Huang Shi-Xiong, Yang Song-Hua, Zeng Biao, Li Xiao-Hua
School of Nuclear Science and Technology, University of South China, Hengyang, 421001, China.
Department of Radiation Oncology, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, 410013, Hunan, People's Republic of China.
Phys Eng Sci Med. 2024 Dec;47(4):1639-1650. doi: 10.1007/s13246-024-01477-y. Epub 2024 Sep 5.
To develop and assess an automated Sub-arc Collimator Angle Optimization (SACAO) algorithm and Cumulative Blocking Index Ratio (CBIR) metrics for single-isocenter coplanar volumetric modulated arc therapy (VMAT) to treat multiple brain metastases. This study included 31 patients with multiple brain metastases, each having 2 to 8 targets. Initially, for each control point, the MLC blocking index was calculated at different collimator angles, resulting in a two-dimensional heatmap. Optimal sub-arc segmentation and collimator angle optimization were achieved using an interval dynamic programming algorithm. Subsequently, VMAT plans were designed using two approaches: SACAO and the conventional Full-Arc Fixed Collimator Angle. CBIR was calculated as the ratio of the cumulative blocking index between the two plan approaches. Finally, dosimetric and planning parameters of both plans were compared. Normal brain tissue, brainstem, and eyes received better protection in the SACAO group (P < 0.05).Query Notable reductions in the SACAO group included 11.47% in gradient index (GI), 15.03% in monitor units (MU), 15.73% in mean control point Jaw area (A), and 19.14% in mean control point Jaw-X width (W), all statistically significant (P < 0.001). Furthermore, CBIR showed a strong negative correlation with the degree of plan improvement. The SACAO method enhanced protection of normal organs while improving transmission efficiency and optimization performance of VMAT. In particular, the CBIR metrics show promise in quantifying the differences specifically in the 'island blocking problem' between SACAO and conventional VMAT, and in guiding the enhanced application of the SACAO algorithm.
开发并评估一种自动子弧准直器角度优化（SACAO）算法和累积阻挡指数比（CBIR）指标，用于单等中心共面容积调强弧形放疗（VMAT）治疗多发脑转移瘤。本研究纳入了31例多发脑转移瘤患者，每位患者有2至8个靶区。最初，对于每个控制点，在不同准直器角度下计算多叶准直器（MLC）阻挡指数，生成二维热图。使用区间动态规划算法实现最佳子弧分割和准直器角度优化。随后，采用两种方法设计VMAT计划：SACAO和传统的全弧固定准直器角度。CBIR计算为两种计划方法之间累积阻挡指数的比值。最后，比较两种计划的剂量学和计划参数。SACAO组中正常脑组织、脑干和眼睛得到了更好的保护（P < 0.05）。SACAO组显著降低的指标包括梯度指数（GI）降低11.47%、监测单位（MU）降低15.03%、平均控制点钳夹面积（A）降低15.73%以及平均控制点钳夹X宽度（W）降低19.14%，所有这些均具有统计学意义（P < 0.001）。此外，CBIR与计划改善程度呈强烈负相关。SACAO方法在增强正常器官保护的同时，提高了VMAT的传输效率和优化性能。特别是，CBIR指标有望量化SACAO与传统VMAT之间在“岛状阻挡问题”方面的差异，并指导SACAO算法的强化应用。
