TY - JOUR
T1 - The Use of Quantitative Imaging in Radiation Oncology
T2 - A Quantitative Imaging Network (QIN) Perspective
AU - Press, Robert H.
AU - Shu, Hui-Kuo G.
AU - Shim, Hyunsuk
AU - Mountz, James M.
AU - Kurland, Brenda F.
AU - Wahl, Richard L.
AU - Jones, Ella F.
AU - Hylton, Nola M.
AU - Gerstner, Elizabeth R.
AU - Nordstrom, Robert J.
AU - Henderson, Lori
AU - Kurdziel, Karen A.
AU - Vikram, Bhadrasain
AU - Jacobs, Michael A.
AU - Holdhoff, Matthias
AU - Taylor, Edward
AU - Jaffray, David A.
AU - Schwartz, Lawrence H.
AU - Mankoff, David A.
AU - Kinahan, Paul E.
AU - Linden, Hannah M.
AU - Lambin, Philippe
AU - Dilling, Thomas J.
AU - Rubin, Daniel L.
AU - Hadjiiski, Lubomir
AU - Buatti, John M.
PY - 2018/11/15
Y1 - 2018/11/15
N2 - 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. (C) 2018 Elsevier Inc. All rights reserved.
AB - 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. (C) 2018 Elsevier Inc. All rights reserved.
KW - POSITRON-EMISSION-TOMOGRAPHY
KW - CELL LUNG-CANCER
KW - NEWLY-DIAGNOSED GLIOBLASTOMA
KW - STANDARDIZED UPTAKE VALUE
KW - MAGNETIC-RESONANCE-SPECTROSCOPY
KW - ENHANCED COMPUTED-TOMOGRAPHY
KW - EXTERNAL-BEAM RADIOTHERAPY
KW - LOCALIZED PROSTATE-CANCER
KW - DIFFUSION-WEIGHTED MRI
KW - ADVANCED RECTAL-CANCER
U2 - 10.1016/j.ijrobp.2018.06.023
DO - 10.1016/j.ijrobp.2018.06.023
M3 - (Systematic) Review article
C2 - 29966725
SN - 0360-3016
VL - 102
SP - 1219
EP - 1235
JO - International Journal of Radiation Oncology Biology Physics
JF - International Journal of Radiation Oncology Biology Physics
IS - 4
ER -