Artificial Intelligence in Breast Cancer Screening Programs

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

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

31301 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-03-15

Study Completion Date

2024-01-11

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The use of artificial intelligence software in breast screening (Transpara®) makes it possible to identify studies with a very low probability of cancer.

The hypothesis raised in this work is that reading strategies based on artificial intelligence (single or double reading only of cases with a score\> 7 with Transpara®), allow reducing the workload of a screening program by more than 50 % with respect to the standard reading of the program (double reading of all cases without Transpara®), without presenting inferiority in terms of detection rates and recalls of the program, both with the use of 2D digital mammography and with the use of tomosynthesis or 3D mammogram.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

Artificial Intelligence in Breast Cancer Screening in Region Östergötland Linkoping

NCT05048095

Breast Cancer

COMPLETED

The Use of AI to Safely Reduce the Workload in Breast Cancer Screening With Mammography in Region Östergötland

NCT06187350

Artificial Intelligence Breast Diseases Neoplasms +1 more

COMPLETED

Artificial Intelligence in Large-scale Breast Cancer Screening

NCT04778670

Breast Neoplasm Female

UNKNOWN NA

Screening Mammography: Single Reading by One Radiologist With AI vs. Double Reading by Two Radiologists (AI-BCSQ)

NCT07075679

Breast Cancer Screening Artificial Intelligence (AI) Breast Cancer Screening and Diagnosis

NOT_YET_RECRUITING NA

Clinical Validation of an Artificial Intelligence Algorithm to Help Interpret Mammograms

NCT05640011

Breast Cancer

COMPLETED

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Breast Cancer Screening

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Double reading of all cases with and without Transpara software

Group Type EXPERIMENTAL

Mammograms

Intervention Type DIAGNOSTIC_TEST

In the women participating in the study, two strategies for reading mammograms will be carried out:

Strategy 1: Standard reading of the program. Double independent and non-consensual reading of all cases, without any artificial intelligence system (standard strategy).

Strategy 2: Reading strategy based on the global Score granted by Transpara® (strategy based on artificial intelligence):

* In studies with a Score \<8 (studies with a low probability of cancer): They will not be evaluated by any radiologist.
* In studies with a Score\> 7 (studies with a high probability of cancer): double reading will be carried out, assisted by Transpara®.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Mammograms

In the women participating in the study, two strategies for reading mammograms will be carried out:

Strategy 1: Standard reading of the program. Double independent and non-consensual reading of all cases, without any artificial intelligence system (standard strategy).

Strategy 2: Reading strategy based on the global Score granted by Transpara® (strategy based on artificial intelligence):

* In studies with a Score \<8 (studies with a low probability of cancer): They will not be evaluated by any radiologist.
* In studies with a Score\> 7 (studies with a high probability of cancer): double reading will be carried out, assisted by Transpara®.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

All women between 50 and 71 years of age (including women who reach that age in the year of appointment), in the Reina Sofía University Hospital district, invited to participate in the Breast Cancer Early Detection Program, that have been randomly assigned in the Hologic equipment (DM or DBT), and who agree to participate in the study by signing the informed consent form.

1. Women studied in the program during the established period and who have previously participated.
2. Women studied in the program for the first time in the established period.

Exclusion Criteria

1. Women invited to the program who do not agree to participate in the research study by signing the informed consent form.
2. Women with breast prostheses.
3. Women with signs or symptoms of suspected breast cancer.

Minimum Eligible Age

50 Years

Maximum Eligible Age

71 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes