Computer modeling of XXXX growth.

@entity5 @entity1 @entity1313
An important objective of @entity1313 modeling is to predict the progression of @entity5 so as to provide guidance about the best possible medical treatment to halt or slow the @entity5 's growth. Such computer models also provide a deeper insight into the physiology of @entity5 . In addition, one can study various what-if scenarios, for instance, investigating the response of @entity5 following the administration of a drug or a variety of drugs. Abrupt changes in growth rate can also be important for surgical decision-making. Despite increased interest in modeling techniques, relatively little progress has been made in improving such technologies. One problem is the limited data available from @entity1 , typically 1 to 3 MRI (magnetic resonance imaging) sessions, from which one has to extrapolate the type of @entity5 so as to successfully predict its evolution over time. Here, the biological and clinical aspects of @entity5 growth and treatment with surgery, radiotherapy and drugs are discussed in the light of a @entity1 with a @entity1313 showing accelerated growth over time. Then, the contributions of mathematical modeling of @entity5 growth and effects of treatment are presented. Current @entity5 growth models can be roughly divided in three main categories, (i) cellular and microscopic models that emphasize isolated cell behavior, (ii) macroscopic models that concentrate on the development of cell density over time, and (iii) hybrid approaches that contain elements of both microscopic and macroscopic models. The mathematical theory that underlies these simulation methods is remarkably similar to the physical theory that forms the basis of protein modeling and molecular mechanics tools. A severe limitation of current models is that they are in fact not @entity1 -specific at all.
