Format

Send to

Choose Destination
J Neurooncol. 2015 May;122(3):497-505. doi: 10.1007/s11060-015-1755-8. Epub 2015 Mar 15.

MRI perfusion measurements calculated using advanced deconvolution techniques predict survival in recurrent glioblastoma treated with bevacizumab.

Author information

1
UCLA Brain Tumor Imaging Laboratory (BTIL), Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.

Abstract

Bevacizumab is a therapeutic drug used in treatment of recurrent glioblastoma to inhibit angiogenesis. Treatment response is often monitored through the use of perfusion MRI measures of cerebral blood volume, flow, and other pharmacokinetic parameters; however, most methods for deriving these perfusion parameters can produce errors depending on bolus kinetics. Recently, a number of new methods have been developed to overcome these challenges. In the current study we examine cerebral blood volume and blood flow characteristics in 45 recurrent glioblastoma patients before and after treatment with bevacizumab. Perfusion MRI data was processed using a standard single value decomposition (SVD) technique, two block-circulant SVD techniques, and a Bayesian estimation technique. A proportional hazards model showed that patients with a large decrease in relative blood volume (RBV) after treatment had extended overall survival (P = 0.0048). Patients with large pre-treatment relative blood flow (RBF) showed extended progression-free survival (P = 0.0216) and overall survival (P = 0.0112), and patients with a large decrease in RBF following treatment showed extended overall survival (P = 0.0049). These results provide evidence that blood volume and blood flow measurements can be used as biomarkers in patients treated with bevacizumab.

PMID:
25773062
DOI:
10.1007/s11060-015-1755-8
[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Springer Icon for eScholarship, California Digital Library, University of California
Loading ...
Support Center