Impact of optional reconstruction kernel on image quality of pulmonary ground glass nodules using the third generation dual-source computed tomography

OBJECTIVETo explore the value of the third generation dual-source computed tomography (CT) convolution kernel in display of pulmonary ground-glass nodule (GGN) in transverse image reconstruction. Methods: A total of 52 lung adenocarcinoma patients with lung CT data were selected from February 2018 to January 2019 for this study. The pulmonary CT data were reconstructed by convolutional nucleus B157, Br54, and Br49. The signal-to-noise ratio (SNR), the contrast-to-noise ratio (CNR), and the standard deviation (SD) of the image at the GGN were used as the objective evaluation standard of image quality. Subjective image quality was scored by 2 radiologists from 3 aspects (overall image quality, noise, and lesion outline). Results: Objective image quality evaluation, SNR and CNR of reconstructed convolution kernel Br49 (SNR: 11.36±5.39, CNR: 7.19±4.29), Br54 (SNR: 8.30±3.35, CNR: 5.09±2.86) are greater than those of Bl57 (SNR: 4.18±2.10, CNR: 3.25±1.78; all P