Literature DB >> 8810224

A patient-specific in vivo tumor model.

R Wasserman1, R Acharya.   

Abstract

A significant body of research, spanning approximately the last 25 years, has focused upon the task of developing a better understanding of tumor growth through the use of in vitro mathematical models. Although such models are useful for simulation, in vivo growth differs in significant ways due to the variety of competing biological, biochemical, and mechanical factors present in a living biological system. An in vivo, macroscopic, primary brain tumor growth model is developed, incorporating previous in vitro growth pattern research as well as scientific investigations into the biological and biochemical factors that affect in vivo neoplastic growth. The tumor growth potential model presents an integrated, universal framework that can be employed to predict the direction and extent of spread of a primary brain tumor with respect to time for a specific patient. This framework may be extended as necessary to include the results of current and future research into parameters affecting neoplastic proliferation. The patient-specific primary brain tumor growth model is expected to have multiple clinical uses, including: predictive modeling, tumor boundary delineation, growth pattern research, improved radiation surgery planning, and expert diagnostic assistance.

Entities:  

Mesh:

Year:  1996        PMID: 8810224     DOI: 10.1016/0025-5564(96)00045-4

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  13 in total

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2.  Realistic simulation of the 3-D growth of brain tumors in MR images coupling diffusion with biomechanical deformation.

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Review 4.  Toward an Ising model of cancer and beyond.

Authors:  Salvatore Torquato
Journal:  Phys Biol       Date:  2011-02-07       Impact factor: 2.583

5.  An imaging-based stochastic model for simulation of tumour vasculature.

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Journal:  Phys Med Biol       Date:  2012-09-13       Impact factor: 3.609

6.  In-silico oncology: an approximate model of brain tumor mass effect based on directly manipulated free form deformation.

Authors:  Stefan Becker; Andreas Mang; Alina Toma; Thorsten M Buzug
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Review 7.  In silico cancer modeling: is it ready for prime time?

Authors:  Thomas S Deisboeck; Le Zhang; Jeongah Yoon; Jose Costa
Journal:  Nat Clin Pract Oncol       Date:  2008-10-14

Review 8.  An imaging-based tumour growth and treatment response model: investigating the effect of tumour oxygenation on radiation therapy response.

Authors:  Benjamin Titz; Robert Jeraj
Journal:  Phys Med Biol       Date:  2008-08-01       Impact factor: 3.609

9.  Virtual glioblastoma: growth, migration and treatment in a three-dimensional mathematical model.

Authors:  S E Eikenberry; T Sankar; M C Preul; E J Kostelich; C J Thalhauser; Y Kuang
Journal:  Cell Prolif       Date:  2009-05-29       Impact factor: 6.831

10.  A mechanically coupled reaction-diffusion model for predicting the response of breast tumors to neoadjuvant chemotherapy.

Authors:  Jared A Weis; Michael I Miga; Lori R Arlinghaus; Xia Li; A Bapsi Chakravarthy; Vandana Abramson; Jaime Farley; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2013-08-06       Impact factor: 3.609

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