Purpose: Radiofrequency ablation is a well established minimally invasive procedure to treat tumors in solid organs. During the procedure applicators are inserted into the tumor and cells around their tips are destroyed by heat-induced denaturation. Manual trajectory planning requires a trained interventionalist, and its complexity and planning time rise significantly with an increasing number of trajectories.

Methods: We propose a trajectory planning method using a genetic algorithm to accelerate the planning process by automatically generating multiple safe plans. Our method uses a non-discrete search space to find the best entry and target points and does not need any prior calculation of such candidate's points sets. The method offers multiple plans, allowing the interventionalists to choose the most appropriate one. We tested on an open-source and in-house dataset, comparing with related work and retrospectively with the in-house clinical planning.

Results: Our method, tested on 154 liver tumors across all segments using a 10 mm ablation radius, achieves a mean coverage of over 99% of the tumors including a 5 mm safety margin. The method provides safe trajectories for all solutions and is on average 4 $\times$ faster than related approaches.

Conclusion: To the best of our knowledge, we are the first to propose a fast and accurate planning technique using multiple applicators with 10 mm ablation radius. Our algorithm can deliver solutions optimizing more than ten trajectories, approaching the clinical practice at our institution, where large tumors are treated with multiple overlapping ablation zones rather than resection.

Keywords: Continuous search space; Genetic algorithm; Radiofrequency ablation; Trajectory planning.

© 2025. The Author(s).

目的： 射频消融是一种治疗实体器官肿瘤的微创手术。在该过程中，应用器被插入到肿瘤中，并通过热变性破坏其顶端附近的细胞。手动路径规划需要经过训练的操作人员，并且随着轨迹数量的增加，复杂性和规划时间也会显著上升。

方法： 我们提出了一种使用遗传算法进行路径规划的方法，该方法可以通过自动生成多个安全计划来加速规划过程。我们的方法采用非离散搜索空间来寻找最佳的入口和目标点，并且不需要预先计算候选点集。该方法提供了多种方案供操作人员选择最合适的那个。我们在开源数据集和内部数据集上进行了测试，并与相关工作以及我们机构的临床规划进行了比较。

结果： 我们的方法在使用10毫米消融半径的情况下，对所有肝段中的154个肿瘤进行了测试。平均覆盖度达到了超过99%的肿瘤范围（包括5毫米的安全边界）。该方法为所有解决方案提供了安全路径，并且比相关方法快约4倍。

结论： 据我们所知，我们是第一个提出使用多个应用器并具有10毫米消融半径的快速和精确规划技术的人。我们的算法可以优化超过十个轨迹，在处理大肿瘤时接近我们在机构中的临床实践，即通过多个重叠消融区域治疗肿瘤而不是切除。

关键词： 连续搜索空间；遗传算法；射频消融；路径规划。