Literature DB >> 26049816

Response Assessment and Magnetic Resonance Imaging Issues for Clinical Trials Involving High-Grade Gliomas.

Jerrold L Boxerman1, Benjamin M Ellingson.   

Abstract

There exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in nonenhancing T2 hyperintensity, and the phenomena of pseudoresponse and pseudoprogression in the setting of antiangiogenic and chemoradiation therapies, respectively. Advanced physiological magnetic resonance imaging (MRI), including diffusion and perfusion (dynamic susceptibility contrast MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multicenter trials for high-grade gliomas. This review chapter highlights the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.

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Year:  2015        PMID: 26049816     DOI: 10.1097/RMR.0000000000000054

Source DB:  PubMed          Journal:  Top Magn Reson Imaging        ISSN: 0899-3459


  8 in total

Review 1.  GBM radiosensitizers: dead in the water…or just the beginning?

Authors:  Ranjit S Bindra; Anthony J Chalmers; Sydney Evans; Mark Dewhirst
Journal:  J Neurooncol       Date:  2017-07-31       Impact factor: 4.130

Review 2.  High-grade glioma management and response assessment-recent advances and current challenges.

Authors:  M N Khan; A M Sharma; M Pitz; S K Loewen; H Quon; A Poulin; M Essig
Journal:  Curr Oncol       Date:  2016-08-12       Impact factor: 3.677

Review 3.  Response Assessment in Neuro-Oncology Clinical Trials.

Authors:  Patrick Y Wen; Susan M Chang; Martin J Van den Bent; Michael A Vogelbaum; David R Macdonald; Eudocia Q Lee
Journal:  J Clin Oncol       Date:  2017-06-22       Impact factor: 44.544

4.  Linearization improves the repeatability of quantitative dynamic contrast-enhanced MRI.

Authors:  Kyle M Jones; Mark D Pagel; Julio Cárdenas-Rodríguez
Journal:  Magn Reson Imaging       Date:  2017-11-15       Impact factor: 2.546

5.  Optimization of Acquisition and Analysis Methods for Clinical Dynamic Susceptibility Contrast MRI Using a Population-Based Digital Reference Object.

Authors:  N B Semmineh; L C Bell; A M Stokes; L S Hu; J L Boxerman; C C Quarles
Journal:  AJNR Am J Neuroradiol       Date:  2018-10-11       Impact factor: 3.825

6.  A Simple Automated Method for Detecting Recurrence in High-Grade Glioma.

Authors:  T K Yanagihara; J Grinband; J Rowley; K A Cauley; A Lee; M Garrett; M Afghan; A Chu; T J C Wang
Journal:  AJNR Am J Neuroradiol       Date:  2016-07-14       Impact factor: 3.825

Review 7.  Quantitative magnetic resonance imaging biomarkers in oncological clinical trials: Current techniques and standardization challenges.

Authors:  Jie Deng; Yi Wang
Journal:  Chronic Dis Transl Med       Date:  2017-03-11

8.  A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials.

Authors:  Natenael B Semmineh; Ashley M Stokes; Laura C Bell; Jerrold L Boxerman; C Chad Quarles
Journal:  Tomography       Date:  2017-03
  8 in total

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