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首页> 外文期刊>Medical Physics >Using flow information to support 3D vessel reconstruction from rotational angiography.
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Using flow information to support 3D vessel reconstruction from rotational angiography.

机译:使用流量信息支持从旋转血管造影术重建3D血管。

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For the assessment of cerebrovascular diseases, it is beneficial to obtain three-dimensional (3D) morphologic and hemodynamic information about the vessel system. Rotational angiography is routinely used to image the 3D vascular geometry and we have shown previously that rotational subtraction angiography has the potential to also give quantitative information about blood flow. Flow information can be determined when the angiographic sequence shows inflow and possibly outflow of contrast agent. However, a standard volume reconstruction assumes that the vessel tree is uniformly filled with contrast agent during the whole acquisition. If this is not the case, the reconstruction exhibits artifacts. Here, we show how flow information can be used to support the reconstruction of the 3D vessel centerline and radii in this case. Our method uses the fast marching algorithm to determine the order in which voxels are analyzed. For every voxel, the rotational time intensity curve (R-TIC) is determined from the image intensities at the projection points of the current voxel. Next, the bolus arrival time of the contrast agent at the voxel is estimated from the R-TIC. Then, a measure of the intensity and duration of the enhancement is determined, from which a speed value is calculated that steers the propagation of the fast marching algorithm. The results of the fast marching algorithm are used to determine the 3D centerline by backtracking. The 3D radius is reconstructed from 2D radius estimates on the projection images. The proposed method was tested on computer simulated rotational angiography sequences with systematically varied x-ray acquisition, blood flow, and contrast agent injection parameters and on datasets from an experimental setup using an anthropomorphic cerebrovascular phantom. For the computer simulation, the mean absolute error of the 3D centerline and 3D radius estimation was 0.42 and 0.25 mm, respectively. For the experimental datasets, the mean absolute error of the 3D centerline was 0.45 mm. Under pulsatile and nonpulsatile conditions, flow information can be used to enable a 3D vessel reconstruction from rotational angiography with inflow and possibly outflow of contrast agent. We found that the most important parameter for the quality of the reconstruction of centerline and radii is the range through which the x-ray system rotates in the time span of the injection. Good results were obtained if this range was at least 135 degrees. As a standard c-arm can rotate 205 degrees, typically one third of the acquisition can show inflow or outflow of contrast agent, which is required for the quantification of blood flow from rotational angiography.
机译:对于评估脑血管疾病,获得有关血管系统的三维(3D)形态和血液动力学信息是有益的。旋转血管造影术通常用于对3D血管几何成像,并且我们先前已经证明了旋转减影血管造影术也有可能提供有关血流的定量信息。当血管造影序列显示造影剂流入或可能流出时,可以确定血流信息。但是,标准体积重建假设在整个采集过程中血管树均匀地充满了造影剂。如果不是这种情况,则重建会显示出伪影。在这里,我们展示了在这种情况下如何使用流量信息来支持3D血管中心线和半径的重建。我们的方法使用快速行进算法来确定分析体素的顺序。对于每个体素,旋转时间强度曲线(R-TIC)由当前体素的投影点处的图像强度确定。接下来,根据R-TIC估算造影剂在体素处的推注到达时间。然后,确定增强的强度和持续时间的度量,从该度量中计算出指导快速行进算法的传播的速度值。快速行进算法的结果用于通过回溯确定3D中心线。根据投影图像上的2D半径估算值重建3D半径。拟议的方法在计算机模拟的旋转血管造影术序列上进行了测试,该序列具有系统地变化的X射线采集,血流和造影剂注射参数,并在使用拟人化脑血管模型的实验设置的数据集中进行了测试。对于计算机模拟,3D中心线和3D半径估计的平均绝对误差分别为0.42和0.25 mm。对于实验数据集,3D中心线的平均绝对误差为0.45 mm。在搏动性和非搏动性条件下,流量信息可用于通过造影剂的流入和可能流出的旋转血管造影术实现3D血管重建。我们发现,对于中心线和半径的重建质量而言,最重要的参数是X射线系统在注射时间内旋转的范围。如果此范围至少为135度,则将获得良好的结果。由于标准C形臂可以旋转205度,因此通常三分之一的采集可以显示造影剂的流入或流出,这是定量来自旋转血管造影术的血流所必需的。

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