NDLI: Monte Carlo Calculation of Radioimmunotherapy with 90Y-, 177Lu-, 131I-, 124I-, and 188Re-Nanoobjects: Choice of the Best Radionuclide for Solid Tumour Treatment by Using TCP and NTCP Concepts

Content Provider	PubMed Central
Author	Lucas, S. Feron, O. Gallez, B. Masereel, B. Michiels, C. Borght, T. Vander
Copyright Year	2015
Abstract	Radioimmunotherapy has shown that the use of monoclonal antibodies combined with a radioisotope like 131I or 90Y still remains ineffective for solid and radioresistant tumour treatment. Previous simulations have revealed that an increase in the number of 90Y labelled to each antibody or nanoobject could be a solution to improve treatment output. It now seems important to assess the treatment output and toxicity when radionuclides such as 90Y, 177Lu, 131I, 124I, and 188Re are used. Tumour control probability (TCP) and normal tissue complication probability (NTCP) curves versus the number of radionuclides per nanoobject were computed with MCNPX to evaluate treatment efficacy for solid tumours and to predict the incidence of surrounding side effects. Analyses were carried out for two solid tumour sizes of 0.5 and 1.0 cm radius and for nanoobject (i.e., a radiolabelled antibody) distributed uniformly or nonuniformly throughout a solid tumour (e.g., Non-small-cell-lung cancer (NSCLC)). 90Y and 188Re are the best candidates for solid tumour treatment when only one radionuclide is coupled to one carrier. Furthermore, regardless of the radionuclide properties, high values of TCP can be reached without toxicity if the number of radionuclides per nanoobject increases.
Related Links	http://dx.doi.org/10.1155/2015/284360
Starting Page	284360
File Format	PDF
ISSN	1748670X
e-ISSN	17486718
Journal	Computational and Mathematical Methods in Medicine
Volume Number	2015
Language	English
Publisher	Hindawi Publishing Corporation
Publisher Date	2015-01-01
Access Restriction	Open
Rights Holder	Hindawi Publishing Corporation
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Modelling and Simulation Immunology and Microbiology(all) Applied Mathematics Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology Modeling and Simulation

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