Cash David M, Miga Michael I, Glasgow Sean C, Dawant Benoit M, Clements Logan W, Cao Zhujiang, Galloway Robert L, Chapman William C
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
J Gastrointest Surg. 2007 Jul;11(7):844-59. doi: 10.1007/s11605-007-0090-6.
Image-guided surgery provides navigational assistance to the surgeon by displaying the surgical probe position on a set of preoperative tomograms in real time. In this study, the feasibility of implementing image-guided surgery concepts into liver surgery was examined during eight hepatic resection procedures. Preoperative tomographic image data were acquired and processed. Accompanying intraoperative data on liver shape and position were obtained through optically tracked probes and laser range scanning technology. The preoperative and intraoperative representations of the liver surface were aligned using the iterative closest point surface matching algorithm. Surface registrations resulted in mean residual errors from 2 to 6 mm, with errors of target surface regions being below a stated goal of 1 cm. Issues affecting registration accuracy include liver motion due to respiration, the quality of the intraoperative surface data, and intraoperative organ deformation. Respiratory motion was quantified during the procedures as cyclical, primarily along the cranial-caudal direction. The resulting registrations were more robust and accurate when using laser range scanning to rapidly acquire thousands of points on the liver surface and when capturing unique geometric regions on the liver surface, such as the inferior edge. Finally, finite element models recovered much of the observed intraoperative deformation, further decreasing errors in the registration. Image-guided liver surgery has shown the potential to provide surgeons with important navigation aids that could increase the accuracy of targeting lesions and the number of patients eligible for surgical resection.
图像引导手术通过在一组术前断层图像上实时显示手术探头位置，为外科医生提供导航辅助。在本研究中，在8例肝切除手术过程中检验了将图像引导手术概念应用于肝脏手术的可行性。获取并处理术前断层图像数据。通过光学跟踪探头和激光测距扫描技术获取术中肝脏形状和位置的相关数据。使用迭代最近点表面匹配算法对肝脏表面的术前和术中表示进行对齐。表面配准产生的平均残余误差为2至6毫米，目标表面区域的误差低于规定的1厘米目标。影响配准精度的问题包括呼吸引起的肝脏运动、术中表面数据的质量以及术中器官变形。在手术过程中，呼吸运动被量化为周期性的，主要沿头-尾方向。当使用激光测距扫描快速获取肝脏表面数千个点以及捕获肝脏表面独特的几何区域（如下边缘）时，所得到的配准更加稳健和准确。最后，有限元模型恢复了大部分观察到的术中变形，进一步降低了配准中的误差。图像引导肝脏手术已显示出为外科医生提供重要导航辅助的潜力，这可能会提高病变靶向的准确性以及适合手术切除的患者数量。
