CELLULAR INVASION, MOTILITY, AND PROLIFERATION LEVEL ESTIMATES (CIMPLE MAPS): APPLICATION TO TEMOZOLOMIDE- AND BEVACIZUMAB-TREATED PATIENTS
Authors: Benjamin M Ellingson, Whitney B Pope, Albert Lai, Phioanh L Nghiemphu, Timothy F Cloughesy
Journal: Neuro-Oncology (2010)

J Neurooncol (2011) 105:91–101 DOI 10.1007/s11060-011-0567-8 C L IN I C AL S T U D Y - P A T IE N T S T U D Y Cell invasion, motility, and pr olifer ation level estimate (CIMPLE) maps der ived fr om ser ial diffusion MR images in r ecur r ent glioblastoma tr eated with bevacizumab Benjamin M. Ellingson • Timothy F. Cloughesy Alber t Lai • Phioanh L. Nghiemphu • Whitney B. Pope Received: 23 December 2010 / Accepted: 17 March 2011 / Published online: 26 March 2011 O Springer Science+Business Media, LLC. 2011 Abstr act Microscopic invasion of tumor cells and undetected tumor proliferation is the primary reason for a dismal prognosis in glioblastoma patients. Identification and quantification of spatially localized brain regions undergoing high rates of cell migration and proliferation is critical for improving patient survival; however, there are currently no non-invasive imaging biomarkers for esti- mating proliferation and migration rates of human gliomas in vivo. To accomplish this, we developed CIMPLE (cell invasion, motility, and proliferation level estimates) image maps using serial diffusion MRI scans and a solution to a glioma growth model equation. CIMPLE represent a novel method of quantifying the level of aggressive malignant behavior. In the current pilot study, we demonstrate the utility of CIMPLE maps to predict progression free sur- vival (PFS) and overall survival (OS) in 26 recurrent glioblastoma patients treated with bevacizumab from our Neuro-Oncology database. Voxel-wise estimates of cell proliferation rate predicted spatial regions of contrast enhancement in 35% of patients. A linear correlation was found between the mean proliferation rate and progression- free survival (PFS; P  0.0001) as well as overall survival (OS; P = 0.0093). Similarly, the mean proliferation rate was able to stratify patients with early and late PFS as well as OS. B. M. Ellingson (& ) W. B. Pope Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024, USA e-mail: bellingson@mednet.ucla.edu; ellingsb@gmail.com T. F. Cloughesy A. Lai P. L. Nghiemphu Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA Keywor ds Diffusion MRI Glioblastoma Bevacizumab Biomarkers CIMPLE maps Intr oduction Glioblastoma multiforme (GBM) is a malignant brain tumor with a very poor patient prognosis. Currently, the standard of care consists of surgical resection, concurrent radiotherapy and chemotherapy, followed by adjuvant chemotherapy [1]. Despite an aggressive approach to tumor control, all GBMs eventually progress. This eventual tumor progression is thought to be due to microscopic invasion of tumor cells undetected by standard imaging techniques [2]. Thus, there is a significant need for non-invasive imaging biomarkers that are sensitive to the presence and activity of invading tumor cells. Recently, a new magnetic resonance imaging biomarker was developed termed cell invasion, motility, and prolif- eration level estimates (CIMPLE maps) [3, 4]. The approach is to use serial diffusion-weighted MRI (DWI) data in the same patient, then solve a partial differential equation describing tumor growth dynamics, assuming the apparent diffusion coefficient (ADC) is a direct reflection of tumor cell density [5]. This partial differential equation, referred to generically as the glioma growth or diffusion– reaction equation, has been used in a number of simulation studies meant to describe the macroscopic growth and invasion of gliomas under a variety of treatment conditions [6–8]. These simulations typically ascribe singular values for ‘‘cell diffusion rate’’ and ‘‘cell proliferation rate’’ to describe growth and invasion of the tumor as a whole. Alternatively, CIMPLE maps utilize serial DWIs to solve the glioma growth equation on a voxel-wise basis for microscopic growth and invasion, creating image maps of