Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
Br J Radiol. 2021 Apr 1;94(1120):20201014. doi: 10.1259/bjr.20201014. Epub 2021 Mar 18.
In real-time portal dosimetry, thresholds are set for several measures of difference between predicted and measured images, and signals larger than those thresholds signify an error. The aim of this work is to investigate the use of an additional composite difference metric (CDM) for earlier detection of errors.
Portal images were predicted for the volumetric modulated arc therapy plans of six prostate patients. Errors in monitor units, aperture opening, aperture position and path length were deliberately introduced into all 180 segments of the treatment plans, and these plans were delivered to a water-equivalent phantom. Four different metrics, consisting of central axis signal, mean image value and two image difference measures, were used to identify errors, and a CDM was added, consisting of a weighted power sum of the individual metrics. To optimise the weights of the CDM and to evaluate the resulting timeliness of error detection, a leave-pair-out strategy was used. For each combination of four patients, the weights of the CDM were determined by an exhaustive search, and the result was evaluated on the remaining two patients.
The median segment index at which the errors were identified was 87 (range 40-130) when using all of the individual metrics separately. Using a CDM as well as multiple separate metrics reduced this to 73 (35-95). The median weighting factors of the four metrics constituting the composite were (0.15, 0.10, 0.15, 0.00). Due to selection of suitable threshold levels, there was only one false positive result in the six patients.
This study shows that, in conjunction with appropriate error thresholds, use of a CDM is able to identify increased image differences around 20% earlier than the separate measures.
This study shows the value of combining difference metrics to allow earlier detection of errors during real-time portal dosimetry for volumetric modulated arc therapy treatment.
在实时门户剂量学中，为预测图像和测量图像之间的几个差异度量设置阈值，并且信号大于这些阈值表示存在误差。本研究的目的是调查使用附加的复合差异度量（CDM）来更早地检测误差。
为 6 例前列腺患者的容积调强弧形治疗计划预测了门户图像。在所有 180 个治疗计划段中故意引入了监视器单位、孔径开口、孔径位置和路径长度的误差，并且将这些计划交付到水等效幻影中。使用四个不同的度量标准，包括中心轴信号、平均图像值和两个图像差异度量标准，来识别误差，并添加了一个由个体度量标准的加权幂和组成的 CDM。为了优化 CDM 的权重并评估由此产生的误差检测及时性，使用了留对出策略。对于每个由四名患者组成的组合，通过穷举搜索确定 CDM 的权重，然后在其余两名患者上评估结果。
当单独使用所有四个个体度量标准时，错误被识别的中位数段索引为 87（范围为 40-130）。当使用 CDM 以及多个单独的度量标准时，该值降低到 73（35-95）。构成复合的四个度量标准的加权因子为（0.15、0.10、0.15、0.00）。由于选择了合适的阈值水平，在六名患者中只有一个假阳性结果。
这项研究表明，结合适当的误差阈值，与单独的度量标准相比，CDM 的使用能够更早地识别出约 20%的图像差异增加。
这项研究表明，在容积调强弧形治疗的实时门户剂量学中，结合使用差异度量标准可以更早地检测到误差。
