Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Med Phys. 2019 Jul;46(7):2944-2954. doi: 10.1002/mp.13572. Epub 2019 May 29.
To develop and implement a fully automated approach to intensity modulated radiation therapy (IMRT) treatment planning.
The optimization algorithm is developed based on a hierarchical constrained optimization technique and is referred internally at our institution as expedited constrained hierarchical optimization (ECHO). Beamlet contributions to regions-of-interest are precomputed and captured in the influence matrix. Planning goals are of two classes: hard constraints that are strictly enforced from the first step (e.g., maximum dose to spinal cord), and desirable goals that are sequentially introduced in three constrained optimization problems (better planning target volume (PTV) coverage, lower organ at risk (OAR) doses, and smoother fluence map). After solving the optimization problems using external commercial optimization engines, the optimal fluence map is imported into an FDA-approved treatment planning system (TPS) for leaf sequencing and accurate full dose calculation. The dose-discrepancy between the optimization and TPS dose calculation is then calculated and incorporated into optimization by a novel dose correction loop technique using Lagrange multipliers. The correction loop incorporates the leaf sequencing and scattering effects into optimization to improve the plan quality and reduce the calculation time. The resultant optimal fluence map is again imported into TPS for leaf sequencing and final dose calculation for plan evaluation and delivery. The workflow is automated using application program interface (API) scripting, requiring user interaction solely to prepare the contours and beam arrangement prior to launching the ECHO plug-in from the TPS. For each site, parameters and objective functions are chosen to represent clinical priorities. The first site chosen for clinical implementation was metastatic paraspinal lesions treated with stereotactic body radiotherapy (SBRT). As a first step, 75 ECHO paraspinal plans were generated retrospectively and compared with clinically treated plans generated by planners using VMAT (volumetric modulated arc therapy) with 4 to 6 partial arcs. Subsequently, clinical deployment began in April, 2017.
In retrospective study, ECHO plans were found to be dosimetrically superior with respect to tumor coverage, plan conformity, and OAR sparing. For example, the average PTV D95%, cord and esophagus max doses, and Paddick Conformity Index were improved, respectively, by 1%, 6%, 14%, and 15%, at a negligible 3% cost of the average skin D10cc dose.
Hierarchical constrained optimization is a powerful and flexible tool for automated IMRT treatment planning. The dosimetric correction step accurately accounts for detailed dosimetric multileaf collimator and scattering effects. The system produces high-quality, Pareto optimal plans and avoids the time-consuming trial-and-error planning process.
开发并实现一种完全自动化的调强放射治疗（IMRT）治疗计划方法。
该优化算法基于分层约束优化技术开发，在我们机构内部被称为加速约束层次优化（ECHO）。感兴趣区域的射束贡献预先计算并捕获在影响矩阵中。规划目标分为两类：严格从第一步强制执行的硬约束（例如，脊髓最大剂量），以及通过三个约束优化问题逐步引入的理想目标（更好的计划靶区（PTV）覆盖、更低的器官风险（OAR）剂量和更平滑的通量图）。使用外部商业优化引擎解决优化问题后，最优通量图被导入 FDA 批准的治疗计划系统（TPS）进行叶片排序和精确的全剂量计算。然后使用拉格朗日乘子的新颖剂量校正循环技术计算优化和 TPS 剂量计算之间的剂量差异，并将其纳入优化中。校正循环将叶片排序和散射效应纳入优化中，以提高计划质量并减少计算时间。再次将生成的最优通量图导入 TPS 进行叶片排序和最终剂量计算，以评估和交付计划。使用应用程序编程接口（API）脚本实现工作流程自动化，仅需要用户交互来准备轮廓和光束布置，然后从 TPS 启动 ECHO 插件。对于每个站点，选择参数和目标函数以代表临床优先级。选择用于临床实施的第一个站点是使用立体定向体放射治疗（SBRT）治疗的转移性脊柱旁病变。作为第一步，回顾性生成了 75 个 ECHO 脊柱旁计划，并与使用 VMAT（容积调制弧形治疗）生成的临床治疗计划进行比较，VMAT 有 4 到 6 个部分弧形。随后，临床部署于 2017 年 4 月开始。
在回顾性研究中，ECHO 计划在肿瘤覆盖、计划一致性和 OAR 保护方面表现出更好的剂量学性能。例如，PTV 的 D95%、脊髓和食管最大剂量以及 Paddick 一致性指数分别提高了 1%、6%、14%和 15%，而平均皮肤 D10cc 剂量仅增加了 3%。
分层约束优化是一种用于自动调强放射治疗计划的强大而灵活的工具。剂量学校正步骤准确考虑了详细的多叶准直器和散射效应。该系统生成高质量、Pareto 最优的计划，并避免了耗时的反复试验规划过程。
