Introduction to Megavoltage X-Ray Dose Computation Algorithms
Read an exclusive interview with Dr. Jerry Battista here.
A critical element of radiation treatment planning for cancer is the accurate prediction and delivery of a tailored radiation dose distribution inside the patient. Megavoltage x-ray beams are aimed at the tumour, while collateral damage to nearby healthy tissue and organs is minimized. The key to optimal treatment therefore lies in adopting a trustworthy three-dimensional (3D) dose computation algorithm, which simulates the passage of both primary and secondary radiation throughout the exposed tissue.
Edited by an award-winning university educator and pioneer in the field of voxel-based radiation dose computation, this book explores the physics and mathematics that underlie algorithms encountered in contemporary radiation oncology. It is an invaluable reference for clinical physicists who commission, develop, or test treatment planning software. This book also covers a core topic in the syllabus for educating graduate students and residents entering the field of clinical physics.
This book starts with a historical perspective gradually building up to the three most important algorithms used for today’s clinical applications. These algorithms can solve the same general radiation transport problem from three vantages: firstly, applying convolution-superposition principles (i.e. Green’s method); secondly, the stochastic simulation of radiation particle interactions with tissue atoms (i.e. the Monte Carlo method); and thirdly, the deterministic solution of the fundamental equations for radiation fields of x-rays and their secondary particles (i.e. the Boltzmann method). It contains clear, original illustrations of key concepts and quantities thoughout, supplemented by metaphors and analogies to facilitate comprehension and retention of knowledge.
- Edited by an authority in the field, enhanced with chapter contributions from physicists with clinical experience in the fields of computational dosimetry and dose optimization
- Contains examples of test phantom results and clinical cases, illustrating pitfalls to avoid in clinical applications to radiation oncology
- Introduces four-dimensional (4D) dose computation, on-line dose reconstruction, and dose accumulation that accounts for tissue displacements and motion throughout a course of radiation therapy
Introduction. X-Ray Interactions and Energy Deposition. Conceptual Overview of Algorithms. Convolution and Superposition Methods. Stochastic Radiation Transport Method. Deterministic Radiation Transport Methods. En Route to 4D Dose Computations.