The essence of modern radiation medicine is the processes of energy transmission and absorption in biological tissue, which allow to use ionizing radiation for diagnosis and treatment of diseases. Computer aided modelling is commonly used for theoretical planning of procedures, but dosimetric control is essential for quality assurance of the treatment procedures. Dosimeters based on various physical principles can be used to verify the resulting radiation treatment plan, but only gel dosimetry allows for an evaluation of the 3D distribution of doses. Principle of the dosimetric gels is based on the change of the polymerization degree, of the gel when exposed to ionizing radiation, which is proportional to the absorbed dose. This dosimetric method also reduces measurement uncertainty, since the composition of the dosimetric gels is close to the biological tissue in terms of radiation absorption. Readout of the dosimetric gels can be performed by different methods, which evaluate their physical properties – optical density, physical density, X-ray absorption, proton density. This project proposes the development of a unique measurement methodology that combines hardware that allows the study of changes in the optical properties of dosimetric gels in real-time, including the irradiation procedure itself, and a data processing algorithm based on the elements of artificial intelligence.
Project funding:
KTU Research and Innovation Fund
Project results:
• The most sensitive formulation of dosimetric gels was experimentally determined – nPAG in the dose range 1.0-5.0Gy. Other gel formulations tested were VIPET, nMAG.
• A prototype of an optical dynamic measurement system has been developed for real-time exposure studies of polymer gels.
• A methodology for dynamic research of polymer gels has been developed, including the developed measurement system and data processing algorithm.
• The stability of the optical properties of nPAG dosimetric gels was found to be achieved 30 minutes after irradiation, which is significantly shorter than the 24-hour recommendations summarized by other authors and allows for more rapid further developments in the field.
Period of project implementation: 2020-04-14 - 2020-12-31
