|International Journal of Nuclear Medicine Research (Volume 3 Issue 2)|
|Beta-Minus Emitters Dose Point Kernel Estimation Model Comprising Different Tissues for Nuclear Medicine Dosimetry Applications|
Pedro Pérez, Federico Geser, Ignacio Scarinci, Francisco Malano and Mauro Valente
Published: 27 September 2016
The use of β-emitters for therapy purposes is one of the most extended procedures for tumor treatments in nuclear medicine practices over the last years. The constantly increasing dose delivery to healthy tissues in this practices, due to their high linear energy transfer and their radiobiological characteristics, might lead to complications in radiosensitive organs/tissues. Research efforts should be conducted to the development of tools and methods devoted to perform precise dosimetric calculations to deal with this issue and assess accurately dosimetric estimations on patients treated regions.
When performing dosimetry at organ level it is usual to assume some approximations on calculations, like uniformity in activity distribution within source regions, homogeneous media distribution for patient treated regions and uniform delivered dose on target organs. In this work, a formula to obtain Dose Point Kernel for different biological media is presented. Results are collated with Monte Carlo simulations suggesting a behavior that can be splitted in three groups, in accordance to their differences against the stochastic estimations: a) skin, blood and brain present differences within the 5% in comparison with the reference data; b) skeletal muscle, soft tissue, striated muscle and adipose tissue have differences lower than 20%; and c) compact bone, cortical bone and lung tissue differences are found above 50%.
This introduction of a medium-specific Dose Point Kernel calculation method could potentially lead to future improvements on dosimetric systems, limiting for now this model to tissues with effective atomic number closed to liquid water.
|Dose point kernel, Radioisotope, Monte carlo simulation, Theoretical models, Targeted radionuclide therapy.|