Petersson Kristoffer, Jaccard Maud, Germond Jean-François, Buchillier Thierry, Bochud François, Bourhis Jean, Vozenin Marie-Catherine, Bailat Claude
CHUV, Institut de Radiophysique, Rue du Grand-Pré 1, CH-1007, Lausanne, Switzerland.
CHUV, Service de Radio-Oncologie, Rue du Bugnon 46, CH - 1011, Lausanne, Switzerland.
Med Phys. 2017 Mar;44(3):1157-1167. doi: 10.1002/mp.12111. Epub 2017 Feb 28.
The purpose of this work was to establish an empirical model of the ion recombination in the Advanced Markus ionization chamber for measurements in high dose rate/dose-per-pulse electron beams. In addition, we compared the observed ion recombination to calculations using the standard Boag two-voltage-analysis method, the more general theoretical Boag models, and the semiempirical general equation presented by Burns and McEwen.
Two independent methods were used to investigate the ion recombination: (a) Varying the grid tension of the linear accelerator (linac) gun (controls the linac output) and measuring the relative effect the grid tension has on the chamber response at different source-to-surface distances (SSD). (b) Performing simultaneous dose measurements and comparing the dose-response, in beams with varying dose rate/dose-per-pulse, with the chamber together with dose rate/dose-per-pulse independent Gafchromic™ EBT3 film. Three individual Advanced Markus chambers were used for the measurements with both methods. All measurements were performed in electron beams with varying mean dose rate, dose rate within pulse, and dose-per-pulse (10 ≤ mean dose rate ≤ 10 Gy/s, 10 ≤ mean dose rate within pulse ≤ 10 Gy/s, 10 ≤ dose-per-pulse ≤ 10 Gy), which was achieved by independently varying the linac gun grid tension, and the SSD.
The results demonstrate how the ion collection efficiency of the chamber decreased as the dose-per-pulse increased, and that the ion recombination was dependent on the dose-per-pulse rather than the dose rate, a behavior predicted by Boag theory. The general theoretical Boag models agreed well with the data over the entire investigated dose-per-pulse range, but only for a low polarizing chamber voltage (50 V). However, the two-voltage-analysis method and the Burns & McEwen equation only agreed with the data at low dose-per-pulse values (≤ 10 and ≤ 10 Gy, respectively). An empirical model of the ion recombination in the chamber was found by fitting a logistic function to the data.
The ion collection efficiency of the Advanced Markus ionization chamber decreases for measurements in electron beams with increasingly higher dose-per-pulse. However, this chamber is still functional for dose measurements in beams with dose-per-pulse values up toward and above 10 Gy, if the ion recombination is taken into account. Our results show that existing models give a less-than-accurate description of the observed ion recombination. This motivates the use of the presented empirical model for measurements with the Advanced Markus chamber in high dose-per-pulse electron beams, as it enables accurate absorbed dose measurements (uncertainty estimation: 2.8-4.0%, k = 1). The model depends on the dose-per-pulse in the beam, and it is also influenced by the polarizing chamber voltage, with increasing ion recombination with a lowering of the voltage.
本研究旨在建立一个用于高剂量率/每脉冲剂量电子束测量的高级马库斯电离室中离子复合的经验模型。此外，我们将观察到的离子复合情况与使用标准博阿格双电压分析法、更通用的理论博阿格模型以及伯恩斯和麦克尤恩提出的半经验通用方程进行的计算结果进行了比较。
采用两种独立方法研究离子复合：(a) 改变直线加速器（直线加速器）枪的栅极张力（控制直线加速器输出），并测量栅极张力在不同源皮距（SSD）下对电离室响应的相对影响。(b) 进行同步剂量测量，并将剂量响应与剂量率/每脉冲剂量变化的电子束中电离室以及剂量率/每脉冲剂量独立的Gafchromic™ EBT3 薄膜的剂量响应进行比较。两种方法的测量均使用了三个单独的高级马库斯电离室。所有测量均在平均剂量率、脉冲内剂量率和每脉冲剂量变化的电子束中进行（10 ≤ 平均剂量率 ≤ 10 Gy/s，10 ≤ 脉冲内平均剂量率 ≤ 10 Gy/s，10 ≤ 每脉冲剂量 ≤ 10 Gy），这是通过独立改变直线加速器枪的栅极张力和 SSD 实现的。
结果表明，随着每脉冲剂量增加，电离室的离子收集效率降低，并且离子复合取决于每脉冲剂量而非剂量率，这是博阿格理论所预测的行为。通用的理论博阿格模型在整个研究的每脉冲剂量范围内与数据吻合良好，但仅适用于低极化室电压（50 V）。然而，双电压分析法和伯恩斯与麦克尤恩方程仅在低每脉冲剂量值（分别≤ 10 和 ≤ 10 Gy）时与数据相符。通过对数据拟合逻辑函数，找到了电离室中离子复合的经验模型。
对于在每脉冲剂量越来越高的电子束中进行测量，高级马库斯电离室的离子收集效率会降低。然而，如果考虑离子复合，该电离室在每脉冲剂量值高达及超过 10 Gy 的电子束剂量测量中仍可正常工作。我们的结果表明，现有模型对观察到的离子复合的描述不够准确。这促使在高每脉冲剂量电子束中使用所提出的经验模型进行高级马库斯电离室的测量，因为它能够进行准确的吸收剂量测量（不确定度估计：2.8-4.0%，k = 1）。该模型取决于电子束中的每脉冲剂量，并且还受极化室电压影响，随着电压降低，离子复合增加。
