Literature DB >> 29966725

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

Robert H Press1, Hui-Kuo G Shu2, Hyunsuk Shim2, James M Mountz3, Brenda F Kurland4, Richard L Wahl5, Ella F Jones6, Nola M Hylton6, Elizabeth R Gerstner7, Robert J Nordstrom8, Lori Henderson8, Karen A Kurdziel9, Bhadrasain Vikram10, Michael A Jacobs11, Matthias Holdhoff12, Edward Taylor13, David A Jaffray13, Lawrence H Schwartz14, David A Mankoff15, Paul E Kinahan16, Hannah M Linden17, Philippe Lambin18, Thomas J Dilling19, Daniel L Rubin20, Lubomir Hadjiiski21, John M Buatti22.   

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 © 2018 Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29966725      PMCID: PMC6348006          DOI: 10.1016/j.ijrobp.2018.06.023

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  191 in total

1.  Dynamic contrast-enhanced MR imaging in predicting progression of enhancing lesions persisting after standard treatment in glioblastoma patients: a prospective study.

Authors:  Roh-Eul Yoo; Seung Hong Choi; Tae Min Kim; Chul-Kee Park; Sung-Hye Park; Jae-Kyung Won; Il Han Kim; Soon Tae Lee; Hye Jeong Choi; Sung-Hye You; Koung Mi Kang; Tae Jin Yun; Ji-Hoon Kim; Chul-Ho Sohn
Journal:  Eur Radiol       Date:  2016-12-14       Impact factor: 5.315

2.  Prognostic significance of hypoxic PET using (18)F-FAZA and (62)Cu-ATSM in non-small-cell lung cancer.

Authors:  Tomonari Kinoshita; Hirofumi Fujii; Yuichiro Hayashi; Ikuo Kamiyama; Takashi Ohtsuka; Hisao Asamura
Journal:  Lung Cancer       Date:  2015-11-28       Impact factor: 5.705

3.  Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans.

Authors:  Ethan J Ulrich; John J Sunderland; Brian J Smith; Imran Mohiuddin; Jessica Parkhurst; Kristin A Plichta; John M Buatti; Reinhard R Beichel
Journal:  Med Phys       Date:  2017-11-23       Impact factor: 4.071

Review 4.  Hypoxia as a cause of treatment failure in non-small cell carcinoma of the lung.

Authors:  Odd Terje Brustugun
Journal:  Semin Radiat Oncol       Date:  2014-11-29       Impact factor: 5.934

5.  Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy.

Authors:  Reza Farjam; Christina I Tsien; Felix Y Feng; Diana Gomez-Hassan; James A Hayman; Theodore S Lawrence; Yue Cao
Journal:  Neuro Oncol       Date:  2013-12-09       Impact factor: 12.300

6.  Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial.

Authors:  Kathleen M Schmainda; Zheng Zhang; Melissa Prah; Bradley S Snyder; Mark R Gilbert; A Gregory Sorensen; Daniel P Barboriak; Jerrold L Boxerman
Journal:  Neuro Oncol       Date:  2015-02-02       Impact factor: 12.300

7.  Optimum lean body formulation for correction of standardized uptake value in PET imaging.

Authors:  Abdel K Tahari; David Chien; Javad R Azadi; Richard L Wahl
Journal:  J Nucl Med       Date:  2014-06-24       Impact factor: 10.057

8.  Role of FDG-PET in the implementation of involved-node radiation therapy for Hodgkin lymphoma patients.

Authors:  Théodore Girinsky; Anne Aupérin; Vincent Ribrag; Manel Elleuch; Christophe Fermé; Guillaume Bonniaud; Claude Ruelle; Jean-Louis Alberini; Aljosa Celebic; Véronique Edeline
Journal:  Int J Radiat Oncol Biol Phys       Date:  2014-07-08       Impact factor: 7.038

9.  Simulating the Effect of Spectroscopic MRI as a Metric for Radiation Therapy Planning in Patients with Glioblastoma.

Authors:  J Scott Cordova; Shravan Kandula; Saumya Gurbani; Jim Zhong; Mital Tejani; Oluwatosin Kayode; Kirtesh Patel; Roshan Prabhu; Eduard Schreibmann; Ian Crocker; Chad A Holder; Hyunsuk Shim; Hui-Kuo Shu
Journal:  Tomography       Date:  2016-12

Review 10.  The Potential of Radiomic-Based Phenotyping in Precision Medicine: A Review.

Authors:  Hugo J W L Aerts
Journal:  JAMA Oncol       Date:  2016-12-01       Impact factor: 31.777

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  13 in total

1.  Tumor Subregion Evolution-Based Imaging Features to Assess Early Response and Predict Prognosis in Oropharyngeal Cancer.

Authors:  Jia Wu; Michael F Gensheimer; Nasha Zhang; Meiying Guo; Rachel Liang; Carrie Zhang; Nancy Fischbein; Erqi L Pollom; Beth Beadle; Quynh-Thu Le; Ruijiang Li
Journal:  J Nucl Med       Date:  2019-08-16       Impact factor: 10.057

Review 2.  MRI-guided Radiation Therapy: An Emerging Paradigm in Adaptive Radiation Oncology.

Authors:  Ricardo Otazo; Philippe Lambin; Jean-Philippe Pignol; Mark E Ladd; Heinz-Peter Schlemmer; Michael Baumann; Hedvig Hricak
Journal:  Radiology       Date:  2020-12-22       Impact factor: 11.105

Review 3.  CT Texture Analysis Challenges: Influence of Acquisition and Reconstruction Parameters: A Comprehensive Review.

Authors:  Mathilde Espinasse; Stéphanie Pitre-Champagnat; Benoit Charmettant; Francois Bidault; Andreas Volk; Corinne Balleyguier; Nathalie Lassau; Caroline Caramella
Journal:  Diagnostics (Basel)       Date:  2020-04-28

4.  Magnetic resonance imaging-derived radiomic signature predicts locoregional failure after organ preservation therapy in patients with hypopharyngeal squamous cell carcinoma.

Authors:  Che-Yu Hsu; Shih-Min Lin; Ngan Ming Tsang; Yu-Hsiang Juan; Chun-Wei Wang; Wei-Chung Wang; Sung-Hsin Kuo
Journal:  Clin Transl Radiat Oncol       Date:  2020-08-31

Review 5.  Medical imaging and nuclear medicine: a Lancet Oncology Commission.

Authors:  Hedvig Hricak; May Abdel-Wahab; Rifat Atun; Miriam Mikhail Lette; Diana Paez; James A Brink; Lluís Donoso-Bach; Guy Frija; Monika Hierath; Ola Holmberg; Pek-Lan Khong; Jason S Lewis; Geraldine McGinty; Wim J G Oyen; Lawrence N Shulman; Zachary J Ward; Andrew M Scott
Journal:  Lancet Oncol       Date:  2021-03-04       Impact factor: 41.316

Review 6.  Quantitative imaging for radiotherapy purposes.

Authors:  Oliver J Gurney-Champion; Faisal Mahmood; Marcel van Schie; Robert Julian; Ben George; Marielle E P Philippens; Uulke A van der Heide; Daniela Thorwarth; Kathrine R Redalen
Journal:  Radiother Oncol       Date:  2020-02-27       Impact factor: 6.280

Review 7.  Medical physics challenges in clinical MR-guided radiotherapy.

Authors:  Christopher Kurz; Giulia Buizza; Guillaume Landry; Florian Kamp; Moritz Rabe; Chiara Paganelli; Guido Baroni; Michael Reiner; Paul J Keall; Cornelis A T van den Berg; Marco Riboldi
Journal:  Radiat Oncol       Date:  2020-05-05       Impact factor: 3.481

8.  Technical Note: A methodology for improved accuracy in stopping power estimation using MRI and CT.

Authors:  Jessica E Scholey; Dharshan Chandramohan; Tarun Naren; William Liu; Peder Eric Zufall Larson; Atchar Sudhyadhom
Journal:  Med Phys       Date:  2020-11-20       Impact factor: 4.071

9.  Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy.

Authors:  Alex Anh-Tu Nguyen; Vignesh A Arasu; Fredrik Strand; Wen Li; Natsuko Onishi; Jessica Gibbs; Ella F Jones; Bonnie N Joe; Laura J Esserman; David C Newitt; Nola M Hylton
Journal:  Tomography       Date:  2020-06

Review 10.  Clinical Trial Design and Development Work Group Within the Quantitative Imaging Network.

Authors:  Ella F Jones; John M Buatti; Hui-Kuo Shu; Richard L Wahl; Brenda F Kurland; Hannah M Linden; David A Mankoff; Daniel L Rubin; Darrell Tata; Robert J Nordstrom; Lubomir Hadjiyski; Matthias Holdhoff; Lawrence H Schwartz
Journal:  Tomography       Date:  2020-06
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