Introduction to Mathematical Oncology

By Yang Kuang, John D. Nagy, Steffen E. Eikenberry

© 2016 – Chapman and Hall/CRC

504 pages | 77 B/W Illus.

Purchasing Options:
Hardback: 9781584889908
pub: 2016-01-28
Available for pre-order
US Dollars$89.95

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About the Book

This self-contained book focuses on mathematical models related to cancer growth and treatment. It presents the medical and biological background of the diseases, specific issues to be modeled, and existing methods and their limitations. The book introduces mathematical and programming tools, along with analytical and numerical studies of the models. The authors also develop new mathematical tools and look to future improvements on dynamical models. The text provides many classroom-tested exercises and projects at the end of most chapters.

Chapter 1 provides a brief introduction to the general theory of medicine and how mathematics can be essential in its understanding. Chapter 2 introduces readers to some well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. Chapter 3 continues the topic of avascular tumor growth in the context of partial differential equation (PDE) models by incorporating the spatial structure while Chapter 4 expands the topic of avascular tumor growth in a PDE context by incorporating physiological structure, such as cell size. Chapter 5 focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. Chapter 6 exposes readers to more mechanistically formulated models, including cell quota-based population growth models with applications to real tumors and validation using clinical data. The remaining chapters present abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts.

Although this book is useful to professionals in various fields, it is designed as a textbook for both graduate and upper-division undergraduate courses in mathematical oncology. The text can be used in a variety of ways, allowing instructors to emphasize specific topics relevant to clinical cancer biology and treatment. A sample single semester undergraduate-level course may cover the first three chapters plus Chapter 5. A more ambitious graduate-level course may cover the first 6 chapters plus selected readings from later material and cited literature. A full year sequence on mathematical oncology may cover most of the chapters.

Table of Contents

Introduction to Theory in Medicine

Introduction to Cancer Modeling

Spatially Structured Tumor Growth

Physiologically Structured Tumor Growth

Prostate Cancer: PSA, AR, and ADT Dynamics

Resource Competition and Cell Quota in Cancer Models

Natural History of Clinical Cancer

Evolutionary Ecology of Cancer

Models of Chemotherapy

Major Anti-Cancer Chemotherapies

Chemical Kinetics

Radiation Therapy

Epilogue: Toward a Quantitative Theory of Oncology

About the Authors

Yang Kuang is a professor of mathematics at Arizona State University in Tempe.

John Nagy is a professor of biology at Scottsdale Community College in Arizona.

Steffen Eikenberry has received his PhD in bioengineering from the University of Southern California and is completing his MD at the University of Southern California.

About the Series

Chapman & Hall/CRC Mathematical and Computational Biology

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Subject Categories

BISAC Subject Codes/Headings:
MEDICAL / Epidemiology
SCIENCE / Life Sciences / Biology / General