放射外科手术是治疗各种颅内肿瘤的成熟方法。与其他成熟的放射外科手术平台不同，新的ZAP-X®允许进行自我屏蔽的陀螺仪放射外科手术。在这里，治疗束具有可变的照射时间，瞄准少量等准中心。现有的计划框架依赖于基于随机选择或手动选择等准中心的启发式方法，这往往会导致临床实践中更高的计划质量。本工作的目的是研究一种改进的放射外科手术治疗计划方法，利用新的ZAP-X®系统自动选择等准中心位置，用于治疗脑肿瘤和头颈区疾病。 我们提出了一种新的方法，自动获取陀螺仪放射外科手术治疗计划中关键的等准中心位置。首先，基于随机选择的非等准候选束集创建最佳治疗计划。然后，在结果的加权束的子集中找到交集以查找等准中心。这种方法与球体填充、随机选择和由专家计划师选择等准中心进行比较。我们回顾性地评估了10个听神经瘤病例的计划质量。 通过聚类方法获得的等准中心对于所有10个测试病例都产生了临床可行的计划。当使用相同数量的等准中心时，相对于随机选择，聚类方法平均提高了31个百分点的覆盖率，比球体填充提高了15个百分点，比专家选择的等准中心提高了2个百分点的覆盖率。自动确定等准中心的数量和位置，导致平均覆盖率为97 ± 3%，符合指数为1.22 ± 0.22，比手动选择的等准中心少2.46 ± 3.60个。在算法性能方面，所有计划都在不到2分钟内计算完成，平均运行时间为75 ± 25 s。 本研究证明了在ZAP-X®系统的治疗计划过程中利用聚类自动选择等准中心的可行性。即使在现有方法无法产生可行计划的复杂病例中，聚类方法生成的计划与专家选择的等准中心产生的计划相当。因此，我们的方法可以帮助降低陀螺仪放射外科手术治疗计划所需的工作量和时间。© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.

Radiosurgery is a well-established treatment for various intracranial tumors. In contrast to other established radiosurgery platforms, the new ZAP-X® allows for self-shielding gyroscopic radiosurgery. Here, treatment beams with variable beam-on times are targeted towards a small number of isocenters. The existing planning framework relies on a heuristic based on random selection or manual selection of isocenters, which often leads to a higher plan quality in clinical practice.The purpose of this work is to study an improved approach for radiosurgery treatment planning, which automatically selects the isocenter locations for the treatment of brain tumors and diseases in the head and neck area using the new system ZAP-X® .We propose a new method to automatically obtain the locations of the isocenters, which are essential in gyroscopic radiosurgery treatment planning. First, an optimal treatment plan is created based on a randomly selected nonisocentric candidate beam set. The intersections of the resulting subset of weighted beams are then clustered to find isocenters. This approach is compared to sphere-packing, random selection, and selection by an expert planner for generating isocenters. We retrospectively evaluate plan quality on 10 acoustic neuroma cases.Isocenters acquired by the method of clustering result in clinically viable plans for all 10 test cases. When using the same number of isocenters, the clustering approach improves coverage on average by 31 percentage points compared to random selection, 15 percentage points compared to sphere packing and 2 percentage points compared to the coverage achieved with the expert selected isocenters. The automatic determination of location and number of isocenters leads, on average, to a coverage of 97 ± 3% with a conformity index of 1.22 ± 0.22, while using 2.46 ± 3.60 fewer isocenters than manually selected. In terms of algorithm performance, all plans were calculated in less than 2 min with an average runtime of 75 ± 25 s.This study demonstrates the feasibility of an automatic isocenter selection by clustering in the treatment planning process with the ZAP-X® system. Even in complex cases where the existing approaches fail to produce feasible plans, the clustering method generates plans that are comparable to those produced by expert selected isocenters. Therefore, our approach can help reduce the effort and time required for treatment planning in gyroscopic radiosurgery.© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.