The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.
The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.
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DOI：
10.1088/1742-6596/102/1/012020
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发表时间：
2008-04
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影响因子：
--
通讯作者：
J. Siebers
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文献类型：
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作者：
J. Siebers
蒙特卡罗（MC）很少用于研究中心以外的调强放射治疗计划优化，因为完成该过程需要大量的计算资源或较长的计算时间。可以通过降低优化循环内使用的MC剂量计算的统计精度来减少时间。然而，这最终引入优化收敛误差（OCE）。本研究确定了优化计划OCEs 0.5D（最大值）条件下MC-IMRT优化过程中可容忍的统计噪声水平。在单个3 Ghz处理器上，OC优化的MC剂量计算时间仅为6.2分钟，结果在临床上等同于高精度MC计算。
Monte Carlo (MC) is rarely used for IMRT plan optimization outside of research centres due to the extensive computational resources or long computation times required to complete the process. Time can be reduced by degrading the statistical precision of the MC dose calculation used within the optimization loop. However, this eventually introduces optimization convergence errors (OCEs). This study determines the statistical noise levels tolerated during MC-IMRT optimization under the condition that the optimized plan has OCEs 0.5D(max). The MC dose computation time for the OC-optimization is only 6.2 minutes on a single 3 Ghz processor with results clinically equivalent to high precision MC computations.