人工智能模型迭代重建对低剂量腹部增强CT图像质量的影响  

Effect of artificial intelligence model-based iterative reconstruction on low-dose abdominal enhanced CT image quality

作　　者：曹建新 朱卓 许炜[1] 刘廷 韩锦涛 陈颖[1] 张清[1] CAO Jianxin;ZHU Zhuo;XU Wei;LIU Ting;HAN Jintao;CHEN Ying;ZHANG Qing(Department of Radiology,Puren Hospital Affiliated to Wuhan University of Science and Technology,Wuhan 430081,Hubei,China;United Imaging Healthcare of Shanghai,Shanghai 201800,China)

机构地区：[1]武汉科技大学附属普仁医院放射科,湖北武汉430081 [2]上海联影医疗科技股份有限公司,上海201800

出　　处：《暨南大学学报（自然科学与医学版）》2023年第5期547-555,共9页Journal of Jinan University(Natural Science & Medicine Edition)

基　　金：武汉科技大学职业危害识别与控制湖北省重点实验室开放基金项目(OHIC2021G04)。

摘　　要：目的:评估人工智能模型迭代重建(AIIR)对低剂量腹部增强CT图像质量的影响,并寻求最佳AIIR等级。方法:对52例患者行低剂量腹部增强CT检查,采用滤波反投影(FBP)重建、混合迭代重建(HIR)及AIIR(5~1级)。评估FBP、HIR及AIIR图像质量的客观参数。两位放射科医师采用盲法按5分法对FBP、HIR及AIIR图像的噪声程度评分(1分为噪声非常小;5分为噪声大不能接受),并按5分法对AIIR图像的蜡状伪影程度评分(1分为无蜡状伪影;5分为完全不能接受的蜡状伪影)。结果:动脉期FBP、HIR及AIIR 5~1级图像上肝脏噪声分别为(22.6±3.1)、(14.6±2.1)、(9.3±0.9)、(7.9±0.8)、(6.4±0.8)、(4.8±0.9)和(3.3±1.1)Hu,静脉期相应图像上肝脏噪声分别为(23.8±3.7)、(15.5±2.4)、(9.7±1.1)、(8.3±0.9)、(6.7±0.8)、(5.0±0.8)和(3.4±1.0)Hu。FBP、HIR及AIIR 5~1级图像上,腰大肌噪声分别为(25.4±4.1)、(16.6±2.7)、(10.3±1.7)、(8.8±1.7)、(7.3±1.7)、(5.6±1.8)和(4.0±2.0)Hu,髂腰肌相应噪声分别为(23.1±4.0)、(15.5±3.2)、(10.2±2.2)、(9.1±2.3)、(7.8±2.5)、(6.5±2.6)和(5.3±2.8)Hu。AIIR图像上肝脏、腰大肌及髂腰肌噪声均明显低于FBP图像和HIR图像(P<0.01)。腹主动脉在FBP、HIR、AIIR 5~1级图像上噪声分别为(27.0±3.9)、(18.0±2.8)、(10.9±1.7)、(9.4±1.6)、(7.7±1.6)、(6.0±1.7)和(4.4±1.9)Hu,相应的信噪比(SNR)分别是(19.4±4.3)、(29.1±6.4)、(48.1±9.1)、(56.2±10.6)、(68.8±13.9)、(90.1±21.5)和(135.0±49.6)。门静脉在FBP、HIR、AIIR 5~1级图像上噪声依次分别是(26.7±4.4)、(17.6±3.5)、(11.2±3.0)、(9.8±3.1)、(8.2±3.3)、(6.6±3.6)和(5.0±3.9)Hu,SNR依次分别是(7.6±2.1)、(11.6±3.4)、(18.4±3.5)、(21.5±4.4)、(26.2±6.0)、(34.6±9.5)和(52.5±21.2)。AIIR图像与FBP图像及HIR图像相比,腹主动脉和门静脉噪声明显减低(P<0.01),SNR明显增加(P<0.01)。医师1动脉期FBP、HIR、AIIR 5~1级图像噪声评分分别为(3.58±0.50)、(2.35±0.48)、(1.42±0.50)、(1.08±Objective:To evaluate the effect of artificial intelligence model-based iterative reconstruction(AIIR)on low-dose abdominal enhanced CT image quality and to determine the optimal AIIR level.Methods:Fifty-two patients underwent low-dose abdominal enhanced CT with filter back projection(FBP)reconstruction,hybrid iterative reconstruction(HIR),and AIIR(level 5~1).Objective parameters of image quality for FBP,HIR,and AIIR images were evaluated.Noise was graded by two blinded radiologists for FBP,HIR,and AIIR images on a 5-point scale(1=very low noise;5=unacceptable increased noise).Wax artifacts were also graded by two blinded radiologists for AIIR images on a 5-point scale(1=no wax artifact;5=completely unacceptable wax artifact).Results:On the FBP,HIR,and AIIR(level 5~1)images,the liver noise was(22.6±3.1),(14.6±2.1),(9.3±0.9),(7.9±0.8),(6.4±0.8),(4.8±0.9)and(3.3±1.1)Hu in the arterial phase,and that was(23.8±3.7),(15.5±2.4),(9.7±1.1),(8.3±0.9),(6.7±0.8),(5.0±0.8)and(3.4±1.0)Hu in the venous phase,respectively.On the FBP,HIR,and AIIR(level 5~1)images,the noise of the psoas major muscle was(25.4±4.1),(16.6±2.7),(10.3±1.7),(8.8±1.7),(7.3±1.7),(5.6±1.8)and(4.0±2.0)Hu,while the noise of the iliopsoas was(23.1±4.0),(15.5±3.2),(10.2±2.2),(9.1±2.3),(7.8±2.5),(6.5±2.6)and(5.3±2.8)Hu,respectively.The noise of the liver,psoas major muscle,and iliopsoas on the AIIR images was all significantly lower than that on the FBP and HIR images(P<0.01).The noise of the abdominal aorta was(27.0±3.9),(18.0±2.8),(10.9±1.7),(9.4±1.6),(7.7±1.6),(6.0±1.7)and(4.4±1.9)Hu,while the signal-to-noise ratios(SNRs)of the abdominal aorta were(19.4±4.3),(29.1±6.4),(48.1±9.1),(56.2±10.6),(68.8±13.9),(90.1±21.5)and(135.0±49.6)on the FBP,HIR,and AIIR(level 5~1)images,respectively.The noise of the portal vein was(26.7±4.4),(17.6±3.5),(11.2±3.0),(9.8±3.1),(8.2±3.3),(6.6±3.6)and(5.0±3.9)Hu,while the SNRs of the portal vein were(7.6±2.1),(11.6±3.4),(18.4±3.5),(21.5±4.4),(26.2±6.0),(34.6±9.5)and(52.5±21.2

关 键 词：人工智能 迭代重建 CT 图像质量 

分 类 号：R318[医药卫生—生物医学工程]