ArticleFrontiers in oncology2021
A Bounding Box-Based Radiomics Model for Detecting Occult Peritoneal Metastasis in Advanced Gastric Cancer: A Multicenter Study.
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 12 papers, 4 of them syntheses that pooled it.
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Who cites it
12 citing papers in PubMed, 4 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Predictive performance of radiomics for peritoneal metastasis in patients with gastric cancer: a meta-analysis and radiomics quality assessment.Journal of cancer research and clinical oncology · 2023Pooled it
- Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review.Frontiers in medicine · 2023Pooled it
- The predictive value of radiomics-based machine learning for peritoneal metastasis in gastric cancer patients: a systematic review and meta-analysis.Frontiers in oncology · 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
- Non-invasive prediction of occult peritoneal metastasis (OPM) in gastric cancer using logistic regression and random forest integrative models with CT radiomics and clinical parameters: machine learning prediction of gastric OPM.Journal of gastrointestinal oncology · 2026Article
- Preoperative CT-based radiomics model for predicting muscle invasion in patients with upper tract urothelial carcinoma below T3 stage.Abdominal radiology (New York) · 2025Article
- Development and Validation of a Computed Tomography-Based Model for Noninvasive Prediction of the T Stage in Gastric Cancer: Multicenter Retrospective Study.Journal of medical Internet research · 2024Article
- Dual-energy CT quantitative parameters to evaluate occult peritoneal metastasis in advanced gastric cancer preoperatively.Abdominal radiology (New York) · 2024Article
- Exploring the value of multiple preprocessors and classifiers in constructing models for predicting microsatellite instability status in colorectal cancer.Scientific reports · 2024Article
- Artificial intelligence applications in computed tomography in gastric cancer: a narrative review.Translational cancer research · 2023Review
- Deep learning-enhanced radiomics for histologic classification and grade stratification of stage IA lung adenocarcinoma: a multicenter study.Frontiers in oncology · 2023Article
- Radiomics features based on internal and marginal areas of the tumor for the preoperative prediction of microsatellite instability status in colorectal cancer.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop a bounding box (BBOX)-based radiomics model for the preoperative diagnosis of occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients. MATERIALS AND
methods599 AGC patients from 3 centers were retrospectively enrolled and were divided into training, validation, and testing cohorts. The minimum circumscribed rectangle of the ROIs for the largest tumor area (R_BBOX), the nonoverlapping area between the tumor and R_BBOX (peritumoral area; PERI) and the smallest rectangle that could completely contain the tumor determined by a radiologist (M_BBOX) were used as inputs to extract radiomic features. Multivariate logistic regression was used to construct a radiomics model to estimate the preoperative probability of OPM in AGC patients.
resultsThe M_BBOX model was not significantly different from R_BBOX in the validation cohort [AUC: M_BBOX model 0.871 (95% CI, 0.814-0.940)
conclusionsThe BBOX-based radiomics could serve as a simpler reliable and powerful tool for the preoperative diagnosis of OPM in AGC patients. And M_BBOX-based radiomics is simpler and less time consuming.
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