2004
Quantitative Analysis of Glioblastoma Treatment Using Dynamic Relaxation Contrast MRI at 9.4T1Department of Psychiatry, and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States, 2Department of Biological Science, Columbia University, New York, NY, United States, 3Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, United States, 4Department of Biomedical Engineering, Columbia University, New York, NY, United States, 5Department of Radiation Oncology, Columbia University, New York, NY, United States, 6Columbia University Irving Medical Center, Columbia University, New York, NY, United States, 7Department of Pathology and Cell Biology, Columbia University, New York, NY, United States, 8Departments of Diagnostic Radiology, or Biomedical Engineering, Yale University, New Haven, CT, United States, 9Departments of Neurology, Radiology or Psychiatry, Columbia University, New York, NY, United States
Synopsis
This abstract describes a novel dynamic T2-relaxation contrast magnetic resonance imaging (DRC-MRI) protocol for mapping the cerebral perfusion dynamics in mice. We demonstrate how to quantify cerebral perfusion dynamics with the proposed DRC modeling, which combines features of both dynamic and the steady-state methods. Quantitative analysis on both simulated and in vivo experimental data are performed. We first validate the reliability of our DRC modeling protocol with healthy mice before we apply the protocol on a tumor treatment study. We are able to demonstrate its ability to model the treatment effect of Etoposide on Glioblastoma in mice.
Introduction
Glioblastoma (GBM) is the most aggressive and serious type of brain tumor [1]. Current standard GBM multiforme treatments [2][3][4] are effective in extending the patients' lifespan. Unfortunately, none of these regimens is curative of the disease [5]. By far, Etoposide administration seems to be one of the most promising chemotherapeutics [6][7][8][9]. However, studies that focused on in vivo evaluation of the treatment effects in animal models are limited. One of the potential obstacles is the lack of an imaging modality that can reflect brain metabolism and function at a high spatial resolution.Hemodynamics modeling is widely used in MRI studies of transgenic mouse models. A commonly used method to obtain hemodynamics is the dynamic susceptibility contrast MRI (DSC-MRI) [10]. However, it is suboptimal for our application given the low resolution and distortion artifact [11]; moreover, it requires intravenous (IV) injection of contrast agent (CA) which is difficult to carry out repeatedly [12]. Steady-state imaging methods, such as steady-state contrast-enhanced (SSCE) MRI, boost the spatial resolution but are only viable for cerebral blood volume (CBV) mapping. To resolve these challenges, we implemented our new method called dynamic T2-relaxation contrast MRI (DRC-MRI) in mice, which allows for simultaneous modeling of hemodynamics at high resolution.
Method
Animal Subjects and Experimental Groups: In vivo experimental validation data was acquired from three 6-month-old wild-type (WT) male C57bl/6j mice and one mouse was scanned twice with 48 hours apart to assess test-retest reliability. Mice with GBM treatment used in our study are 4 age-matched C576J/BL mice which were randomly assigned to the treatment and control groups with 2 mice per group. PDGFB(+/+)PTEN(-/-)p53(-/-) GBM cells were administered into the brains of all mice in both experimental groups. 5,000 cells, with a total volume of 1 μL, were stereotactically injected into the brains. In the treatment group, Etoposide was intraperitoneally (IP) injected into the mice at a dosage of 40 mg/kg-body-weight 7 and 14 days after tumor implantation. T2-weighted MRI scans with IP-injected Gadodiamide were acquired for all subjects at 10 and 14 days after the initial treatment.MRI Acquisition: A Bruker BioSpec 94/30 USR MRI with ParaVision 6.0.1 was used for the imaging. Twenty-five T2-weighted RARE scans of the mouse brain were dynamically acquired before and after the IP injections of the Gadodiamide at the dosage of 10 mmol/kg [12].
Hemodynamics Modeling: The proposed pipeline is illustrated in Fig.1. The mechanism of our DRC-MRI is described in Fig.2. This method was developed under the assumption that the IP injection of CA can be thought equivalent to continuous IV injection with dosage decreasing with time. Cerebral blood flow (CBF) was quantified based on the deconvolution model with tissue residue function analyzed in a similar way as the DSC-MRI. The product of CBF and the tissue residual function (R), CBF∙R, relates to the CA concentration time course (CTC) and the arterial input function (AIF) as described in equation $$$CTC(t) = (CBF\cdot R(t))\otimes AIF(t)$$$ [13], and can be isolated with SVD-deconvolution. We approximated the $$$\widehat{AIF}$$$ observed in the DRC experiment (Fig.2G) as a summation of 100 time-shifted mono-exponentially decaying fast bolus pass AIFs (Fig.2D). The CBV was quantified in a similar way as the SSCE-MRI, and the method will be illustrated as follows. With the CBF∙R calculated, the $$$\widehat{CTC}$$$ observed in the DRC experiment was calculated using equation $$$\widehat{CTC} (t)=(CBF\cdot R(t))\otimes(\Sigma_{i=1}^{N}(\alpha (i)\cdot AIF(t - i\cdot \Delta t)))$$$by first convolving each individual $$$AIF(t-i\cdot \Delta t)$$$ (Fig.2D) with the corresponding CBF-scaled TRF $$$CBF\cdot R (t-i\cdot \Delta t)$$$ (Fig.2E) to obtain $$$CTC(t-i\cdot \Delta t)$$$ (Fig.2F), and then summing them together to derive $$$\widehat{CTC}$$$ (Fig.2H). Relative CBF (rCBF) was modeled as the maximum value of $$$CBF\cdot R(t)$$$. Mean transit time (MTT) and wash-in rate (WIR) were derived as previously described in DSC-MRI (Fig.2M) [10].
GBM Treatment Analysis: To quantitatively evaluate the treatment effect at the GBM, we performed a multivariate K-means clustering on the WIR and relative CBV (rCBV) values to segment out the tumor region. Voxels in the scans automatically aggregated into 4 clusters corresponding to gray matter, white matter, cerebral spinal fluid, and tumor. Quantitative analysis was based on the tumor size and the averaged rCBV, rCBF, WIR values inside the tumor region.
Result
To validation DRC test-retest reliability, two scans of the same healthy mouse demonstrate high reliability for both CBF and CBV with whole-brain voxel-wise coefficient of determination R2>0.8 and ROI-wise R2>0.95 (Fig.3B). DRC-derived CBF and CBV were also quantitatively comparable to published results measured by FAIR [14] or SSCE [15] (Fig.3C). Moreover, our GBM study with DRC modeling was able to demonstrate the effective treatment of Etoposide to restrict the proliferation of GBM cells in mice (Fig.4), as previously reported [6][7][8][9]. We also replicated the previous result stating that rCBV was the hemodynamic parameter most sensitive to GBM proliferation [16].Discussion
Our study presents a novel DRC-MRI protocol to generate high-resolution hemodynamic mapping in both WT and tumor mice. We have observed that changes in hemodynamics are reflective of the therapeutic treatment, and this observation demonstrates the potential of DRC-MRI in predicting the therapy response at an early time point in GBM mouse models.Acknowledgements
This study was funded by the Seed Grant Program and Technical Development Grant Program and Matheson Foundation (UR010590). This study was performed at the Zuckerman Mind Brain Behavior Institute MRI Platform, a shared resource.References
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