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Dose Kernels in Water for More Than 700 Radioisotopes

S Graves1*, D Hyer1 , R Flynn1 , B Bednarz2 , (1) University Of Iowa, Iowa City, IA (2) University of Wisconsin, Madison, WI


(Tuesday, 7/31/2018) 11:00 AM - 12:15 PM

Room: Room 202

Purpose: Growing use of targeted radionuclide therapies, such as ¹��Lu-DOTATOC (Lutathera) has driven the field of nuclear medicine toward personalized internal dosimetry. Voxel-wise dose calculations based on the patient’s own CT dataset are potentially superior to conventional anthropomorphic phantom-based approaches, however accurate dose kernels for convolution-superposition methods are sparse in literature. The purpose of this work was to generate a library of dose kernels for use in voxel-wise dose calculations.

Methods: Scripts were written to automatically generate MCNP5 input files for more than 700 radionuclides based on available nuclear decay data (National Nuclear Data Center, Brookhaven National Laboratory, accessed Jan. 2018). Isotropic point sources were simulated in water with spherical bins being used to tally dose (*F8 MCNP5 tally) from photons and electrons. Bins were spaced every 0.1 mm below a radius of 10 cm, and every 1 mm between 10 cm and 2 m. Photons (x-rays and γ-rays), discrete electron energies, and beta spectra were simulated separately for each isotope, where applicable. Positrons were treated as electrons for transport, with annihilation photons generated at the origin within the photon simulation. Alpha emissions were assumed to stop within 0.1 mm of the origin with no radiative energy losses.

Results: Transport of 1x10â?¶ particles per mode of decay was found to provide sufficient statistics in a subset of kernels which were manually reviewed. Where published data was available, the kernels generated herein were found to agree closely. Tabulated kernels will be made freely available online before presentation of this abstract.

Conclusion: A large library of high-resolution dose kernels was generated and compared against published data. In addition to enabling patient-specific voxel-wise internal dosimetry by convolution superposition, the generated kernelss will likely prove useful to the wider health physics community.


Internal Dosimetry, Monte Carlo, Convolution/superposition


IM- Nuclear Medicine General: Radiation dosimetry & risk

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