AI Triage for Breast Cancer Screening
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial explores whether radiologists can quickly and accurately determine if a breast cancer screening is normal by examining a 2D image, without a detailed 3D scan. The researchers aim to assess whether adding AI (a computer program that learns and makes decisions) can help radiologists make these assessments more confidently. The goal is to speed up the screening process while ensuring no cancer cases are missed. Radiologists or radiology trainees with experience in reading mammograms might be suitable for this study. As an unphased trial, participants contribute to innovative research that may enhance future breast cancer screening methods.
What prior data suggests that this AI triage method is safe for breast cancer screening?
Research has shown that AI technology is generally safe in medical settings. Most studies focus on its accuracy in assisting doctors rather than causing harm. In this study, AI assists with breast cancer screenings. AI doesn't directly affect the body; instead, it aids radiologists (doctors who interpret images like X-rays) in decision-making.
This trial is in an early stage, primarily testing how well AI collaborates with human experts. With no physical treatment involved, safety risks remain low. The main goal is to ensure the AI accurately identifies normal cases and detects any signs of cancer.
While this trial tests the process, the AI itself is unlikely to cause harm. Participants can feel confident that the primary aim is to enhance screening accuracy and speed, not to introduce new physical risks.
Why are researchers excited about this trial?
Researchers are excited about AI Triage for Breast Cancer Screening because it uses advanced artificial intelligence to enhance early detection of breast cancer. Unlike traditional screening methods like mammograms that rely heavily on human interpretation, this AI system analyzes imaging data with high precision, potentially identifying subtle changes that may be missed by the human eye. This approach could lead to earlier diagnosis, improve treatment outcomes, and reduce unnecessary biopsies, making the screening process more efficient and less stressful for patients.
What evidence suggests that this AI triage method is effective for breast cancer screening?
Studies have shown that AI can enhance the accuracy and efficiency of breast cancer screening. In some real-world tests, AI-supported screenings identified 6.7 cases of breast cancer per 1,000 screenings, a 17.6% improvement over traditional methods. AI assists radiologists by enabling them to concentrate on more complex cases, thus reducing their workload. The technology aims to detect more cancers while accelerating the screening process. Despite AI's promise, some concerns remain about relying on machines for health decisions.12345
Are You a Good Fit for This Trial?
This trial is for radiologists or radiology trainees with experience in reading mammography. Participants must have good vision, at least 20/25 with correction, to be eligible.Inclusion Criteria
Exclusion Criteria
Timeline for a Trial Participant
Screening
Participants are screened for eligibility to participate in the trial
Radiologist Evaluation
Radiologists evaluate 2D mammogram images for up to 5 seconds and provide a normality rating. They also assess AI's opinion on the images.
AI Evaluation
AI system evaluates the same images and provides a probability of malignancy score. Radiologists assess the AI's ability to triage cases.
Follow-up
Participants are monitored for safety and effectiveness after treatment
What Are the Treatments Tested in This Trial?
Find a Clinic Near You
Who Is Running the Clinical Trial?
Brigham and Women's Hospital
Lead Sponsor