TY - CHAP
T1 - Computational modeling of brain tumors
T2 - Discrete, continuum or hybrid?
AU - Wang, Zhihui
AU - Deisboeck, Thomas S.
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.
AB - In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.
KW - Agent-based model
KW - Brain tumor
KW - Cellular automata
KW - Continuum
KW - Multi-scale
UR - http://www.scopus.com/inward/record.url?scp=61349156235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=61349156235&partnerID=8YFLogxK
U2 - 10.1007/s10820-008-9094-0
DO - 10.1007/s10820-008-9094-0
M3 - Chapter (peer-reviewed)
AN - SCOPUS:61349156235
VL - 15
T3 - Scientific Modeling and Simulation SMNS
SP - 381
EP - 393
BT - Scientific Modeling and Simulation SMNS
ER -