Studies On The Technical Aspects In Susceptibility Weighted Imaging

Susceptibility-weighted imaging (SWI) has recently demonstrated great clinical significance in the diagnosis of several intracranial venous lesions and diseases. SWI is a 3D, high resolution, T2*-weighted, and gradient-echo imaging technique. SWI utilizes the relative phase and magnitude change in the venous vasculature introduced by the susceptibility difference between venous blood and parenchyma. A relatively long echo time (TE) is typically used in SWI to achieve nearly optimal venous contrast, resulting in long data acqusition time. The SWI data have relatively low signal-to-noise ratio (SNR) due to the T2* decay at a long TE. Artifact can arise during the construction of the 3D phase mask in regions with severe field inhomogeneity due to the off-resonance effect. Image artifacts can also arise from minimum-intensity projection (mIP), which is commonly used for the display of venous vasculature because of the negative venous contrast. In axial projection, voxels in air and bone can be in the path of projection in peripheral regions of the brain due to the nature shape of the brain. The low intensity in air or bone results in the disappearance of signal from brain tissue, including veins, in mIP images in that region. The low intensity of air and bone also make mIP impractical for sagittal and coronal projections of whole-brain SWI data. Moreover, visualization of the venous vasculature in the magnitude data can be enhanced by background suppression. In this study, we investigated following aspects:(1) The partial k-space acquisition was studied to reduce scan time and the magnitude images were reconstructed by the projection onto convex sets algorithm. A 3D Fermi filter in k-space was demonstrated to increase the SNR and to reduce angular dependence of spatial resolution.(2) A dual-echo and multi-echo pulse sequence for simultaneous acquisition of magnetic resonance angiography and venography (MRAV) were developed. Using this pulse sequence, the magnetic resonance venography (MRV) data can be acquired without increasing the scan time of magnetic resonance angiography (MRA). The effect of spatial resolution on vein-to-background contrast was demonstrated. The venous contrast and off-resonance artifacts of MRV data acquired at different TEs were studied. The R2* value at each voxel was quantified using multi-TE exponential fitting. The R2* map can be used for the quantification of iron deposition.(3) A novel postprocessing approach was studied to calculate the local field gradient (LFG) for the reduction of the off-resonance artifacts without phase-unwrapping. LFG measurements were used to assess the severity of field inhomogeneity and suppress the residual phase in the phase mask induced by the off-resonance effect.(4) Two volume segmentation algorithms of the brain tissue were studied. A multivariate measure based on the statistics of phase and magnitude was constructed for robust tissue-air volume segmentation. An improved version of the variational level set algorithm was used for volume segmentation of brain tissue directly based on magnitude images. Both algorithms provide a feasible solution to reduce the signal loss in the peripheral regions of the brain in the through-plane mIP images and enable in-plane mIP display of MRV.(5) Three enhancement algorithms of small vein were presented. First, the image-domain high-pass filters based on second-order phase difference were applied to the complex 3D SWI data to enhance the susceptibility phase shift of the veins and suppress background signal in SWI. Second, high-pass filter was applied to the Fourier domain of the magnitude images to suppress the background signal and enahnce the visibility of the venous vasculature in the brain. Third, a 3D multi-scale vessel enhancement algorithm based on the Hessian matrix was proposed. Eigenvalue analysis of the Hessian matrix was used to enhance the veins, suppress the background tissue, and reduce the noise in air.