Apparent diffusion coefficient changes predict survival after intra-arterial bevacizumab treatment in recurrent glioblastoma

Background The aim of this study was to determine whether apparent diffusion coefficient (ADC) bi-component curve-fitting histogram analysis and volume percentage change (VPC) prior to bevacizumab treatment can stratify progression-free survival (PFS) and overall survival (OS) in patients with glioblastoma multiforme (GBM) on first recurrence. Methods We retrospectively evaluated 17 patients with recurrent GBM who received bevacizumab and fotemustine ( n = 13) or only bevacizumab ( n = 4) on first recurrence at our institution between December 2009 and July 2015. Both T2/FLAIR abnormalities and enhancing tumor on T1 images were mapped to the ADC images. ADC-L and ADC-M values were obtained trough bi-Gaussian curve fitting histogram analysis. Furthermore, the study population was dichotomized into two subgroups: patients displaying a reduction in enhancing tumor volume of either >55% or <55% between the mean value calculated at baseline and first follow-up. Subsequently, a second dichotomization was performed according to a reduction in the T2 / FLAIR volume >41% or <41% at first check after treatment. OS and PFS were assessed using volume parameters in a Cox regression model adjusted for significant clinical parameters. Results In univariate analysis, contrast-enhanced (CE)-ADC-L was significantly predictive of PFS ( p = 0.01) and OS ( p = 0.03). When we dichotomized our sample using the 55% cut-off for enhancing tumor volume, CE-VPC was able to predict PFS ( p = 0.01) but not OS ( p = 0.08). In multivariate analysis, only the CE-ADC-L was predictive of PFS ( p = 0.01), albeit not predictive of OS ( p = 0.14). CE-ADC-M, T2/FLAIR-ADC-L, T2/FLAIR-ADC, and T2/FLAIR VPC were not significantly predictive of PFS and OS ( p > 0.05) in both univariate and multivariate analysis. Conclusions CE-ADC and CE-VPC can stratify PFS for patients with recurrent glioblastoma prior to bevacizumab treatment.

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A change in the apparent diffusion coefficient after treatment with bevacizumab is associated with decreased survival in patients with recurrent glioblastoma multiforme

British Journal of Radiology ◽

10.1259/bjr/24774491 ◽

2012 ◽

Vol 85 (1012) ◽

pp. 382-389 ◽

Cited By ~ 15

Author(s):

M J Paldino ◽

A Desjardins ◽

H S Friedman ◽

J J Vredenburgh ◽

D P Barboriak

Keyword(s):

Diffusion Coefficient ◽

Glioblastoma Multiforme ◽

Apparent Diffusion Coefficient ◽

Recurrent Glioblastoma ◽

Recurrent Glioblastoma Multiforme ◽

Apparent Diffusion

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ADC quantification to classify patients candidate to receive bevacizumab treatment for recurrent glioblastoma

Acta Radiologica ◽

10.1177/0284185119864842 ◽

2019 ◽

Vol 61 (3) ◽

pp. 404-413

Author(s):

Beatriz Asenjo García ◽

Félix Navarro Guirado ◽

Fátima Nagib Raya ◽

María Vidal Denis ◽

Francisco Bravo Rodríguez ◽

...

Keyword(s):

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Magnetic Resonance Images ◽

Recurrent Glioblastoma ◽

High Grade ◽

Rank Tests ◽

Apparent Diffusion ◽

Antiangiogenic Drugs ◽

High Grade Gliomas ◽

Log Rank Tests

Background Recurrent high-grade gliomas progressing after surgery and temozolomide plus radiation therapy have traditionally been treated using antiangiogenic drugs as the first-line therapy. Since the phase 3 EORTC 26101 trial showed no significant benefit of administering antiangiogenic drugs, the need to identify a biomarker to classify subgroups of potential responders has increased. Purpose To investigate the feasibility of using apparent diffusion coefficient as a predictor of the response of recurrent high-grade gliomas to bevacizumab or classifier for patients showing better response. Material and Methods This retrospective study analyzed magnetic resonance images obtained from 39 patients at the time of high-grade glioma progression who were treated using bevacizumab. The apparent diffusion coefficient maps were quantified and modelled as a mixture of Gaussian functions. The correlation of their descriptors and the time to second progression was studied. Log-rank tests were performed to determine the power of these descriptors as the classifiers for patients exhibiting better survival. Results None of the descriptors showed correlation with time to second progression (r < 0.35) but several of them stratified subgroups showing a better time to second progression passing log-rank tests ( P < 0.02). Conclusion Apparent diffusion coefficient cannot be used to predict the time to second progression of recurrent high-grade gliomas treated with bevacizumab, but it can stratify groups with better time to second progression distributions.

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