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用于调强放射治疗质量保证的三维胶片测量剂量与计划剂量的最佳匹配

Optimal matching of 3D film-measured and planned doses for intensity-modulated radiation therapy quality assurance.

作者信息

Shin Dongho, Yoon Myonggeun, Park Sung Yong, Park Dong Hyun, Lee Se Byeong, Kim Dae Yong, Cho Kwan Ho

机构信息

Research Institute and Hospital, National Cancer Center, Ilsandong-gu, Goyang, Republic of Korea.

出版信息

Med Dosim. 2007 Winter;32(4):316-24. doi: 10.1016/j.meddos.2007.08.001. Epub 2007 Sep 11.

Abstract

Intensity-modulated radiation therapy (IMRT) is one of the most complex applications of radiotherapy that requires patient-specific quality assurance (QA). Here, we describe a novel method of 3-dimensional (3D) dose-verification using 12 acrylic slabs in a 3D phantom (30 x 30 x 12 cm(3)) with extended dose rate (EDR2) films, which is both faster than conventionally used methods, and clinically useful. With custom-written software modules written in Microsoft Excel Visual Basic Application, the measured and planned dose distributions for the axial, coronal, and sagittal planes were superimposed by matching their origins, and the point doses were compared at all matched positions. Then, an optimization algorithm was used to correct the detected setup errors. The results show that this optimization method significantly reduces the average maximum dose difference by 7.73% and the number of points showing dose differences of more than 5% by 8.82% relative to the dose differences without an optimization. Our results indicate that the dose difference was significantly decreased with optimization and this optimization method is statistically reliable and effective. The results of 3D optimization are discussed in terms of various patient-specific QA data obtained from statistical analyses.

摘要

调强放射治疗(IMRT)是放射治疗中最复杂的应用之一,需要针对患者进行质量保证(QA)。在此,我们描述了一种在3D体模(30×30×12 cm³)中使用12块丙烯酸板和延长剂量率(EDR2)胶片进行三维(3D)剂量验证的新方法,该方法比传统方法更快,且具有临床实用性。通过用Microsoft Excel Visual Basic Application编写的自定义软件模块,通过匹配原点将轴向、冠状面和矢状面的测量剂量分布与计划剂量分布叠加,并在所有匹配位置比较点剂量。然后,使用优化算法校正检测到的设置误差。结果表明,相对于未进行优化时的剂量差异,该优化方法显著降低了平均最大剂量差异7.73%,并将显示剂量差异超过5%的点数减少了8.82%。我们的结果表明,优化后剂量差异显著降低,且该优化方法在统计学上可靠且有效。根据从统计分析中获得的各种患者特定QA数据讨论了3D优化的结果。

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