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Fixed-Point MR Imaging for Early Gliobrastoma Detection1Chemistry and Biochemistry, UCLA, Los Angeles, CA, United States, 2UCLA, Los Angeles, CA, United States
Synopsis
Problem Early detection of high-grade malignancy, such as GBM, remains challenging using MRI.
Methods A new approach using continuous-wave and feedback field to reach “fixed-point spin dynamics” was developed to enhances the local magnetic-field gradient variations due to irregular water contents and deoxyhemoglobin concentration in early GBM.
Results In vivo MR images and mappings acquired on orthotopic GBM mice using “fixed-point pulse sequence” shows 3-4 times of enhancement in GBM contrast than the best conventional images acquired.
Conclusion Simulations and in vivo GBM mouse models validated the superior contrast/sensitivity and robustness of fixed-point spin dynamics method towards early GBM detection.
Introduction
Early detection of high-grade malignancy, such
as glioblastoma multiforme (GBM), using
enhanced MRI techniques significantly increases not only the treatment options
available, but also the patients’ survival rate. For this purpose, a
conceptually new approach, named “fixed-point MR imaging”, was developed. An
active feedback electronic device was homebuilt to implement active-feedback
pulse sequences to generate avalanching spin amplification and fixed-point spin
dynamics, which enhances the local magnetic-field gradient variations due to
irregular water contents and deoxyhemoglobin concentration in early GBM.Methods
The general principles of the “active-feedback controlled MR” and details in the device design can be found in our publications. 1-5 Here, the specific pulse sequence to carry out the “fixed-point MR imaging” and its applications to early GBM detection were developed and demonstrated.
(i) First, an active-feedback electronic device was home-built to generate feedback fields from the received FID current. The device is to filter, phase shift, and amplify the signal from the receiver coils and then retransmit the modified signal into the RF transmission coil, with adjustable and programmable feedback phases and gains, allowing us to utilize the active feedback fields in novel ways.
(ii) Next, an innovative pulse sequence was developed for early GBM detection and was statistically tested on in vivo orthotopic GBM mice models, as shown in Fig. 1. It is a phase-cycled repeating block of [cw-pi-cw], where active-feedback field is also on during the cw (continuous wave) pulse to enhance the contrast originated from local magnetic-field gradient variations due to irregular water contents and deoxyhemoglobin concentration in early GBM. In essence, the enhanced GBM contrast arises from “selective self-excitation” 6 and “fixed-point dynamics” (discussed below) generated by the bulk water 1H under active feedback fields.
(iii) Computer simulations for a simple two-component system with small resonance offset and a more realistic early GBM model based on blood-oxygen-level-dependent (BOLD) model 7,8 were carried out (Fig. 2 and Fig. 3, respectively).
(iv) In vivo images of orthotopic GBM mouse models were acquired on a 300 MHz microimaging system incorporated with our active-feedback device (Fig. 4 and Fig. 5).
Results
Stage-1 orthotopic GBM mouse models infected with human U87MG cell line were imaged. Representative results from 2 mice were shown in Fig. 4 and Fig. 5. For a very early stage GBM model (4 days after tumor implantation), fixed-point image shows a positive contrast and reaches a maximum contrast of 72.9% between GBM and normal brain tissue, much higher than conventional spin-echo image (-7.3%) and gradient-echo image (4.8%). The early-stage GBM is also highlighted in the time constant mapping of fixed-point images acquired at different preparation time. Since we can freely adjust the strength and phase of our active feedback field using our home-made device, the fixed-point pulse sequence was further improved by incorporating local-field-dependent active feedback phase. Such improved pulse sequence shows a superior contrast than CPMG pulse sequence with very short pi pulse spacing (τCP = 1 ms): 47.7% over 14.7%, as shown in Fig. 5. Statistical results (N=15) show that this new approach provides 3-4 times of improvements in GBM contrast than the best conventional images acquired, as measured by “contrast-to-noise ratio” (CNR) or “percentage contrast” between tumor and normal brain tissue.Discussion
In dynamical analysis, fixed points are locations in phase space where the evolution of a system is said to cease, without any additional external forces (Fig. 2). Understanding the instability of initial conditions has been used to develop non-linear evolution schemes which can be used to amplify small differences in resonance offset,1 such as is the case between white and gray matter in the brain.4,5 The joint interaction between the continuous wave and the feedback field allows for extended non-linear evolution, capable of producing useful contrast enhancement for imaging purposes. For early stages of GBM growth, differences in magnetic susceptibility originate from variations in blood oxygenation level, increased water content in the compact extracellular space of the tumor, and enhanced angiogenesis (the rapid development of new blood vessels).7,8 The use of a continuous wave in the presence of the active feedback field is able to produce unique fixed-point spin dynamics, resulting in positive, robust contrast between the early-stage GBM and the normal brain tissue.Conclusion
Computer simulations and in vivo orthotopic xenografts GBM mouse models validated the superior contrast/sensitivity and robustness of fixed-point spin dynamics method towards early GBM detection. Statistical results (N=15) for GBM mouse models at various cancer stages, alternative fixed-point pulse sequences with further improved performance will also be presented.Acknowledgements
No acknowledgement found.References
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2. Huang SY, Wolahan SM, Mathern GW, et al. Improving MRI Differentiation of Gray and White Matter in Epileptogenic Lesions Based on Nonlinear Feedback. Magn Reson Med. 2006;56:776-786.
3. Huang SY, Yang SS, Lin YY. Sensitivity of feedback-enhanced MRI contrast to macroscopic and microscopic field variations. Magn Reson Med. 2009;61:925-936.
4. Datta S, Huang SY, Lin YY. Contrast Enhancement by Feedback Fields in Magnetic Resonance Imaging. J Phys Chem B. 2006;110:22071-22078.
5. Huang SY, Furuyama JK, Lin YY. Designing feedback based contrast enhancement for in vivo imaging. Magn Reson Mater Phy. 2006;19:333-346.
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8. Wang G, Tsai SL, Li Z, et al. Towards Early Glioblastoma Detection: In Vivo MR Imaging and Spin Dynamics Simulations (invited paper to Cancers, submitted).
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