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NCT Number: NCT07411443

AI-Enhanced Imaging in Population Breast Cancer Screening

Artificial Intelligence (AI)-assisted imaging technologies (including AI-assisted breast ultrasound and AI-assisted mammography) can effectively improve the accuracy and efficiency of breast imaging examinations, but their application in large-scale population-based breast cancer screening remains very limited.

This project aims to improve the effectiveness and feasibility of breast cancer screening by addressing the core issues and bottlenecks in population-based breast cancer screening. We will conduct a prospective cluster-controlled screening trial in the general population, with district-based cluster grouping. The intervention group will undergo combined screening using AI-assisted ultrasound plus AI-assisted mammography, while the control group will receive conventional screening: breast ultrasound for initial screening and mammography for secondary screening.

Based on population screening practices, we will evaluate the effectiveness of AI-assisted imaging diagnostic technology in various technical aspects of actual screening and perform cost-effectiveness analyses. This study will investigate the application of AI-assisted breast imaging technology in population-based breast cancer screening, providing scientific evidence for the large-scale implementation of AI-assisted imaging technologies. Furthermore, by combining population screening practices with model simulations, we will explore multi-dimensional breast cancer screening strategies to optimize screening approaches and technologies for the Chinese population.

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Key information

Conditions

Breast Cancer Screening

Age range

35 year–69 year

Sex eligibility

Female

Study type

Interventional

Phase

Not applicable

Primary location

Fudan University Shanghai Cancer Center

Shanghai, Shaghai, 021, China

Location status: Recruiting

Location contact

Ying Zheng

CONTACT

[email protected]

862164172290

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • women aged 35 to 69 years, who were attending the "Two Cancers (Breast and Cervical Cancer) Screening" project, and had no history of breast cancer, including in-situ cancer, or any other cancers in the previous five years.

Exclusion criteria

  • have serious cardiopulmonary insufficiency, liver or kidney insufficiency, or other systemic diseases, and a life expectancy of less than five years

Treatment and study plan

AI-assisted screening

Device

The intervention group will undergo combined screening using AI-assisted ultrasound plus AI-assisted mammography

Primary outcomes

  1. The incidence of early-stage breast cancer over a one-year follow-up period, compared between women who underwent AI-assisted screening and those with routine screening

    Time frame: From enrollment to 1-year after the end of screening

    Early-stage breast cancer was defined as cancer confined to the breast (local) or to the breast and regional lymph nodes (locoregional). Specifically, it referred to tumors <2 cm in diameter, with no ipsilateral axillary lymph node involvement and no distant metastasis. According to the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition) and the Chinese Guideline for Breast Cancer Screening and Early Diagnosis and Treatment (2021, Beijing), early-stage breast cancer encompassed stage 0 (including ductal carcinoma in situ and lobular carcinoma in situ), stage I, and stage II.

  2. The detection rate of suspicious breast lesions (including masses and calcifications) over a one-year follow-up period, compared between women who underwent AI-assisted ultrasound combined with AI-assisted mammography and those who received routine scree

    Time frame: From enrollment to 1-year after the end of screening

Study contacts

Contact information is provided by the study sponsor or research team.

Ying Zheng

CONTACT

[email protected]

862164175590

Sponsors and collaborators

Lead sponsor

Fudan University

Other

Registry information

Official study title

Population-based Breast Cancer Screening Study Using AI-Assisted Imaging Technology

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Feb 13, 2026
Registry last updated
Feb 13, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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