Journal of Neuro-Oncology

, Volume 122, Issue 3, pp 497–505 | Cite as

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

  • Robert J. Harris
  • Timothy F. Cloughesy
  • Anthony J. Hardy
  • Linda M. Liau
  • Whitney B. Pope
  • Phioanh L. Nghiemphu
  • Albert Lai
  • Benjamin M. Ellingson
Clinical Study

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.

Keywords

DSC-MRI CBV CBF MTT Deconvolution Glioblastoma 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Robert J. Harris
    • 1
    • 2
  • Timothy F. Cloughesy
    • 3
  • Anthony J. Hardy
    • 1
    • 2
  • Linda M. Liau
    • 4
  • Whitney B. Pope
    • 1
  • Phioanh L. Nghiemphu
    • 3
  • Albert Lai
    • 3
  • Benjamin M. Ellingson
    • 1
    • 2
    • 5
  1. 1.UCLA Brain Tumor Imaging Laboratory (BTIL), Department of Radiological Sciences, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesUSA
  2. 2.Department of Biomedical Physics, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesUSA
  3. 3.Department of Neurology, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesUSA
  4. 4.Department of Neurosurgery, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesUSA
  5. 5.Department of Bioengineering, Henry Samueli School of Engineering and Applied ScienceUniversity of California Los AngelesLos AngelesUSA

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