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Abstract：
Quality assurance (QA) for clinical trials is important. Lack of compliance can affect trial outcome. Clinical trial QA groups have different methods of dose distribution verification and analysis, all with the ultimate aim of ensuring trial compliance. The aim of this study was to gain a better understanding of different processes to inform future dosimetry audit reciprocity.
Six clinical trial QA groups participated. Intensity modulated treatment plans were generated for three different cases. A range of 17 virtual \'measurements\' were generated by introducing a variety of simulated perturbations (such as MLC position deviations, dose differences, gantry rotation errors, Gaussian noise) to three different treatment plan cases. Participants were blinded to the \'measured\' data details. Each group analysed the datasets using their own gamma index (γ) technique and using standardised parameters for passing criteria, lower dose threshold, γ normalisation and global γ.
For the same virtual \'measured\' datasets, different results were observed using local techniques. For the standardised γ, differences in the percentage of points passing with γ < 1 were also found, however these differences were less pronounced than for each clinical trial QA group\'s analysis. These variations may be due to different software implementations of γ.
This virtual dosimetry audit has been an informative step in understanding differences in the verification of measured dose distributions between different clinical trial QA groups. This work lays the foundations for audit reciprocity between groups, particularly with more clinical trials being open to international recruitment.
Six clinical trial QA groups participated. Intensity modulated treatment plans were generated for three different cases. A range of 17 virtual \'measurements\' were generated by introducing a variety of simulated perturbations (such as MLC position deviations, dose differences, gantry rotation errors, Gaussian noise) to three different treatment plan cases. Participants were blinded to the \'measured\' data details. Each group analysed the datasets using their own gamma index (γ) technique and using standardised parameters for passing criteria, lower dose threshold, γ normalisation and global γ.
For the same virtual \'measured\' datasets, different results were observed using local techniques. For the standardised γ, differences in the percentage of points passing with γ < 1 were also found, however these differences were less pronounced than for each clinical trial QA group\'s analysis. These variations may be due to different software implementations of γ.
This virtual dosimetry audit has been an informative step in understanding differences in the verification of measured dose distributions between different clinical trial QA groups. This work lays the foundations for audit reciprocity between groups, particularly with more clinical trials being open to international recruitment.
摘要：
临床试验的质量保证（QA）非常重要。缺乏依从性会影响试验结果。临床试验QA组有不同的剂量分布验证和分析方法,所有这些都是为了确保审判的合规性。这项研究的目的是更好地了解不同的过程，以告知未来的剂量测定审核互惠。
六个临床试验QA组参与。针对三种不同的情况生成了强度调制的治疗计划。通过引入各种模拟扰动（例如MLC位置偏差，剂量差异，龙门架旋转误差，高斯噪声)对三种不同的治疗方案病例。参与者对“测量的”数据细节视而不见。每个小组使用自己的伽马指数（γ）技术分析数据集，并使用标准化参数作为通过标准，较低的剂量阈值，γ归一化和全局γ。
对于相同的虚拟\'测量\'数据集，使用本地技术观察到不同的结果。对于标准化的γ，还发现了γ<1的通过点百分比的差异，然而,这些差异没有每个临床试验QA组的分析那么明显.这些变化可能是由于γ的不同软件实现。
此虚拟剂量测定审核是了解不同临床试验QA组之间测量剂量分布验证差异的信息步骤。这项工作为小组之间的审计互惠奠定了基础，特别是随着更多的临床试验向国际招聘开放。
六个临床试验QA组参与。针对三种不同的情况生成了强度调制的治疗计划。通过引入各种模拟扰动（例如MLC位置偏差，剂量差异，龙门架旋转误差，高斯噪声)对三种不同的治疗方案病例。参与者对“测量的”数据细节视而不见。每个小组使用自己的伽马指数（γ）技术分析数据集，并使用标准化参数作为通过标准，较低的剂量阈值，γ归一化和全局γ。
对于相同的虚拟\'测量\'数据集，使用本地技术观察到不同的结果。对于标准化的γ，还发现了γ<1的通过点百分比的差异，然而,这些差异没有每个临床试验QA组的分析那么明显.这些变化可能是由于γ的不同软件实现。
此虚拟剂量测定审核是了解不同临床试验QA组之间测量剂量分布验证差异的信息步骤。这项工作为小组之间的审计互惠奠定了基础，特别是随着更多的临床试验向国际招聘开放。
