Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, St. Thomas’ Hospital, London, SE1 7EH, UK.
IEEE Trans Biomed Eng. 2012 Jan;59(1):122-31. doi: 10.1109/TBME.2011.2168393. Epub 2011 Sep 15.
X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3-D roadmaps derived from preprocedural volumetric data can be used to add anatomical information. However, the registration between the 3-D roadmap and the 2-D X-ray image can be compromised by patient respiratory motion. Three methods were designed and evaluated to correct for respiratory motion using features in the 2-D X-ray images. The first method is based on tracking either the diaphragm or the heart border using the image intensity in a region of interest. The second method detects the tracheal bifurcation using the generalized Hough transform and a 3-D model derived from 3-D preoperative volumetric data. The third method is based on tracking the coronary sinus (CS) catheter. This method uses blob detection to find all possible catheter electrodes in the X-ray image. A cost function is applied to select one CS catheter from all catheter-like objects. All three methods were applied to X-ray images from 18 patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. The 2-D target registration errors (TRE) at the pulmonary veins were calculated to validate the methods. A TRE of 1.6 mm ± 0.8 mm was achieved for the diaphragm tracking; 1.7 mm ± 0.9 mm for heart border tracking, 1.9 mm ± 1.0 mm for trachea tracking, and 1.8 mm ± 0.9 mm for CS catheter tracking. We present a comprehensive comparison between the techniques in terms of robustness, as computed by tracking errors, and accuracy, as computed by TRE using two independent approaches.
X 射线透视引导的心脏电生理程序通常用于诊断和治疗心律失常。X 射线图像软组织对比度差,因此,可以使用来自术前容积数据的静态 3D 路标叠加来添加解剖学信息。然而,3D 路标与 2D X 射线图像之间的配准可能会因患者呼吸运动而受到影响。为了纠正呼吸运动的影响,设计并评估了三种利用 2D X 射线图像中的特征的方法。第一种方法基于使用感兴趣区域中的图像强度跟踪膈肌或心脏边界。第二种方法使用广义霍夫变换和从 3D 术前容积数据得出的 3D 模型检测气管分叉。第三种方法基于跟踪冠状窦(CS)导管。该方法使用斑点检测在 X 射线图像中找到所有可能的导管电极。应用成本函数从所有导管状物体中选择一个 CS 导管。将所有三种方法应用于 18 例接受射频消融治疗心房颤动的患者的 X 射线图像。计算肺静脉处的二维目标配准误差(TRE)以验证这些方法。膈肌跟踪的 TRE 为 1.6mm±0.8mm;心脏边界跟踪的 TRE 为 1.7mm±0.9mm;气管跟踪的 TRE 为 1.9mm±1.0mm;CS 导管跟踪的 TRE 为 1.8mm±0.9mm。我们在鲁棒性(通过跟踪误差计算)和准确性(通过使用两种独立方法计算的 TRE 计算)方面对这些技术进行了全面比较。