Development of Imaging Biomarkers for Clinical Trials: Applications in Glioblastoma Multiforme

• Activity Number: 189
• Type: Invited
• Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
• Sponsor: WNAR
• Author(s): Hyun (Grace) Kim*+ and Jing Huo and Matt Brown and Jonathan Goldin
• Companies: University of California, Los Angeles and University of California, Los Angeles and University of California, Los Angeles and University of California, Los Angeles
• Keywords: Biomarker ; Imaging ; Predictive Classifier ; MRI ; Oncology ; Surrogate Outcome

Abstract

The drug development and evaluation of oncology requires efficient strategies to predict the patient population who will benefit from treatment as well as surrogate imaging outcome in early phase of treatment. As an example, Glioblastoma Multiforme (GBM) will be used in this paper. GBM is a grade IV glioma tumor, and are the most aggressive and lethal primary brain cancer. Not all patients have responded to the standard therapy. Considering the short life expectancy for patients with GBM, it is critically important to predict which patients will benefit from the treatment. Apparent Diffusion Coefficient (ADC) from Magnetic Resonance Imaging (MRI) shows the cellularity or cystic regions of GBM and Fluid Attenuation Inversion Recovery (FLAIR) shows the effect if fluid. We proposed new quantitative imaging "biomarker", which is derived from estimated mixture of Gaussian distribution.