ArticleSurgical endoscopy2018
Model to identify early-stage gastric cancers with deep invasion of submucosa based on endoscopy and endoscopic ultrasonography findings.
Article in Surgical endoscopy, 2018. 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.
- Preoperative H. pylori Eradication Therapy Facilitates Precise Delineation in Early Gastric Cancer with Current H. pylori Infection.Digestive diseases (Basel, Switzerland) · 2024Trial
- A nomogram for predicting non-curative resection in patients with early gastric cancer based on white light imaging.Scientific reports · 2025Article
- Comprehensive analysis of risk factors associated with submucosal invasion in patients with early-stage gastric cancer.World journal of gastroenterology · 2024Article
- Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics.Scientific reports · 2024Article
- Dual-branch hybrid network for lesion segmentation in gastric cancer images.Scientific reports · 2023Article
- Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions.Computational and mathematical methods in medicine · 2022Article
- Enlarged folds on endoscopic gastritis as a predictor for submucosal invasion of gastric cancers.World journal of gastrointestinal endoscopy · 2021Article
- A Gratifying Step forward for the Application of Artificial Intelligence in the Field of Endoscopy: A Narrative Review.Surgical laparoscopy, endoscopy & percutaneous techniques · 2020Review
- Endoscopic Ultrasonography Miniature Probe Performance for Depth Diagnosis of Early Gastric Cancer with Suspected Submucosal Invasion.Gut and liver · 2020Article
- Predictive Factors and Long-Term Outcomes of Early Gastric Carcinomas in Patients with Non-Curative Resection by Endoscopic Submucosal Dissection.Cancer management and research · 2020Article
- Factors Affecting the Accuracy of Endoscopic Ultrasonography in the Diagnosis of Early Gastric Cancer Invasion Depth: A Meta-analysis.Gastroenterology research and practice · 2019Review
- Value of EUS in determining infiltration depth of early carcinoma and associated precancerous lesions in the upper gastrointestinal tract.Endoscopic ultrasoundArticle
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Authors and funding
14 authors.
Funding
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Abstract
backgroundConventional endoscopy and endoscopic ultrasonography (EUS) are used to estimate the invasion depth of early-stage gastric cancers (EGCs), but estimates made by either technique are often inaccurate. We developed a model to determine the invasion depth of EGCs using conventional endoscopy and EUS findings, with pathology results as the reference.
methodsWe performed a retrospective study of 195 patients (205 lesions) diagnosed with gastric cancers who underwent endoscopy and EUS followed by resection. Based on pathology analyses, lesions (n = 205) were assigned to categories of: mucosa invasion or minute invasion into the submucosal layer less than 500 μm from the muscularis mucosae (M-SM1) or penetration of 500 μm or more (≥SM2). The lesions were randomly assigned to derivation (138 lesions) and validation sets (67 lesions). A depth predictive model was proposed in the derivation set using multivariate logistic regression analyses. The discriminative power of this model was assessed in both sets.
resultsRemarkable redness (OR 5.42; 95% CI 1.32-22.29), abrupt cutting of converging folds (OR 8.58; 95% CI 1.65-44.72), lesions location in the upper third of the stomach (OR 10.26; 95% CI 2.19-48.09), and deep invasion based on EUS findings (OR 16.53; 95% CI 4.48-61.15) significantly associated with ≥SM2 invasion. A model that incorporated these 4 variables discriminated between M-SM1 and ≥SM2 lesions with the area under the ROC curve of 0.865 in the derivation set and 0.797 in the validation set. In the derivation set, a cut-off score of 8 identified lesions as ≥SM2 with 54% sensitivity and 97% specificity. The model correctly predicted the invasion depth 89.86% of lesions; it overestimated the depth of 2.17% of lesions.
conclusionsWe developed a model to identify EGCs with invasion depth ≥SM2 based on endoscopy and EUS findings. This model might reduce overestimation of gastric tumor depth and prevent unnecessary gastrectomy.
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