Ma YingLiang, King Andy P, Gogin Nicolas, Rinaldi C Aldo, Gill Jaswinder, Razavi Reza, Rhode Kawal S
Division of Imaging Sciences, King's College London, SE1 7EH, UK.
Med Image Comput Comput Assist Interv. 2010;13(Pt 1):391-9. doi: 10.1007/978-3-642-15705-9_48.
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 3D roadmaps derived from pre-procedural volumetric data can be used to add anatomical information. However, the registration between the 3D roadmap and the 2D X-ray data can be compromised by patient respiratory motion. We propose a novel method to correct for respiratory motion using real-time image-based coronary sinus (CS) catheter tracking. The first step of the proposed technique is to use a blob detection method to detect all possible catheter electrodes in the Xray data. We then compute a cost function to select one CS catheter from all catheter-like objects. For correcting respiratory motion, we apply a low pass filter to the 2D motion of the CS catheter and update the 3D roadmap using this filtered motion. We tested our CS catheter tracking method on 1048 fluoroscopy frames from 15 patients and achieved a success rate of 99.3% and an average 2D tracking error of 0.4 mm +/- 0.2 mm. We also validated our respiratory motion correction strategy by computing the 2D target registration error (TRE) at the pulmonary veins and achieved a TRE of 1.6 mm +/- 0.9 mm.
X射线荧光透视引导下的心脏电生理手术通常用于诊断和治疗心律失常。X射线图像的软组织对比度较差，因此，可以使用术前容积数据生成的静态三维路线图叠加来添加解剖学信息。然而，三维路线图与二维X射线数据之间的配准可能会因患者呼吸运动而受到影响。我们提出了一种使用基于实时图像的冠状窦（CS）导管跟踪来校正呼吸运动的新方法。所提出技术的第一步是使用斑点检测方法在X射线数据中检测所有可能的导管电极。然后，我们计算一个成本函数，从所有类似导管的物体中选择一根CS导管。为了校正呼吸运动，我们对CS导管的二维运动应用低通滤波器，并使用该滤波后的运动更新三维路线图。我们在15名患者的1048帧荧光透视图像上测试了我们的CS导管跟踪方法，成功率达到99.3%，二维跟踪平均误差为0.4毫米±0.2毫米。我们还通过计算肺静脉处的二维目标配准误差（TRE）验证了我们的呼吸运动校正策略，TRE为1.6毫米±0.9毫米。
