This study proposes that incorporating marker-based visibility constraints into the optimization of volumetric modulated arc therapy (VMAT) will generate treatment plans which not only ensure a higher chance of successfully applying real-time tumor tracking techniques, but also simultaneously satisfy dosimetric objectives. This was applied clinically and investigated for multiple disease sites (10 prostate, 5 liver, and 5 lung) using a radiotherapy optimization software (MonArc), where these new constraints were added to conventional dosimetric constraints. For all the investigated sites, three fiducial markers were located inside or around the planning target volume (PTV), and VMAT plans were created for each patient. We modified MonArc to analyze the multi-leaf collimator (MLC) beam’s-eye-view at all control points in the gantry arc, while including marker-based visibility constraints of type ‘hard’ (i.e. requiring 100% visibility of all markers, HC) and ‘soft’ (i.e. penalizes visibility for one marker [SC_I] or two markers [SC_II] only) in the optimization process. Dose distributions resulting from the constrained plans (HC, SC_I, and SC_II) were compared to the non-constrained plan (NC—plans optimized without visibility constraints) using several quantitative dose metrics including the conformity index, homogeneity index, doses to PTV and to organs-at-risk (OAR). Generally, the NC plan produced the best PTV dose conformity and the least OAR doses for the entire patient datasets, followed by the SC and then HC plans, with all the optimization approaches typically achieving acceptable dose metrics. Across the three disease sites, visibility of all three markers in MLC apertures increased from 32% to 100% of available control points as visibility constraints strengthened. Although dose metrics showed some deterioration for constrained plans (−6% for SC_I up to −15% for HC using the PTV average index), the required dosimetric objectives were still satisfied in at least 90% of patients. In conclusion, we demonstrated that marker and tumour visibility constraints can be incorporated with dosimetric objectives to produce treatment plans satisfying both objectives, which should ensure greater success when applying real-time tracking for VMAT delivery.

本研究提出，将基于标记的可见性约束纳入容积调制弧治疗 (VMAT) 的优化中，将生成治疗计划，不仅确保成功应用实时肿瘤跟踪技术的机会更高，而且同时满足剂量学目标。这在临床上应用并使用放射治疗优化软件 ( MonArc ) 对多个疾病部位（10 个前列腺、5 个肝脏和 5 个肺）进行了研究，其中这些新的约束被添加到传统的剂量学约束中。对于所有调查的站点，三个基准标记位于计划目标体积 (PTV) 内部或周围，并为每位患者创建了 VMAT 计划。我们修改了 MonArc分析机架弧中所有控制点的多叶准直器 (MLC) 光束的视野，同时包括“硬”类型的基于标记的可见性约束（即要求所有标记 100% 可见性，HC）和“ soft'（即仅惩罚一个标记 [SC _I ] 或两个标记 [SC _II ] 的可见性）在优化过程中。受限计划（HC、SC _I和 SC _{II ）产生的剂量分布}) 与无约束计划（NC - 无可见性限制的优化计划）进行了比较，使用了几种定量剂量指标，包括一致性指数、同质性指数、PTV 和风险器官 (OAR) 的剂量。一般来说，NC 计划为整个患者数据集产生了最好的 PTV 剂量一致性和最少的 OAR 剂量，其次是 SC，然后是 HC 计划，所有优化方法通常都能达到可接受的剂量指标。在三个疾病部位，随着可见性限制的加强，MLC 孔径中所有三个标记的可见性从可用控制点的 32% 增加到 100%。尽管剂量指标显示受限计划的一些恶化（SC _{I为 -6%}HC 使用 PTV 平均指数高达 -15%），至少 90% 的患者仍满足所需的剂量测定目标。总之，我们证明了标记物和肿瘤可见性约束可以与剂量学目标相结合，以制定满足这两个目标的治疗计划，这将确保在对 VMAT 交付应用实时跟踪时取得更大的成功。