深度学习重建算法在提高门静脉CT图像质量中的应用研究

Deep learning reconstruction algorithm in improving portal vein CT image quality

目的探讨深度学习重建算法(DLIR)在提高门静脉图像质量中的应用研究。方法回顾性纳入32例行腹部双期增强检查的患者,门静脉图像分别采用50%自适应统计迭代重建(ASIR V)及深度学习重建算法的中、高模式(DLIR-M、DLIR-H)进行重建。测量门静脉主干、右支、左支和同层椎旁肌肉的CT值和标准差,计算其对比噪声比,测量门静脉主干血管壁CT值边缘上升斜率(ERS)以评价其空间分辨率。主观评价由两名医师采用5分法分别从整体图像噪声、图像对比度、门静脉小分支显示三个方面进行评分,图像伪影则采用4分法进行评价;此外,单独计算门静脉小分支在三种重建算法中的显示率。结果门静脉主干、右支、左支的噪声在DLIR重建算法下显著低于ASIR-V 50%算法,其中DLIR-H噪声最低,CNR最高;门静脉主干的ERS在DLIR算法下也显著高于ASIR-V 50%算法(P<0.01)。主观评价方面,DLIR算法均显著优于ASIR-V 50%算法(P<0.01);此外,DLIR图像门静脉小分支的显示率分别是DLIR-M 93.75%、DLIR-H 100%,高于ASIR-V 50%(68.75%)。结论与ASIR-V 50%算法相比,DLIR算法能显著降低门静脉图像噪声,提高空间分辨率且可以有效提高门静脉小分支的显示率。

Objective To explore the value of deep learning reconstruction algorithm(DLIR)in improving image quality of portal vein.Methods We retrospectively enrolled 32 patients who underwent double-phasic enhanced abdominal CT scanning.Images at the portal venous phase were reconstructed using the 50%adaptive statistical iterative reconstruction(ASIR-V),DLIR at medium(DLIR-M)and high strength(DLIR-H).The CT value and image noise(standard deviation)of the main portal vein,the right portal vein branch,the left portal vein branch,and the paravertebral muscle were measured,and the contrast-noise-ratio(CNR)for vessels were calculated.Moreover,the edge-rising-slope(ERS)of the main portal vein edge was measured to evaluate image spatial resolution.The overall image noise,image contrast,and portal vein branch display were evaluated using a 5-point grading scale and image artifacts using a 4-point grading scare by two experienced radiologists.In addition,we calculated the display rate of small branches of the portal vein in the three reconstruction algorithms.Results Image noise of the DLIR images in the main portal vein,right branch and left branch was significantly lower than that of ASIR-V 50%images,of which the DLIR-H images had the lowest noise and highest CNR.The ERS of the DLIR images in the main portal vein was significantly higher than that of the ASIR-V 50%images.For qualitative analyses,the DLIR images were significantly better than the ASIR-V 50%ones(P<0.01).In addition,the display rates of small branches of the portal vein in DLIR images were(DLIR-M:93.75%;DLIR-H:100%),significantly higher than that of ASIR-V 50%(68.75%).Conclusion Compared with ASIR-V 50%images,DLIR images can significantly reduce the image noise and improve the spatial resolution of the portal vein and the display rate of small branches of the portal vein.