4.6 Article

A spatiotemporal, patient individualized simulation model of solid tumor response to chemotherapy in vivo:: The paradigm of glioblastoma multiforme treated by temozolomide

Journal

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 53, Issue 8, Pages 1467-1477

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2006.873761

Keywords

cancer; chemotherapy; chemotherapy optimization; glioblastoma multiforme; in silico oncology; Monte Carlo; neovasculature; patient individualized optimization; temozolomide; Temodal (TM); Temodar (TM); tumor growth; simulation model

Funding

  1. NCI NIH HHS [CA113004] Funding Source: Medline

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A novel four-dimensional, patient-specific Monte Carlo simulation model of solid tumor response to chemotherapeutic treatment in vivo is presented. The special case of glioblastoma multiforme treated by temozolomide is addressed as a simulation paradigm. Nevertheless, a considerable number of the involved algorithms are generally applicable. The model is based on the patient's imaging, histopathologic and genetic data. For a given drug administration schedule lying within acceptable toxicity boundaries, the concentration of the prodrug and its metabolites within the tumor is calculated as a function of time based on the drug pharamacokinetics. A discretization mesh is superimposed upon the anatomical region of interest and within each geometrical cell of the mesh the most prominent biological laws (cell cycling, necrosis, apoptosis, mechanical restictions, etc.) are applied. The biological cell fates are predicted based on the drug pharmacodynamics. The outcome of the simulation is a prediction of the spatiotemporal activity of the entire tumor and is virtual reality visualized. A good qualitative agreement of the model's predictions with clinical experience supports the applicability of the approach. The proposed model primarily aims at providing a platform for performing patient individualized in silico experiments as a means of chemotherapeutic treatment optimization.

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