6750
clinical study

The Use of Artificial Intelligence to Improve Detection of Incidental Pulmonary Emboli

Materials & Methods

An artificial intelligence algorithm (Aidoc) was used to retrospectively review 14,453 conventional chest CT exams with IV contrast for the presence of incidental pulmonary emboli. All exams were performed as part of a combined CT of the chest, abdomen, and pelvis and read by thoracic radiologists. Natural language processing was used to search the exam reports to find cases of iPE detected prospectively. All cases read as positive for pulmonary emboli by the AI algorithm and NLP search were reviewed by thoracic radiologists to confirm the presence of acute PE. The most proximal level of clot and overall clot burden were assessed during this review.

Results

A total of 254 chest CT exams had acute iPE detected by AI or by review of the radiologist original reports and confirmed by subsequent review for a prevalence of 1.8%. 218 iPE were detected prospectively by radiologists. The sensitivity of radiologists for iPE detection was 0.858. AI detected an additional 36 cases of iPE that were missed prospectively (radiologist false negative rate of 14.2%). 30 cases indicated as positive by the AI algorithm were classified as negative on further clinical review. The AI algorithm had a sensitivity for iPE detection of 0.882 and specificity of 0.998 and accuracy of 0.996. Of the 36 cases of iPE missed by the radiologist, 19 were solitary segmental or subsegmental emboli and the average Qanadli score of clot burden was 1.9. Of the 30 cases of iPE missed by the AI algorithm, one case had large central emboli, but the other cases had small emboli with 23 having solitary subsegmental emboli and an average Qanadli score of 1.5. Tumor/adenopathy adjacent to the pulmonary vessel was the most common cause of AI false positives. Beam hardening artifact, motion artifact, and image noise were also causes of AI false positives.

Conclusions

Acute iPE are sometimes missed during interpretation of conventional chest CT with IV contrast. The use of an AI tool significantly improved detection of iPE which had been missed prospectively. The AI tool had high accuracy with a l ow false positive rate. The iPE missed by the radiologist were small. Further studies of patient outcome are needed to assess the clinical significance of missed untreated iPE.

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Amalia Schreier

<p>Amalia Schreier serves as the Senior Vice President of Regulatory Affairs and Legal at Aidoc, guiding our company and product’s regulatory strategies and ensuring alignment with AI-focused medical device compliance requirements. Since her tenure began, she has streamlined our FDA clearance processes, emphasizing a meticulous approach that underscores our commitment to product and clinical quality.</p> <p>With a solid foundation from her legal background and leadership role in AI startup regulatory departments, Schreier brings invaluable insights and expertise to our regulatory framework. Prior to her tech world experience, she worked as a human-rights lawyer and legal policy scholar, with a BA and LLM in law from the Hebrew University of Jerusalem.</p>

Deepak Srikant

<p>Deepak Srikant is a global marketing executive with over 20 years of experience, specializing in the commercialization of medical devices and digital health solutions. He has a proven track record in driving growth, having led successful go-to-market strategies, product launches and market expansions across the U.S. and EMEA.</p> <p>Srikant’s expertise extends to upstream and downstream marketing, professional education and sales enablement. His leadership at companies such as Silk Road Medical (acquired by Boston Scientific) and Aptus Endosystems (acquired by Medtronic) has consistently resulted in revenue growth, enhanced customer retention and successful product adoption.</p> <p>Srikant holds an MBA from the Yale School of Management and a bachelor’s degree in mechanical engineering from Rensselaer Polytechnic Institute. Currently, he leads product marketing for Aidoc’s cardiovascular service line.</p>

Laci Costa

<p>Laci Costa is the Director of Neurovascular Product Marketing at Aidoc. She leads marketing and commercial strategy for the neuro AI portfolio of products. She has 16 years of experience working in the medical device and healthcare industry, with over 12 years dedicated to neurovascular solutions.</p> <p>Costa’s known for her expertise in the neurovascular industry, go-to-market experience with new technologies and upstream and downstream product marketing leadership. She’s held various leadership positions in product marketing, clinical education and professional affairs spanning across start-up organizations to large publicly traded companies.</p> <p>Costa holds a bachelor’s degree in psychology from the University of Oklahoma and an MBA from USC Marshall School of Business.</p>