Geant4-DNA models for the track-structure simulation of lithium and carbon ions in water: a new approach for ions heavier than helium

When doctors treat cancer with beams of particles, they often use protons or heavier ions like carbon. These particles are powerful tools because they deposit their energy very precisely, destroying tumors while sparing the surrounding healthy tissue. To plan these treatments safely, scientists rely on computer simulations that track how these tiny particles move through the body, which is mostly made of water. For decades, these simulations have worked well for protons and helium ions, but they have struggled with heavier ions like lithium and carbon. The problem is that as these heavier ions slow down, they do not just crash into atoms; they constantly swap electrons with the water molecules they pass, changing their electrical charge in a complex dance. Without a detailed map of these interactions, the simulations cannot accurately predict where the energy goes or how much damage it causes to living cells.

A team of researchers has now filled this gap by creating a new set of rules for the Geant4-DNA software, a powerful open-source program used to simulate radiation at the smallest scales. They developed specific models for lithium and carbon ions that track every time an ion loses or gains an electron as it travels through water. By calculating how these charge changes affect the particle's path and energy loss, the team created a much more realistic picture of what happens when these ions move through biological tissue. Their work allows scientists to simulate the journey of these particles with a level of detail previously reserved only for lighter ions, opening the door to better cancer treatments and more accurate safety assessments for astronauts traveling in space.

The core of this new work lies in understanding how ions interact with water at very low speeds. When a fast-moving ion enters the body, it is usually stripped of its electrons, carrying a strong positive charge. As it slows down, it begins to snatch electrons from the water molecules around it, becoming less charged, and sometimes even losing them again. This constant shifting of charge state is critical because it determines how much energy the ion transfers to the tissue. The researchers realized that existing models were too simple; they treated all heavy ions as if they were a single, average type of particle, ignoring the specific steps of this charge-shifting process. To fix this, the team built a new approach that calculates the probability of an ion capturing or losing an electron at every moment of its journey. They used a method that simulates the paths of the particles and electrons as if they were tiny billiard balls, solving the equations of motion to see exactly how often these interactions happen.

For the processes where the ion simply knocks electrons out of water atoms or excites them without removing them, the team used a scaling method. They took the known behavior of protons and adjusted it based on the speed and charge of the lithium or carbon ion. This allowed them to estimate how much energy the heavier ions would lose without needing to run millions of new, time-consuming calculations for every single scenario. They also included the effects of the ion bouncing off water molecules without losing energy, a process known as elastic scattering, which changes the direction of the particle. By combining these different physical processes, they created a complete toolkit that can follow a lithium or carbon ion from its high-speed entry all the way down to a complete stop.

The researchers tested their new models by comparing the results against existing data from experiments and other theoretical calculations. They looked at how much energy the ions lost per unit of distance, a value known as stopping power, and how far the ions traveled before stopping, known as their range. The simulations showed that the new models agree very well with experimental data at high speeds and at very low speeds. However, in a specific middle range of speeds, between 50 and 500 kiloelectronvolts per atomic mass unit, the new models predicted slightly less energy loss than some older reference data. This middle range is the most difficult to predict because it is exactly where the ions are rapidly changing their charge states. The fact that the new models, which track these charge changes individually, predict lower energy loss than older models that use an average charge suggests that the older models might be overestimating the damage in this specific region.

Despite this difference in the middle speed range, the overall agreement with the most reliable experimental data available is strong. The team also checked how the ions spread out their energy in a circle around their path, a pattern called radial dose distribution. Here, the new models matched the expected patterns almost perfectly, showing that they correctly describe how the energy is deposited in the tissue surrounding the particle's track. This consistency gives scientists confidence that the models are capturing the essential physics of the situation. The researchers noted that while their results are robust, the lack of a large amount of new experimental data for these specific ions means that some uncertainty remains. They emphasized that more measurements are needed to fully confirm the accuracy of the models in that tricky middle speed range.

The impact of this work extends beyond just improving a computer program. By making these detailed models available in Geant4-DNA, the researchers have enabled the simulation of carbon therapy, a growing cancer treatment that uses carbon ions to target tumors. It also supports research into Boron Neutron Capture Therapy, a treatment that relies on the interaction of neutrons with boron atoms inside cells, which can produce lithium and other heavy ions as byproducts. Furthermore, the models are vital for space exploration, where astronauts are exposed to cosmic rays containing heavy ions that can damage DNA. With these new tools, scientists can now simulate the biological effects of these heavy ions with much greater precision, helping to design better radiation shields and treatment plans. The software infrastructure built for lithium and carbon can also be quickly adapted for other ions, such as oxygen and neon, ensuring that the field of radiation physics can continue to evolve and protect human health in both hospitals and the cosmos.