theUrology Robotics Laboratory, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA.
IEEE Trans Biomed Eng. 2013 Jun;60(6):1728-34. doi: 10.1109/TBME.2013.2241430. Epub 2013 Jan 21.
Image-to-robot registration is a typical step for robotic image-guided interventions. If the imaging device uses a portable imaging probe that is held by a robot, this registration is constant and has been commonly named probe calibration. The same applies to probes tracked by a position measurement device. We report a calibration method for 2-D ultrasound probes using robotic manipulation and a planar calibration rig. Moreover, a needle guide that is attached to the probe is also calibrated for ultrasound-guided needle targeting. The method is applied to a transrectal ultrasound (TRUS) probe for robot-assisted prostate biopsy. Validation experiments include TRUS-guided needle targeting accuracy tests. This paper outlines the entire process from the calibration to image-guided targeting. Freehand TRUS-guided prostate biopsy is the primary method of diagnosing prostate cancer, with over 1.2 million procedures performed annually in the U.S. alone. However, freehand biopsy is a highly challenging procedure with subjective quality control. As such, biopsy devices are emerging to assist the physician. Here, we present a method that uses robotic TRUS manipulation. A 2-D TRUS probe is supported by a 4-degree-of-freedom robot. The robot performs ultrasound scanning, enabling 3-D reconstructions. Based on the images, the robot orients a needle guide on target for biopsy. The biopsy is acquired manually through the guide. In vitro tests showed that the 3-D images were geometrically accurate, and an image-based needle targeting accuracy was 1.55 mm. These validate the probe calibration presented and the overall robotic system for needle targeting. Targeting accuracy is sufficient for targeting small, clinically significant prostatic cancer lesions, but actual in vivo targeting will include additional error components that will have to be determined.
图像到机器人的配准是机器人图像引导介入的典型步骤。如果成像设备使用由机器人持有的便携式成像探头,则该配准是恒定的,通常被命名为探头校准。同样适用于由位置测量设备跟踪的探头。我们报告了一种使用机器人操作和平面校准架对 2-D 超声探头进行校准的方法。此外,还对附接到探头的针引导器进行校准,以进行超声引导针靶向。该方法应用于用于机器人辅助前列腺活检的经直肠超声(TRUS)探头。验证实验包括 TRUS 引导针靶向准确性测试。本文概述了从校准到图像引导靶向的整个过程。徒手 TRUS 引导前列腺活检是诊断前列腺癌的主要方法,仅在美国每年就有超过 120 万例。但是,徒手活检是一项极具挑战性的手术,具有主观的质量控制。因此,出现了活检设备来协助医生。在这里,我们提出了一种使用机器人 TRUS 操作的方法。一个 2-D TRUS 探头由一个 4 自由度的机器人支撑。机器人执行超声扫描,实现 3-D 重建。根据图像,机器人将针引导器定向到活检目标。活检是通过引导器手动获取的。体外测试表明,3-D 图像具有几何精度,基于图像的针靶向准确性为 1.55 毫米。这验证了所提出的探头校准和用于针靶向的整体机器人系统。靶向准确性足以靶向小的、具有临床意义的前列腺癌病变,但实际的体内靶向将包括必须确定的其他误差分量。