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Triaging mammography with artificial intelligence: an implementation study
Sarah M Friedewald1,2, Marcin Sieniek3, Sunny Jansen3
1Feinberg School of Medicine, Northwestern University, 420 E Superior St, Chicago, IL, 60611, USA. sarah.friedewald@nm.org.
Breast Cancer Research and Treatment
|January 29, 2025
Summary
Artificial intelligence (AI) significantly reduced diagnostic delays for patients needing further breast cancer screening. This AI prioritization accelerated time to imaging and biopsy, improving patient care timelines.
Area of Science:
- Medical Imaging
- Artificial Intelligence in Healthcare
- Oncology
Background:
- Screening mammography often lacks immediate results, leading to delayed patient care.
- Artificial intelligence (AI) offers a potential solution to expedite diagnosis and treatment.
Purpose of the Study:
- To evaluate the impact of an AI system on reducing diagnostic timelines in screening mammography.
- To assess the effectiveness of AI in prioritizing patients for timely diagnostic imaging and biopsy.
Main Methods:
- A prospective randomized controlled study involving 1000 screening participants.
- An AI system prioritized cases for same-visit evaluation and potential diagnostic workup in the experimental group.
- The control group received standard care; primary endpoints were time to additional imaging (TA) and time to biopsy diagnosis (TB).
Main Results:
- The AI group showed a 25% reduction in time to additional imaging (TA) and a 30% reduction in time to biopsy diagnosis (TB).
- AI-prioritized patients experienced more pronounced time reductions.
- All participants diagnosed with breast cancer were successfully prioritized by the AI system.
Conclusions:
- AI prioritization effectively accelerates care timelines for patients requiring further diagnostic evaluation.
- Reduced diagnostic delays can improve patient adherence, decrease anxiety, and address healthcare disparities.
