Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, Washington, DC, USA.
Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
Int J Comput Assist Radiol Surg. 2018 Nov;13(11):1829-1841. doi: 10.1007/s11548-018-1839-y. Epub 2018 Aug 11.
PURPOSE: This paper presents new quantitative data on a signal-to-noise ratio (SNR) study, distortion study, and targeting accuracy phantom study for our patient-mounted robot (called Arthrobot). Arthrobot was developed as an MRI-guided needle placement device for diagnostic and interventional procedures such as arthrography. METHODS: We present the robot design and inverse kinematics. Quantitative assessment results for SNR and distortion study are also reported. A respiratory motion study was conducted to evaluate the shoulder mounting method. A phantom study was conducted to investigate end-to-end targeting accuracy. Combined error considering targeting accuracy, respiratory motion, and structure deformation is also reported. RESULTS: The SNR study showed that the SNR changes only 2% when the unpowered robot was placed on top of a standard water phantom. The distortion study showed that the maximum distortion from the ground truth was 2.57%. The average error associated with respiratory motion was 1.32 mm with standard deviation of 1.38 mm. Results of gel phantom targeting studies indicate average needle placement error of 1.64 mm, with a standard deviation of 0.90 mm. CONCLUSIONS: Noise and distortion of the MR images were not significant, and image quality in the presence of the robot was satisfactory for MRI-guided targeting. Combined average total error, adding mounting stability errors and structure deformation errors to targeting error, is estimated to be 3.4 mm with a standard deviation of 1.65 mm. In clinical practice, needle placement accuracy under 5 mm is considered sufficient for successful joint injection during shoulder arthrography. Therefore, for the intended clinical procedure, these results indicate that Arthrobot has sufficient positioning accuracy.
目的:本文提供了关于我们的患者安装机器人(称为 Arthrobot)的信噪比(SNR)研究、失真研究和靶向准确性体模研究的新定量数据。Arthrobot 是作为一种用于诊断和介入性程序(如关节造影术)的 MRI 引导的针放置设备而开发的。
方法:我们介绍了机器人的设计和运动学反解。还报告了 SNR 和失真研究的定量评估结果。进行了呼吸运动研究以评估肩部安装方法。进行了体模研究以调查端到端靶向准确性。还报告了考虑靶向准确性、呼吸运动和结构变形的综合误差。
结果:SNR 研究表明,当未通电的机器人放置在标准水模顶部时,SNR 仅变化 2%。失真研究表明,与真实值的最大失真为 2.57%。与呼吸运动相关的平均误差为 1.32 毫米,标准差为 1.38 毫米。凝胶体模靶向研究的结果表明,平均针放置误差为 1.64 毫米,标准偏差为 0.90 毫米。
结论:MR 图像的噪声和失真不明显,并且存在机器人时的图像质量对于 MRI 引导的靶向是令人满意的。将安装稳定性误差和结构变形误差与靶向误差相加得到的平均总误差估计为 3.4 毫米,标准差为 1.65 毫米。在临床实践中,在肩部关节造影术中,针放置精度低于 5 毫米被认为足以成功进行关节注射。因此,对于预期的临床程序,这些结果表明 Arthrobot 具有足够的定位精度。
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