Using AI to predict treatment response in advanced gastric cancer
Research on Intelligent Screening and Decision-making for Neoadjuvant Therapy in Locally Advanced Gastric Cancer Based on Multi-omics Integration
This study is testing whether an AI system can help doctors predict how well patients with advanced stomach cancer will respond to treatment before surgery.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 120 (estimated) |
| Ages | 18 Years to 75 Years |
| Sex | All |
| Sponsor | Zhejiang University Academic / other |
| Drugs / interventions | trastuzumab, chemotherapy, immunotherapy |
| Locations | 4 sites (Hanzhou, Zhejiang and 3 other locations) |
| Trial ID | NCT06396143 on ClinicalTrials.gov |
What this trial studies
This observational study aims to validate an artificial intelligence system that integrates radiopathomics to predict how patients with locally advanced gastric cancer will respond to neoadjuvant chemoradiotherapy. Patients diagnosed with gastric adenocarcinoma at clinical stages II-IVa will be enrolled from multiple hospitals in Zhejiang, China. They will receive standardized neoadjuvant chemotherapy before undergoing radical surgery, with their pre-treatment imaging analyzed by the AI system to forecast postoperative tumor regression grades. The study seeks to enhance treatment decision-making through improved prediction of treatment outcomes.
Who should consider this trial
Good fit: Ideal candidates are patients diagnosed with gastric adenocarcinoma at clinical stages II-IVa without distant metastasis.
Not a fit: Patients with a history of other tumors or insufficient imaging quality will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more personalized treatment plans and improved outcomes for patients with locally advanced gastric cancer.
How similar studies have performed: While the use of AI in predicting treatment responses is gaining traction, this specific integration of radiopathomics in gastric cancer treatment is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Pathological diagnosis of gastric adenocarcinoma 2. Gastric cancer CT evaluation is clinical stage II-IVa (≥ T3, and/or lymph node positive), with or without local tissue or organ invasion, and no distant metastasis. 3. Acceptance criteria for 2-4 courses of 5-FU+platinum neoadjuvant chemotherapy regimen, or 2-4 courses of 5-FU+platinum neoadjuvant chemotherapy combined with trastuzumab regimen, or 2-4 courses of 5-FU+platinum neoadjuvant chemotherapy combined with anti-PD-L1 treatment regimen. 4. D2 gastric cancer radical surgery after neoadjuvant therapy 5. Digital images of enhanced CT images and HE stained gastroscopy biopsy sections before neoadjuvant therapy are available. 6. Complete clinical diagnosis and treatment information, as well as expression information of targeted and immunotherapy related molecular markers. Exclusion Criteria: 1. Has a history of other tumors. 2. Insufficient imaging quality of CT or biopsy slides, unable to obtain features. 3. Unable to extract molecular information related to research from organizational samples. 4. Interruption of neoadjuvant therapy course for any reason.
Where this trial is running
Hanzhou, Zhejiang and 3 other locations
- Gastrointestinal Department of First Affiliated Hospital of Zhejiang University — Hanzhou, Zhejiang, China (Recruiting)
- Gastrointestinal Department of Second Affiliated Hospital of Zhejiang University — Hanzhou, Zhejiang, China (Recruiting)
- Gastrointestinal Department of Zhejiang Cancer Hospital — Hanzhou, Zhejiang, China (Recruiting)
- Shaoxing Shangyu People's Hospital — Shaoxing, Zhejiang, China (Recruiting)
Study contacts
- Study coordinator: Jian Chen
- Email: zrchenjian@zju.edu.cn
- Phone: +86-13957102733
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.