Format

Send to

Choose Destination
Int J Radiat Oncol Biol Phys. 2018 Nov 15;102(4):1219-1235. doi: 10.1016/j.ijrobp.2018.06.023. Epub 2018 Jun 30.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective.

Author information

1
Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University, Atlanta, Georgia. Electronic address: rhpress@emory.edu.
2
Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University, Atlanta, Georgia.
3
Department of Radiology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
4
Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
5
Department of Radiology, Washington University, St. Louis, Missouri.
6
Department of Radiology, University of California San Francisco, San Francisco, California.
7
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
8
Cancer Imaging Program, National Cancer Institute, Bethesda, Maryland.
9
Molecular Imaging Program, National Cancer Institute, Bethesda, Maryland.
10
Radiation Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland.
11
Department of Radiology and Radiological Science, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland.
12
Brain Cancer Program, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland.
13
Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.
14
Department of Radiology, Columbia University Medical Center, Columbia University, New York, New York.
15
Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.
16
Department of Radiology, University of Washington, Seattle, Washington.
17
Department of Medicine, University of Washington, Seattle, Washington.
18
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands.
19
Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
20
Department of Radiology, Stanford University, Stanford, California.
21
Department of Radiology, University of Michigan, Ann Arbor, Michigan.
22
Department of Radiation Oncology, University of Iowa, Iowa City, Iowa.

Abstract

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center