基于轴-组织力模型的可操纵针安全运动规划

Michael Bentley, Caleb Rucker, C. Reddy, Oren Salzman, A. Kuntz
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摘要

可操纵的针头能够精确地瞄准身体中难以到达的临床部位。通过在敏感的解剖结构周围弯曲,可操纵针有可能减少许多医疗程序的侵入性。然而,由于针轴施加在周围组织上的垂直力,插入这些弯曲轨迹的针增加了组织损伤的风险,可能导致组织横向剪切。这种力量会对周围组织造成严重损害,对患者的预后产生负面影响。在这项工作中,我们推导了一个基于Cosserat管柱公式的组织和针刺力模型,该模型描述了沿轴的法向力和摩擦力作为计划针刺路径、摩擦模型和参数以及尖端穿刺力的函数。我们提出这个新的力模型和相关的成本函数,作为一个比目前用于可操纵针运动规划的更安全、更临床相关的度量。我们通过在凝胶模型中进行物理针机器人实验来拟合和验证我们的模型。我们使用该力模型定义了运动规划的瓶颈成本函数,并将其与数百个随机生成的3d环境中常用的路径长度成本函数进行了评估。与在规划中使用路径长度成本相比,使用基于力的成本生成的计划显示,峰值模拟组织力减少62%,平均长度仅增加0.07%。此外,我们展示了在分段计算机断层扫描(CT)的肺肿瘤活检场景中,使用基于力的成本函数来规划运动的能力。通过规划针的运动,旨在明确地将模拟的针对组织的力最小化,我们的方法规划了针的路径,可以降低显著组织损伤的风险,同时仍然达到体内所需的目标。
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Safer Motion Planning of Steerable Needles via a Shaft-to-Tissue Force Model
Steerable needles are capable of accurately targeting difficult-to-reach clinical sites in the body. By bending around sensitive anatomical structures, steerable needles have the potential to reduce the invasiveness of many medical procedures. However, inserting these needles with curved trajectories increases the risk of tissue damage due to perpendicular forces exerted on the surrounding tissue by the needle's shaft, potentially resulting in lateral shearing through tissue. Such forces can cause significant damage to surrounding tissue, negatively affecting patient outcomes. In this work, we derive a tissue and needle force model based on a Cosserat string formulation, which describes the normal forces and frictional forces along the shaft as a function of the planned needle path, friction model and parameters, and tip piercing force. We propose this new force model and associated cost function as a safer and more clinically relevant metric than those currently used in motion planning for steerable needles. We fit and validate our model through physical needle robot experiments in a gel phantom. We use this force model to define a bottleneck cost function for motion planning and evaluate it against the commonly used path-length cost function in hundreds of randomly generated 3-D environments. Plans generated with our force-based cost show a 62% reduction in the peak modeled tissue force with only a 0.07% increase in length on average compared to using the path-length cost in planning. Additionally, we demonstrate the ability to plan motions with our force-based cost function in a lung tumor biopsy scenario from a segmented computed tomography (CT) scan. By planning motions for the needle that aim to minimize the modeled needle-to-tissue force explicitly, our method plans needle paths that may reduce the risk of significant tissue damage while still reaching desired targets in the body.
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