Prostate cancer diagnosis continues to encounter challenges, often due to imprecise needle placement in standard biopsies. Several control strategies have been developed to compensate for needle tip prediction inaccuracies, however none were compared against each other, and it is unclear whether any of them can be safely and universally applied in clinical settings. This paper compares the performance of two resolved-rate controllers, derived from a mechanics-based and a data-driven approach, for bevel-tip needle control using needle shape manipulation through a template. We demonstrate for a simulated 12-core biopsy procedure under model parameter uncertainty that the mechanics-based controller can better reach desired targets when only the final goal configuration is presented even with uncertainty on model parameters estimation, and that providing a feasible needle path is crucial in ensuring safe surgical outcomes when either controller is used for needle shape manipulation.

翻译：前列腺癌诊断仍面临挑战，常因标准活检中针尖定位不精确所致。目前已开发多种控制策略来补偿针尖预测误差，但尚无研究对它们进行相互比较，且尚不清楚其中任何一种策略能否安全、通用地应用于临床。本文比较了两种分解速率控制器（分别基于力学模型和数据驱动方法）的性能，用于通过模板操纵针形实现斜尖针控制。我们通过模拟模型参数不确定性下的12芯活检手术证明：当仅给定最终目标构型时，即使模型参数估计存在不确定性，基于力学的控制器能更准确地达到预定靶点；同时，无论使用何种控制器进行针形操控，提供可行的针道路径对于确保手术安全结局至关重要。