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

•Radiology Business
Stanford Pilots AI Tool for Explaining Imaging Results to Providers
Stanford Health Care reports primary care providers find value in AI tools generating imaging result explanations.

•AI in Healthcare
Economic Evaluations of AI in Healthcare Face Major Gaps
A Finnish review finds significant deficiencies in how studies evaluate and report the economic impact of healthcare AI.

•AI in Healthcare
Literature Review Highlights Gaps in Economic Evaluation of Healthcare AI
A Finnish review finds significant gaps in economic evaluation reporting of AI technologies in Western healthcare.