Literature DB >> 25754089

Relative cerebral blood volume is a potential predictive imaging biomarker of bevacizumab efficacy in recurrent glioblastoma.

Philipp Kickingereder1, Benedikt Wiestler1, Sina Burth1, Antje Wick1, Martha Nowosielski1, Sabine Heiland1, Heinz-Peter Schlemmer1, Wolfgang Wick1, Martin Bendszus1, Alexander Radbruch1.   

Abstract

BACKGROUND: To analyze the relevance of dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI) derived relative cerebral blood volume (rCBV) analysis for predicting response to bevacizumab (BEV) in patients with recurrent glioblastoma (rGB).
METHODS: A total of 127 patients diagnosed with rGB receiving either bevacizumab (71 patients, BEV cohort) or alkylating chemotherapy (56 patients, non-BEV cohort) underwent conventional anatomic MRI and DSC-MRI at baseline and at first follow-up after treatment initiation. The mean rCBV of the contrast-enhancing tumor (cT1) as well as cT1 and fluid-attenuated inversion recovery (FLAIR) volumes at both time points were correlated with progression-free survival (PFS) and overall survival (OS) using Cox proportional hazard models, logistic regression, and the log-rank test.
RESULTS: Baseline rCBV was associated with both PFS (hazard ratio [HR] = 1.3; P < .01) and OS (HR = 1.3; P < .01) in the BEV cohort and predicted 6-month PFS in 82% and 12-month OS in 79% of patients, whereas it was not associated with PFS (HR = 1.0; P = .70) or OS (HR = 1.0; P = .47) in the non-BEV cohort. Corresponding median OS and PFS rates in the BEV cohort for patients with rCBV-values less than 3.92 (optimal threshold from receiver operating characteristic [ROC] analysis of 12-month OS data) were 14.2 and 6.0 months, as compared to 6.6 and 2.8 months for patients with rCBV-values greater than 3.92 (P < .01, respectively). cT1 and FLAIR volumes at first follow-up were significant predictors of 6-month PFS and 12-month OS in the BEV cohort but not in the non-BEV cohort. Corresponding volumes at baseline were not significant in any cohort.
CONCLUSIONS: Pretreatment rCBV is a potential predictive imaging biomarker in BEV-treated rGB but not alkylating chemotherapy-treated rGB, which is superior to volumetric analysis of conventional anatomic MRI and predicts 6-month PFS and 12-month OS in 80% of BEV-treated patients.
© 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:  bevacizumab; biomarker; cerebral blood volume; glioblastoma; rCBV

Mesh:

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Year:  2015        PMID: 25754089      PMCID: PMC4490872          DOI: 10.1093/neuonc/nov028

Source DB:  PubMed          Journal:  Neuro Oncol        ISSN: 1522-8517            Impact factor:   12.300


  27 in total

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  44 in total

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2.  Evidence for rCBV as an early response marker following bevacizumab treatment.

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Journal:  Neuro Oncol       Date:  2015-11       Impact factor: 12.300

3.  pH-weighted amine chemical exchange saturation transfer echoplanar imaging (CEST-EPI) as a potential early biomarker for bevacizumab failure in recurrent glioblastoma.

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4.  Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project.

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Review 5.  Perfusion MRI as the predictive/prognostic and pharmacodynamic biomarkers in recurrent malignant glioma treated with bevacizumab: a systematic review and a time-to-event meta-analysis.

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6.  Predictive imaging marker of bevacizumab efficacy: perfusion MRI.

Authors:  Whitney B Pope
Journal:  Neuro Oncol       Date:  2015-04-24       Impact factor: 12.300

7.  Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma.

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8.  Moving Toward a Consensus DSC-MRI Protocol: Validation of a Low-Flip Angle Single-Dose Option as a Reference Standard for Brain Tumors.

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9.  Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma.

Authors:  Sina Burth; Philipp Kickingereder; Oliver Eidel; Diana Tichy; David Bonekamp; Lukas Weberling; Antje Wick; Sarah Löw; Anne Hertenstein; Martha Nowosielski; Heinz-Peter Schlemmer; Wolfgang Wick; Martin Bendszus; Alexander Radbruch
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