ArticleFrontiers in oncology2021
Development and Validation of a Radiomics Model Based on
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review.Frontiers in medicine · 2023Pooled it
- Machine learning for lymph node metastasis prediction of in patients with gastric cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Preoperative clinical-imaging nomogram for peritoneal metastasis in gastric cancer: a retrospective cohort study.BMC gastroenterology · 2026Article
- Molecular imaging in gastric cancer: state-of-the-art techniques and emerging opportunities.Journal of translational medicine · 2026Review
- Research on Cancer Prediction Based on Feature Optimization and Multimodal Fusion.Health care science · 2025Article
- Diagnostic value of the cardiophrenic lymph nodes in gastric peritoneum metastases.African health sciences · 2025Article
- ASO Author Reflections: Preoperative Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer: AAnnals of surgical oncology · 2024Article
- Development and validation of a machine learning-basedCancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Deep learning radiomics model based on PET/CT predicts PD-L1 expression in non-small cell lung cancer.European journal of radiology open · 2024Article
- Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques.Korean journal of radiology · 2024Review
- Nuclear medicine radiomics in digestive system tumors: Concept, applications, challenges, and future perspectives.View (Beijing, China) · 2023Article
- Systematic review of diagnostic tools for peritoneal metastasis in gastric cancer-staging laparoscopy and its alternatives.World journal of gastrointestinal surgery · 2023Article
- Prognostic Value of [Cancers · 2023Article
- Construction of a nomogram model for predicting peritoneal metastasis in gastric cancer: focused on cardiophrenic angle lymph node features.Abdominal radiology (New York) · 2023Article
- Prognostic significance of serum CA125 in the overall management for patients with gastrointestinal stromal tumors.BMC gastroenterology · 2023Article
- Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers.Cancers · 2022Review
- Article
- Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine.Cancers · 2022Review
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim of this study was to develop a preoperative positron emission tomography (PET)-based radiomics model for predicting peritoneal metastasis (PM) of gastric cancer (GC).
methodsIn this study, a total of 355 patients (109PM+, 246PM-) who underwent preoperative fluorine-18-fludeoxyglucose (
resultsAfter dimensionality reduction, 12 radiomics feature parameters were obtained to construct radiomics signatures. According to the results of the multivariate logistic regression analysis, only carbohydrate antigen 125 (CA125), maximum standardized uptake value (SUVmax), and the radiomics signature showed statistically significant differences between patients (P<0.05). A radiomics model was developed based on the logistic analyses with an AUC of 0.86 in the training cohort and 0.87 in the validation cohort. The clinical prediction model based on CA125 and SUVmax was 0.76 in the training set and 0.69 in the validation set. The comprehensive model, which contained a rad-score and the clinical factor (CA125) as well as the metabolic parameter (SUVmax), showed promising performance with an AUC of 0.90 in the training cohort and 0.88 in the validation cohort, respectively. The calibration curve showed the actual rate of the nomogram-predicted probability of peritoneal metastasis. Decision curve analysis (DCA) also demonstrated the good clinical utility of the radiomics nomogram.
conclusionsThe comprehensive model based on the rad-score and other factors (SUVmax, CA125) can provide a novel tool for predicting peritoneal metastasis of gastric cancer patients preoperatively.
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