Peng Fei, Jiang Steve B, Romeijn H Edwin, Epelman Marina A
Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Phys Med Biol. 2015 Apr 7;60(7):2955-79. doi: 10.1088/0031-9155/60/7/2955. Epub 2015 Mar 19.
This article considers the treatment plan optimization problem for Volumetric Modulated Arc Therapy (VMAT) with constant gantry speed and dose rate (VMATc). In particular, we consider the simultaneous optimization of multi-leaf collimator leaf positions and a constant gantry speed and dose rate. We propose a heuristic framework for (approximately) solving this optimization problem that is based on hierarchical decomposition. Specifically, an iterative algorithm is used to heuristically optimize dose rate and gantry speed selection, where at every iteration a leaf position optimization subproblem is solved, also heuristically, to find a high-quality plan corresponding to a given dose rate and gantry speed. We apply our framework to clinical patient cases, and compare the resulting VMATc plans to idealized IMRT, as well as full VMAT plans. Our results suggest that VMATc is capable of producing treatment plans of comparable quality to VMAT, albeit at the expense of long computation time and generally higher total monitor units.
本文考虑了具有恒定机架速度和剂量率的容积调强弧形治疗(VMATc)的治疗计划优化问题。具体而言,我们考虑多叶准直器叶片位置与恒定机架速度和剂量率的同步优化。我们提出了一种基于分层分解的启发式框架来(近似)解决此优化问题。具体来说,使用迭代算法启发式地优化剂量率和机架速度选择,在每次迭代中,还通过启发式方法解决叶片位置优化子问题,以找到与给定剂量率和机架速度相对应的高质量计划。我们将我们的框架应用于临床患者病例,并将所得的VMATc计划与理想化的调强放射治疗(IMRT)以及完整的VMAT计划进行比较。我们的结果表明,VMATc能够产生质量与VMAT相当的治疗计划,尽管代价是计算时间长且总监测单位通常更高。