Padasdao Blayton, Konh Bardia
Department of Mechanical Engineering, University of Hawaii at Manoa, 2540 Dole St., Holmes Hall 302, Honolulu, HI 96822.
J Eng Sci Med Diagn Ther. 2024 Feb 1;7(1):011006. doi: 10.1115/1.4063205. Epub 2023 Sep 26.
The last decade has witnessed major progress in the field of minimally invasive and robotic-assisted surgeries. Needle insertion, a minimally invasive technique, has proven its efficacy in procedures such as brachytherapy, ablation, drug delivery, and biopsy. Manual needle steering inside tissue is a challenging task due to complex needle-tissue interactions, needle and tissue movement, lack of actuation and control, as well as poor sensing and visualization. Recently, active tendon-driven notched needles, and robotic manipulation systems have been proposed to assist surgeons to guide the needles in desired trajectories toward target positions. This work introduces a new deflection model for the active tendon-driven notched needle steering inside soft tissue for intention to use in model-based robotic control. The model is developed to predict needle deflection in a single-layer tissue. To validate the proposed deflection model, five sets of needle insertion experiments with a bevel-tipped active needle into single-layer phantom tissues were performed. A real-time robot-assisted ultrasound tracking method was used to track the needle tip during needle insertion. It was shown that the model predicts needle deflection with an average error of 0.58 ± 0.14 mm for the bevel-tipped active needle insertion into a single-layer phantom tissue.
过去十年见证了微创和机器人辅助手术领域的重大进展。针插入作为一种微创技术，已在近距离放射治疗、消融、药物输送和活检等手术中证明了其有效性。由于针与组织的复杂相互作用、针和组织的移动、缺乏驱动和控制以及传感和可视化效果不佳，在组织内手动操纵针是一项具有挑战性的任务。最近，已提出主动腱驱动的带缺口针和机器人操纵系统，以协助外科医生将针沿所需轨迹导向目标位置。这项工作引入了一种新的挠度模型，用于基于主动腱驱动的带缺口针在软组织内的转向，旨在用于基于模型的机器人控制。该模型用于预测单层组织中的针挠度。为了验证所提出的挠度模型，使用了一个带斜角尖端的主动针在单层虚拟组织中进行了五组针插入实验。在针插入过程中，采用实时机器人辅助超声跟踪方法跟踪针尖。结果表明，对于带斜角尖端的主动针插入单层虚拟组织，该模型预测针挠度的平均误差为0.58±0.14毫米。
