Dose Point Kernel calculation and modelling with nuclear medicine dosimetry purposes

IGNACIO SCARINCI; MAURO VALENTE; PEDO PÉREZ

Simposio; X Latin American Symposium on Nuclear Physics and Applications; 2013

Monoclonal labeled antibodies are commonly used for radioimmunotherapy purposes in nuclear medicine The procedure is based on the deposition of specific radiactivity concentrations on tumoral regions with the aim of treating tumoral diseases. Patient metabolism produces nonuniform organ activity distributions, but there are some traditional approaches for internal dosimetry assuming uniform spatial distribution of activity within organ or tissues of interest. When patient-specific dosimetry needs to be performed, these methods may involve non negligible uncertainties. Treatment evaluation and preliminary planning require the estimation of absorbed dose distribution and this goal can be achieved by different approaches. For example, it is possible to perform Monte Carlo simulations for numerical dose assessments; whereas analyticalcalculations can be carried out by convolution of activity distribution using Dose Point Kernels.Besides, it is often found that some internal dosimetry approaches assume simplified conditions of infinite ad homogeneous media for radiation transport and corresponding dose deposition. This work presents a method for internal dosimetry in nuclear medicine by means of Dose Point Kernels. The proposed method is capable of performing calculations over heterogeneous systems. The starting point is a set of suitable kernels previously calculated by Monte Carlo simulations in different tissues. Thus, dose distribution is obtained by the proposed hybrid approach involving both numerical and analytical methods. Preliminary tests on simplified geometries demonstrated the capability of the developed technique; whereas computation of patient-specific internal dosimetry suggest promising performance. Hence, the developed method may constitute a valuable tool for nuclear medicine dosimetry purposes.