A commercial AI system can identify up to 33% of interval breast cancers missed by radiologists on digital breast tomosynthesis exams.
Key Details
- 1Study published in Radiology tested AI on digital breast tomosynthesis (DBT) exams preceding confirmed interval cancer diagnoses.
- 2The AI algorithm (Lunit INSIGHT DBT v1.1) flagged up to one-third of interval cancers missed by radiologists.
- 3Interval breast cancers are often more aggressive and have worse prognoses than screen-detected cancers.
- 4Nearly 12 years of retrospective DBT data (Feb 2011–Jun 2023) were analyzed.
- 5Algorithm scored lesions; those over 10 marked as positive, and radiologist review correlated AI findings with actual cancer sites.
Why It Matters
Interval cancers are frequently aggressive and linked with higher morbidity and mortality due to later detection. AI's ability to identify a significant portion of these previously missed cancers suggests potential for earlier intervention and improved patient outcomes in breast imaging.
Source
Health Imaging
Related News
•Radiology Business
Aidoc Receives FDA Breakthrough Status for Multi-Condition CT AI Triage
Aidoc has received FDA Breakthrough Device status for its AI solution that flags multiple critical conditions in CT scans.
•AI in Healthcare
FDA Seeks Real-World Performance Insights on AI Medical Devices
FDA calls for healthcare worker feedback to enhance monitoring of AI-enabled medical devices in real-world settings.
•Radiology Business
AI Triage Cuts CT Report Turnaround for Pulmonary Embolism—Daytime Only
FDA-backed study finds AI triage tools reduce radiology CT report turnaround times for pulmonary embolism during peak hours.