Monte Carlo simulation-based approach to model the size distribution of metastatic tumors.
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.
California High School, San Ramon, California 94583, USA. firstname.lastname@example.org
SourcePhysical review. E, Statistical, nonlinear, and soft matter physics 85:1 Pt 1 2012 Jan pg 012901
Monte Carlo Method
Pub Type(s)Journal Article