The onboard imaging unit of the first commercial MR-IGRT system meets ACR, NEMA, and vendor specifications.
The extended version of the generalized autocalibrating partially parallel acquisition (GRAPPA) technique incorporates multiple lines and multiple columns of measured k-space data to estimate missing data. For a given accelerated dataset, the selection of the measured data points for fitting a missing datum (i.e., the kernel support) that provides optimal reconstruction depends on coil array configuration, noise level in the acquired data, imaging configuration, and number and position of autocalibrating signal lines. In this work, cross-validation is used to select the kernel support that best balances the conflicting demands of fit accuracy and stability in GRAPPA reconstruction. The result is an optimized tradeoff between artifacts and noise. As demonstrated with experimental data, the method improves image reconstruction with GRAPPA. Because the method is simple and applied in postprocessing, it can be used with GRAPPA routinely. Parallel MRI techniques (1) have been widely used to shorten MR scanning time. This is achieved by skipping k-space data points during data acquisition and utilizing variations in sensitivities of receiving RF coils to reconstruct the image. In k-space-based parallel imaging techniques (2-9), the missing k-space data are estimated by interpolation between the measured k-space data points. The interpolation kernel (or matrix) for each coil can be determined for a given acquisition scheme if coil sensitivity maps are known (10). With the generalized autocalibrating partially parallel acquisition (GRAPPA) technique (9), the interpolation kernel is estimated using calibration lines by assuming a small kernel size and k-space invariance of the kernel. A recent extension of GRAPPA includes k-space data in the readout direction in the interpolation to improve reconstruction (11).The GRAPPA procedure can be viewed as a special case of k-space interpolation in which a truncated version of the interpolation kernel support is used. The kernel weights are estimated through the least-squares solution of a linear system of equations relating the acquired signals to autocalibrating signal (ACS) lines. It can be inferred from this procedure that two main categories of error exist with the GRAPPA technique: model error and noise-related error. Model error has two components: one from using a limited number (as well as position) of ACS lines instead of the true coil sensitivity maps and the other from using a limited kernel size. Noise-related error arises from noise in the measured data and includes noise-induced errors that occur during kernel weights estimation, mainly due to the matrix inversion process (inversion error (10)), and errors that result from the application of the weights to noisy measured data. It is well recognized that the number and position of ACS lines used in the parameter estimation and the size and shape (or configuration) of the GRAPPA reconstruction kernel support significantly affect the reconstruction quality available with GRAPPA (1). For a given dataset, the error due ...
BackgroundMost humans are right handed, and most humans exhibit left-right asymmetries of the precentral corticospinal system. Recent studies indicate that chimpanzees also show a population-level right-handed bias, although it is less strong than in humans.Methodology/Principal FindingsWe used in vivo diffusion-weighted and T1-weighted magnetic resonance imaging (MRI) to study the relationship between the corticospinal tract (CST) and handedness in 36 adult female chimpanzees. Chimpanzees exhibited a hemispheric bias in fractional anisotropy (FA, left>right) and mean diffusivity (MD, right>left) of the CST, and the left CST was centered more posteriorly than the right. Handedness correlated with central sulcus depth, but not with FA or MD.Conclusions/SignificanceThese anatomical results are qualitatively similar to those reported in humans, despite the differences in handedness. The existence of a left>right FA, right>left MD bias in the corticospinal tract that does not correlate with handedness, a result also reported in some human studies, suggests that at least some of the structural asymmetries of the corticospinal system are not exclusively related to laterality of hand preference.
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