Evaluating the effect of higher Monte Carlo statistical uncertainties on accumulated doses after daily adaptive fractionated radiotherapy in prostate cancer

Thyrza Z. Jagt, Tomas M. Janssen, Jan-Jakob Sonke
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Abstract

Background and purpose

Monte Carlo (MC) based dose calculations are widely used in radiotherapy with a low statistical uncertainty, being accurate but slow. Increasing the uncertainty accelerates the calculation, but reduces quality. In online adaptive planning, however, dose is recalculated every treatment fraction, potentially decreasing the cumulative calculation error. This study aimed to evaluate the effect of higher MC statistical uncertainty in the context of daily online plan adaptation.

Materials and methods

For twenty prostate cancer patients, daily plans were simulated for 5 fractions and three modes of variation: rigid whole body translations, local-rigid prostate translations and local-rigid prostate rotations. For each mode and fraction, adaptive plans were generated from a clinical reference plan using three MC uncertainty values: 1 % (standard), 2 % and 3 % per plan. Dose-volume criteria were evaluated for accumulated doses, checking plan acceptability and comparing higher uncertainty plans to the standard.

Results

Increasing the statistical uncertainty setting from 1 % to 2–3 % caused an accumulated median target D98% reduction of 0.1 Gy, with interquartile ranges (IQRs) up to 0.12 Gy. Rectum V35Gy increased in median up to 0.16 cm3 with IQRs up to 0.33 cm3. The bladder V28Gy and V32Gy showed median increases up to 0.24 %-point, with IQRs up to 0.54 %-point. Using 2 % uncertainty reduced calculation times by more than a minute for all modes of variation, with no further time gain when increasing to 3 %.

Conclusion

A 2–3 % MC statistical uncertainty was clinically feasible. Using a 2 % uncertainty setting reduced calculation times at the cost of limited relative dose-volume differences.

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评估前列腺癌每日自适应分次放疗后较高的蒙特卡洛统计不确定性对累积剂量的影响
背景和目的基于蒙特卡洛(MC)的剂量计算广泛应用于放射治疗中,其统计不确定性较低,准确但速度较慢。增加不确定性会加快计算速度,但会降低质量。然而,在在线自适应规划中,每个治疗分量都会重新计算剂量,这有可能减少累积计算误差。本研究旨在评估较高 MC 统计不确定性对每日在线计划适应性的影响。材料和方法对 20 名前列腺癌患者模拟了 5 个分次和三种变化模式的每日计划:刚性全身平移、局部刚性前列腺平移和局部刚性前列腺旋转。对于每种模式和每个分段,自适应计划都是根据临床参考计划生成的,并使用了三种 MC 不确定值:每个计划的不确定性分别为 1%(标准)、2% 和 3%。结果将统计不确定性设置从 1% 提高到 2-3%,目标 D98% 的累积中值减少了 0.1 Gy,四分位数间距 (IQR) 达到 0.12 Gy。直肠 V35Gy 中位数增加到 0.16 cm3,IQRs 增加到 0.33 cm3。膀胱 V28Gy 和 V32Gy 的中位数增加了 0.24 %-点,IQRs 增加了 0.54 %-点。使用 2% 的不确定性可将所有变异模式的计算时间缩短 1 分钟以上,如果增加到 3%,时间将不再增加。使用 2% 的不确定性设置可减少计算时间,但代价是相对剂量-体积差异有限。
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来源期刊
Physics and Imaging in Radiation Oncology
Physics and Imaging in Radiation Oncology Physics and Astronomy-Radiation
CiteScore
5.30
自引率
18.90%
发文量
93
审稿时长
6 weeks
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