AI Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy

Chinese Academy of Sciences

Status: Enrolling

Conditions: Gastric Cancer; Image; Pathology

Treatments: Drug: Neoadjuvant Chemotherapy

Study type: Observational

Funder types: Other

Identifiers

NCT06035250

CASMI004

Details and patient eligibility

About

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.

Full description

This study seeks to develop a deep learning model to predict the outcomes of neoadjuvant chemotherapy in patients with gastric cancer. Leveraging participants' CT scans, biopsy pathology images, and clinical profiles, this model aims to forecast the effectiveness of post-neoadjuvant chemotherapy and the subsequent prognosis, thereby aiding in individualized treatment choices for these participants.

Data Collection: The investigators will gather data from 1,800 retrospective cases and 200 prospective cases from multiple hospitals. The retrospective data will be divided into training and testing sets to train and validate the model, respectively. The model's performance will subsequently be evaluated using the prospective dataset.

Clinical Information: This encompasses the participant's gender, age, tumor markers, staging, type, specific treatment plans, pre and post-treatment lab results, etc.

Imaging Data: CT imaging data taken within one month prior to the neoadjuvant chemotherapy, with at least the venous phase CT imaging included.

Pathology Data: Pathology images from a gastric tumor biopsy stained with Hematoxylin and Eosin (HE) taken within one month prior to treatment.

TRG Grading: Based on the pathology report of the surgical samples using the Ryan TRG grading system.

Prognostic Endpoints: The recorded endpoints are a 3-year progression-free survival (PFS) and a 5-year overall survival (OS). All deaths due to non-disease factors are excluded from the prognosis analysis.

Enrollment: 200 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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.

Trial design

200 participants in 1 patient group

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.

Treatment:

Drug: Neoadjuvant Chemotherapy