Four-dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times.
Four-dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times.
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DOI：
10.1002/mp.15550
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发表时间：
2022-04
期刊：
影响因子：
3.8
通讯作者：
McVeigh ER
中科院分区：
文献类型：
--
作者：
Manohar A;Pack JD;Schluchter AJ;McVeigh ER
我们证明了四维X射线计算机断层扫描（4DCT）成像系统的可行性，以准确和精确地估计左心室（LV）室壁运动的机械激活时间。准确和可重复的LV室壁运动的时间估计可能有利于心脏起搏治疗（CRT）的成功规划和管理。我们根据程控室间隔-侧壁不同步的人体CT图像开发了一种拟人精确的计算机模拟LV体模。使用计算机体模的26个时间相位对1秒心动周期进行采样。对于26个相位中的每一个，提取、3D打印模拟轴向CT图像体积的1cm厚的轴向平板，并使用市售CT扫描仪进行成像。通过混合来自这些静态相位的正弦图来合成连续动态正弦图;合成的正弦图模拟在真实连续体模运动下采集的正弦图。使用合成的动态正弦图，以70 ms的间隔重建图像，跨越整个心动周期;这些图像表现出预期的运动伪影特征，在从真实的动态数据重建的图像中可见。然后用一种新的运动校正算法（ResyncCT）处理运动损坏的图像，以产生运动校正的图像。生成五对运动未校正和运动校正图像，每对对应于不同的起始机架角度（0至180度，增量为45度）。两条垂直于内膜表面的线轮廓分别用于在间隔和侧壁处采样局部心肌运动轨迹。室壁运动的机械激活时间定义为收缩期收缩过程中，当向左心室中心移动时，内膜边界穿过两条线轮廓中任一条上定义的固定位置的时间。然后将根据运动未校正和运动校正图像估计的这些心肌轨迹的机械激活时间与从3D打印体模的静态图像（地面实况）导出的机械激活时间进行比较。从五个不同的起始机架角度模拟中获得定时估计的精度。对于运动未校正图像，在所有起始机架角度上观察到的估计机械激动时间的范围显著大于运动校正图像（侧壁：58±15 ms vs 12±4 ms，p<0.005;间隔壁：61±13 ms vs 13±9 ms，p<0.005）。使用ResyncCT运动校正算法处理的4DCT图像可获得LV室壁运动的机械激动时间估计值，其准确度和精度显著提高。本研究中报告的令人鼓舞的结果突出了4DCT在估计CRT引导的感兴趣机械事件的时间方面的潜在效用。
We demonstrate the viability of a four-dimensional x-ray computed tomography (4DCT) imaging system to accurately and precisely estimate mechanical activation times of left ventricular (LV) wall motion. Accurate and reproducible timing estimates of LV wall motion may be beneficial in the successful planning and management of cardiac resynchronization therapy (CRT). We developed an anthropomorphically accurate in-silico LV phantom based on human CT images with programmed septal-lateral wall dyssynchrony. Twenty-six temporal phases of the in-silico phantom were used to sample the cardiac cycle of 1 second. For each of the 26 phases, 1 cm thick axial slabs emulating axial CT image volumes were extracted, 3D printed, and imaged using a commercially available CT scanner. A continuous dynamic sinogram was synthesized by blending sinograms from these static phases; the synthesized sinogram emulated the sinogram that would be acquired under true continuous phantom motion. Using the synthesized dynamic sinogram, images were reconstructed at 70 ms intervals spanning the full cardiac cycle; these images exhibited expected motion artifact characteristics seen in images reconstructed from real dynamic data. The motion corrupted images were then processed with a novel motion correction algorithm (ResyncCT) to yield motion corrected images. Five pairs of motion uncorrected and motion corrected images were generated, each corresponding to a different starting gantry angle (0 to 180 degrees in 45 degree increments). Two line profiles perpendicular to the endocardial surface were used to sample local myocardial motion trajectories at the septum and the lateral wall, respectively. The mechanical activation time of wall motion was defined as the time at which the endocardial boundary crossed a fixed position defined on either of the two line profiles while moving towards the center of the LV during systolic contraction. The mechanical activation times of these myocardial trajectories estimated from the motion uncorrected and the motion corrected images were then compared with those derived from the static images of the 3D printed phantoms (ground-truth). Precision of the timing estimates was obtained from the five different starting gantry angle simulations. The range of estimated mechanical activation times observed across all starting gantry angles was significantly larger for the motion uncorrected images than the motion corrected images (lateral wall: 58±15 ms vs 12±4 ms, p<0.005; septal wall: 61±13 ms vs 13±9 ms, p<0.005). 4DCT images processed with the ResyncCT motion correction algorithm yield estimates of mechanical activation times of LV wall motion with significantly improved accuracy and precision. The promising results reported in this study highlight the potential utility of 4DCT in estimating the timing of mechanical events of interest for CRT guidance.
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影响因子：
3.8
作者：
Faris, OP;Evans, FJ;McVeigh, ER
通讯作者：
McVeigh, ER
影响因子：
24
作者：
Bader, H;Garrigue, S;Roudaut, R
通讯作者：
Roudaut, R
影响因子：
2.1
作者：
Rybicki, Frank J.;Otero, Hansel J.;Di Carli, Marcelo F.
通讯作者：
Di Carli, Marcelo F.
影响因子：
14
作者：
Truong, Quynh A.;Singh, Jagmeet P.;Hoffmann, Udo
通讯作者：
Hoffmann, Udo
DOI：
10.1016/s0894-7317(99)70050-7
发表时间：
1999-05-01
影响因子：
6.5
作者：
Strotmann, JM;Kvitting, JPE;Sutherland, GR
通讯作者：
Sutherland, GR