Radiomics and Radiogenomics: Technical Basis and Clinical Applications (Imaging in Medical Diagnosis and Therapy)

Radiomics and Radiogenomics: Technical Basis and Clinical Applications provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical bases, and clinical applications with a focus on oncology. The book’s expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and evaluation of therapy response. This book is intended for audiences including imaging scientists, medical physicists, as well as medical professionals and specialists such as diagnostic radiologists, radiation oncologists, and medical oncologists. Features Provides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics Shows how they are improving diagnostic and prognostic decisions with greater efficacy Discusses the image informatics, quantitative imaging, feature extraction, predictive modeling, software tools, and other key areas Covers applications in oncology and beyond, covering all major disease sites in separate chapters Includes an introduction to basic principles and discussion of emerging research directions with a roadmap to clinical translation Contents Preface Acknowledgments About the Editors Contributors Foreword Part 1: Introduction 1 Principles and rationale of radiomics and radiogenomics • Sandy Napel Part 2: Technical Basis 2 Imaging informatics: An overview • Assaf Hoogi and Daniel L. Rubin 3 Quantitative imaging using CT • Lin Lu, Lawrence H. Schwartz, and Binsheng Zhao 4 Quantitative PET/CT for radiomics • Stephen R. Bowen, Paul E. Kinahan, George A. Sandison, and Matthew J. Nyflot 5 Quantitative imaging using MRI • David A. Hormuth II, John Virostko, Ashley Stokes, Adrienne Dula, Anna G. Sorace, Jennifer G. Whisenant, Jared A. Weis, C. Chad Quarles, Michael I. Miga, and Thomas E. Yankeelov 6 Tumor segmentation • Spyridon Bakas, Rhea Chitalia, Despina Kontos, Yong Fan, and Christos Davatzikos 7 Habitat imaging of tumor evolution by magnetic resonance imaging (MRI) • Bruna Victorasso Jardim-Perassi, Gary Martinez, and Robert Gillies 8 Feature extraction and qualification • Lise Wei and Issam El Naqa 9 Predictive modeling, machine learning, and statistical issues • Panagiotis Korfiatis, Timothy L. Kline, Zeynettin Akkus, Kenneth Philbrick, and Bradley J. Erickson 10 Radiogenomics: Rationale and methods • Olivier Gevaert 11 Resources and datasets for radiomics • Ken Chang, Andrew Beers, James Brown, and Jayashree Kalpathy-Cramer Part 3: Clinical Applications 12 Pathways to radiomics-aided clinical decision-making for precision medicine • Tianyue Niu, Xiaoli Sun, Pengfei Yang, Guohong Cao, Khin K. Tha, Hiroki Shirato, Kathleen Horst, and Lei Xing 13 Brain cancer • William D. Dunn Jr. and Rivka R. Colen 14 Breast cancer • Hui Li and Maryellen L. Giger 15 Radiomics for lung cancer • Jie Tian, Di Dong, and Shuo Wang 16 The essence of R in head and neck cancer: Role of radiomics and radiogenomics from a radiation oncology perspective • Hesham Elhalawani, Arvind Rao, and Clifton D. Fuller 17 Gastrointestinal cancers • Zaiyi Liu 18 Radiomics in genitourinary cancers: Prostate cancer • Satish E. Viswanath and Anant Madabhushi 19 Radiomics analysis for gynecologic cancers • Harini Veeraraghavan 20 Applications of imaging genomics beyond oncology • Xiaohui Yao, Jingwen Yan, and Li Shen Part 4: Future Outlook 21 Quantitative imaging to guide mechanism-based modeling of cancer • David A. Hormuth II, Matthew T. Mckenna, and Thomas E. Yankeelov 22 Looking ahead: Opportunities and challenges in radiomics and radiogenomics • Ruijiang Li, Yan Wu, Michael Gensheimer, Masoud Badiei Khuzani, and Lei Xing Index "This book provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical basis, and clinical applications with a focus on cancer. The expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and therapy planning"-- Provided by publisher