Department of Radiology & Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-Gu, Seoul, 06351, South Korea.
Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, 02841, South Korea.
Eur Radiol. 2021 Dec;31(12):8937-8946. doi: 10.1007/s00330-021-07942-6. Epub 2021 May 26.
To evaluate whether the advanced spatial noise reduction (ASNR) algorithm installed in a digital radiography system generates acceptable images at a lower dose than a conventional denoising algorithm in pediatric patients.
Nine sets of 30 images of pediatric patients, classified under three protocols and three age groups, were retrospectively selected. Different levels of low-dose image sets of these 270 images were generated by a noise simulation tool after validation testing using phantoms. Each image set was obtained with both the ASNR and conventional algorithm, and grouped randomly and blinded. Three experienced pediatric radiologists were asked to pick the "image with optimum dose" among images of different dose levels with an ALARA (as low as reasonably achievable) perspective. Dose reduction rates for each protocol and age group were calculated, and entrance skin exposure (ESE) was calculated using the values of kVp and mAs, assuming a standard body depth for each age group.
With the ASNR algorithm, estimated dose reduction rates were highest for abdominal radiographs (45.0%, 27.3%, and 24.3% in infants, children, and adolescents, respectively, p < 0.001). The mean dose reductions for all age groups in the abdominal, chest, and skull radiographs were 32.8%, 12.9%, and 23.2%, respectively (p < 0.001). Average of the calculated ESE was lower with the ASNR algorithm than with the conventional algorithm group (p < 0.001).
The ASNR algorithm facilitated optimization of image quality with a higher reduction in radiation dose than the conventional algorithm, making it more acceptable for use in pediatric patients.
•ASNR algorithm in DR system improves image quality via enhanced contrast and noise removal by estimating actual noise distribution based on a multi-scale noise covariance and frequency processing. •Noise simulation tool (NST) generating images of different dose levels can be used for evaluation of the optimum dose without unnecessary additional radiation exposure to pediatric patients. •Retrospective clinical study using NST showed that the ASNR algorithm enabled a higher reduction in radiation dose than the conventional algorithm in pediatric patients.
评估数字射线摄影系统中的高级空间降噪（ASNR）算法是否能在降低剂量的情况下生成可接受的图像，优于传统的降噪算法，尤其在儿科患者中。
回顾性选择了三个协议和三个年龄组的 30 张儿科患者图像。通过使用体模进行验证测试后，使用噪声模拟工具生成了这些 270 张图像的不同低剂量图像集。使用 ASNR 和常规算法分别获得了每个图像集，并随机分组和盲法。三位经验丰富的儿科放射科医生要求从不同剂量水平的图像中，以合理尽量低的原则（ALARA）的角度选择“最佳剂量图像”。计算了每个协议和年龄组的剂量降低率，并使用 kVp 和 mAs 的值计算了入口皮肤暴露（ESE），假设每个年龄组的标准身体深度。
使用 ASNR 算法，腹部射线照片的估计剂量降低率最高（婴儿、儿童和青少年分别为 45.0%、27.3%和 24.3%，p < 0.001）。所有年龄组的腹部、胸部和颅骨射线照片的平均剂量降低率分别为 32.8%、12.9%和 23.2%（p < 0.001）。与常规算法组相比，ASNR 算法的平均 ESE 更低（p < 0.001）。
ASNR 算法通过基于多尺度噪声协方差和频率处理来估计实际噪声分布，从而增强对比度并去除噪声，从而优化图像质量，比常规算法能更显著地降低辐射剂量，因此更适用于儿科患者。
数字射线摄影系统中的 ASNR 算法通过基于多尺度噪声协方差和频率处理来估计实际噪声分布，从而增强对比度并去除噪声，从而改善图像质量。
噪声模拟工具（NST）可生成不同剂量水平的图像，用于评估最佳剂量，而无需对儿科患者进行不必要的额外辐射暴露。
使用 NST 的回顾性临床研究表明，与常规算法相比，ASNR 算法可在儿科患者中实现更高的辐射剂量降低。
