Microsoft Word - ISMRM2009-003037.DOC
نویسندگان
چکیده
Introduction Temporal fluctuations in a magnetic field produce artifacts and distortion in MR images. The main sources of such fluctuations are eddy currents, which are induced by gradient switching. Fluctuations induced by gradient switching cause significant effects in MR images, especially in DWEPI (diffusion weighted echo-planar imaging), that uses MPG (motion probing gradient) pulses with a huge amplitude. However, we lack good tools for evaluation of the effects caused by temporal fluctuations from gradient switching. We developed a pulse-sequence simulator for evaluation of arbitrary temporal fluctuations in the magnetic field caused by external vibrations such as those produced by cryocoolers [1]. However, evaluating the fluctuations caused by gradient switching by using the simulator is not so easy because the temporal fluctuation data under the gradient switching should be calculated by some means such as computer simulations of electromagnetic field. In this paper, we describe an extension of the pulse-sequence simulator for easy evaluation of MR image quality in the presence of temporal fluctuations of the magnetic field caused by gradient switching. The fluctuation data are given as feature parameters, which are inputs to the simulator. The feature parameters of the fluctuations are spatial distributions of amplitude, decay time constant, frequency, and phase. We confirmed that geometrical distortions in images obtained by DWEPI simulations correspond well with those from the experiments when eddy currents are intentionally increased. Method A schematic diagram of the pulse-sequence simulator is shown in Fig. 1. The inputs to the simulator are the subject model (as distributions of density of spins with relaxation times T1 and T2), the pulse sequence, and the feature parameters for temporal fluctuations of a static magnetic field induced by gradient switching. The temporal fluctuations, ΔH, are shown in Fig. 2 and defined in the following equations using the feature parameters:
منابع مشابه
Microsoft Word - ISMRM2009-003009.DOC
E-L. Lin, H-H. Peng, T-Y. Huang, Y-S. Wang, W-S. Chen, and W-Y. I. Tseng Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, Taipei, Taiwan, Center for Optoelectronic Bio...
متن کاملMicrosoft Word - ISMRM2009-001038.DOC
Introduction: This abstract presents a new approach towards a fast, simultaneous B1 and T1 mapping technique. This is especially important due to the mutual dependency of these parameters. The new method is based on the “actual flip angle imaging” (AFI) sequence [1], however, using multiple TR pairs instead of the standard AFI approach of a single TR pair. In the following, this multiple TR met...
متن کاملMicrosoft Word - ISMRM2009-001687.DOC
S-Y. Tsai, S. Posse, and F-H. Lin Department of Electrical Engineering, Chang Gung University, Tao Yuan, Taiwan, Department of Neurology, University of New Mexico School of Medicine, Alberquerque, NM, United States, Department of Electrical & Computer Engineering, University of New Mexico, Alberquerque, NM, United States, MGH-HMS-MIT Athinoula A. Martinos Center for Biomedical Imaging, Charlest...
متن کاملMicrosoft Word - ISMRM2009-001691.DOC
L. Yan, Y. Zhuo, Y. Ye, S. Xie, J. An, G. Aguirre, and J. Wang State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, CAS, Beijing, China, People's Republic of, Department of Biostatistics & Epidemiology, University of Pennsylvania, Philadelphia, PA, United States, Siemens Mindit Magnetic Resonance Ltd., Shenzhen, China, People's Republic of, Neurology, University of Penn...
متن کاملMicrosoft Word - ISMRM2009-000775.DOC
INTRODUCTION Synchronized low-frequency fluctuations in the resting-state functional MRI (fMRI) signal have been suggested to be associated with functional connectivity in brain networks (1). However, the underlying mechanism of this connectivity is still poorly understood. To better interpret the resting signal, we examined spontaneous fluctuations at the level of cerebral metabolic rate of ox...
متن کامل