ArticleCancer imaging : the official publication of the International Cancer Imaging Society2018
Tumor heterogeneity in gastrointestinal stromal tumors of the small bowel: volumetric CT texture analysis as a potential biomarker for risk stratification.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- CT texture analysis in histological classification of epithelial ovarian carcinoma.European radiology · 2021Trial
- Integrating CT radiomics and morphologic features for preoperative risk stratification of gastrointestinal stromal tumours.Scientific reports · 2026Article
- Differentiating small intestinal stromal tumors from primary small intestinal lymphomas using contrast-enhanced CT and texture analysis: a diagnostic study.Frontiers in oncology · 2025Article
- Oral contrast-enhanced ultrasonographic features and radiomics analysis to predict NIH risk stratification for gastrointestinal stromal tumors.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
- Preliminary study on diagnosis of gallbladder neoplastic polyps based on contrast-enhanced ultrasound and grey scale ultrasound radiomics.Frontiers in oncology · 2024Article
- Comparing endoscopic ultrasonography and double contrast-enhanced ultrasonography in the preoperative diagnosis of gastric stromal tumor.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- [Update: Small bowel diseases in computed tomography and magnetic resonance imaging].Radiologie (Heidelberg, Germany) · 2023Review
- Gastrointestinal stromal tumors: a comprehensive radiological review.Japanese journal of radiology · 2022Review
- Application of radiomics in predicting the preoperative risk stratification of gastric stromal tumors.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Article
- Building contrast-enhanced CT-based models for preoperatively predicting malignant potential and Ki67 expression of small intestine gastrointestinal stromal tumors (GISTs).Abdominal radiology (New York) · 2022Article
- Differential Diagnosis and Molecular Stratification of Gastrointestinal Stromal Tumors on CT Images Using a Radiomics Approach.Journal of digital imaging · 2022Article
- Correlation of CT radiomic features for GISTs with pathological classification and molecular subtypes: preliminary and monocentric experience.La Radiologia medica · 2022Article
- Ultrasound radiomics model-based nomogram for predicting the risk Stratification of gastrointestinal stromal tumors.Frontiers in oncology · 2022Article
- Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study.Frontiers in oncology · 2022Article
- CT classification model of pancreatic serous cystic neoplasms and mucinous cystic neoplasms based on a deep neural network.Abdominal radiology (New York) · 2022Article
- Primary Gastro-Intestinal Lymphoma and Gastro-Intestinal Adenocarcinoma: An Initial Study of CT Texture Analysis as Quantitative Biomarkers for Differentiation.Life (Basel, Switzerland) · 2021Article
- Development of a Malignancy Potential Binary Prediction Model Based on Deep Learning for the Mitotic Count of Local Primary Gastrointestinal Stromal Tumors.Korean journal of radiology · 2021Article
- Computed Tomography-Based Tumor Heterogeneity Analysis Reveals Differences in a Cohort with Advanced Pancreatic Carcinoma under Palliative Chemotherapy.Visceral medicine · 2021Article
- Computed-Tomography-Based Radiomics Model for Predicting the Malignant Potential of Gastrointestinal Stromal Tumors Preoperatively: A Multi-Classifier and Multicenter Study.Frontiers in oncology · 2021Article
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Abstract
backgroundTo explore whether volumetric CT texture analysis (CTTA) can serve as a potential imaging biomarker for risk stratification of small bowel gastrointestinal stromal tumors (small bowel-GISTs).
methodsA total of 90 patients with small bowel-GISTs were retrospectively reviewed, of these, 26 were rated as high risk, 13 as intermediate risk, and 51 as low or very low risk. Histogram parameters extracted from CT images were compared among small bowel-GISTs with different risk levels by using one-way analysis of variance. Receiver operating characteristics (ROCs) and areas under the curve (AUCs) were analyzed to determine optimal histogram parameters for stratifying tumor risk.
resultsSignificant differences in mean attenuation, 10th, 25th, 50th, 75th and 90th percentile attenuation, and entropy were found among high, intermediate, and low risk small bowel-GISTs (p ≤ 0.001). Mean attenuation, 10th, 25th, 50th, 75th and 90th percentile attenuation, and entropy derived from arterial phase and venous phase images correlated significantly with risk levels (r = 0.403-0.594, r = 0.386-0.593, respectively). Entropy in venous phase reached the highest accuracy (AUC = 0.830, p < 0.001) for differentiating low risk from intermediate to high risk small bowel-GISTs, with a cut-off value of 5.98, and the corresponding sensitivity and specificity were 82.4 and 74.4%, respectively.
conclusionsVolumetric CT texture features, especially entropy, may potentially serve as biomarkers for risk stratification of small bowel-GISTs.
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