Multiparameter computational modeling of tumor invasion. Academic Article uri icon

Overview

abstract

  • Clinical outcome prognostication in oncology is a guiding principle in therapeutic choice. A wealth of qualitative empirical evidence links disease progression with tumor morphology, histopathology, invasion, and associated molecular phenomena. However, the quantitative contribution of each of the known parameters in this progression remains elusive. Mathematical modeling can provide the capability to quantify the connection between variables governing growth, prognosis, and treatment outcome. By quantifying the link between the tumor boundary morphology and the invasive phenotype, this work provides a quantitative tool for the study of tumor progression and diagnostic/prognostic applications. This establishes a framework for monitoring system perturbation towards development of therapeutic strategies and correlation to clinical outcome for prognosis.

publication date

  • April 14, 2009

Research

keywords

  • Brain Neoplasms
  • Glioblastoma
  • Models, Theoretical
  • Neoplasm Invasiveness
  • Neoplasms

Identity

PubMed Central ID

  • PMC2835777

Scopus Document Identifier

  • 66249101668

Digital Object Identifier (DOI)

  • 10.1158/0008-5472.CAN-08-3834

PubMed ID

  • 19366801

Additional Document Info

volume

  • 69

issue

  • 10