ArticleEuropean journal of radiology open2024
Preoperative prediction of perineural invasion and lymphovascular invasion with CT radiomics in gastric cancer.
Article in European journal of radiology open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
- A Composite Histopathologic Invasion Score Predicts Lymph Node Metastasis in Gastric Cancer.Journal of clinical medicine · 2026Article
- The added value of intratumoral and peritumoral radiomic scores based on iodine density map for preoperative prediction of lymphovascular invasion in patients with gastric adenocarcinoma: a two-center study.Abdominal radiology (New York) · 2026Article
- Therapeutic Value of Dissecting Distal Lymph Nodes in Proximal Gastric Cancer: A TVI-Based Risk Stratification.Journal of gastrointestinal cancer · 2026Article
- Construction and validation of a risk prediction model for perineural invasion in early gastric cancer based on multivariate analysis.BMC cancer · 2026Article
- Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.Scientific reports · 2025Article
- CT-based radiomics model for predicting perineural invasion status in gastric cancer.Abdominal radiology (New York) · 2025Article
- Dual-phase contrast-enhanced CT-based intratumoral and peritumoral radiomics for preoperative prediction of lymphovascular invasion in gastric cancer.BMC medical imaging · 2025Article
- Development of a multimodal predictive model using PET/CT radiomics and clinical data for preoperative assessment of lymphovascular invasion in gastric cancer.American journal of translational research · 2025Article
- Application and progress of nomograms in gastric cancer.Frontiers in medicine · 2025Review
- Establishment and validation of a prediction model for gastric cancer with perineural invasion based on preoperative inflammatory markers.Translational cancer research · 2024Article
- A radiomics model for predicting perineural invasion in stage II-III colon cancer based on computer tomography.BMC cancer · 2024Article
- Applications of artificial intelligence in digital pathology for gastric cancer.Frontiers in oncology · 2024Review
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To determine whether contrast-enhanced CT radiomics features can preoperatively predict lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancer (GC). Methods: A total of 148 patients were included in the LVI group, and 143 patients were included in the PNI group. Three predictive models were constructed, including clinical, radiomics, and combined models. A nomogram was developed with clinical risk factors to predict LVI and PNI status. The predictive performance of the three models was mainly evaluated using the mean area under the curve (AUC). The performance of three predictive models was assessed concerning calibration and clinical usefulness. Results: In the LVI group, the predictive power of the combined model (AUC=0.871, 0.822) outperformed the clinical model (AUC=0.792, 0.728) and the radiomics model (AUC=0.792, 0.728) in both the training and testing cohorts. In the PNI group, the combined model (AUC=0.834, 0.828) also had better predictive power than the clinical model (AUC=0.764, 0.632) and the radiomics model (AUC=0.764, 0.632) in both the training and testing cohorts. The combined models also showed good calibration and clinical usefulness for LVI and PNI prediction. Conclusion: CECT-based radiomics analysis might serve as a non-invasive method to predict LVI and PNI status in GC.
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