Diffusion-weighted MRI of the prostate without susceptibility artifacts: Undersampled multi-shot turbo-STEAM with rotated radial trajectories.

The aim of this study was to develop and evaluate a clinically feasible approach to diffusion-weighted (DW) MRI of the prostate without susceptibility-induced artifacts. The proposed method relies on an undersampled multi-shot DW turbo-STEAM sequence with rotated radial trajectories and a multi-step inverse reconstruction with denoised multi-shot phase maps. The total acquisition time was below 6 min for a resolution of 1.4 × 1.4 × 3.5 mm3 and six directions at b = 600 s mm-2 . Studies of eight healthy subjects and two patients with prostate cancer were performed at 3 T employing an 18-channel body-array coil and elements of the spine coil. The method was compared with conventional DW echo-planar imaging (EPI) of the prostate. The results confirm that DW STEAM MRI avoids geometric distortions and false image intensities, which were present for both single-shot EPI (ssEPI) and readout-segmented EPI, particularly near the intestinal wall of the prostate. Quantitative accuracy of the apparent diffusion coefficient (ADC) was validated with use of a numerical phantom providing ground truth. ADC values in the central prostate gland of healthy subjects were consistent with those measured using ssEPI and with literature data. Preliminary results for patients with prostate cancer revealed a correct anatomical localization of lesions with respect to T2 -weighted MRI in both mean DW STEAM images and ADC maps. In summary, DW STEAM MRI of the prostate offers clinically relevant advantages for the diagnosis of prostate cancer compared with state-of-the-art EPI-based approaches. The method warrants extended clinical trials.

Rapid Diffusion-Weighted Magnetic Resonance Imaging of the Brain Without Susceptibility Artifacts: Single-Shot STEAM With Radial Undersampling and Iterative Reconstruction.

OBJECTIVE: The aim of this study was to develop a rapid diffusion-weighted (DW) magnetic resonance imaging (MRI) technique for whole-brain studies without susceptibility artifacts and measuring times below 3 minutes. MATERIALS AND METHODS: The proposed method combines a DW spin-echo module with a single-shot stimulated echo acquisition mode MRI sequence. Previous deficiencies in image quality due to limited signal-to-noise ratio are compensated for (1) by radial undersampling to enhance the flip angle and thus the signal strength of stimulated echoes; (2) by defining the image reconstruction as a nonlinear inverse problem, which is solved by the iteratively regularized Gauss-Newton method; and (3) by denoising with use of a modified nonlocal means filter. The method was implemented on a 3 T MRI system (64-channel head coil, 80 mT · m gradients) and evaluated for 10 healthy subjects and 2 patients with an ischemic lesion and epidermoid cyst, respectively. RESULTS: High-quality mean DW images of the entire brain were obtained by acquiring 1 non-DW image and 6 DW images with different diffusion directions at b = 1000 s · mm. The achievable resolution for a total measuring time of 84 seconds was 1.5 mm in plane with a section thickness of 4 mm (55 sections). A measuring time of 168 seconds allowed for an in-plane resolution of 1.25 mm and a section thickness of 3 mm (54 sections). Apparent diffusion coefficient values were in agreement with literature data. CONCLUSIONS: The proposed method for DW MRI offers immunity against susceptibility problems, high spatial resolution, adequate signal-to-noise ratio and clinically feasible scan times of less than 3 minutes for whole-brain studies. More extended clinical trials require accelerated computation and online reconstruction.

A variational approach to image registration in dynamic contrast-enhanced MRI of the human kidney.

Kidney function can be accessed by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measurements which yield spatially resolved maps of physiological parameters like perfusion or filtration. The motion of the kidneys during the scan is a dominant limitation of the measurement quality, and image registration is necessary for accurate quantification. We analyzed the feasibility of applying an algorithm, originally developed for multimodal registration, to kidney perfusion time series. The algorithm uses a variational calculation scheme to align the images. In four out of five data sets, kidney motion could be reduced to below the spatial resolution of the images of 1.6mm while preserving the enhancement pattern of kidney perfusion. Fitting a pharmacokinetic model to the data showed an average reduction of the Akaike fit error of 10% for the registered data, suggesting more stable parameters. We conclude that this image registration algorithm is feasible for correcting kidney motion in renal DCE-MRI.

Wavelet-based segmentation of renal compartments in DCE-MRI of human kidney: initial results in patients and healthy volunteers.

Renal diseases can lead to kidney failure that requires life-long dialysis or renal transplantation. Early detection and treatment can prevent progression towards end stage renal disease. MRI has evolved into a standard examination for the assessment of the renal morphology and function. We propose a wavelet-based clustering to group the voxel time courses and thereby, to segment the renal compartments. This approach comprises (1) a nonparametric, discrete wavelet transform of the voxel time course, (2) thresholding of the wavelet coefficients using Stein's Unbiased Risk estimator, and (3) k-means clustering of the wavelet coefficients to segment the kidneys. Our method was applied to 3D dynamic contrast enhanced (DCE-) MRI data sets of human kidney in four healthy volunteers and three patients. On average, the renal cortex in the healthy volunteers could be segmented at 88%, the medulla at 91%, and the pelvis at 98% accuracy. In the patient data, with aberrant voxel time courses, the segmentation was also feasible with good results for the kidney compartments. In conclusion wavelet based clustering of DCE-MRI of kidney is feasible and a valuable tool towards automated perfusion and glomerular filtration rate quantification.