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Phys Med Biol ; 61(19): 6935-6952, 2016 10 07.
Article in English | MEDLINE | ID: mdl-27617585

ABSTRACT

Current preclinical dosimetric models often fail to take account of the complex nature of absorbed dose distribution typical of in vitro clonogenic experiments in targeted radionuclide therapy. For this reason, clonogenic survival is often expressed as a function of added activity rather than the absorbed dose delivered to cells/cell nuclei. We designed a multi-cellular dosimetry model that takes into account the realistic distributions of cells in the Petri dish, for the establishment of survival curves as a function of the absorbed dose. General-purpose software tools were used for the generation of realistic, randomised 3D cell culture geometries based on experimentally determined parameters (cell size, cell density, cluster density, average cluster size, cell cumulated activity). A mixture of Monte Carlo and analytical approaches was implemented in order to achieve as accurate as possible results while reducing calculation time. The model was here applied to clonogenic survival experiments carried out to compare the efficacy of Betalutin®, a novel 177Lu-labelled antibody radionuclide conjugate for the treatment of non-Hodgkin lymphoma, to that of 177Lu-labelled CD20-specific (rituximab) and non-specific antibodies (Erbitux) on lymphocyte B cells. The 3D cellular model developed allowed a better understanding of the radiative and non-radiative processes associated with cellular death. Our approach is generic and can also be applied to other radiopharmaceuticals and cell distributions.


Subject(s)
Antineoplastic Agents/therapeutic use , Lutetium/therapeutic use , Lymphoma, Non-Hodgkin/radiotherapy , Models, Biological , Radiopharmaceuticals/therapeutic use , Rituximab/therapeutic use , Antineoplastic Agents/pharmacokinetics , Humans , Lutetium/pharmacokinetics , Lymphoma, Non-Hodgkin/metabolism , Monte Carlo Method , Radiometry/methods , Radiopharmaceuticals/pharmacokinetics , Rituximab/pharmacokinetics , Software , Tissue Distribution , Tumor Cells, Cultured
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