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AI-Enhanced Imaging in Population Breast Cancer Screening

NCT07411443 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 16000

Last updated 2026-02-13

No results posted yet for this study

Summary

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.

Conditions

  • Breast Cancer Screening

Interventions

DEVICE

AI-assisted screening

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

Sponsors & Collaborators

  • Fudan University

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
SCREENING
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
35 Years
Max Age
69 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-01-01
Primary Completion
2027-12-31
Completion
2027-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07411443 on ClinicalTrials.gov