Qu Tingting, Guo Yinxia, Li Jianying, Cao Le, Li Yanan, Chen Lihong, Sun Jingtao, Lu Xueni, Guo Jianxin
Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P.R. China.
CT Research Center, GE Healthcare China, Beijing, China.
Br J Radiol. 2022 Dec 1;95(1140):20220196. doi: 10.1259/bjr.20220196. Epub 2022 Nov 15.
To compare image quality and diagnostic accuracy of arterial stenosis in low-dose lower-extremity CT angiography (CTA) between adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) algorithms.
46 patients undergoing low-dose lower-extremity CTA were enrolled. Images were reconstructed using ASIR-V (blending factor of 50% (AV-50) and 100% (AV-100)) and DLIR (medium (DL-M), and high (DL-H)). CT values and standard deviation of the aorta, psoas, popliteal artery, popliteal and ankle muscles were measured. The edge-rise distance and edge-rise slope were calculated. The degrees of granularity and edge blurring were assessed using a 5-point scale. The stenosis degrees were measured on the four reconstructions, and their mean square errors against that of digital subtraction angiography were calculated and compared.
For both ASIR-V and DLIR, higher reconstruction intensity generated lower noise and higher signal-to-noise ratio and contrast-to-noise ratio values. The standard deviation values in AV-100 images were significantly lower than other reconstructions. The two DLIR image groups had higher edge-rise slope and lower edge-rise distance (DL-M:1.79 ± 0.37 mm and DL-H:1.82 ± 0.38 mm AV-50:1.96 ± 0.39 mm and AV-100:2.01 ± 0.36 mm, = 0.014) than ASIR-V images. The overall image quality of DLIR was rated higher than ASIR-V (DL-M:0.83 ± 0.61, DL-H:0.41 ± 0.62, AV-50:1.85 ± 0.60 and AV-100:2.37 ± 0.77, < 0.001), with DL-H having the highest overall image quality score. For stenosis measurement, DL-H had the lowest mean-square-errors compared to digital subtraction angiography among all reconstruction groups.
DLIR images had higher image quality ratings with lower image noise and sharper vessel walls in low-dose lower-extremity CTA, and DL-H provides the best overall image quality and highest accuracy in diagnosing artery stenoses.
DLIR provides high-quality images with sharper edges compared to ASIR-V during low-dose CTA of lower extremity arteries, and DLIR (high) provides the best overall image quality and highest accuracy in diagnosing artery stenoses among all reconstruction algorithms (ASIR-V and DLIR). ASIR-V with blending factor of 100% has the strongest noise reduction ability among all reconstruction algorithms (ASIR-V and DLIR); however, it generates the most blurred images.
比较自适应统计迭代重建-V（ASIR-V）和深度学习图像重建（DLIR）算法在低剂量下肢CT血管造影（CTA）中动脉狭窄的图像质量和诊断准确性。
纳入46例行低剂量下肢CTA的患者。图像采用ASIR-V（混合因子50%（AV-50）和100%（AV-100））和DLIR（中等（DL-M）和高（DL-H））重建。测量主动脉、腰大肌、腘动脉、腘肌和踝关节肌肉的CT值及标准差。计算边缘上升距离和边缘上升斜率。采用5分制评估颗粒度和边缘模糊程度。在四种重建图像上测量狭窄程度，并计算其与数字减影血管造影的均方误差并进行比较。
对于ASIR-V和DLIR，较高的重建强度均产生较低的噪声以及较高的信噪比和对比噪声比值。AV-100图像中的标准差显著低于其他重建图像。与ASIR-V图像相比，两个DLIR图像组具有更高的边缘上升斜率和更低的边缘上升距离（DL-M：1.79±0.37mm，DL-H：1.82±0.38mm，AV-50：1.96±0.39mm，AV-100：2.01±0.36mm，P=0.014）。DLIR的整体图像质量评分高于ASIR-V（DL-M：0.83±0.61，DL-H：0.41±0.62，AV-50：1.85±0.60，AV-100：2.37±0.77，P<0.001），其中DL-H的整体图像质量评分最高。对于狭窄测量，在所有重建组中，DL-H与数字减影血管造影相比的均方误差最低。
在低剂量下肢CTA中，DLIR图像具有更高的图像质量评分、更低的图像噪声和更清晰的血管壁，且DL-H在诊断动脉狭窄方面提供了最佳的整体图像质量和最高的准确性。
在下肢动脉低剂量CTA期间，与ASIR-V相比，DLIR提供具有更清晰边缘的高质量图像，并且在所有重建算法（ASIR-V和DLIR）中，DLIR（高）在诊断动脉狭窄方面提供了最佳的整体图像质量和最高的准确性。在所有重建算法（ASIR-V和DLIR）中，混合因子为100%的ASIR-V具有最强的降噪能力；然而，它产生的图像最模糊。
