Literature DB >> 31579522

Standardized MRI assessment of high-grade glioma response: a review of the essential elements and pitfalls of the RANO criteria.

Dewen Yang1.   

Abstract

Accurately evaluating response in the treatment of high-grade gliomas presents considerable challenges. This review looks at the advancements made in response criteria while critically outlining remaining weaknesses, and directs our vision toward promising endpoints to come. The 2010 guidelines from the Response Assessment in Neuro-Oncology (RANO) working group have enhanced interpretation of clinical trials involving novel treatments for high-grade glioma. Yet, while the criteria are considered clinically applicable to high-grade glioma trials, as well as reasonably accurate and reproducible, RANO lacks sufficient detail for consistent implementation in certain aspects and leaves some issues from the original Macdonald guidelines unresolved. To provide the most accurate assessment of response to therapeutic intervention currently possible, it is essential that trial oncologists and radiologists not only have a solid understanding of RANO guidelines, but also proper insight into the inherent limitations of the criteria. With the expectation of improved data collection as a standard, the author anticipates that the next high-grade glioma response criteria updates will incorporate advanced MRI methods and quantitative tumor volume measurements, availing a more accurate interpretation of response in the future.
© The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  MRI; RANO criteria; clinical trials; high grade glioma

Year:  2015        PMID: 31579522      PMCID: PMC6760341          DOI: 10.1093/nop/npv023

Source DB:  PubMed          Journal:  Neurooncol Pract        ISSN: 2054-2577


  52 in total

Review 1.  Treatment of glioblastoma multiforme: a new standard.

Authors:  John W Henson
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2.  Postoperative changes in the brain: MR imaging findings in patients without neoplasms.

Authors:  N Sato; R A Bronen; G Sze; Y Kawamura; W Coughlin; C M Putman; D D Spencer
Journal:  Radiology       Date:  1997-09       Impact factor: 11.105

3.  Potential utility of conventional MRI signs in diagnosing pseudoprogression in glioblastoma.

Authors:  R J Young; A Gupta; A D Shah; J J Graber; Z Zhang; W Shi; A I Holodny; A M P Omuro
Journal:  Neurology       Date:  2011-05-31       Impact factor: 9.910

4.  Outcomes and prognostic factors in recurrent glioma patients enrolled onto phase II clinical trials.

Authors:  E T Wong; K R Hess; M J Gleason; K A Jaeckle; A P Kyritsis; M D Prados; V A Levin; W K Yung
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Journal:  J Clin Oncol       Date:  2008-12-15       Impact factor: 44.544

Review 6.  Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas.

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7.  Reporting results of cancer treatment.

Authors:  A B Miller; B Hoogstraten; M Staquet; A Winkler
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8.  FDA drug approval summary: bevacizumab (Avastin) as treatment of recurrent glioblastoma multiforme.

Authors:  Martin H Cohen; Yuan Li Shen; Patricia Keegan; Richard Pazdur
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Authors:  D S Chow; J Qi; X Guo; V Z Miloushev; F M Iwamoto; J N Bruce; A B Lassman; L H Schwartz; A Lignelli; B Zhao; C G Filippi
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10.  Early postoperative magnetic resonance imaging following nonneoplastic cortical resection.

Authors:  M M Henegar; C J Moran; D L Silbergeld
Journal:  J Neurosurg       Date:  1996-02       Impact factor: 5.115

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  10 in total

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