ABSTRACT
PURPOSE: To demonstrate the high-resolution numerical simulation of the respiration-induced dynamic B0 shift in the head using generalized susceptibility voxel convolution (gSVC). MATERIALS AND METHODS: Previous dynamic B0 simulation research has been limited to low-resolution numerical models due to the large computational demands of conventional Fourier-based B0 calculation methods. Here, we show that a recently-proposed gSVC method can simulate dynamic B0 maps from a realistic breathing human body model with high spatiotemporal resolution in a time-efficient manner. For a human body model, we used the Extended Cardiac And Torso (XCAT) phantom originally developed for computed tomography. The spatial resolution (voxel size) was kept isotropic and varied from 1 to 10 mm. We calculated B0 maps in the brain of the model at 10 equally spaced points in a respiration cycle and analyzed the spatial gradients of each of them. The results were compared with experimental measurements in the literature. RESULTS: The simulation predicted a maximum temporal variation of the B0 shift in the brain of about 7 Hz at 7T. The magnitudes of the respiration-induced B0 gradient in the x (right/left), y (anterior/posterior), and z (head/feet) directions determined by volumetric linear fitting, were < 0.01 Hz/cm, 0.18 Hz/cm, and 0.26 Hz/cm, respectively. These compared favorably with previous reports. We found that simulation voxel sizes greater than 5 mm can produce unreliable results. CONCLUSION: We have presented an efficient simulation framework for respiration-induced B0 variation in the head. The method can be used to predict B0 shifts with high spatiotemporal resolution under different breathing conditions and aid in the design of dynamic B0 compensation strategies.