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Published in: Journal of Neuro-Oncology 1/2017

01-03-2017 | Clinical Study

Quantitative multi-modal MR imaging as a non-invasive prognostic tool for patients with recurrent low-grade glioma

Authors: Evan Neill, Tracy Luks, Manisha Dayal, Joanna J. Phillips, Arie Perry, Llewellyn E. Jalbert, Soonmee Cha, Annette Molinaro, Susan M. Chang, Sarah J. Nelson

Published in: Journal of Neuro-Oncology | Issue 1/2017

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Abstract

Low-grade gliomas can vary widely in disease course and therefore patient outcome. While current characterization relies on both histological and molecular analysis of tissue resected during surgery, there remains high variability within glioma subtypes in terms of response to treatment and outcome. In this study we hypothesized that parameters obtained from magnetic resonance data would be associated with progression-free survival for patients with recurrent low-grade glioma. The values considered were derived from the analysis of anatomic imaging, diffusion weighted imaging, and 1H magnetic resonance spectroscopic imaging data. Metrics obtained from diffusion and spectroscopic imaging presented strong prognostic capability within the entire population as well as when restricted to astrocytomas, but demonstrated more limited efficacy in the oligodendrogliomas. The results indicate that multi-parametric imaging data may be applied as a non-invasive means of assessing prognosis and may contribute to developing personalized treatment plans for patients with recurrent low-grade glioma.
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Metadata
Title
Quantitative multi-modal MR imaging as a non-invasive prognostic tool for patients with recurrent low-grade glioma
Authors
Evan Neill
Tracy Luks
Manisha Dayal
Joanna J. Phillips
Arie Perry
Llewellyn E. Jalbert
Soonmee Cha
Annette Molinaro
Susan M. Chang
Sarah J. Nelson
Publication date
01-03-2017
Publisher
Springer US
Published in
Journal of Neuro-Oncology / Issue 1/2017
Print ISSN: 0167-594X
Electronic ISSN: 1573-7373
DOI
https://doi.org/10.1007/s11060-016-2355-y

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