2017-06-26 | An approach to treatment plan optimization for VMAT



We study the treatment plan optimization problem for Volumetric Modulated Arc Therapy (VMAT).

We propose a new column generation based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. 

The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on 5 clinical prostate cancer cases demonstrate similar quality with respect to clinical dose-volume criteria. For all cases our algorithm yields treatment plans that can be delivered in around 2 minutes. Implementation on Graphics Processing Unit (GPU) allows for solution times that enable clinical implementation in an adaptive treatment planning setting. 


2017年6月26日(周一)18:30 - 20:00


Edwin Romeijn 于1992年从荷兰鹿特丹大学获得博士学位,曾在鹿特丹管理学院、佛罗里达大学和密歇根大学工业与运营工程系任教,在加入乔治亚理工大学之前曾担任国家科学基金会的服务和制造企业系统和运筹学项目的项目主管。

目前是乔治亚理工大学工业与系统工程学院院长,讲授运筹学、随机过程、应用概率和统计、供应链管理和决策支持系统的课程;研究重点是优化理论和应用, 特别是在供应链优化和优化的医疗保健领域。

Edwin获得过无数奖项,如密歇根大学Richard C. Wilson Faculty Scholar;工业工程研究会议最佳论文奖;ICCR会议Young Investigator’s Award等,与此同时他也是100多位同行评议刊物的作者。