摘要
目的探讨100kV深度学习图像重建(DLIR)在CT尿路造影(CTU)中双低(低辐射剂量、低对比剂剂量)技术的可行性,并与传统的120kV自适应统计迭代重建-V(ASIR-V)标准方案进行比较。方法收集60例行腹部CTU增强扫描的患者按扫描方案分为标准方案组(S组)和双低方案组(L组),记录L组和S组对比剂剂量、容积CT剂量指数和剂量长度乘积,计算有效剂量。对S组采用60%ASIR-V(S-AV60)重建,L组采用60%ASIR-V(L-AV60)DLIR-M、DLIR-H重建。测量右侧肾盂、右侧肾脏实质、左侧肾盂、左侧肾脏实质、右侧输尿管、左侧输尿管、膀胱、腰大肌CT值和标准差(SD),计算信噪比(SNR)和对比噪声比(CNR)。由两名临床经验丰富的诊断医师对原始轴位影像、重建后容积再现(VR)图像和最大强度投影(MIP)图像进行双盲法主观评分。两组有效剂量(ED)比较采用t检验,CT、SD、SNR、CNR值等客观评价参数的分析采用单因素方差分析,主观评分采用Kruskal-Wallis检验,用Kappa检验分析2名放射科医师主观评分的一致性。结果L组的有效剂量和对比剂剂量分别比S组减少了29.1%(P<0.001)和32.1%(P<0.001),DLIR-H组的SD最低,SNR,CNR最大。四个因素的独立分数和图像最终评分,DLIR-H组图像评分最高(P<0.001)。两名放射科医师对4个CTU的主观图像质量评分亦有很好的一致性(K_(appa)=0.770,P<0.001)。结论在CT尿路造影(CTU)中,DLIR重建的双低技术可显著降低放射剂量(29.1%)对比剂剂量(32.1%)。与60%ASIR-V标准方案相比,DLIR-H可以进一步改善图像质量,是较好的重建算法。
Objective To explore the feasibility of 100 kV deep learning image reconstruction(DLIR)in CT urography(CTU)and compare them with the traditional 120kV adaptive statistical iterative reconstruction-V(ASIR-V)standard scheme.MethodsAccording to the scanning scheme,60 patients with abdominal CTU enhancement scan were divided into standard plan group(group S)and double low plan group(group L).The contrast dose,volume CT dose index and dose length product of group L and group S were recorded,and the effective dose was calculated.Group S was reconstructed with 60%ASIR-V(S-AV60),and group L was reconstructed with 60%ASIR-V(L-AV60),DLIR-M and DLIR-H.The CT values and standard deviation(SD)of right renal pelvis,right renal parenchyma,left renal pelvis,left renal parenchyma,right ureter,left ureter,bladder and psoas major muscle were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.The original axial images,reconstructed volume rendering(VR)images and maximum intensity projection(MIP)images were subjectively scored by two experienced clinicians.t-test was used to compare ED between the two groups.One-way ANOVA was used to analyze the objective evaluation parameters such as CT,SD,SNR and CNR.Kruskal-Wallis test was used to analyze the subjective score of the two radiologists.Kappa test was used to analyze the consistency of subjective scores of the two radiologists.Results Compared with group S,the effective dose and contrast dose of group L decreased by 29.1%(P<0.001)and 32.1%(P<0.001),respectively.The SD of DLIR-H group was the lowest and the SNR,CNR was the largest.The independent score and the final image score of the four factors were the highest in the DLIR-H group(P<0.001).The subjective image quality scores of 4 CTU were also consistent among 2 radiologists(K_(appa)=0.770,P<0.001).ConclusionsIn CT urography(CTU),the double-low technique of DLIR reconstruction can significantly reduce the radiation dose(29.1%)and contrast dose(32.1%).Compared with the 60%ASIR-V standard scheme,DLIR-H can further improve the image quality and is a better reconstruction algorithm.
作者
张悦
张可
郭月飞
郭焯欣
孟占鳌
Zhang Yue;Zhang Ke;Guo Yuefei;Guo Zhuoxin;Meng Zhan'ao(Department of Radiology,the Third Afiliated Hospital,Sun Yat-sen University,Guangzhou510630,China)
出处
《中华腔镜泌尿外科杂志(电子版)》
2022年第6期539-545,共7页
Chinese Journal of Endourology(Electronic Edition)
基金
广州市科技计划项目(202007030007)。
关键词
深度学习
图像重建
CT尿路造影
人工智能
1]Deep learning
Image reconstruction
CT urography
Artificial intelligence(Al)