Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
Int J Radiat Oncol Biol Phys. 2011 Aug 1;80(5):1559-66. doi: 10.1016/j.ijrobp.2010.10.027. Epub 2010 Dec 14.
To calculate the linear energy transfer (LET) distributions in patients undergoing proton therapy. These distributions can be used to identify areas of elevated or diminished biological effect. The location of such areas might be influenced in intensity-modulated proton therapy (IMPT) optimization.
Because Monte Carlo studies to investigate the LET distribution in patients have not been undertaken so far, the code is first validated with simulations in water. The code was used in five patients, for each of them three planning and delivery techniques were simulated: passive scattering, three-dimensional modulation IMPT (3D-IMPT), and distal edge tracking IMPT (DET-IMPT).
The inclusion of secondary particles led to significant differences compared with analytical techniques. In addition, passive scattering and 3D-IMPT led to largely comparable LET distributions, whereas the DET-IMPT plans resulted in considerably increased LET values in normal tissues and critical structures. In the brainstem, dose-averaged LET values exceeding 5 keV/μm were observed in areas with significant dose (>70% of prescribed dose). In noncritical normal tissues, even values >8 keV/μm occurred.
This work demonstrates that active scanning offers the possibility of influencing the distribution of dose-averaged LET (i.e., the biological effect) without significantly altering the distribution of physical dose. On the basis of this finding, we propose a method to alter deliberately the LET distribution of a treatment plan in such a manner that the LET is maximized within certain target areas and minimized in normal tissues, while maintaining the prescribed target dose and dose constraints for organs at risk.
计算接受质子治疗的患者的线性能量转移(LET)分布。这些分布可用于识别生物效应升高或降低的区域。这些区域的位置可能会受到强度调制质子治疗(IMPT)优化的影响。
由于迄今为止尚未进行过用于研究患者中 LET 分布的蒙特卡罗研究,因此首先在水中进行模拟来验证代码。该代码用于五名患者,对每位患者模拟了三种计划和交付技术:被动散射、三维调制 IMPT(3D-IMPT)和远端边缘跟踪 IMPT(DET-IMPT)。
与分析技术相比,包括二次粒子导致了显著差异。此外,被动散射和 3D-IMPT 导致了大致可比的 LET 分布,而 DET-IMP 计划导致正常组织和关键结构中的 LET 值显著增加。在脑干中,在剂量>70%的规定剂量的区域中观察到剂量平均值超过 5 keV/μm 的 LET 值。在非关键的正常组织中,甚至出现了>8 keV/μm 的值。
这项工作表明,主动扫描提供了在不显著改变物理剂量分布的情况下影响剂量平均 LET(即生物效应)分布的可能性。基于这一发现,我们提出了一种方法来故意改变治疗计划的 LET 分布,以使 LET 在某些目标区域最大化,在正常组织中最小化,同时保持规定的靶剂量和危及器官的剂量限制。