Kuwajima Shiho, Oura Daisuke
Department of Radiology, Otaru General Hospital, Otaru, Hokkaido, Japan.
Department of Biomedical Science and Engineering, Faculty of Health Sciences, Hokkaido University, Sapporo, Hokkaido, Japan.
Phys Eng Sci Med. 2025 Sep 10. doi: 10.1007/s13246-025-01633-y.
In lung CT imaging, motion artifacts caused by cardiac motion and respiration are common. Recently, CLEAR Motion, a deep learning-based reconstruction method that applies motion correction technology, has been developed. This study aims to quantitatively evaluate the clinical usefulness of CLEAR Motion. A total of 129 lung CT was analyzed, and heart rate, height, weight, and BMI of all patients were obtained from medical records. Images with and without CLEAR Motion were reconstructed, and quantitative evaluation was performed using variance of Laplacian (VL) and PSNR. The difference in VL (DVL) between the two reconstruction methods was used to evaluate which part of the lung field (upper, middle, or lower) CLEAR Motion is effective. To evaluate the effect of motion correction based on patient characteristics, the correlation between body mass index (BMI), heart rate and DVL was determined. Visual assessment of motion artifacts was performed using paired comparisons by 9 radiological technologists. With the exception of one case, VL was higher in CLEAR Motion. Almost all the cases (110 cases) showed large DVL in the lower part. BMI showed a positive correlation with DVL (r = 0.55, p < 0.05), while no differences in DVL were observed based on heart rate. The average PSNR was 35.8 ± 0.92 dB. Visual assessments indicated that CLEAR Motion was preferred in most cases, with an average preference score of 0.96 (p < 0.05). Using Clear Motion allows for obtaining images with fewer motion artifacts in lung CT.
在肺部CT成像中，由心脏运动和呼吸引起的运动伪影很常见。最近，基于深度学习的重建方法CLEAR Motion被开发出来，该方法应用了运动校正技术。本研究旨在定量评估CLEAR Motion的临床实用性。共分析了129例肺部CT，并从病历中获取了所有患者的心率、身高、体重和BMI。重建了有无CLEAR Motion的图像，并使用拉普拉斯方差（VL）和PSNR进行定量评估。两种重建方法之间的VL差异（DVL）用于评估CLEAR Motion在肺野的哪一部分（上、中或下）有效。为了评估基于患者特征的运动校正效果，确定了体重指数（BMI）、心率与DVL之间的相关性。由9名放射技师通过配对比较对运动伪影进行视觉评估。除1例病例外，CLEAR Motion中的VL更高。几乎所有病例（110例）在下肺部分均显示出较大的DVL。BMI与DVL呈正相关（r = 0.55，p < 0.05），而基于心率未观察到DVL的差异。平均PSNR为35.8±0.92 dB。视觉评估表明，在大多数情况下，CLEAR Motion更受青睐，平均偏好评分为0.96（p < 0.05）。使用CLEAR Motion可以在肺部CT中获得运动伪影较少的图像。
