In the world of cancer treatment, proton therapy has emerged as a beacon of hope, offering a precise and targeted approach to combating tumors while minimizing damage to surrounding healthy tissues. However, beneath this promising facade lies a hidden challenge: the generation of secondary neutrons during proton irradiation. These neutrons, born from the interaction of the therapeutic beam with the patient's body, pose a potential risk of contributing to secondary cancer risks. This is where a groundbreaking study, led by a team at Clínica Universidad de Navarra in Spain, steps in to shed light on this critical issue and offer a practical solution. The research, published in Physics in Medicine & Biology, introduces a Python-based calculation tool that estimates out-of-field neutron dose during proton therapy, a feat that has never been achieved before. This tool, developed by medical physicist Verónica Morán and her colleagues, is a game-changer in the field of radiation protection and workplace dose assessments.
The study, conducted using a Hitachi PROBEAT-CR proton therapy system with pencil-beam scanning, employed a diverse array of detectors to measure neutron dose. These included ambient detectors and four types of personal dosimeters: thermoluminescent dosimeters (TLDs), track-etch detectors, bubble detectors (BDs), and electronic personal dosimeters (EPDs). By examining the dependence of out-of-field neutron dose on various beam and room parameters, the team gained valuable insights into the behavior of these neutrons. The ambient detectors proved to be the most reliable, functioning as expected in a synchrotron-based facility, while the personal dosimeters exhibited variations in response.
One of the key findings of the study was the symmetry of the treatment room. The team discovered that the room was largely symmetric for certain gantry orientations, which significantly reduces the number of measurements needed and extends the applicability of the dose calculation model. This symmetry is a crucial factor in ensuring accurate dose estimates, as it allows for the prediction of neutron doses on one side of the room to be used as a basis for doses on the opposite side.
The study also revealed that neutron doses created by a single spot field and a 10x10 cm field were similar, while larger fields of 20x20 cm and 30x30 cm exhibited differences of up to 22% relative to the single spot. The dependence of neutron dose on proton energy followed the expected power law, with the ambient detectors providing the best fits, followed by the BDs and TLDs. This understanding of the relationship between proton energy and neutron dose is crucial for accurate dose calculations.
Furthermore, the researchers delivered a clinical proton treatment to a scattering phantom, comprising 27 energy layers, and examined the linear superposition approach to estimating total neutron dose. This approach, which assumes that the total neutron dose can be expressed as a weighted sum of contributions from individual energy layers, proved to be effective with the ambient detectors and BDs. However, it did not work as well with the EPDs, suggesting that these detectors may require a different approach for accurate dose estimation.
The development of the Python-based tool is a significant milestone in the field. It requires the radiotherapy plan, detector data, and calculation parameters as inputs and outputs neutron dose estimates along with associated uncertainties. The tool has been verified through additional measurement points, demonstrating its reliability and usefulness for ambient detectors and BDs. However, the researchers caution that EPD results should be interpreted with caution due to the broad calculated intervals.
The potential impact of this tool extends far beyond the walls of the research laboratory. As Morán notes, the methodology behind the tool is believed to be transferable to other centers using comparable technology. This means that the tool can be adapted for use in various clinical settings, ensuring that proton therapy centers worldwide can benefit from this groundbreaking research. The researchers are now extending the tool to include paediatric cases, different proton energies, patient sizes, and treatment configurations, further expanding its applicability.
In conclusion, this study represents a significant advancement in our understanding of out-of-field neutron dose during proton therapy. The development of the Python-based calculation tool not only provides a practical solution for radiation protection and workplace dose assessments but also opens up new avenues for research and innovation. As proton therapy continues to play a crucial role in cancer treatment, this study serves as a reminder of the importance of ongoing research and collaboration in the field. It is through such efforts that we can ensure that proton therapy remains a safe and effective treatment option for patients worldwide.
