Modern medical imaging and radiation therapy technologies are so complex and computer driven that it is difficult for physicians and technologists to know exactly what is happening at the point-of-care. Medical physicists responsible for filling this gap in knowledge must stay abreast of the latest advances at the intersection of medical imaging an

ABSTRACT: Image guided radiation therapy (IGRT) requires developing advanced methods for target localization. Once target motion is identified, the patient specific treatment margin can be incorporated into the treatment planning, accurately delivering the radiation dose to the target and minimizing the dose to the normal tissues. Deformable image registration (DIR) has become an indispensable tool to analyze target motion and measure physiological change by temporal imaging or time series volumetric imaging, such as four-dimensional computed tomography (4DCT). Current DIR algorithms suffer from inverse inconsistency, where the deformation mapping is not unique after switching the order of the images. Moreover, long computation time of current DIR implementation limits its clinical application to offline analysis. This dissertation makes several major contributions: First, an inverse consistent constraint (ICC) is proposed to constrain the uniqueness of the correspondence between image pairs. The proposed ICC has the advantage of 1) improving registration accuracy and robustness, 2) not requiring explicitly computing the inverse of the deformation field, and 3) reducing the inverse consistency error (ICE). Moreover, a variational registration model, based on the maximum likelihood estimation, is proposed to accelerate the algorithm convergence and allow for inexact image pixel matching within an optimized variation for noisy image pairs.

“This is a high quality book with directions and guidelines on how to generate valid treatment plans in the modern era of radiation oncology. It is very useful for any student (dosimetry, therapy, physicist, or physician) who is entering a practical treatment planning rotation...It is written as a companion to the Handbook of Treatment Planning in Radiation Oncology, 2nd edition, Videtic et al. (Demos Medical Publishing, 2015), and pairs very well with it.” Score: 88, 3 Stars, Doody’s Medical Reviews “Comparing with earlier published books about radiotherapy treatment planning, which are prone to the pedagogical side as textbooks, this new book serves an unmet need as a pocket-sized book with details and up to date information for user’s quick resource for treatment planning knowledge... “Strategies for Radiation Therapy Treatment Planning” is a handy and essential reference for modern treatment planning. It is therefore recommended as a valuable book for the bookshelf and pocket of everyone involved in radiotherapy treatment planning.” -- Dr. Chengyu Shi of Memorial Sloan Kettering Cancer Center for Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. Strategies for Radiation Therapy Treatment Planning provides radiation oncologists, physicists, and dosimetrists with a step-by-step guide to implementing external beam treatment plans that meet clinical requirements for each major disease site. As a companion book to the Handbook of Treatment Planning in Radiation Oncology Second Edition, this book focuses on the technical aspects of treatment planning and the major challenges in creating highly conformal dose distributions, referenced to as treatment plans, for external beam radiotherapy. To overcome challenges associated with each step, leading experts at the Cleveland Clinic have consolidated their knowledge and experience of treatment planning techniques, potential pitfalls, and other difficulties to develop quality plans across the gamut of clinical scenarios in radiation therapy. The book begins with an overview of external beam treatment planning principles, inverse planning and advanced planning tools, and descriptions of all components in simulation and verification. Following these introductory chapters are disease-site examples, including central nervous system, head and neck, breast, thoracic, gastrointestinal, genitourinary, gynecologic, lymphoma, and soft tissue sarcoma. The book concludes with expert guidance on planning for pediatric cancers and how to tailor palliative plans. Essential for all radiation therapy team members, including trainees, this book is for those who wish to learn or improve their treatment planning skills and understand the different treatment planning processes, plan evaluation, and patient setup. KEY FEATURES: Provides basic principles of treatment planning Contains step-by-step, illustrated descriptions of the treatment planning process Discusses the pros and cons of advanced treatment planning tools, such as auto-planning, knowledge-based planning, and multi-criteria based planning Describes each primary treatment site from simulation, patient immobilization, and creation of various treatment plans to plan evaluations Includes instructive sample plans to highlight best practices

The goal of this research was to propose and evaluate solutions to four important aspects of adaptive radiation therapy in order to make it more reliable, accurate, and efficient in clinical environment. The first study focused on the evaluation of several deformable image registration algorithms. Results demonstrated that the Dense Anatomical Block Matching registration outperformed the other methods making it a very promising alternative to the existing registration methods for challenging CT-to-CBCT registration and its applications for radiation dose calculation, dose mapping and contour propagation in adaptive radiation therapy (ART) of the pelvic region. The second study focused on the quantitative evaluation of eight proposed adaptive radiation therapy approaches for prostate cancer patients treated with hypofractionated VMAT. The ART strategies included online and offline methods. The comprehensive analysis showed that daily on-line adaptation approaches were the most impactful. The findings of this study provided applicable insights into the selection of the optimal ART strategy, improving the quality of the decision-making process based on the quantitatively evaluated dosimetric benefits. The third study aimed to utilize a deep learning network to automatically contour critical organs on the computed tomography (CT) scans of head and neck cancer patients. Proposed model achieved expert level accuracy and was able to segment 25 critical organs on unseen CT images in approximately 7 seconds per patient. High accuracy and short contouring time allow for the implementation of the model within a clinical ART workflow, which would lead to a significant decrease in the time required to create a new adapted treatment plan. The objective of the fourth study was to use artificial intelligence methods to build a decision making support system that would classify previously delivered plans of brain tumor patients into those that met treatment planning objectives and those for which objectives were not met due to the priority given to one or more organs-at-risk. Among evaluated machine learning algorithms, the Logistic Regression model achieved the highest accuracy and can be used by radiation oncologists to support their decision-making process in terms of treatment plan adaptations and plan approvals in a data-driven quality assurance program.

This volume will describe recent progress and future directions in radiation oncology and biology research, focusing on strategies designed to improve disease control and reduce the risk of long-term adverse effects on patients. As more and more patients are becoming long-term survivors, this strategy will become increasingly important--in radiation oncology and throughout the field of oncology.

External-beam radiotherapy has long been challenged by the simple fact that patients can (and do) move during the delivery of radiation. Recent advances in imaging and beam delivery technologies have made the solution—adapting delivery to natural movement—a practical reality. Adaptive Motion Compensation in Radiotherapy provides the first detailed treatment of online interventional techniques for motion compensation radiotherapy. This authoritative book discusses: Each of the contributing elements of a motion-adaptive system, including target detection and tracking, beam adaptation, and patient realignment Treatment planning issues that arise when the patient and internal target are mobile Integrated motion-adaptive systems in clinical use or at advanced stages of development System control functions essential to any therapy device operating in a near-autonomous manner with limited human interaction Necessary motion-detection methodology, repositioning techniques, and approaches to interpreting and responding to target movement data in real time Medical therapy with external beams of radiation began as a two-dimensional technology in a three-dimensional world. However, in all but a limited number of scenarios, movement introduces the fourth dimension of time to the treatment problem. Motion-adaptive radiation therapy represents a truly four-dimensional solution to an inherently four-dimensional problem. From these chapters, readers will gain not only an understanding of the technical aspects and capabilities of motion adaptation but also practical clinical insights into planning and carrying out various types of motion-adaptive radiotherapy treatment.