Predicting gastric cancer response to chemotherapy using AI
Deep Learning-Based Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
This study is testing if a new AI tool can help doctors predict how well gastric cancer patients will respond to chemotherapy based on their medical images and information.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 200 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Chinese Academy of Sciences Government |
| Drugs / interventions | chemotherapy |
| Locations | 22 sites (Beijing and 21 other locations) |
| Trial ID | NCT06035250 on ClinicalTrials.gov |
What this trial studies
This study aims to create a deep-learning model that predicts how well gastric cancer patients will respond to neoadjuvant chemotherapy. By analyzing CT imaging data, biopsy pathology images, and clinical information from participants, the model will forecast treatment efficacy and prognosis. The research will utilize data from 1,800 retrospective cases and 200 prospective cases, with the retrospective data used to train the model and the prospective data to validate its performance. The ultimate goal is to assist in personalized treatment decisions for gastric cancer patients.
Who should consider this trial
Good fit: Ideal candidates are adults aged 18 and older with advanced gastric cancer who have not received prior anti-cancer treatments.
Not a fit: Patients with unclear CT or pathology images or those diagnosed with other concurrent tumors may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to more personalized and effective treatment plans for gastric cancer patients.
How similar studies have performed: Other studies utilizing AI for treatment outcome prediction in oncology have shown promising results, indicating potential success for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
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.
Where this trial is running
Beijing and 21 other locations
- Cancer Institute and Hospital, Chinese Academy of Medical Sciences — Beijing, China (Not_yet_recruiting)
- Peking Union Medical College Hospital — Beijing, China (Not_yet_recruiting)
- Peking University Cancer Hospital & Institute — Beijing, China (Recruiting)
- Peking University People's Hospital — Beijing, China (Not_yet_recruiting)
- Xiangya Hospital of Central South University — Changsha, China (Not_yet_recruiting)
- Fujian Cancer Hospital — Fuzhou, China (Not_yet_recruiting)
- Fujian Medical University Union Hospital — Fuzhou, China (Recruiting)
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University — Guangzhou, China (Not_yet_recruiting)
- First Affiliated Hospital, Sun Yat-Sen University — Guangzhou, China (Not_yet_recruiting)
- Nanfang Hospital of Southern Medical University — Guangzhou, China (Not_yet_recruiting)
- Sixth Affiliated Hospital, Sun Yat-sen University — Guangzhou, China (Recruiting)
- Yunnan Cancer Hospital — Kunming, China (Recruiting)
- Cancer Hospital of Guangxi Medical University — Nanning, China (Not_yet_recruiting)
- The Affiliated Hospital of Qingdao University — Qingdao, China (Not_yet_recruiting)
- Ruijin Hospital — Shanghai, China (Not_yet_recruiting)
- First Hospital of China Medical University — Shenyang, China (Not_yet_recruiting)
- The First Affiliated Hospital of Soochow University — Suzhou, China (Not_yet_recruiting)
- Tianjin Medical University Cancer Institute and Hospital — Tianjin, China (Not_yet_recruiting)
- Henan Cancer Hospital — Zhengzhou, China (Recruiting)
- The First Affiliated Hospital of Zhengzhou University — Zhengzhou, China (Recruiting)
- Zhenjiang First People's Hospital — Zhenjiang, China (Recruiting)
- San Raffaele University Hospital, Italy — Milan, Italy (Recruiting)
Study contacts
- Study coordinator: Di Dong, Ph.D.
- Email: di.dong@ia.ac.cn
- Phone: +86 13811833760
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.