Objective:To investigate the impact of deep learning image reconstruction (DLIR), adaptive statistical iterative reconstruction-veo (ASiR-V) and filtered back projection (FBP) on the histogram and wavelet features of portal venous phase abdominal CT in patients with hepatic tumor.Methods:The CT data of 68 patients with hepatic tumor who underwent enhanced CT scans were retrospectively collected. FBP, 30%ASiR-V, DLIR-L, DLIR-M and DLIR-H images were reconstructed. The images of portal venous phase were reconstructed with five algorithms, including FBP, ASIR-V at a level of 30% (ASiR-V 30%), DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H). Histogram and wavelet features were extracted from hepatic lesion, liver, spleen, kidney and erector spinae muscle, and compared using one-way analysis of variance or Kruskal-Wallis test. Two radiologists delineated the three-dimensional lesions independently and one of them repeated the delineation after one month. Intra-class correlation coefficients ( ICC) among five sets of images were calculated to evaluate the consistency of radiomics features of hepatic lesion. P<0.05 was considered to indicate statistical significance. Results:Most histogram and wavelet features extracted from hepatic lesion, liver, spleen, kidney and erector spinae muscle showed significant differences among five groups (all P<0.05). The number of features without significant differences decreased with the intensity of DLIR reconstruction increased. For histogram features, there were no significant differences of energy, mean, median, and total energy among five sets of images ( P>0.05). For wavelet features, there were no significant differences of mean and median among five sets of images ( P>0.05). The consistency of all histogram features was high except for the mean value of wavelet feature. The intra-and inter-observer ICC ranged from 0.756 to 1 and 0.767 to 1, respectively. Conclusion:Both 30%ASiR-V and DLIR at three levels algorithms had influence on the histogram and wavelet features of abdominal organs and hepatic tumors extracted from CT images in portal venous phase, and the effects expanded with the strengthening of levels. Median can be a reliable quantitative parameter for CT texture analysis of hepatic tumor.

Objective:To investigate the impact of deep learning image reconstruction (DLIR), adaptive statistical iterative reconstruction-veo (ASiR-V) and filtered back projection (FBP) on the histogram and wavelet features of portal venous phase abdominal CT in patients with hepatic tumor.Methods:The CT data of 68 patients with hepatic tumor who underwent enhanced CT scans were retrospectively collected. FBP, 30%ASiR-V, DLIR-L, DLIR-M and DLIR-H images were reconstructed. The images of portal venous phase were reconstructed with five algorithms, including FBP, ASIR-V at a level of 30% (ASiR-V 30%), DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H). Histogram and wavelet features were extracted from hepatic lesion, liver, spleen, kidney and erector spinae muscle, and compared using one-way analysis of variance or Kruskal-Wallis test. Two radiologists delineated the three-dimensional lesions independently and one of them repeated the delineation after one month. Intra-class correlation coefficients ( ICC) among five sets of images were calculated to evaluate the consistency of radiomics features of hepatic lesion. P<0.05 was considered to indicate statistical significance. Results:Most histogram and wavelet features extracted from hepatic lesion, liver, spleen, kidney and erector spinae muscle showed significant differences among five groups (all P<0.05). The number of features without significant differences decreased with the intensity of DLIR reconstruction increased. For histogram features, there were no significant differences of energy, mean, median, and total energy among five sets of images ( P>0.05). For wavelet features, there were no significant differences of mean and median among five sets of images ( P>0.05). The consistency of all histogram features was high except for the mean value of wavelet feature. The intra-and inter-observer ICC ranged from 0.756 to 1 and 0.767 to 1, respectively. Conclusion:Both 30%ASiR-V and DLIR at three levels algorithms had influence on the histogram and wavelet features of abdominal organs and hepatic tumors extracted from CT images in portal venous phase, and the effects expanded with the strengthening of levels. Median can be a reliable quantitative parameter for CT texture analysis of hepatic tumor.

Objective To investigate the change of T helper 17 cells (Th17) in the peripheral blood mononuclear cell (PBMC) in patients with liver cystic echinococcosis. Methods Fifty-six subjects were divided into three groups: healthy controls (HD, n = 20), patients with cystic echinococcosis (CE, n= 18) and patients with cystic echinococcosis combined with bile fistula (BF,n= 18). The frequency of Th17 cells in CD4+ T lymphocytes was detected by flow cytometry. Th17-related cytokines including interleukin (IL)-17 and IL-23 were measured by enzyme-linked immunosorbent assay (ELISA). The data were analyzed by t test and Pearson correlation analysis.Results The frequency of Th17 in the peripheral blood was significantly lower in CE group compared to BF group and HD group [(0. 23±0. 11)% vs (0. 76±0.43)% vs (0.52±0.50)%; t=2. 225 and4. 077 respectively, both P＜0.05), while there was no statistical difference between BF group and HD group (t=1. 931, P＞0.05). The levels IL-17 and IL-23 were (12.1±3.7) ng/L and (84.4±46.0) ng/L respectively in CE group, which were lower than those in BF group [(15.5±4.1) ng/L and (138.6±37. 9) ng/L, respectively; t=2. 515 and 3. 649 respectively, both P＜0.05] and those in HD group [(14.8±4.4) ng/L and (138.1±48. 7) ng/L, respectively; t=2. 401 and 3. 706 respectively,both P ＜0.05], while there was no statistical difference between BF group and HD group (t=0. 534,P ＞0.05). Serum concentrations of IL-17 were all positively correlated with the concentrations of IL23 in these three groups (r=0. 657, P＜0.05). Conclusion The frequeny of Th17 cells in PBMC and the serum concentrations of IL-17, IL-23 are significantly reduced in patients with cystic echinococcosis.