Deep learning-based algorithm for automatic detection of incidental pulmonary embolism on contrast-enhanced CT: a multicenter multivendor study.

ABSTRACT:

Background

Incidenal pulmonary embolism (iPE) is increasingly detected on contrast-enhanced computed tomography (CECT) performed for non-PE indications, reflecting the growing volume and complexity of cross-sectional imaging. These findings, although unexpected, carry important clinical implications and may be underreported due to the primary diagnostic focus of the study. Artificial intelligence (AI) applications offer the potential to augment radiologist workflow bt training exams and highlighting cases suspicious for iPE, thereby improving detection accuracy and timeliness in routine clinical practice.

Purpose

Likelihood of incidental pulmonary embolism (iPE) increases with increased body computed tomography CT) imaging. This study evaluates the diagnostic performance and

SUBMITTER: Farzaneh H 

PROVIDER: S-EPMC12429201 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature