Literature DB >> 32190946

Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma.

Fabrício Guimarães Gonçalves1, Sanjeev Chawla2, Suyash Mohan2.   

Abstract

Glioblastoma is the most common and most malignant primary brain tumor. Despite aggressive multimodal treatment, its prognosis remains poor. Even with continuous developments in MRI, which has provided us with newer insights into the diagnosis and understanding of tumor biology, response assessment in the posttherapy setting remains challenging. We believe that the integration of additional information from advanced neuroimaging techniques can further improve the diagnostic accuracy of conventional MRI. In this article, we review the utility of advanced neuroimaging techniques such as diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, proton magnetic resonance spectroscopy, and chemical exchange saturation transfer in characterizing and evaluating treatment response in patients with glioblastoma. We will also discuss the existing challenges and limitations of using these techniques in clinical settings and possible solutions to avoiding pitfalls in study design, data acquisition, and analysis for future studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:978-997.
© 2020 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  arterial spin labeling; artificial intelligence; chemical exchange saturation transfer; diffusion weighted imaging; dynamic contrast enhancement; dynamic susceptibility contrast; glioblastoma; perfusion weighted imaging; proton MR spectroscopy

Mesh:

Year:  2020        PMID: 32190946      PMCID: PMC7492394          DOI: 10.1002/jmri.27105

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  136 in total

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Review 2.  Deep Learning in Radiology.

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Review 4.  Diffusion and diffusion tensor imaging in brain cancer.

Authors:  Elizabeth R Gerstner; A Gregory Sorensen
Journal:  Semin Radiat Oncol       Date:  2011-04       Impact factor: 5.934

5.  Quantification of cerebral metabolites in glioma patients with proton MR spectroscopy using T2 relaxation time correction.

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Journal:  Magn Reson Imaging       Date:  2002-05       Impact factor: 2.546

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

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7.  Magnetic resonance spectroscopic imaging in the era of pseudoprogression and pseudoresponse in glioblastoma patient management.

Authors:  Hyunsuk Shim; Chad A Holder; Jeffrey J Olson
Journal:  CNS Oncol       Date:  2013-09

8.  Role of proton magnetic resonance spectroscopy in differentiating oligodendrogliomas from astrocytomas.

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Journal:  J Neuroimaging       Date:  2010-01       Impact factor: 2.486

9.  Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides.

Authors:  Jinyuan Zhou; Erik Tryggestad; Zhibo Wen; Bachchu Lal; Tingting Zhou; Rachel Grossman; Silun Wang; Kun Yan; De-Xue Fu; Eric Ford; Betty Tyler; Jaishri Blakeley; John Laterra; Peter C M van Zijl
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Review 10.  Radiation Necrosis, Pseudoprogression, Pseudoresponse, and Tumor Recurrence: Imaging Challenges for the Evaluation of Treated Gliomas.

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Journal:  Contrast Media Mol Imaging       Date:  2018-12-02       Impact factor: 3.161

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  3 in total

Review 1.  Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma.

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Journal:  NMR Biomed       Date:  2022-03-15       Impact factor: 4.478

2.  Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine.

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Review 3.  Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism.

Authors:  Manoj Kumar; Ravi Prakash Reddy Nanga; Gaurav Verma; Neil Wilson; Jean Christophe Brisset; Kavindra Nath; Sanjeev Chawla
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  3 in total

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