Unbound MEDLINE

Monte Carlo simulation-based approach to model the size distribution of metastatic tumors.

Abstract

The size distribution of metastatic tumors and its time evolution are traditionally described by integrodifferential equations and stochastic models. Here we develop a simple Monte Carlo approach in which each event of metastasis is treated as a chance event through random-number generation. We demonstrate the accuracy of this approach on a specific growth and metastasis model by showing that it quantitatively reproduces the size distribution and the total number of tumors as a function of time. The approach also yields statistical distribution of patient-to-patient variations, and has the flexibility to incorporate many real-life complexities.

Links

  • Publisher Full Text
  • Authors

    Maiti E

    Institution

    California High School, San Ramon, California 94583, USA. emaiti96@gmail.com

    Source

    Physical review. E, Statistical, nonlinear, and soft matter physics 85:1 Pt 1 2012 Jan pg 012901

    MeSH

    Cell Proliferation
    Cell Size
    Computer Simulation
    Humans
    Models, Biological
    Models, Statistical
    Monte Carlo Method
    Neoplasm Invasiveness
    Neoplasm Metastasis
    Nonlinear Dynamics

    Pub Type(s)

    Journal Article

    Language

    eng

    PubMed ID

    22400608