Pepley David F, Adhikary Sanjib D, Miller Scarlett R, Moore Jason Z
Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, 319 Leonhard Building, University Park, PA 16802.
Department of Anesthesiology and Perioperative Medicine, Penn State Health Milton S. Hershey Medical Center, 500 University Drive, H187, Hershey, PA 17033.
J Comput Nonlinear Dyn. 2019 Oct 1;14(10):101004-1010048. doi: 10.1115/1.4042809. Epub 2019 Sep 9.
Ultrasound guidance is used for a variety of surgical needle insertion procedures, but there is currently no standard for the teaching of ultrasound skills. Recently, computer ultrasound simulation has been introduced as an alternative teaching method to traditional manikin and cadaver training because of its ability to provide diverse scenario training, quantitative feedback, and objective assessment. Current computer ultrasound training simulation is limited in its ability to image tissue deformation caused by needle insertions, even though tissue deformation identification is a critical skill in performing an ultrasound-guided needle insertion. To fill this need for improved simulation, a novel method of simulating ultrasound tissue-needle deformation is proposed and evaluated. First, a cadaver study is conducted to obtain ultrasound video of a peripheral nerve block. Then, optical flow analysis is conducted on this video to characterize the tissue movement due to the needle insertion. Tissue movement is characterized into three zones of motion: tissue near the needle being pulled, and zones above and below the needle where the tissue rolls. The rolling zones were centered 1.34 mm above and below the needle and 4.53 mm behind the needle. Using this characterization, a vector field is generated mimicking these zones. This vector field is then applied to an ultrasound image using inverse mapping to simulate tissue movement. The resulting simulation can be processed at 3.1 frames per second. This methodology can be applied through future optimized graphical processing to allow for accurate real time needle tissue simulation.
超声引导被用于多种手术针插入操作,但目前超声技能教学尚无标准。近来,计算机超声模拟作为一种替代传统人体模型和尸体训练的教学方法被引入,因为它能够提供多样化的场景训练、定量反馈和客观评估。当前的计算机超声训练模拟在成像由针插入引起的组织变形方面能力有限,尽管识别组织变形是进行超声引导针插入的一项关键技能。为满足对改进模拟的这一需求,提出并评估了一种模拟超声组织 - 针变形的新方法。首先,进行尸体研究以获取周围神经阻滞的超声视频。然后,对该视频进行光流分析以表征因针插入导致的组织运动。组织运动被表征为三个运动区域:针附近的组织被拉动,以及针上方和下方组织滚动的区域。滚动区域以针为中心,在针上方和下方1.34毫米处以及针后方4.53毫米处。利用这一表征,生成一个模仿这些区域的矢量场。然后使用逆映射将该矢量场应用于超声图像以模拟组织运动。生成的模拟可以每秒3.1帧的速度进行处理。这种方法可以通过未来优化的图形处理来应用,以实现精确的实时针组织模拟。