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

Summary

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.

Eligibility

Inclusion Criteria:

1. Subject is able and willing to provide informed consent and sign an informed consent form.
2. Subject has undergone an abdominal or chest non-contrast CT scan.

Exclusion Criteria:

1. Subject has been diagnosed with one of the following cancers within the last five years: lung, liver, stomach, colon, esophageal, pancreatic, or breast cancer;
2. Subject has any medical condition that contraindicates high-resolution MRI/CT/Endoscopy;
3. Subject cannot be followed up or is participating in other clinical trials.

Conditions10

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