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Title: How Advances in Imaging Will Affect Precision Radiation Oncology

Journal Article · · International Journal of Radiation Oncology, Biology and Physics
 [1];  [1];  [1];  [2]
  1. Department of Medical Physics, Princess Margaret Cancer Centre, Toronto, Ontario (Canada)
  2. The D-Lab: Decision Support for Precision Medicine, GROW –School for Oncology, Maastricht University Medical Centre+, Maastricht, the (Netherlands)

Radiation oncology is 1 of the most structured disciplines in medicine. It is of a highly technical nature with reliance on robotic systems to deliver intervention, engagement of diverse expertise, and early adoption of digital approaches to optimize and execute the application of this highly effective cancer treatment. As a localized intervention, the dependence on sensitive, specific, and accurate imaging to define the extent of disease, its heterogeneity, and adjacency to normal tissues directly affects the therapeutic ratio. Image-based in vivo temporal monitoring of the response to treatment enables adaptation and further affects the therapeutic ratio. Thus, more precise intervention will enable fractionation schedules that better interoperate with advances such as immunotherapy. In the data set–rich era that promises precision and personalized medicine, the radiation oncology field will integrate these new data into highly protocoled pathways of care that begin with multimodality prediction and enable patient-specific adaptation of therapy based on quantitative measures of the individual's dose–volume temporal trajectory and midtherapy predictions of response. In addition to advancements in computed tomography imaging, emerging technologies, such as ultra-high-field magnetic resonance and molecular imaging will bring new information to the design of treatments. Next-generation image guided radiation therapy systems will inject high specificity and sensitivity data and stimulate adaptive replanning. In addition, a myriad of pre- and peritherapeutic markers derived from advances in molecular pathology (eg, tumor genomics), automated and comprehensive imaging analytics (eg, radiomics, tumor microenvironment), and many other emerging biomarkers (eg, circulating tumor cell assays) will need to be integrated to maximize the benefit of radiation therapy for an individual patient. We present a perspective on the promise and challenges of fully exploiting imaging data in the pursuit of personalized radiation therapy, drawing from the presentations and broader discussions at the 2016 American Society of Therapeutic Radiation Oncology–National Cancer Institute workshop on Precision Medicine in Radiation Oncology (Bethesda, MD).

OSTI ID:
23065581
Journal Information:
International Journal of Radiation Oncology, Biology and Physics, Vol. 101, Issue 2; Other Information: Copyright (c) 2018 Published by Elsevier Inc.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0360-3016
Country of Publication:
United States
Language:
English