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Applying a RapidPlan model trained on a technique and orientation to another: a feasibility and dosimetric evaluation

机译:将经过技术和方向培训的RapidPlan模型应用于另一种方法:可行性和剂量学评估

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Background The development of a dose-volume-histogram (DVH) estimation model for knowledge-based planning is very time-consuming and it could be inefficient if it was only used for similar upcoming cases as supposed. It is clinically desirable to explore and validate other potential applications for a configured model. This study tests the hypothesis that a supine volumetric modulated arc therapy (VMAT) model can optimize intensity modulated radiotherapy (IMRT) plans of other patient setup orientations. Methods Based on RapidPlan, a DVH estimation model was trained using 81 supine VMAT rectal plans and validated on 10 similar cases to ensure the robustness of its designed purpose. Attempts were then made to apply the model to re-optimize the dynamic MLC-sequences of the duplicated IMRT plans from 30 historical patients (20 prone and 10 supine) that were treated with the same prescription as for the model (50.6 and 41.8?Gy to 95?% of PGTV and PTV simultaneously/22 fractions). The performance of knowledge-based re-optimization and the impact of setup orientations were evaluated dosimetrically. Results The VMAT model validation on similar cases showed comparable target dose distribution and significantly improved organ sparing (by 10.77?~?18.65?%) than the original plans. IMRT plans of either setup can be re-optimized using the supine VMAT model, which significantly reduced the dose to the bladder (by 25.88?% from 33.85?±?2.96 to 25.09?±?1.32?Gy for D50 %; by 22.77?% from 33.99?±?2.77 to 26.25?±?1.22?Gy for mean dose) and femoral head (by 12.27?% from 15.65?±?3.33 to 13.73?±?1.43?Gy for D50 %; by 10.09?% from 16.26?±?2.74 to 14.62?±?1.10?Gy for mean dose), all P _PGTV) changed slightly (≤0.01), CI_PTV of IMRT plans was significantly increased (Δ?=?0.17, P 107 % due to the missing of hot spot suppression by specific manual optimizing or fluence map editing. Conclusions The Varian RapidPlan model trained on a technique and orientation can be used for another. Knowledge-based planning improves organ sparing and quality consistency, yet the target-objectives defined for VMAT-optimizer should be readapted to IMRT planning, followed by manual hot spot processing.
机译:背景技术用于基于知识的计划的剂量-体积-直方图(DVH)估计模型的开发非常耗时,并且如果仅按预期将其用于类似的即将发生的情况,则效率可能较低。临床上期望探索和验证配置模型的其他潜在应用。这项研究检验了以下假设:仰卧式容积调制弧光治疗(VMAT)模型可以优化其他患者放置方向的强度调制放射治疗(IMRT)计划。方法基于RapidPlan,使用81个仰卧位VMAT直肠计划训练了DVH估计模型,并在10个类似案例中进行了验证,以确保其设计目的的鲁棒性。然后尝试应用该模型以重新优化来自30名历史患者(20例俯卧位和10例仰卧位)的重复IMRT计划的动态MLC序列,这些患者接受了与该模型相同的处方(50.6和41.8?Gy)同时达到PGTV和PTV的95%/ 22分数)。剂量学评估了基于知识的重新优化的性能以及安装方向的影响。结果在类似病例上的VMAT模型验证显示,目标剂量分布可比,并且与原始计划相比显着改善了器官保留(提高了10.77?〜?18.65?%)。可以使用仰卧VMAT模型重新优化这两种设置的IMRT计划,从而显着减少膀胱的剂量(D <50%时从33.85?±?2.96降低25.88?%至25.09?±?1.32?Gy。 ;平均剂量从33.99?±?2.77降至26.25?±?1.22?Gy 22.77%;股骨头(从15.65?±?3.33降至13.73?±?1.43?Gy 12.27%) D 50%;从16.26?±?2.74到14.62?±?1.10?Gy(平均剂量)增加10.09%,所有P _PGTV )略有变化(≤0.01),CI Varian RapidPlan模型的结果是,IMRT计划的 _PTV 显着增加(Δ?=?0.17,P 107%),这是由于缺少通过特定的手动优化或注量图编辑来抑制热点的结果。经过技术和方向训练的知识可以用于其他方面,基于知识的计划可以改善器官保留和质量一致性,但为VMAT优化器定义的目标应该重新适应IMRT计划,然后进行手动热点处理。

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