首页> 外文期刊>Medical dosimetry: official journal of the American Association of Medical Dosimetrists >Optimal matching of 3D film-measured and planned doses for intensity-modulated radiation therapy quality assurance.
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Optimal matching of 3D film-measured and planned doses for intensity-modulated radiation therapy quality assurance.

机译:3D胶片测量和计划剂量的最佳匹配,以确保强度调制的放射治疗质量。

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摘要

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. Ourresults 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.
机译:调强放射疗法(IMRT)是放射疗法最复杂的应用之一,需要患者特定的质量保证(QA)。在这里,我们描述了一种3维(3D)剂量验证的新方法,该方法在扩展剂量率(EDR2)膜的3D幻像(30 x 30 x 12 cm(3))中使用12块丙烯酸板。常规使用的方法,并在临床上有用。使用以Microsoft Excel Visual Basic应用程序编写的自定义编写的软件模块,通过匹配其原点来叠加轴向,冠状和矢状面的测量和计划剂量分布,并比较所有匹配位置的点剂量。然后,使用优化算法来纠正检测到的设置错误。结果表明,相对于未经优化的剂量差异,该优化方法可将平均最大剂量差异显着降低7.73%,并且显示剂量差异大于5%的点数可达到8.82%。我们的结果表明,通过优化可以明显减少剂量差异,并且该优化方法在统计学上是可靠且有效的。根据从统计分析获得的各种特定于患者的QA数据,讨论了3D优化的结果。

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