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 (CTDI vol), 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.
ABSTRACT
This study presents the differential diagnosis of metastatic tumors of the pleura vs. primary pleural malignancies in a male patient whose diagnosis was multiple myeloma with pleural involvement and confirmed by bone marrow aspiration and pleural biopsy. Computed tomography [CT] manifestations of this case were retrospectively analyzed, and compared with those of primary pleural malignancies. The CT manifestations of this case mainly involved bilateral multiple pleural nodules with irregular thickening. These nodules were also associated with rib damage and lung metastases, manifestations characteristic of metastatic tumors. The presence of a primary pleural malignancy correlated with patients' clinical history and imaging data, and involved unilateral pleural involvement, and to a lesser extent, mediastinal pleural involvement and pleural effusions. A pleural biopsy can establish a definitive diagnosis. Therefore, multiple myeloma with pleural involvement can be differentiated from primary pleural malignancies by using a combination of imaging data and clinical laboratory tests