Computer-assisted detection of acute pulmonary embolism at CT pulmonary angiography in children and young adults: a diagnostic performance analysis. (August 2019)

• Record Type: Journal Article
• Authors: Tang, Chun Xiang; Zhou, Chang Sheng; Schoepf, Uwe Joseph; Mastrodicasa, Domenico; Duguay, Taylor; Cline, Anna; Zhao, Yan E; Lu, Li; Li, Xie; Tao, Shu Min; Lu, Meng Jie; Lu, Guang Ming; Zhang, Long Jiang
• Is Part Of: Acta radiologica. Volume 60:Number 8(2019)
• Page Start: 1011
• Page End: 1019
• Publication Date: 2019-08
• Subjects: Pulmonary embolism -- children -- computer-assisted detection -- diagnosis; Radiology, Medical -- Periodicals; Radiography, Medical -- Periodicals; Radiotherapy -- Periodicals; 616.0757
• DOI: 10.1177/0284185118808547
• Languages: English
• ISSNs: 0284-1851

Abstract

Background: To diagnose pulmonary embolism (PE) in children and adults since evaluating tiny pulmonary vasculature beyond segmental level is a challenging and demanding task with thousands of images. Purpose: To evaluate the effect of computer-assisted detection (CAD) on acute PE on CTPA in children and young adults by readers with varying experience levels. Material and Methods: Six radiologists were retrospectively divided into three groups according to experience levels and assessed the CTPA studies on a per-emboli basis. All readers identified independently the PE presence, and ranked diagnostic confidence on a 5-point scale with and without CAD. Reading time, sensitivities, specificities, accuracies, positive predictive values (PPVs), and negative predictive values (NPVs) were calculated for each reading. Results: The sensitivities and NPVs differed significantly in most readers ( P = 0.004, 0.001, 0.010, 0.010, and 0.012 for sensitivities and P = 0.011, 0.003, 0.016, 0.017, and 0.019 for NPVs) except for reader 6 ( P = 0.148 and 0.165, respectively), and the accuracies of all readers differed significantly (all P < 0.05) in peripheral PE (beyond segmental level) detection readings with CAD versus without CAD between two reading methods. The overall time using CAD was longer than those without CAD (76.6 ± 54.4 s vs. 49.4 ± 17.7 s, P = 0.000) for all readers. Significant differences were found for confidence scores in inter-group measurements with CAD ( P = 0.045) and without CAD ( P < 0.001). Conclusion: At the expense of longer reading time, the use of the CAD algorithms improves sensitivities, NPVs, and the accuracies of readers in peripheral PE detection, especially for readers with a poor level of interpretation experience.