Influence of Monoenergetic Images at Different Energy Levels in Dual-Energy Spectral CT on the Accuracy of Computer-Aided Detection for Pulmonary Embolism

Publication date: Available online 22 February 2019

Source: Academic Radiology

Author(s): Guangming Ma, Yuequn Dou, Shan Dang, Nan Yu, Yanbing Guo, Chuangbo Yang, Shuanhong Lu, Dong Han, Chenwang Jin

Purpose

To investigate the influence of monoenergetic images of different energy levels in spectral computed tomography (CT) on the accuracy of computer aided detection (CAD) for pulmonary embolism (PE).

Materials and Methods

CT images of 20 PE patients who underwent spectral CT pulmonary angiography were retrospectively analyzed. Nine sets of monochromatic images from 40 to 80 keV at 5 keV interval were reconstructed and then independently analyzed for detecting PE using a commercially available CAD software. Two experienced radiologists reviewed all images and recorded the number of emboli manually, which was used as the reference standard. The CAD findings for the number of PE at different energies were compared with the reference standard to determine the number of true positives and false positives with CAD and to calculate the sensitivity and false positive rate at different energies.

Result

There were 120 true emboli. The total numbers of CAD-detected PE at 40–80 keV were 48, 67, 63, 87, 106, 115, 138, 157, and 226. Images at low energies had low sensitivities and low false positive rates; images at high energies had high sensitivities and high false positive rates. At 60 keV and 65 keV, CAD achieved sensitivity at 81.67% and 84.17%, respectively and false positive rate at 7.55% and 12.17%, respectively to provide the optimum combination of high sensitivity and low false positive rate.

Conclusion

Monochromatic images of different energies in dual-energy spectral CT affect the accuracy of CAD for PE. The combination of CAD with images at 60–65 keV provides the optimum combination of high sensitivity and low false positive rate in detecting PE.

from #Head and Neck by Sfakianakis via simeraentaxei on Inoreader https://ift.tt/2Eqb84Q