| Zhang Lei,Shi Hongkun,Dong Shushan,Zhu Wan'an.Impact of artificial intelligence imaging optimization technique on image quality of low-dose chest CT scan[J].Chinese Journal of Radiological Medicine and Protection,2020,40(9):722-727 |
| Impact of artificial intelligence imaging optimization technique on image quality of low-dose chest CT scan |
| Received:June 03, 2020 |
| DOI：10.3760/cma.j.issn.0254-5098.2020.09.013 |
| KeyWords:Artificial intelligence Chest computed tomography Radiation dose |
| FundProject: |
| Author Name | Affiliation | E-mail | | Zhang Lei | Department of Radiology, Ji Lin University 1st hospital, Changchun 130021, China | | | Shi Hongkun | Department of Radiology, Ji Lin University 1st hospital, Changchun 130021, China | | | Dong Shushan | CT Business Unit, Neusoft Medical System Co., Ltd, Shenyang 110167, China | | | Zhu Wan'an | Department of Radiology, Ji Lin University 1st hospital, Changchun 130021, China | 448336550@qq.com |
|
| Hits: 2206 |
| Download times: 1120 |
| Abstract:: |
| Objective To investigate the impact of artificial intelligence imaging optimization technique on the image quality and radiation dose of low-dose chest CT scan. Methods Eighty patients who underwent chest CT examination in the Jilin University 1st hospital from July to August, 2019 were randomly divided into two groups(A, B), with 40 patients in each. The voltage of group A was 100 kV, while the other was 120 kV. According to different reconstruction method, group A was divided into two subgroups, group A1 and group A2. The images of A1 were reconstructed by iterative algorithm (ClearView 50%), while A2 images were optimized A1 by NeuAI imaging optimization technique. Group B used iterative algorithm (ClearView 50%) to reconstruct the image. The CT dose index (CTDIvol), dose-length product (DLP) and effective radiation dose (E) of group A and group B were recorded and compared.Objective the evaluation indicators were CT noise (SD), signal-to-noise ratio (SNR) and comparative noise ratio (CNR) of ROI. Subjective evaluation was done by 2 chief radiologists using double-blind method and image quality was graded by 5-point Likert scale.Results The patient characteristics between group A and group B showed no significant differences(P>0.05). Compared with group B, the effective radiation dose in group A was reduced by 72.1%[(1.48±0.49) mSv vs. (5.30±1.40) mSv]. The SD in group A1 was higher than that in group B, while SNR and CNR were lower (ZSD=-4.24, ZSNR=-2.54, tCNR=-2.27, P<0.05). The SD in group A2 was significantly lower than that in group B (ZSD=-28.24, P<0.001), and SNR and CNR were significantly higher than that in group B (tSNR=-26.04, tCNR=-36.88, P<0.001). There was no significant difference in subjective scores of image noise between group A2 and group B, while subjective scores of lung structure in group B were better than those in group A2(χ2=4.96、7.04,P<0.05). Conclusions Although the radiation dose was reduced by 72.1%, the low-dose chest CT images optimized by AI could reach the image quality level of standard dose. |
| HTML View Full Text View/Add Comment Download reader |
| Close |
|
|
|
