AI-Assisted Detection and Staging of Gastric Cancer Using Contrast-Enhanced CT
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: CT scan.
- Who it may be relevant to
- Registry conditions: Gastric Cancer Stage, Gastric Cancer Patients Undergoing Gastrectomy. Basic parameters: 18 years — 85 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Langue and Imaging-integrated Foundation Model for Gastric Cancer Detection and Staging Via Contrast-Enhanced CT: a Multicenter Study
Overview
Accurate preoperative assessment of gastric cancer stage guides eligibility for endoscopic resection, extent of gastrectomy and lymphadenectomy, selection for neoadjuvant therapy, and use of staging laparoscopy. Contrast-enhanced CT (CECT) is guideline-endorsed for initial staging, yet performance varies across institutions and readers. This study will evaluate an artificial-intelligence (AI) system that analyzes routine CECT to detect gastric cancer and assign four-class T stage (T1-T4) and N stage (N0-N3) .
Detailed description
Adults with confirmed gastric cancer undergoing pre-treatment CECT will be enrolled. The AI analysis will be applied to clinically acquired images. Radiologist interpretations with and without AI support will be collected in a prespecified reader study. The reference standard will include surgical pathology, supplemented by clinical follow-up when applicable. The primary outcome is detection performance, diagnostic performance of the AI for four-class staging (e.g., accuracy and area under the receiver operating characteristic curve). Secondary outcomes include the effect of AI assistance on reader accuracy and interpretation time, inter-reader agreement, and cross-site reproducibility.
Interventions
- Diagnostic test CT scan
preoperative contrast-enhanced CT
Primary outcome measures
- Diagnostic performance of the AI model for staging [Time frame: 3 years]
Secondary outcome measures (2)
- Reader Accuracy with AI Support [Time frame: 3 years]
- Survival time [Time frame: 3 years]
Eligibility criteria
Inclusion criteria
- pathologically confirmed gastric cancer;
- preoperative contrast-enhanced CT performed;
- no evidence of distant metastasis on baseline staging;
- curative-intent management with complete postoperative histopathology.
Exclusion criteria
- prior treatment before surgery;
- non-diagnostic or poor-quality CT precluding evaluation.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Case-only
Study locations
China · 1 center
- The First Affiliated Hospital of Nanjing Medical University — Nanjing
Identifiers
NCT: NCT07250347 · 2025-SR-842