Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
J Appl Clin Med Phys. 2023 Mar;24(3):e13853. doi: 10.1002/acm2.13853. Epub 2022 Nov 21.
The single isocenter for multiple-target (SIMT) technique has become a popular treatment technique for multiple brain metastases. We have implemented a method to obtain a nonuniform margin for SIMT technique. In this study, we further propose a method to determine the isocenter position so that the total expanded margin volume is minimal.
Based on a statistical model, the relationship between nonuniform margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. Due to the existence of rotational error, there is a nonlinear relationship between the margin volume and the isocenter position. Using numerical simulation, we study the relationship between optimal isocenter position and translational error, rotational error, and target size. In order to find the optimal isocenter position quickly, adaptive simulated annealing (ASA) algorithm was used. This method was implemented in the Pinnacle treatment planning system and compared with isocenter at center-of-geometric (COG), center-of-volume (COV), and center-of-surface (COS). Ten patients with multiple brain metastasis targets treated with the SIMT technique was selected for evaluation.
When the size of tumors is equal, the optimal isocenter obtained by ASA and numerical simulation coincides with COG, COV, and COS. When the size of tumors is different, the optimal isocenter is close to the large tumor. The position of COS point is closer to the optimal point than the COV point for nearly all cases. Moreover, in some cases the COS point can be approximately selected as the optimal point. The ASA algorithm can reduce the calculating time from several hours to tens of seconds for three or more tumors. Using multiple brain metastases targets, a series of volume difference and calculating time were obtained for various tumor number, tumor size, and separation distances. Compared with the margin volume with isocenter at COG, the margin volume for optimal point can be reduced by up to 27.7%.
Optimal treatment isocenter selection of multiple targets with large differences could reduce the total margin volume. ASA algorithm can significantly improve the speed of finding the optimal isocenter. This method can be used for clinical isocenter selection and is useful for the protection of normal tissue nearby.
对于多个脑转移瘤,单等中心多靶区(SIMT)技术已成为一种流行的治疗技术。我们已经提出了一种为 SIMT 技术获得非均匀边界的方法。在本研究中,我们进一步提出了一种确定等中心点位置的方法,以使总扩展边界体积最小。
基于统计模型,建立了非均匀边界与距离 d(等中心点与靶区点之间的距离)、摆位不确定度和显著性水平之间的关系。由于存在旋转误差,边界体积与等中心点位置之间存在非线性关系。通过数值模拟,研究了最佳等中心点位置与平移误差、旋转误差和靶区大小之间的关系。为了快速找到最佳等中心点位置,使用了自适应模拟退火(ASA)算法。该方法已在 Pinnacle 治疗计划系统中实现,并与几何中心(COG)、体积中心(COV)和表面中心(COS)进行了比较。选择了 10 例采用 SIMT 技术治疗的多脑转移瘤患者进行评估。
当肿瘤大小相同时,ASA 和数值模拟得到的最佳等中心点与 COG、COV 和 COS 重合。当肿瘤大小不同时,最佳等中心点接近大肿瘤。对于几乎所有病例,COS 点的位置比 COV 点更接近最佳点。此外,在某些情况下,COS 点可近似选为最佳点。对于三个或更多肿瘤,ASA 算法可以将计算时间从数小时缩短到数十秒。使用多个脑转移瘤靶区,对于不同的肿瘤数量、肿瘤大小和分离距离,获得了一系列体积差异和计算时间。与 COG 等中心点的边界体积相比,最佳点的边界体积最多可减少 27.7%。
对于具有较大差异的多个靶区,选择最佳治疗等中心点可减少总边界体积。ASA 算法可以显著提高寻找最佳等中心点的速度。该方法可用于临床等中心点选择,有助于保护附近的正常组织。