通过轴-组织力模型实现更安全的可控针运动规划
Safer Motion Planning of Steerable Needles via a Shaft-to-Tissue Force Model
摘要：
可控针能够准确定位体内难以到达的临床部位。通过在敏感的解剖结构周围弯曲，可操纵针具有减少许多医疗程序的侵入性的潜力。然而，插入这些具有弯曲轨迹的针增加了组织损伤的风险，这是由于通过针的杆施加在周围组织上的垂直力，可能导致横向剪切穿过组织。这种力会对周围组织造成严重损伤，对患者的治疗效果产生负面影响。在这项工作中，我们推导出一个组织和针力模型的基础上Cosserat字符串制定，它描述了正常的力量和摩擦力沿轴作为一个功能的计划针路径，摩擦模型和参数，和尖端穿刺力。我们提出了这种新的力模型和相关的成本函数，作为比目前用于可控针运动规划的更安全和更临床相关的度量。我们通过凝胶体模中的物理针机器人实验来拟合和验证我们的模型。我们使用这个力模型来定义一个瓶颈成本函数的运动规划和评估它对常用的路径长度成本函数在数百个随机生成的3-D环境。使用我们的基于力的成本生成的计划显示，与使用规划中的路径长度成本相比，峰值建模组织力降低62%，平均长度仅增加0.07%。此外，我们证明了我们的力为基础的成本函数在肺肿瘤活检的情况下，从分段的计算机断层扫描（CT）扫描计划运动的能力。通过规划针的运动，旨在明确地最小化建模的针-组织力，我们的方法规划针路径，可以降低显著组织损伤的风险，同时仍然到达体内的期望目标。
英文摘要：
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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