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Type: Artigo
Title: Estimation of Tumor Size Evolution Using Particle Filters
Author(s)/Inventor(s): Costa, José Mir Justino da
Orlande, Hélcio Rangel Barreto
Campos Velho, Haroldo Fraga de
Pinho, Suani Tavares Rubim de
Dulikravich, George S.
Cotta, Renato Machado
Cunha Neto, Sílvio Henriques da
Abstract: Indisponível.
Abstract: Cancer is characterized by the uncontrolled growth of cells with the ability of invading local organs and/or tissues and of spreading to other sites. Several kinds of mathematical models have been proposed in the literature, involving different levels of refinement, for the evolution of tumors and their interactions with chemotherapy drugs. In this article, we present the solution of a state estimation problem for tumor size evolution. A system of nonlinear ordinary differential equations is used as the state evolution model, which involves as state variables the numbers of tumor, normal and angiogenic cells, as well as the masses of the chemotherapy and anti-angiogenic drugs in the body. Measurements of the numbers of tumor and normal cells are considered available for the inverse analysis. Parameters appearing in the formulation of the state evolution model are treated as Gaussian random variables and their uncertainties are taken into account in the estimation of the state variables, by using an algorithm based on the auxiliary sampling importance resampling particle filter. Test cases are examined in the article dealing with a chemotherapy protocol for pancreatic cancer.
Keywords: Cancer modeling
Inverse problem
Particle filter
State estimation problem
Tumor size
Department : Núcleo Interdisciplinar de Dinâmica dos Fluidos
Publisher: Mary Ann Liebert
In: Journal of Computational Biology
Volume: 22
Issue: 7
Issue Date: 10-Jul-2015
DOI: 10.1089/cmb.2014.0003
Publisher country: Brasil
Language: eng
Right access: Acesso Aberto
ISSN: 1066-5277
Appears in Collections:Engenharias

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