Zhang Hanyin, Lu Wenli, Cui Haixia, Li Ying, Yi Xin
Department of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Oncol. 2022 May 18;12:862635. doi: 10.3389/fonc.2022.862635. eCollection 2022.
In the patient-specific quality assurance (QA), DVH is a critical clinically relevant parameter that is finally used to determine the safety and effectiveness of radiotherapy. However, a consensus on DVH-based action levels has not been reached yet. The aim of this study is to explore reasonable DVH-based action levels and optimal DVH metrics in detecting systematic MLC errors for cervical cancer RapidArc plans.
In this study, a total of 148 cervical cancer RapidArc plans were selected and measured with COMPASS 3D dosimetry system. Firstly, the patient-specific QA results of 110 RapidArc plans were retrospectively reviewed. Then, DVH-based action limits (AL) and tolerance limits (TL) were obtained by statistical process control. Secondly, systematic MLC errors were introduced in 20 RapidArc plans, generating 380 modified plans. Then, the dose difference (%DE) in DVH metrics between modified plans and original plans was extracted from measurement results. After that, the linear regression model was used to investigate the detection limits of DVH-based action levels between %DE and systematic MLC errors. Finally, a total of 180 test plans (including 162 error-introduced plans and 18 original plans) were prepared for validation. The error detection rate of DVH-based action levels was compared in different DVH metrics of 180 test plans.
A linear correlation was found between systematic MLC errors and %DE in all DVH metrics. Based on linear regression model, the systematic MLC errors between -0.94 mm and 0.88 mm could be caught by the TL of PTV ([-1.54%, 1.51%]), and the systematic MLC errors between -1.00 mm and 0.80 mm could also be caught by the TL of PTV ([-2.06%, 0.38%]). In the validation, for original plans, PTV showed the minimum error detection rate of 5.56%. For error-introduced plans with systematic MLC errors more than 1mm, PTV showed the maximum error detection rate of 88.89%, and then was followed by PTV (86.67%). All the TL of DVH metrics showed a poor error detection rate in identifying error-induced plans with systematic MLC errors less than 1mm.
In 3D quality assurance of cervical cancer RapidArc plans, process-based tolerance limits showed greater advantages in distinguishing plans introduced with systematic MLC errors more than 1mm, and reasonable DVH-based action levels can be acquired through statistical process control. During DVH-based verification, main focus should be on the DVH metrics of target volume. OARs in low-dose regions were found to have a relatively higher dose sensitivity to smaller systematic MLC errors, but may be accompanied with higher false error detection rate.
在针对患者的质量保证（QA）中，剂量体积直方图（DVH）是一个关键的临床相关参数，最终用于确定放射治疗的安全性和有效性。然而，基于DVH的行动水平尚未达成共识。本研究的目的是探索基于DVH的合理行动水平以及用于检测宫颈癌容积旋转调强放疗（RapidArc）计划中系统多叶准直器（MLC）误差的最佳DVH指标。
本研究共选取了148个宫颈癌RapidArc计划，并使用COMPASS 3D剂量测定系统进行测量。首先，回顾性分析了110个RapidArc计划的患者特定QA结果。然后，通过统计过程控制获得基于DVH的行动限值（AL）和公差限值（TL）。其次，在20个RapidArc计划中引入系统MLC误差，生成380个修改后的计划。然后，从测量结果中提取修改后计划与原始计划之间DVH指标的剂量差异（%DE）。之后，使用线性回归模型研究%DE与系统MLC误差之间基于DVH的行动水平的检测限。最后，准备了总共180个测试计划（包括162个引入误差的计划和18个原始计划）进行验证。比较了180个测试计划在不同DVH指标下基于DVH的行动水平的误差检测率。
在所有DVH指标中，系统MLC误差与%DE之间存在线性相关性。基于线性回归模型，计划靶体积（PTV）的TL（[-1.54%，1.51%]）可检测到-0.94 mm至0.88 mm之间的系统MLC误差，PTV的TL（[-2.06%，0.38%]）也可检测到-1.00 mm至0.80 mm之间的系统MLC误差。在验证中，对于原始计划，PTV的误差检测率最低，为5.56%。对于系统MLC误差大于1mm的引入误差计划，PTV的误差检测率最高，为88.89%，其次是PTV（86.67%）。所有DVH指标的TL在识别系统MLC误差小于1mm的误差诱导计划时，误差检测率均较低。
在宫颈癌RapidArc计划的三维质量保证中，基于过程的公差限值在区分引入系统MLC误差大于1mm的计划方面具有更大优势，并且可以通过统计过程控制获得基于DVH的合理行动水平。在基于DVH的验证过程中，应主要关注靶区体积的DVH指标。发现低剂量区域的危及器官（OAR）对较小的系统MLC误差具有相对较高的剂量敏感性，但可能伴随着较高的假误差检测率。
