Artificial Intelligence Assisted Breast Ultrasound in Breast Cancer Screening

NCT ID: NCT06521788

Last Updated: 2024-07-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

21790 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-09-01

Study Completion Date

2023-12-31

Brief Summary

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AIBU is a randomized, open-label study assessing the effectiveness of an articificial intelligence-assisted breast ultrasound breast cancer screening strategy compared to standard screening (according to the current local guidelines in each participating area) in detecting late-stage breast cancers.

Detailed Description

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we enrolled asymptomatic women Women From January 2021 to December 2022, and then followed up for the next 1 year. The main study endpoint will be measured at the end of the one year after intervention.

Conditions

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Breast Cancer Screening

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

NONE

Study Groups

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AI assisted B-ultrasound breast cancer screening

Participants aged 35-70 years will be screened for breast cancer with AI assisted B-ultrasound

Group Type EXPERIMENTAL

AI-assisted breast ultrasound

Intervention Type DEVICE

AI-assisted breast ultrasound in community-based breast cancer screening

routine screening

Participants aged 35-70 years will be screened for breast cancer with routine B-ultrasound by experienced primary care physicians.

Group Type ACTIVE_COMPARATOR

Routine breast ultrasound

Intervention Type DEVICE

Routine breast ultrasound conducted by primary care physicians

Interventions

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AI-assisted breast ultrasound

AI-assisted breast ultrasound in community-based breast cancer screening

Intervention Type DEVICE

Routine breast ultrasound

Routine breast ultrasound conducted by primary care physicians

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Women aged 35-70 who participated in breast cancer screening (Shanghai Rural Women "Women two cancer screening project", national major public health service project "Rural women breast cancer screening Project" and "Gynecological diseases and breast diseases screening project for retired and living difficult women") in Shanghai district

Exclusion Criteria

* 1\. Personal history of breast carcinoma, either invasive or ductal carcinoma in situ (DCIS); 2. Personal history of any types of malignant neoplasms; 3. Known condition or suspicion of severe cardiopulmonary insufficiency, liver and kidney insufficiency and other systemic diseases; 4. Known condition or suspicion of serious comorbidities and average life expectancy less than 5 years; 5. History of lateral or bilateral mastectomy; 6. Disagree to participate in the study and follow-up interviews.
Minimum Eligible Age

35 Years

Maximum Eligible Age

70 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes

Sponsors

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Fudan University

OTHER

Sponsor Role lead

Responsible Party

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Ying Zheng

Director of Cancer Prevention Department, Fudan University Shanghai Cancer Center

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Ying Zheng

Role: STUDY_CHAIR

Fudan University

Locations

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Maternal and Infant Healthy Centre of Hongkou District, Shanghai

Shanghai, Shanghai Municipality, China

Site Status

Fudan University Shanghai Cancer Center

Shanghai, , China

Site Status

Shanghai Pudong New Area Healthcare Hospital For Women & Children

Shanghai, , China

Site Status

Countries

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China

References

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Shen J, Liu Y, Liu A, Gu X, Zhou J, Jiang P, Mo M, Zhang L, Yang C, Zhou C, Wang Z, Xie Z, Yao W, Zhou S, Zheng Y, Chang C. Artificial intelligence-assisted ultrasound screening for breast cancer in China: a prospective, clustered, controlled, population-based study. Breast Cancer Res. 2025 Oct 7;27(1):173. doi: 10.1186/s13058-025-02128-0.

Reference Type DERIVED
PMID: 41057952 (View on PubMed)

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

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20210712

Identifier Type: -

Identifier Source: org_study_id

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