ABSTRACT

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

part 1|1 pages

Introduction

chapter 1|10 pages

Principles and rationale of radiomics and radiogenomics

BySandy Napel

part 2|1 pages

Technical Basis

chapter 2|13 pages

Imaging informatics

An overview
ByAssaf Hoogi, Daniel L. Rubin

chapter 3|17 pages

Quantitative imaging using CT

ByLin Lu, Lawrence H. Schwartz, Binsheng Zhao

chapter 4|25 pages

Quantitative PET/CT for radiomics

ByStephen R. Bowen, Paul E. Kinahan, George A. Sandison, Matthew J. Nyflot

chapter 5|26 pages

Quantitative imaging using MRI

ByDavid A. Hormuth, John Virostko, Ashley Stokes, Adrienne Dula, Anna G. Sorace, Jennifer G. Whisenant, Jared A. Weis, C. Chad Quarles, Michael I. Miga, Thomas E. Yankeelov

chapter 6|16 pages

Tumor segmentation

BySpyridon Bakas, Rhea Chitalia, Despina Kontos, Yong Fan, Christos Davatzikos

chapter 7|6 pages

Habitat imaging of tumor evolution by magnetic resonance imaging (MRI)

ByBruna Victorasso Jardim-Perassi, Gary Martinez, Robert Gillies

chapter 8|29 pages

Feature extraction and qualification

ByLise Wei, Issam El Naqa

chapter 9|18 pages

Predictive modeling, machine learning, and statistical issues

ByPanagiotis Korfiatis, Timothy L. Kline, Zeynettin Akkus, Kenneth Philbrick, Bradley J. Erickson

chapter 10|10 pages

Radiogenomics

Rationale and methods
ByOlivier Gevaert

chapter 11|11 pages

Resources and datasets for radiomics

ByKen Chang, Andrew Beers, James Brown, Jayashree Kalpathy-Cramer

part 3|1 pages

Clinical Applications

chapter 12|9 pages

Pathways to radiomics-aided clinical decision-making for precision medicine

ByTianye Niu, Xiaoli Sun, Pengfei Yang, Guohong Cao, Khin K. Tha, Hiroki Shirato, Kathleen Horst, Lei Xing

chapter 13|25 pages

Brain cancer

ByWilliam D. Dunn, Rivka R. Colen

chapter 14|21 pages

Breast cancer

ByHui Li, Maryellen L. Giger

chapter 15|13 pages

Radiomics for lung cancer

ByJie Tian, Di Dong, Shuo Wang

chapter 16|18 pages

The essence of R in head and neck cancer

Role of radiomics and radiogenomics from a radiation oncology perspective
ByHesham Elhalawani, Arvind Rao, Clifton D. Fuller

chapter 17|17 pages

Gastrointestinal cancers

ByZaiyi Liu

chapter 18|17 pages

Radiomics in genitourinary cancers

Prostate cancer
BySatish E. Viswanath, Anant Madabhushi

chapter 19|17 pages

Radiomics analysis for gynecologic cancers

ByHarini Veeraraghavan

chapter 20|30 pages

Applications of imaging genomics beyond oncology

ByXiaohui Yao, Jingwen Yan, Li Shen

part 4|1 pages

Future Outlook

chapter 21|17 pages

Quantitative imaging to guide mechanism-based modeling of cancer

ByDavid A. Hormuth, Matthew T. McKenna, Thomas E. Yankeelov

chapter 22|23 pages

Looking ahead Opportunities and challenges in radiomics and radiogenomics

ByRuijiang Li, Yan Wu, Michael Gensheimer, Masoud Badiei Khuzani, Lei Xing