12168
clinical study

The Role of Artificial Intelligence in Detection of Incidental Pulmonary Embolism in Cardiac CT Angiography

Accuracy, Incidental Pulmonary Embolism, Pulmonary Embolism, Time to Treatment

Materials & Methods

Evaluated the performance of an artificial intelligence algorithm (AIA, Aidoc) for detecting incidental pulmonary embolism (iPE) in cardiac CT angiography (CCTA) scans. A total of 1,534 CCTA scans from 2021 to 2023 were analyzed. The AIA’s findings were compared to radiology reports reviewed through a natural language processing (NLP) system.

Results

Despite a focused field of view in CCTA, iPE is detected in about 1% of scans. The AIA identified 27 scans as positive for PE. Of these, 22 were confirmed by a second review, and five were negated. Notably, the AIA detected 45.5% (10/22) of the confirmed cases that were missed by initial radiologists, all segmental or subsegmental PEs (p<0.05). The AIA demonstrated high sensitivity (100%), specificity (99.6%), accuracy (99.6%), positive predictive value (81.4%) and negative predictive value (100%).

Conclusions

The AIA is effective in identifying iPE in CCTA scans and could improve diagnostic accuracy and lead to earlier detection and treatment.

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