ArticleGastroenterology report2023
A new radiomics approach combining the tumor and peri-tumor regions to predict lymph node metastasis and prognosis in gastric cancer.
Article in Gastroenterology report, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review.Frontiers in medicine · 2023Pooled it
- Radiomics in Gastric Cancer: Advancing Precision Medicine.Journal of gastric cancer · 2026Review
- Predictability of peripheral blood inflammatory markers in prediction of lymph node metastasis in gastric cancer.Therapeutic advances in gastroenterology · 2026Article
- Oncologic outcomes of patients with negative nodal involvement on preoperative imaging undergoing surgery for gastric cancer.World journal of surgical oncology · 2025Article
- Development and Validation of a Computed Tomography-based Radiomics Nomogram for Diagnosing Cervical Lymph Node Metastasis in Oropharyngeal Squamous Cell Carcinomas.Advances in radiation oncology · 2025Article
- Machine learning models for diagnosing lymph node recurrence in postoperative PTC patients: a radiomic analysis.BMC cancer · 2025Article
- Habitat radiomics assists radiologists in accurately diagnosing lymph node metastasis of adenocarcinoma of the esophagogastric junction.Insights into imaging · 2025Article
- Dual-phase contrast-enhanced CT-based intratumoral and peritumoral radiomics for preoperative prediction of lymph node metastasis in gastric cancer.BMC gastroenterology · 2025Article
- Delta dual‑region DCE-MRI radiomics from breast masses predicts axillary lymph node response after neoadjuvant therapy for breast cancer.BMC cancer · 2025Article
- Intratumoral and peritumoral radiomics for forecasting microsatellite status in gastric cancer: a multicenter study.BMC cancer · 2025Article
- Preoperative prediction of lymph node metastasis in patients with ovarian cancer using contrast-enhanced computed tomography-based intratumoral and peritumoral radiomics features.Frontiers in oncology · 2025Article
- The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2023.Cancer communications (London, England) · 2024Article
- Preoperative prediction of lymph node metastasis in endometrial cancer patients via an intratumoral and peritumoral multiparameter MRI radiomics nomogram.Frontiers in oncology · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The development of non-invasive methods for evaluating lymph node metastasis (LNM) preoperatively in gastric cancer (GC) is necessary. In this study, we developed a new radiomics model combining features from the tumor and peri-tumor regions for predicting LNM and prognoses. Methods: This was a retrospective observational study. In this study, two cohorts of patients with GC treated in Zhongshan Hospital Fudan University (Shanghai, China) were included. In total, 193 patients were assigned to the internal training/validation cohort; another 98 patients were assigned to the independent testing cohort. The radiomics features were extracted from venous phase computerized tomography (CT) images. The radiomics model was constructed and the output was defined as the radiomics score (RS). The performance of the RS and CT-defined N status (ctN) for predicting LNM was compared using the area under the curve (AUC). The 5-year overall survival and progression-free survival were compared between different subgroups using Kaplan-Meier curves. Results: In both cohorts, the RS was significantly higher in the LNM-positive group than that in the LNM-negative group (all Conclusions: The radiomics model combining features from the tumor and peri-tumor regions could effectively predict the LNM in GC. Risk stratification based on the RS was capable of distinguishing patients with poor prognoses.
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