探讨深度学习图像重建（DLIR）算法结合前置自适应迭代重建-V（ASIR-V）技术在过重患者门静脉成像（CTPV）中的应用价值。

本前瞻性研究对象为2021年6月至9月在中山大学附属第三医院接受腹部增强CTPV检查的50例患者。其中男31例，女19例；年龄19~74岁，中位年龄56岁；BMI>25 kg/m²。患者均签署患者知情同意书，符合医学伦理学规定。比较前置50%ASIR-V技术（开启）和前置0%ASIR-V（关闭）时有效辐射剂量（ED）。采用60%ASIR-V、80%ASIR-V、DLIR-M（中等级别）和DLIR-H（高等级别）4种算法分别对患者门静脉期数据进行薄层重建。图像质量的客观评价指标包括门静脉CT值的标准差（SD）值、信噪比（SNR）和对比噪声比（CNR），主观评价由两名放射科医师对重建图像质量进行双盲法评分。前置ASIR-V开启前后ED比较采用t检验。不同算法的SD、SNR、CNR等客观评价指标比较采用单因素方差分析；主观图像质量评分比较采用Kruskal-Wallis检验，采用Kappa检验分析两名放射科医师的主观图像质量评分的一致性。

前置ASIR-V关闭和开启后平均ED分别为（11.1±1.4）、（7.6±1.1）mSv，ED降低32%（t=14.01，P<0.05）。对于门静脉主干，DLIR-H组SD最小，SNR和CNR最大（P<0.05）。对于门静脉分支，80%ASIR-V组SD最小，SNR最大；DLIR-H组CNR最大（P<0.05）。在所有算法重建的图像中，DLIR-H组门静脉重建图像质量的主观评分最高（P<0.05）。两名放射科医师对60%ASIR-V、80%ASIR-V、DLIR-M和DLIR-H算法的门静脉重建图像质量的主观评分一致性较好（κ=0.810，0.556，0.705，0.676；P<0.05）；对门静脉整体和分支图像质量的主观评分一致性亦较好（κ=0.661，0.959；P<0.05）。

在过重患者门静脉造影中，前置ASIR-V技术可明显降低ED；DLIR算法可显著降低噪声，不改变其纹理，相比ASIR-V算法可获得更好的门静脉期图像，其中高级别DLIR算法重建图像最佳。

To evaluate the application value of deep learning image reconstruction (DLIR) algorithm combined with pre-adaptive statistical iterative reconstruction-V (ASIR-V) in CT portal venography (CTPV) for overweight patients.

50 patients receiving abdominal enhanced CTPV in the Third Affiliated Hospital of Sun Yat-sen University from June to September 2021 were enrolled in this prospective study. Among them, 31 patients were male and 19 female, aged from 19 to 74 years, with a median age of 56 years and BMI>25 kg/m². The informed consents of all patients were obtained and the local ethical committee approval was received. The effective dose (ED) was compared between 50% pre-ASIR-V (turned on) and 0% pre-ASIR-V (turned off). The data of portal venous phase were thin-slice reconstructed with 4 algorithms 60%ASIR-V, 80%ASIR-V, DLIR-M (middle level) and DLIR-H (high level), respectively. The objective evaluation parameters of image quality included standard deviation (SD) of CT value of portal vein, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The subjective assessment of reconstructed images was performed with double-blind method by two radiologists. The ED before and after turning on pre-ASIR-V was statistically compared by t test. The SD, SNR, CNR and other objective evaluation parameters of image quality among different algorithms were compared by one-way ANOVA. The subjective scores were compared by Kruskal-Wallis test. The consistency of subjective scores of image quality between two radiologists was analyzed by Kappa test.

The average ED was (11.1±1.4) and (7.6±1.1) mSv before and after turning on pre-ASIR-V, respectively, which was decreased by 32% (t=14.01, P<0.05). For the main portal vein, the SD was the lowest, the SNR and CNR were the highest in DLIR-H group (P<0.05). For the portal vein branches, the SD was the lowest and the SNR was the highest in 80%ASIR-V group, and the CNR was the highest in DLIR-H group (P<0.05). Among all the images reconstructed by different algorithms, the subjective score was the highest in DLIR-H group (P<0.05). The consistency of scores of two radiologists was comparatively high for the portal vein images reconstructed with 60%ASIR-V, 80%ASIR-V, DLIR-M and DLIR-H algorithms (κ=0.810, 0.556, 0.705, 0.676; P<0.05). Comparatively high consistency was also observed in the subjective scores for the images of portal vein system and portal vein branches (κ=0.661, 0.959; P<0.5).

In the CTPV for overweight patients, pre-ASIR-V can significantly reduce the ED. DLIR algorithm can significantly reduce the noise without changing the texture. Compared with ASIR-V algorithm, DLIR algorithm can obtain better portal vein phase images, especially the DLIR-H algorithm.