Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Siemens Healthcare GmbH, Forchheim, Germany.
Int J Comput Assist Radiol Surg. 2019 Nov;14(11):1891-1899. doi: 10.1007/s11548-019-02052-7. Epub 2019 Aug 22.
Endovascular repair of aortic aneurysms (EVAR) can be supported by fusing pre- and intraoperative data to allow for improved navigation and to reduce the amount of contrast agent needed during the intervention. However, stiff wires and delivery devices can deform the vasculature severely, which reduces the accuracy of the fusion. Knowledge about the 3D position of the inserted instruments can help to transfer these deformations to the preoperative information.
We propose a method to simultaneously reconstruct the stiff wires in both iliac arteries based on only a single monoplane acquisition, thereby avoiding interference with the clinical workflow. In the available X-ray projection, the 2D course of the wire is extracted. Then, a virtual second view of each wire orthogonal to the real projection is estimated using the preoperative vessel anatomy from a computed tomography angiography as prior information. Based on the real and virtual 2D wire courses, the wires can then be reconstructed in 3D using epipolar geometry.
We achieve a mean modified Hausdorff distance of 4.2 mm between the estimated 3D position and the true wire course for the contralateral side and 4.5 mm for the ipsilateral side.
The accuracy and speed of the proposed method allow for use in an intraoperative setting of deformation correction for EVAR.
血管内修复主动脉瘤（EVAR）可以通过融合术前和术中数据来支持，以允许更好的导航，并减少介入过程中所需的造影剂的量。然而，刚性的导丝和输送装置会严重变形血管，从而降低融合的准确性。对插入器械的 3D 位置的了解有助于将这些变形转移到术前信息中。
我们提出了一种基于单平面采集同时重建双侧髂内动脉中的刚性导丝的方法，从而避免了对临床工作流程的干扰。在现有的 X 射线投影中，提取导丝的 2D 轨迹。然后，使用来自计算机断层血管造影术的术前血管解剖结构作为先验信息，估计每个导丝相对于真实投影的虚拟第二视图。基于真实和虚拟的 2D 导丝轨迹，可以使用极线几何来重建 3D 导丝。
我们在对侧和同侧分别实现了估计的 3D 位置与真实导丝轨迹之间的平均改进 Hausdorff 距离分别为 4.2mm 和 4.5mm。
该方法的准确性和速度允许在 EVAR 的变形校正术中环境中使用。
