Clinical trial · Observational
AI Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
Deep Learning-Based Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study seeks to develop a deep-learning-based intelligent predictive model for the efficacy of neoadjuvant chemotherapy in gastric cancer patients. By utilizing the patients' CT imaging data, biopsy pathology images, and clinical information, the intelligent model will predict the post-neoadjuvant chemotherapy efficacy and prognosis, offering assistance in personalized treatment decisions for gastric cancer patients.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Gastric Cancer | Malignant Gastric Neoplasm | CURATED_BROADER | 0.80 |
| Image | — | UNRESOLVED | — |
| Pathology | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Neoadjuvant Chemotherapy | Drug | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Gastric Cancer Patients Undergoing Neoadjuvant Chemotherapy
- description
- This group comprises participants diagnosed with advanced gastric cancer. The participants will be treated with standard neoadjuvant chemotherapy regimens recommended by clinical guidelines. Treatment details, including the generic name of the drugs, dosage form, dosage, frequency, and duration, will be recorded according to the specific regimen.
- interventionNames
- Drug: Neoadjuvant Chemotherapy
Primary outcomes (2)
- measure
- Area under the receiver operating characteristic curve (AUC) for TRG prediction by the AI model
- timeFrame
- two months
- description
- The AUC will be used to evaluate the performance of the AI model in predicting TRG grading of gastric cancer patients after neoadjuvant chemotherapy. An AUC of 1 indicates perfect prediction, while an AUC of 0.5 indicates prediction no better than chance.
- measure
- Accuracy of TRG prediction by the AI model
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Age 18 years or older; * Pathologically diagnosed with advanced gastric cancer in accordance with the American AJCC's TNM staging standards; * Have not undergone any systematic anti-cancer treatments before neoadjuvant chemotherapy and have not had surgery for local progression or distant metastasis; * Received standard neoadjuvant chemotherapy as recommended by the clinical guidelines, and have documented treatment details; * CT imaging and biopsy pathology images strictly taken within one month prior to starting neoadjuvant treatment; * Patients possess comprehensive preoperative clinical information and post-operative TRG grading. Exclusion Criteria: * Patients whose CT or pathology images are unclear, making lesion assessment infeasible; * Patients diagnosed with other concurrent tumors.
References
Publications (0)
Data not yet available