Kang Deqiang, Hua Haiqin, Peng Nan, Zhao Jing, Wang Zhiqun
Department of Radiology, Dongfang Hospital of Beijing University of Chinese Medicine, Beijing 100078, China.
Department of Radiology, Dongfang Hospital of Beijing University of Chinese Medicine, Beijing 100078, China.
Acad Radiol. 2017 Apr;24(4):462-469. doi: 10.1016/j.acra.2016.11.013. Epub 2016 Dec 9.
We aim to improve the image quality of coronary computed tomography angiography (CCTA) by using personalized weight and height-dependent scan trigger threshold.
This study was divided into two parts. First, we performed and analyzed the 100 scheduled CCTA data, which were acquired by using body mass index-dependent Smart Prep sequence (trigger threshold ranged from 80 Hu to 250 Hu based on body mass index). By identifying the cases of high quality image, a linear regression equation was established to determine the correlation among the Smart Prep threshold, height, and body weight. Furthermore, a quick search table was generated for weight and height-dependent Smart Prep threshold in CCTA scan. Second, to evaluate the effectiveness of the new individual threshold method, an additional 100 consecutive patients were divided into two groups: individualized group (n = 50) with weight and height-dependent threshold and control group (n = 50) with the conventional constant threshold of 150 HU. Image quality was compared between the two groups by measuring the enhancement in coronary artery, aorta, left and right ventricle, and inferior vena cava. By visual inspection, image quality scores were performed to compare between the two groups.
Regression equation between Smart Prep threshold (K, Hu), height (H, cm), and body weight (BW, kg) was K = 0.811 × H + 1.917 × BW - 99.341. When compared to the control group, the individualized group presented an average overall increase of 12.30% in enhancement in left main coronary artery, 12.94% in proximal right coronary artery, and 10.6% in aorta. Correspondingly, the contrast-to-noise ratios increased by 26.03%, 27.08%, and 23.17%, respectively, and by 633.1% in contrast between aorta and left ventricle. Meanwhile, the individualized group showed an average overall decrease of 22.7% in enhancement of right ventricle and 32.7% in inferior vena cava. There was no significant difference of the image noise between the two groups (P > .05). By visual inspection, the image quality score of the individualized group was higher than that of the control group.
Using personalized weight and height-dependent Smart Prep threshold to adjust scan trigger time can significantly improve the image quality of CCTA.
我们旨在通过使用个性化的体重和身高相关扫描触发阈值来提高冠状动脉计算机断层扫描血管造影（CCTA）的图像质量。
本研究分为两部分。首先，我们对100例计划进行的CCTA数据进行了采集和分析，这些数据是使用基于体重指数的智能准备序列（根据体重指数，触发阈值范围为80Hu至250Hu）获得的。通过识别高质量图像的病例，建立线性回归方程以确定智能准备阈值、身高和体重之间的相关性。此外，还生成了一个用于CCTA扫描中体重和身高相关智能准备阈值的快速查找表。其次，为了评估新的个体阈值方法的有效性，将另外100例连续患者分为两组：个体化组（n = 50），采用体重和身高相关阈值；对照组（n = 50），采用传统的150Hu恒定阈值。通过测量冠状动脉、主动脉、左心室和右心室以及下腔静脉的强化程度来比较两组的图像质量。通过视觉检查，对两组的图像质量进行评分比较。
智能准备阈值（K，Hu）、身高（H，cm）和体重（BW，kg）之间的回归方程为K = 0.811×H + 1.917×BW - 99.341。与对照组相比，个体化组左主干冠状动脉强化平均总体增加12.30%，右冠状动脉近端强化增加12.94%，主动脉强化增加10.6%。相应地，对比噪声比分别增加26.03%、27.08%和23.17%，主动脉与左心室之间的对比度增加633.1%。同时，个体化组右心室强化平均总体下降22.7%，下腔静脉强化下降32.7%。两组图像噪声无显著差异（P > 0.05）。通过视觉检查，个体化组的图像质量评分高于对照组。
使用个性化的体重和身高相关智能准备阈值来调整扫描触发时间可显著提高CCTA的图像质量。
