DeCunha J M, Missiaggia M, Newpower M, Traneus E, La Tessa C, Mohan R
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, USA.
Medical Physics Program, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, USA.
Med Phys. 2025 May;52(5):3471-3480. doi: 10.1002/mp.17561. Epub 2025 Jan 14.
In locations where the proton energy spectrum is broad, lineal energy spectrum-based proton biological effects models may be more accurate than dose-averaged linear energy transfer (LET) based models. However, the development of microdosimetric spectrum-based biological effects models is hampered by the extreme computational difficulty of calculating microdosimetric spectra. Given a precomputed library of lineal energy spectra for monoenergetic protons, a weighted summation can be performed which yields the lineal energy spectrum of an arbitrary polyenergetic beam. Using this approach, lineal energy spectra can be rapidly calculated on a voxel-by-voxel level.
Monoenergetic proton tracks generated using Geant4-DNA were imported into SuperTrack, a GPU-accelerated software for calculation of microdosimetric spectra. Libraries of proton lineal energy spectra which span the energy range of 0-300 MeV were computed. The libraries were validated by comparison to Monte Carlo calculations in the literature, as well as lineal energy spectra measured experimentally with a tissue equivalent proportional counter.
The lineal energy libraries have been made available in three data formats, two are plain-text, .csv and .les, and one binary encoded, root. Library files include the lineal energy bin abscissa in keV per micron and the unnormalized number of counts occurring within that bin. A computational technique for summation of the library files to yield the lineal energy of a polyenergetic beam is described in this work.
The lineal energy libraries can be used to rapidly determine the lineal energy spectra at the location of cell cultures for in-vitro experiments and in each voxel of a treatment plan for in-vivo outcome modelling. These libraries have already been incorporated into RayStation 2023B-IonPG for lineal energy spectra calculation and we anticipate they will be incorporated into further dose calculation engines and Monte Carlo toolkits.
在质子能谱较宽的区域，基于线能量谱的质子生物效应模型可能比基于剂量平均线能量转移（LET）的模型更准确。然而，基于微剂量谱的生物效应模型的开发受到计算微剂量谱的极端计算难度的阻碍。给定一个预先计算的单能质子线能量谱库，可以进行加权求和，从而得到任意多能束的线能量谱。使用这种方法，可以在逐个体素的水平上快速计算线能量谱。
使用Geant4-DNA生成的单能质子轨迹被导入SuperTrack，这是一款用于计算微剂量谱的GPU加速软件。计算了跨越0 - 300 MeV能量范围的质子线能量谱库。通过与文献中的蒙特卡罗计算以及使用组织等效正比计数器实验测量的线能量谱进行比较，对这些库进行了验证。
线能量库以三种数据格式提供，两种是纯文本格式，即.csv和.les，一种是二进制编码格式，即.root。库文件包括以keV/μm为单位的线能量区间横坐标以及该区间内出现的未归一化计数。本文描述了一种将库文件求和以得到多能束线能量的计算技术。
线能量库可用于快速确定体外实验细胞培养位置处以及体内结果建模治疗计划每个体素中的线能量谱。这些库已经被纳入RayStation 2023B - IonPG用于线能量谱计算，我们预计它们将被纳入更多的剂量计算引擎和蒙特卡罗工具包中。
