Division of Medical and Biological Informatics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Med Phys. 2011 Jun;38(6):3246-59. doi: 10.1118/1.3590374.
Computed tomography (CT) guided minimally invasive interventions such as biopsies or ablation therapies often involve insertion of a needle-shaped instrument into the target organ (e.g., the liver). Today, these interventions still require manual planning of a suitable trajectory to the target (e.g., the tumor) based on the slice data provided by the imaging modality. However, taking into account the critical structures and other parameters crucial to the success of the intervention--such as instrument shape and penetration angle--is challenging and requires a lot of experience.
To overcome these problems, we present a system for the automatic or semiautomatic planning of optimal trajectories to a target, based on 3D reconstructions of all relevant structures. The system determines possible insertion zones based on so-called hard constraints and rates the quality of these zones by so-called soft constraints. The concept of pareto optimality is utilized to allow for a weight-independent proposal of insertion trajectories. In order to demonstrate the benefits of our method, automatic trajectory planning was applied retrospectively to n = 10 data sets from interventions in which complications occurred.
The efficient (graphics processing unit-based) implementation of the constraints results in a mean overall planning time of about 9 s. The examined trajectories, originally chosen by the physician, have been rated as follows: in six cases, the insertion point was labeled invalid by the planning system. For two cases, the system would have proposed points with a better rating according to the soft constraints. For the remaining two cases the system would have indicated poor rating with respect to one of the soft constraints. The paths proposed by our system were rated feasible and qualitatively good by experienced interventional radiologists.
The proposed computer-assisted trajectory planning system is able to detect unsafe and propose safe insertion trajectories and may especially be helpful for interventional radiologist at the beginning or during their interventional training.
计算机断层扫描（CT）引导的微创介入，如活检或消融治疗，通常涉及将针状器械插入目标器官（如肝脏）。如今，这些介入仍然需要根据成像方式提供的切片数据手动规划到目标（如肿瘤）的合适轨迹。然而，考虑到对介入成功至关重要的关键结构和其他参数，如器械形状和穿透角度，是具有挑战性的，需要大量经验。
为了克服这些问题，我们提出了一种基于所有相关结构的 3D 重建，自动或半自动规划到目标的最佳轨迹的系统。该系统基于所谓的硬约束确定可能的插入区域，并通过所谓的软约束来评估这些区域的质量。利用 Pareto 最优性的概念，允许独立于权重的插入轨迹建议。为了证明我们方法的优势，回顾性地将自动轨迹规划应用于 n = 10 个发生并发症的介入数据。
高效（基于图形处理单元）的约束实现导致平均整体规划时间约为 9 秒。最初由医生选择的检查轨迹如下：在六种情况下，规划系统将插入点标记为无效。对于两种情况，系统将根据软约束提出评分更高的点。对于其余两种情况，系统将表明一个软约束的评分较差。我们的系统提出的路径被经验丰富的介入放射科医生评为可行和定性良好。
所提出的计算机辅助轨迹规划系统能够检测到不安全和提出安全的插入轨迹，特别是对于介入放射科医生在开始或介入培训期间可能会有帮助。
