Predicting the Effectiveness of Low-Energy Ions, an Extension of the Local Effect Model

In the field of radiation physics, understanding the impact of low-energy ions with high-linear energy transfer (LET) is crucial for assessing both radiation protection and particle therapy risks. However, predicting their biological effectiveness is challenging, because commonly assumed track-segment conditions, where ions maintain a constant LET and energy, no longer hold at low energies. Additionally, as ion track sizes shrink to the scale of chromatin structures, inhomogeneities within the cell nucleus can be resolved and the assumption of a uniformly sensitive nucleus becomes inadequate. To address these challenges, we present a low-energy adaption (LEA) of the local effect model (LEM IV), which introduces three key modifications: 1. modeling ion deceleration within the cell nucleus by dividing it into discrete slices to account for energy and LET gradients; 2. incorporating a heterogeneous target structure by distinguishing between radiation-sensitive and insensitive chromatin domains; 3. a more accurate prediction of the linear-quadratic parameter by introducing a saturation correction for very high LET. Our results demonstrate that the LEA LEM IV notably improves predictive accuracy at low ion energies. With these adaptions, the LEA successfully reflects the reduced inactivation cross sections observed experimentally, which remain below the geometric cross section of the nucleus. The model shows good agreement with three sets of experimental data, including inactivation cross sections for carbon, argon, and uranium ions, as well as values for alpha particles. While computationally more intensive, the LEA provides a crucial tool for precise modeling in low-energy scenarios.