深度学习重建算法在低管电压冠状动脉CT血管成像中的应用

The application of deep learning algorithm reconstruction in low tube voltage coronary CT angiography

目的:比较深度学习重建算法(deep learning-based image reconstruction,DLIR)、自适应统计迭代重建算法(adaptive statistical iterative reconstruction-veo,ASiR-V)和滤波反投影重建算法(filtered back-projection,FBP)对低管电压冠状动脉CT血管成像(coronary computed tomographic angiography,CCTA)图像质量的优化效果。方法:前瞻性纳入100例行CCTA扫描的患者,根据其身体质量指数(body mass index,BMI),选择使用70 kVp(50例,BMI≤26 kg/m~2)或80 kVp(50例,BMI>26 kg/m~2)管电压扫描,每例患者的图像分别用FBP(A组)、ASiR-V 50%(B组)、中级DLIR(DLIR-Medium,DLIR-M,C组)和高级DLIR(DLIR-High,DLIR-H,D组)进行重建,比较4组重建算法图像的CT值、噪声、信噪比(signal-to-noise ratio,SNR)和对比噪声比(contrast-noise ratio,CNR),并采用李克特5级评分法对图像质量进行主观评价。结果:在客观图像质量评价中,A、B、C、D 4组两两组间比较,图像噪声、SNR、CNR差异均有统计学意义(P<0.05),其中D组的图像噪声最低,而SNR和CNR最高;在主观图像质量评价中,C组与D组间差异无统计学意义,但均明显高于A组及B组(P<0.05)。结论:在低管电压CCTA扫描中,使用DLIR重建的图像质量优于ASiR-V 50%和FBP,提示DLIR适用于临床低管电压CCTA扫描。

Objective:To compare the quality of low tube voltage coronary CT angiography(CCTA) images reconstructed with deep learning-based image reconstruction(DLIR) and with filter back projection(FBP) and with adaptive statistical iterative reconstruction-veo(ASiR-V).Methods:One hundred patients who underwent CCTA were included.The CCTA tube voltage were set as 70 kVp(n=50,BMI≤26 kg/m~2) and 80 kVp(n=50,BMI>26 kg/m~2) according to body mass index(BMI).The images were reconstructed with FBP(Group A),ASIR-V 50%(Group B),DLIR at medium(DLIR-M,Group C) and high DLIR(DLIR-H,Group D) levels,respectively.Objective evaluation indice including CT attenuation,noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR) were measured or calculated between groups,and Likert5-point scale was adopted for subjective image quality assessment.Results:There were significant differences in image noise,SNR,CNR among the 4 groups(P<0.05),and Group D had the highest SNR and CNR,and lowest noise.There was no significant difference between Group C and Group D in subjective scores,but Group C and D both had higher subjec-tive scores than those of Group A and B(P<0.05).Conclusions:For low tube voltage CCTA,images reconstructed with DLIR generate higher quality,and DLIR may be suitable to apply in low tube voltage CCTA.