An AI algorithm enhanced radiologists' detection of incidental pulmonary emboli (IPE) on routine contrast-enhanced CT studies.
Key Details
- 1Study assessed 14,453 contrast-enhanced outpatient CT chest/abdomen/pelvis exams for IPEs using Aidoc's AI algorithm.
- 2AI detected 224 IPE cases, 36 of which radiologists missed; these were mostly small and distal emboli.
- 3AI missed 30 IPEs that radiologists found, most being small, with one large central embolus missed.
- 4Radiologist re-review of 1,400 negative cases found 8 additional IPEs missed initially.
- 5Specificity for identifying IPE: 65.1% for radiologists, 66.9% for AI, and 75.8% when combined.
- 6AI showed similar sensitivity as radiologists but a lower positive predictive value; false positive rate noted.
Why It Matters
Automated AI second reads can improve detection of incidental findings on routine CT exams, suggesting a synergistic workflow where AI and human expertise together outperform either alone. This has potential clinical impact for patient outcomes and radiology practice, though current AI tools require continued human oversight.

Source
AuntMinnie
Related News

•AuntMinnie
Study: Computer Vision Models Best LLMs in Chest CT Breast Abnormality Detection
Computer vision models (CVMs) surpass large language models (LLMs) in accurately labeling incidental breast abnormalities on chest CT scans.

•Cardiovascular Business
Radiology Maintains Lead in FDA-Cleared AI Algorithms, Cardiology Follows
Radiology remains the top specialty for FDA-cleared AI, with cardiology as a strong second, particularly in cardiovascular imaging.

•Radiology Business
Private Equity Backs AIRS Medical to Expand MRI AI Globally
TA Associates is investing in AIRS Medical to accelerate its global expansion of AI-powered MRI efficiency solutions.