Résumé
Objective:To investigate the efficiency of deep learning image reconstruction (DLIR) algorithm in the image quality and detection of hypovascular hepatic metastases under low radiation doses in comparison with adaptive statistical iterative construction-V (ASiR-V).Methods:Fifty-six patients with suspected hypovascular hepatic metastases who needed abdominal enhanced CT scans were collected prospectively in the First Affiliated Hospital of Zhengzhou University from January to April 2021. The patients received conventional radiation dose with tube current-time products of 400 mA CT scans in the first venous phase, low-dose CT scans in the second venous phase, which were set as tube current-time products of 280 mA for group A (19 cases), 200 mA for group B (19 cases) and 120 mA for group C (18 case), respectively. The images of first venous phase and 3 groups of second venous phase were both reconstructed with ASiR-V60% and high-DLIR (DLIR-H). Quantitative parameters [image noise, liver and portal vein signal to noise ratio (SNR), contrast to noise ratio (CNR)] and qualitative parameters (overall image quality, lesion conspicuity, diagnostic confidence) were compared between ASiR-V60% and DLIR-H images, and the effective radiation dose (ED) and the lesion detectability of each group was recorded. The paired t test was used to compare quantitative parameters, whereas the Wilcoxon signed-rank test of paired data was used to compare qualitative parameters. Results:In the second venous phase, ED was (5.56±0.35) mSv in group A, (3.88±0.23) mSv in group B, and (2.42±0.23) mSv in group C, with a decrease of 30%, 50% and 70% compared with the first venous phase, respectively. Moreover, with the decrease of radiation dose, the noise gradually increased, and the CNR lesions, SNR liver and SNR portal vein all gradually decreased. DLIR-H images had statistically better quantitative scores than ASiR-V60% images when the same radiation dose was applied (all P<0.001). Furthermore, the qualitative parameters of each group decreased with the decrease of radiation dose. Under the same radiation dose, the overall image quality, lesion conspicuity and diagnostic confidence of DLIR-H were higher than those of ASiR-V60% (all P<0.001). All lesions [100% (84/84)] were detected by ASIR-V60% and DLIR-H in group A, 92.0% (75/81) in group B, and 88.0% (79/89) in group C. Conclusions:Compared with ASiR-V60%, DLIR-H could reduce image noise, improve overall image quality and lesion conspicuity of hypovascular hepatic metastases as well as increase diagnostic confidence under different radiation doses.
Résumé
Objective To prepare a mouse monoclonal antibody against human asialoglycoprotein receptor (ASGPR), and to apply it for detecting ASGPR expression in cell lines and tissues. Methods The structure of ASGPR HI major subunit was analyzed and the full length of ASGPR1 was selected to synthesize immunizing peptide. cDNA was amplified by RT-PCR and then subcloned into prokaryotic vector pGEX-4T-1. The recombinant protein was expressed by E. coli BL21 and purified for subsequent immunization. The conventional hybridoma technique was used to generate mouse monoclonal antibody. The isotype and the titer were regularly tested. Inhibition experiment was conducted to identify the specific binding of the antibody to ASGPR. Finally, the expression of ASGPR was detected in various intra-hepatic and extra-hepatic cell lines by flow cytometry and in different liver tissues by immunohistochemistry method. Results Monoclonal antibody against human ASGPR was successfully prepared and was identified as IgG1, with the titer reaching 1: 12 800. Inhibition experiment indicated a satisfactory specific binding of the antibody to ASGPR and that the recognition epitope was located in the extracellular domain of ASGPR. Flow cytometric analysis showed various levels of ASGPR expression in intra-hepatic cell lines, but not in extra-hepatic cell lines. Immunohistochemistry detection showed that ASGPR was specifically expressed in the normll liver tissues and hepatocellular carcinoma (HCC) tissues, and the expression in HCC tissues was associated with the differentiation degree, with the expression being significantly higher in well-differentiated HCC than that in the poorly-differentiated HCC (75. 0% vs 28. 6%, P<0. 05). Conclusion We have successfully prepared the monoclonal antibody against human ASGPR with high specificity; the antibody can be used for flow cytometric analsis and immunohistochemistry detection of ASGPR and for clinical distinguish of primary or metastatic liver cancer.