Joskowicz L, Shamir R, Freiman M, Shoham M, Zehavi E, Umansky F, Shoshan Y
School of Engineering and Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel.
Comput Aided Surg. 2006 Jul;11(4):181-93. doi: 10.3109/10929080600909351.
This paper describes a novel image-guided system for precise automatic targeting in minimally invasive keyhole neurosurgery. The system consists of the MARS miniature robot fitted with a mechanical guide for needle, probe or catheter insertion. Intraoperatively, the robot is directly affixed to a head clamp or to the patient's skull. It automatically positions itself with respect to predefined targets in a preoperative CT/MRI image following an anatomical registration with an intraoperative 3D surface scan of the patient's facial features and registration jig. We present the system architecture, surgical protocol, custom hardware (targeting and registration jig), and software modules (preoperative planning, intraoperative execution, 3D surface scan processing, and three-way registration). We also describe a prototype implementation of the system and in vitro registration experiments. Our results indicate a system-wide target registration error of 1.7 mm (standard deviation = 0.7 mm), which is close to the required 1.0-1.5 mm clinical accuracy in many keyhole neurosurgical procedures.
本文介绍了一种用于微创锁孔神经外科手术中精确自动靶向的新型图像引导系统。该系统由配备用于插入针、探头或导管的机械导向装置的MARS微型机器人组成。术中,机器人直接固定在头夹或患者颅骨上。在通过对患者面部特征和配准夹具进行术中三维表面扫描进行解剖配准后,它会根据术前CT/MRI图像中的预定义目标自动定位自身。我们展示了系统架构、手术方案、定制硬件(靶向和配准夹具)以及软件模块(术前规划、术中执行、三维表面扫描处理和三方配准)。我们还描述了该系统的原型实现和体外配准实验。我们的结果表明,全系统目标配准误差为1.7毫米(标准差 = 0.7毫米),这接近许多锁孔神经外科手术所需的1.0 - 1.5毫米临床精度。