Optimization Problems in Radiotherapy for Hypoxic Tumors
Series: Biological and Medical Physics, Biomedical Engineering;
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63 540 Ft (60 515 Ft + 5% VAT)
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63 540 Ft
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Product details:
- Publisher Springer
- Date of Publication 7 July 2025
- Number of Volumes 1 pieces, Book
- ISBN 9789819670000
- Binding Hardback
- No. of pages162 pages
- Size 235x155 mm
- Language English
- Illustrations 40 Illustrations, black & white; 7 Illustrations, color 700
Categories
Short description:
This book highlights the mathematical aspects of treatment outcomes analysis and dose optimization in radiotherapy for heterogeneous hypoxic tumors. Hypoxia is a major factor of cancer resistance to radiotherapy treatment and is present in most tumors encountered in humans. The author tried to present a systematic consideration of radiotherapy for hypoxic tumors, but the emphasis was put on mathematical content of the problems. The book contains new approaches to the concepts of tumor control probability, equivalent uniform dose and radiotherapy dose optimization for hypoxic tumors developed by the author. Significant attention in this book is paid to comparison of models with measured and clinical data; therefore, the reduction of model parameters to overcome overfitting (model parsimony) was followed as much as possible.
MoreLong description:
This book highlights the mathematical aspects of treatment outcomes analysis and dose optimization in radiotherapy for heterogeneous hypoxic tumors. Hypoxia is a major factor of cancer resistance to radiotherapy treatment and is present in most tumors encountered in humans. The author tried to present a systematic consideration of radiotherapy for hypoxic tumors, but the emphasis was put on mathematical content of the problems. The book contains new approaches to the concepts of tumor control probability, equivalent uniform dose and radiotherapy dose optimization for hypoxic tumors developed by the author. Significant attention in this book is paid to comparison of models with measured and clinical data; therefore, the reduction of model parameters to overcome overfitting (model parsimony) was followed as much as possible.
MoreTable of Contents:
Introduction.- Tumor Models for Optimization of Radiotherapy Response.- Dose-Volume Effects in Tumor Control Probability.- Equivalent Uniform Aerobic Dose.- Dose Nonuniformity Effectiveness in Hypoxic Tumors.- Stability of Inverse Planning with Different Objective Functions.
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Optimization Problems in Radiotherapy for Hypoxic Tumors
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