WIMP: SELF-NAVIGATING MAGNETIZATION TRANSFER POOL MAPPING WITH STIMULATED ECHOES

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Introduction: Magnetization transfer (MT) provides information on the rate of exchange as well as relative amount of bound macromolecules present in tissue. MT has been shown useful in detecting early white matter degeneration, such as with multiple sclerosis [6]. However, quantitative MT sequences require complex multi-parametric fits. Therefore, sequences were normally only combined with simple on or off-resonant pre-pulses, from which semi-quantitative parameters, such as MTR, can be computed. However, these variants of MT sequences do not map pure bio-physical parameters and can be confounded by several factors. Transfer rate and relative fraction sizes of bound and free water pools are expected to provide more quantitative information on tissue composition [4] but presently require complicated multi-parametric models and prohibitively long imaging times [3-5]. Recently, Ropele et al. [1] introduced a novel method that provides direct measurement of bound macromolecular water content, which is based on a stimulated echo (STE) preparation scheme that modulates the phase distribution of water spins. These labeled spins are then used as an intrinsic indicator, which dilutes due to magnetization exchange with macromolecular protons. Currently, this method is limited to single-shot acquisitions due to the application of small magnetic field gradients in the preparation phase of the sequence that renders the sequence sensitive to bulk physiologic motion. In this work, we will capitalize on the self-navigating capabilities of variable density spiral trajectories [2] to accurately compensate for motion and phase accumulation, which in turn allows a more accurate BPF calculation and higher spatial resolution. References: [1] Ropele, et al. MRM (49),864-871,2003. [2] Liu, et al. MRM (52),1388-1396,2004. [3] Sled et al. MRM (46),923-931,2001. [4] Henkelman, MRM (29),759-766,1993. [5] Yarnykh, MRM (47),929-939,2002. [6] Tozer et al. MRM 5:83-91, 2003. [7] Ramani, MRI, 20(10), 721-31, 2002. [8] Liu, MRM (54), 2005. Acknowledgements: Work was supported in part by the NIH (1R01EB002771), Center of Advanced MR Technology at Stanford (P41RR09784), Lucas and Oak Foundations