Target tracking using DMLC for volumetric modulated arc therapy: a simulation study.
Target tracking using DMLC for volumetric modulated arc therapy: a simulation study.
复制标题
使用 DMLC 进行体积调制电弧治疗的目标跟踪：一项模拟研究。
DOI：
10.1118/1.3511516
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发表时间：
2010
期刊：
影响因子：
3.8
通讯作者：
Li,HHarold
中科院分区：
文献类型：
--
作者：
Sun,Baozhou;Rangaraj,Dharanipathy;Papiez,Lech;Oddiraju,Swetha;Yang,Deshan;Li,HHarold
目的利用动态多叶准直器(DMLC)进行目标跟踪是放射治疗中一种很有前途的片内运动管理方法。该工作的目的是开发一种DMLC跟踪算法，该算法能够将体积调制弧疗(VMAT)传递给在射束视场中经历二维刚性运动的目标。推导了龙门速度、龙门加速度、MLC叶速、剂量率与目标运动之间的关系。提出了一种迭代搜索算法，用于在2D DMLC跟踪的情况下，有效地将特定的VMAT计划交付给运动目标。模拟了五种VMAT肺计划的投放情况。仿真结果表明，二维跟踪算法能够在不违反机器约束和治疗计划完整性的前提下，快速、准确地将VMAT计划传递到运动目标。平均送货时间仅比无跟踪送货时间长29 S，分别为101和72 S。将注量图归一化到200MU，期望注量与提供注量之间的平均均方根误差为2.1MU，而无跟踪和一维跟踪的平均均方根误差分别为14.8MU和3.6MU。结论提出了一种局部最优MLC跟踪算法，在保持治疗计划不变的情况下，以最短的投放时间为目标。DMLC跟踪导致的治疗时间的增加在临床上是可取的，这使得DMLC跟踪的VMAT在治疗移行肿瘤方面具有吸引力。
PurposeTarget tracking using dynamic multileaf collimator (DMLC) is a promising approach for intrafraction motion management in radiation therapy. The purpose of this work is to develop a DMLC tracking algorithm capable of delivering volumetric‐modulated arc therapy (VMAT) to the targets that experience two‐dimensional (2D) rigid motion in the beam's eye view.MethodsThe problem of VMAT delivery to moving targets is formulated as a control problem with constraints. The relationships between gantry speed, gantry acceleration, MLC leaf‐velocity, dose rate, and target motion are derived. An iterative search algorithm is developed to find numerical solutions for efficient delivery of a specific VMAT plan to the moving target using 2D DMLC tracking. The delivery of five VMAT lung plans is simulated. The planned and delivered fluence maps in the target‐reference frame are calculated and compared.ResultsThe simulation demonstrates that the 2D tracking algorithm is capable of delivering the VMAT plan to a moving target fast and accurately without violating the machine constraints and the integrity of the treatment plan. The average delivery time is only 29 s longer than that of no‐tracking delivery, 101 versus 72 s, respectively. The fluence maps are normalized to 200 MU and the average root‐mean‐square error between the desired and the delivered fluence is 2.1 MU, compared to 14.8 MU for no‐tracking and 3.6 MU for one‐dimensional tracking.ConclusionsA locally optimal MLC tracking algorithm for VMAT delivery is proposed, aiming at shortest delivery time while maintaining treatment plan invariant. The inconsequential increase of treatment time due to DMLC tracking is clinically desirable, which makes VMAT with DMLC tracking attractive in treating moving tumors.