Ionizing radiation exists as either subatomic particles (alpha and beta particles, and neutrons) or photons (electromagnetic waves at X-ray and gamma ray wavelengths, i.e. energies of a few electron volts). The energy from such radiation can strip electrons from atoms or molecules, thus ionizing them, but it has to have an energy above a certain threshold. An intense flood of particles or photons will not cause ionization if the individual particles do not have enough energy. The energy of a photon correlates with its frequency (it is inversely proportional to its wavelength). So, radiation of short wavelength are high-frequency ultraviolet, X-ray, and gamma rays, and are thus ionizing, whereas visible light, infra-red, microwave, and radio waves with much lower frequencies but longer wavelengths are non-ionising.
High-energy ionising radiation, which comes from natural radioactive sources, particle accelerators, and X-ray machines, is a well-established risk factor for human cancer. Exposure to radiation causes damage to living tissue, DNA damage and at low doses can cause tumour growth. At high dose, skin burns, radiation sickness and death occur.
Epidemiology based on patients treated with ionising radiation, survivors of atomic bomb blasts, and uranium workers, has revealed the risks of leukaemia, lung cancer and various tumour types associated with exposure. Equally well known, of course, is that ionising radiation has many practical uses in medicine. X-rays in imaging and other forms of ionising radiation in cancer therapy, for instance. Alpha particles, beta particles, positrons, gamma emitters, protons and X-rays are all uses to either deliberately cause ionisation to kill malignant cells or as a way of highlighting different types of tissue or diseased cells within the body.
Radiological and nuclear medicine confer a long-term risk of cancer, explains Mauro Valente of the University of Cordoba, and this risk applies not only to patients undergoing examination or treatment but also to healthcare staff and even those simply visiting a patient in hospital. Valente and his colleagues have now turned to statistical tools to help them map out the risk and to offer new boundaries to improve safety for those working in radiology and nuclear medicine.
They have developed a computational tool with an easy to use graphical user interface (GUI) based on a form of statistical analysis known as a Monte Carlo technique. The tool takes into account, the configuration of the treatment or examination room, the specific ionising radiation being used and the shape and size of the individual being irradiated.
“The first preliminary investigation confirmed that the introduced user-defined geometry was satisfactorily capable of mimicking typical treatment room,” the team says, “With the aim of representing realistic situations, all target ‘phantom’ positions were defined in such a way that at every simulated location the target phantom would mimic a person viewing the patient.”
The tool can process the necessary data and produce the corresponding graphic visualisation of potential radiation exposure for any area within a treatment room, the team adds.
“The developed system may be used for the study, characterization and quantification of exposure levels associated with specific arrangements of treatment room and facilities,” Tirao told Sciencebase. “In particularly, it is possible for each user (expert or not) to introduce the specific treatment room characteristics, facilities and patient disposition, locations where medical and technical staff are typically positioned during treatments and so on.”
In addition, the system allows the user to specify isotope emission properties, like radiation type (beta or gamma), emission spectrum and activity distribution.
“The implementation of this system may help in the assessment of exposure levels according to actual treatment room and typical exposed people locations as well as specifying radiation source distribution and emission properties,” he adds. “Authorities and departments responsible may take advantage from this information with the aim of reducing occupational exposure levels as well as minimizing the risks for occasionally exposed people, like the patient’s family.”
Mauro Valente, Francisco Malano, & Germán Tirao (2010). A computational tool for evaluating the exposure risk in nuclear medicine treatments Int. J. Low Radiation, 7 (4), 333-346