Spinczyk Dominik, Zyłkowski Jaroslaw, Wróblewski Tadeusz
Silesian University of Technology, Katowice, Poland.
Second Department of Clinical Radiology, Medical University of Warsaw, Warsaw, Poland.
Wideochir Inne Tech Maloinwazyjne. 2013 Dec;8(4):265-72. doi: 10.5114/wiitm.2013.39505. Epub 2013 Dec 18.
Image guidance for intervention is applied for complex and difficult anatomical regions. Nowadays, it is typically used in neurosurgery, otolaryngology, orthopedics and dentistry. The application of the image-guided system for soft tissues is challenging due to various deformations caused by respiratory motion, tissue elasticity and peristalsis.
The main task for the presented approach is continuous registration of preoperative computed tomography (CT) and patient position in the operating room (OR) without touching the patient and compensation of breathing motion. This approach is being developed as a step to image-guided percutaneous liver RF tumor ablation.
Up to ten integrated radiological markers are placed on the patient's skin before CT scans. Then the anatomical model based on CT images is calculated. Point-to-point registration based on the Horn algorithm during a few breathing cycles is performed using a videometric tracking system. The transformation which corresponds to the minimum fiducial registration error (FRE) is found during the registration and it is treated as the initial transformation for calculating local deformation field of breathing motion compensation based on the spline approach.
For manual registration of the abdominal phantom, the mean values of target registration error (TRE), fiducial localization error (FLE) and FRE are all below 4 mm for the rigid transformation and are below 1 mm for the affine transformation. For the patient's data they are all below 9 mm and 6 mm, respectively. For the automatic method, different marker configurations have been evaluated while dividing the respiratory cycle into inhale and exhale. Average median values for FRE, TRE rigid estimation and TRE based on spline deformation were 15.56 mm, 0.82 mm and 7.21 mm respectively.
In this application two registration methods of abdominal preoperative CT anatomical model and physical patient position in OR were presented and compared. The presented approach is being developed as a step to image-guided percutaneous liver radiofrequency ablation tumor ablation. Implementation of the automated registration method to clinical practice is easier because of shortening of preparation time in OR, no necessity of touching the patient, and no dependency on the physician's experience.
介入手术的图像引导适用于复杂且解剖结构困难的区域。如今,它通常用于神经外科、耳鼻喉科、骨科和牙科。由于呼吸运动、组织弹性和蠕动引起的各种变形,图像引导系统在软组织中的应用具有挑战性。
本方法的主要任务是在不接触患者的情况下,连续记录术前计算机断层扫描(CT)图像与手术室(OR)中患者的位置,并补偿呼吸运动。此方法正作为图像引导经皮肝射频肿瘤消融的一个步骤进行开发。
在CT扫描前,在患者皮肤上放置多达十个集成放射标记物。然后基于CT图像计算解剖模型。使用视频测量跟踪系统在几个呼吸周期内基于霍恩算法进行点对点配准。在配准过程中找到对应于最小基准配准误差(FRE)的变换,并将其作为基于样条方法计算呼吸运动补偿局部变形场的初始变换。
对于腹部模型的手动配准,刚性变换的目标配准误差(TRE)、基准定位误差(FLE)和FRE的平均值均低于4毫米,仿射变换的平均值均低于1毫米。对于患者数据,它们分别低于9毫米和6毫米。对于自动方法,在将呼吸周期分为吸气和呼气时评估了不同的标记配置。FRE、刚性估计的TRE和基于样条变形的TRE的平均中值分别为15.56毫米、0.82毫米和7.21毫米。
在本应用中,展示并比较了腹部术前CT解剖模型与手术室中患者实际位置的两种配准方法。本方法正作为图像引导经皮肝射频消融肿瘤的一个步骤进行开发。自动配准方法在临床实践中的实施更容易,因为缩短了手术室的准备时间,无需接触患者,且不依赖医生的经验。