared to GISTs with KIT mutations (59.3% vs 23.0%, p = 0.004). • Ill-defined margins (hazard ratio 9.66) were associated with shorter progression-free survival at multivariate analysis, while ill-defined margins (hazard ratio 44.41) and intralesional hemorrhage (hazard ratio 30.22) were independently associated with shorter overall survival.
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