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Author Notes:

Co-Corresponding Authors: Robert H. Press, MD, rhpress@emory.edu, Hui-Kuo G. Shu, MD, PhD, hgshu@emory.edu, Emory University, Department of Radiation Oncology, 1365 Clifton Road NE, Suite CT-104, Atlanta, GA 30322, Telephone: 404-778-3473, Fax: 404-778-5520.

All authors participated significantly and have read and approved the manuscript.

To the best of our knowledge, no conflict of interest, financial or other, exists for any individual author.

Subjects:

Research Funding:

Hui-Kuo G. Shu - R01CA214557, U01CA172027.

Hyunsuk Shim - R01CA214557, U01CA172027.

Nola Hylton – P01CA210961–01A1, R01CA132870.

Elizabeth Gerstner – R01CA211238–01, K23CA169021–04, U01CA15460.

Michael Jacobs – U01CA140204, 1R01CA190299.

James Mountz – U01CA140230.

Brenda Kurland – U01CA148131, U01CA140230, P30CA047904.

David Jaffray – Canadian Institutes for Health Research (CIHR) funding reference number 137992.

Matthias Holdhoff – U01CA172027, Abbvie -- scientific advisory board (compensated), Celgene -- scientific advisory board (compensated).

Lawrence Schwartz – U01CA211205–01, R01CA194783–03.

David Mankoff – P30CA016520–41, R01CA211337–01, R33CA225310–01, P30CA016520.

Paul Kinahan – U01CA148131.

Hannah Linden – U01CA148131.

Daniel Rubin – U01CA190214, U01CA187947.

Lubomir Hadjiiski – U01CA179106.

John Buatti – U01CA140206.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Oncology
  • Radiology, Nuclear Medicine & Medical Imaging
  • POSITRON-EMISSION-TOMOGRAPHY
  • NEWLY-DIAGNOSED GLIOBLASTOMA
  • SQUAMOUS-CELL CARCINOMA
  • RECURRENT PROSTATE-CANCER
  • STANDARDIZED UPTAKE VALUE
  • DIFFUSION-WEIGHTED MRI
  • LOCALLY ADVANCED HEAD
  • ENHANCED CT DATA
  • FDG-PET-CT
  • LUNG-CANCER

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

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Journal Title:

International Journal of Radiation Oncology - Biology - Physics

Volume:

Volume 102, Number 4

Publisher:

, Pages 1219-1235

Type of Work:

Article | Post-print: After Peer Review

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.

Copyright information:

© 2018 Elsevier Inc.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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