Literature DB >> 29737395

Estimating intratumoral heterogeneity from spatiotemporal data.

E M Rutter1, H T Banks1, K B Flores2.   

Abstract

Glioblastoma multiforme (GBM) is a malignant brain cancer with a tendency to both migrate and proliferate. We propose modeling GBM with heterogeneity in cell phenotypes using a random differential equation version of the reaction-diffusion equation, where the parameters describing diffusion (D) and proliferation ([Formula: see text]) are random variables. We investigate the ability to perform the inverse problem to recover the probability distributions of D and [Formula: see text] using the Prohorov metric, for a variety of probability distribution functions. We test the ability to perform the inverse problem for noisy synthetic data. We then examine the predicted effect of treatment, specifically, chemotherapy, when assuming such a heterogeneous population and compare with predictions from a homogeneous cell population model.

Entities:  

Keywords:  Glioblastoma multiforme; Parameter estimation; Random differential equation

Mesh:

Substances:

Year:  2018        PMID: 29737395     DOI: 10.1007/s00285-018-1238-6

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  41 in total

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Journal:  Exp Cell Res       Date:  2013-08-22       Impact factor: 3.905

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Journal:  Sci Rep       Date:  2017-05-31       Impact factor: 4.379

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  1 in total

1.  THE PROHOROV METRIC FRAMEWORK AND AGGREGATE DATA INVERSE PROBLEMS FOR RANDOM PDEs.

Authors:  H T Banks; K B Flores; I G Rosen; E M Rutter; Melike Sirlanci; W Clayton Thompson
Journal:  Commun Appl Anal       Date:  2018-06-19
  1 in total

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