AI-Assisted Non-Contrast CT for Multi-Cancer Screening

Conditions studied

Lung Cancers, Liver Cancer, Gastric Cancers, Colorectal, Cancer, Esophageal Cancer, Pancreatic Cancer, Breast Cancer

About this study

Cancer poses a major public health challenge in China. Early detection can improve treatment outcomes and survival rates. In this study, we will conduct a large-scale, prospective, multi-center cohort study to evaluate the utility of AI-assisted non-contrast CT for multi-cancer screening. The study aims to enroll 1 million asymptomatic participants undergoing routine health examinations, using an AI imaging model based on non-contrast CT to detect seven cancers such as lung, liver, gastric, colorectal, esophageal, pancreatic, and breast cancers. Positive cases will be required to be referred to Shanghai Changhai Hospital for further imaging and care based on National Comprehensive Cancer Network (NCCN) and American College of Radiology (ACR) guidelines. The goal is to assess the AI model's diagnostic performance for seven cancer types, especially for early-stage, resectable tumors.

Interventions

• Diagnostic Test: AI-Assisted Non-Contrast CT for Multi-Cancer Screening — Participants identified by the AI model as having potential cancerous lesions, including those suspected of lung, liver, gastric, colorectal, esophageal, pancreatic, and breast cancer, will be required to undergo blood tests (for tumor markers) and additional imaging studies (such as contrast-enhanced CT, MRI, Endoscopy, etc.) to confirm the diagnosis of cancerous lesions.

Primary outcomes

• Diagnostic yield (3 years)
• Incidence (3 years)
• Resectable rate (3 years)

Eligibility information

Study locations

• Changhai Hospital, Shanghai, Shanghai Municipality 200433 China