Simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) for dynamic contrast-enhanced MRI of liver.

PURPOSE: To propose a simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) method for liver dynamic contrast-enhanced MRI. METHODS: The proposed SAHA simultaneously acquired high temporal-resolution 2D images for vascular input function extraction using Cartesian sampling and 3D large-coverage high spatial-resolution liver dynamic contrast-enhanced images using golden angle stack-of-stars acquisition in an interleaved way. Simulations were conducted to investigate the accuracy of SAHA in pharmacokinetic analysis. A healthy volunteer and three patients with cirrhosis or hepatocellular carcinoma were included in the study to investigate the feasibility of SAHA in vivo. RESULTS: Simulation studies showed that SAHA can provide closer results to the true values and lower root mean square error of estimated pharmacokinetic parameters in all of the tested scenarios. The in vivo scans of subjects provided fair image quality of both 2D images for arterial input function and portal venous input function and 3D whole liver images. The in vivo fitting results showed that the perfusion parameters of healthy liver were significantly different from those of cirrhotic liver and HCC. CONCLUSIONS: The proposed SAHA can provide improved accuracy in pharmacokinetic modeling and is feasible in human liver dynamic contrast-enhanced MRI, suggesting that SAHA is a potential tool for liver dynamic contrast-enhanced MRI. Magn Reson Med 79:2629-2641, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Large coverage black-bright blood interleaved imaging sequence (LaBBI) for 3D dynamic contrast-enhanced MRI of vessel wall.

PURPOSE: To propose a large coverage black-bright blood interleaved imaging sequence (LaBBI) for 3D dynamic contrast-enhanced MRI (DCE-MRI) of the vessel wall. METHODS: LaBBI consists of a 3D black-blood stack-of-stars golden angle radial acquisition with high spatial resolution for vessel wall imaging and a 2D bright-blood Cartesian acquisition with high temporal resolution for arterial input function estimation. The two acquisitions were performed in an interleaved fashion within a single scan. Simulations, phantom experiments, and in vivo tests in three patients were performed to investigate the feasibility and performance of the proposed LaBBI. RESULTS: In simulation tests, the estimated Ktrans and vp by LaBBI were more accurate than conventional bright-blood DCE-MRI with lower root mean square error in all the tested conditions. In phantom test, no signal interference was found on the 2D scan in LaBBI. Pharmacokinetic analysis of the patients' data acquired by LaBBI showed that Ktrans was higher in fibrous tissue (0.0717 ± 0.0279 min-1 ), while lower in necrotic core (0.0206 ± 0.0040 min-1 ) and intraplaque hemorrhage (0.0078 ± 0.0007 min-1 ), compared with normal vessel wall (0.0273 ± 0.0052 min-1 ). CONCLUSION: The proposed LaBBI sequence, with high spatial and temporal resolution, and large coverage blood suppression, was promising to probe the perfusion properties of vessel wall lesions. Magn Reson Med 79:1334-1344, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Simultaneous measurement of brain perfusion and labeling efficiency in a single pseudo-continuous arterial spin labeling scan.

PURPOSE: The aim of this study was to propose, optimize, and validate a pseudo-continuous arterial spin labeling (pCASL) sequence for simultaneous measurement of brain perfusion and labeling efficiency. METHODS: The proposed sequence incorporates the labeling efficiency measurement into the postlabeling delay period of a conventional perfusion pCASL sequence by using the time-encoding approach. In vivo validation experiments were performed on nine young subjects by comparing it to separate perfusion and labeling efficiency sequences. Sensitivity of the proposed combined sequence for measuring labeling efficiency changes was further addressed by varying the flip angles of the pCASL labeling radiofrequency pulses. RESULTS: The proposed combined sequence decreased the perfusion signal by ∼4% and a lower labeling efficiency (by ∼10%) was found as compared to the separate sequences. However, the temporal signal-noise-ratio of the perfusion signal remained unchanged. When the pCASL flip angle was decreased to a suboptimal setting, a strong correlation was found between the combined and the separate sequences for the relative change in pCASL perfusion signal as well as for the relative change in labeling efficiency. High correlation was also observed between relative changes in perfusion signal and the measured labeling efficiencies. CONCLUSION: The proposed sequence allows simultaneous measurement of brain perfusion and labeling efficiency with high time-efficiency at the price of only a small compromise in measurement accuracy. The additional labeling efficiency measurement can be used to facilitate qualitative interpretation of pCASL perfusion images. Magn Reson Med 79:1922-1930, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

POCS-enhanced inherent correction of motion-induced phase errors (POCS-ICE) for high-resolution multishot diffusion MRI.

PURPOSE: For multishot diffusion weighted imaging (DWI), one of the challenges is to remove phase variations induced by physiological motion among different shots. In this study, a new method is proposed to iteratively solve the phase errors and DWI images simultaneously, for navigator-free acquisitions. THEORY AND METHODS: Instead of solving phase errors and the image sequentially in the two-step parallel imaging, the proposed method, named POCS-enhanced Inherent Correction of motion-induced phase Errors (POCS-ICE), treats both the phase and DWI image as unknowns and solves them simultaneously. Multishot DWI with constant density spiral trajectory served as a specific example. Simulation and in vivo experiments were performed to evaluate the proposed method. RESULTS: POCS-ICE shows improved image quality in terms of higher SNR and fewer artifacts than the compared method, SENSE+CG. The improvement becomes more conspicuous as the number of shots increases. The convergence behavior of POCS-ICE was also shown to be more stable. CONCLUSION: POCS-ICE can inherently and reliably correct motion-induced phase errors in navigator-free multishot DWI, and it is easier to determine the stopping criterion without manual interventions. The improved spatial resolution and image resolvability are beneficial to study of brain microstructures and physiological features for neuroscience.

[Decreased occipital GABA concentrations in patients with first-episode major depressive disorder: a magnetic resonance spectroscopy study].

Gamma amino butyric acid (GABA) is the major inhibitory neurotransmitter in the human brain. Alterations in GABAergic function are associated with a variety of neurological and psychiatric disorders. However, noninvasive in vivo measurement of GABA is difficult because of its low concentration and the presence of overlapping resonances. To study GABA concentration in the occipital cortex in major depressive disorder (MDD), a group of medication-naive, first episode depressed patients (n = 18, HAMD > 17), and a group of healthy controls (n = 23) were investigated using a Point Resolved Spectroscopy (MEGA-PRESS) on a 3.0 T MR scanner. The results showed that occipital GABA levels were significantly lower (P < 0.001) in the patient group than those in the healthy controls, yet the correlations between the severity of MDD (HAMD, BDI) and the GABA concentration is insignificant. Therefore, our data suggest that patients with first episode, unmedicated MDD have changes in cortical concentrations of GABA. This biochemical abnormality may be a marker of a trait vulnerability to mood disorder, and may explain the visual problem of severe MDD patients.

Multiscale coherence regularization reconstruction using a nonlocal operator for fast variable-density spiral imaging.

PURPOSE: Nonlinear reconstruction can suppress pseudo-incoherent aliasing artifacts from variable-density spiral (VDS) trajectories when interleaves are undersampled for acquisition acceleration during MR imaging. However, large-scale aliasing artifact suppression often conflicts with fine-scale structure preservation and may cause deterioration of image quality in the reconstructed images. To address this issue, a sequential, multiscale coherence regularization algorithm using a nonlocal operator (mCORNOL) is proposed. METHODS: mCORNOL is formed by exploiting the scale-control capacity of nonlocal operators in image structure measurement. By changing the scale of the structure measurement, the smoothing constraint scales can be adjusted. Starting with a large value, mCORNOL gradually reduces the smoothing constraint scale until it reaches the same level as the noise. Therefore, the large-scale smoothing constraint dominates the first few iterations of the reconstruction and removes aliasing artifacts as well as fine structures. In the following iterations, the smoothing constraint is restricted to a smaller and smaller scale, so the fidelity term progressively dominates and restores lost structures. Thus, aliasing artifact removal and structure preservation can be decoupled and achieved sequentially, which alleviates the conflicts between them. RESULTS: Numerical simulation and in vivo experiment results demonstrate the superiority of mCORNOL for aliasing artifact suppression and image structure preservation at high reduction factors, compared to SENSE, Total Variation and the original CORNOL reconstruction. CONCLUSIONS: mCORNOL reconstruction provides an effective way to improve image quality for undersampled VDS acquisitions.

Convergence behavior of iterative SENSE reconstruction with non-Cartesian trajectories.

In non-Cartesian SENSE reconstruction based on the conjugate gradient (CG) iteration method, the iteration very often exhibits a "semi-convergence" behavior, which can be characterized as initial convergence toward the exact solution and later divergence. This phenomenon causes difficulties in automatic implementation of this reconstruction strategy. In this study, the convergence behavior of the iterative SENSE reconstruction is analyzed based on the mathematical principle of the CG method. It is revealed that the semi-convergence behavior is caused by the ill-conditioning of the underlying generalized encoding matrix (GEM) and the intrinsic regularization effect of CG iteration. From the perspective of regularization, each iteration vector is a regularized solution and the number of iterations plays the role of the regularization parameter. Therefore, the iteration count controls the compromise between the SNR and the residual aliasing artifact. Based on this theory, suggestions with respect to the stopping rule for well-behaved reconstructions are provided. Simulated radial imaging and in vivo spiral imaging are performed to demonstrate the theoretical analysis on the semi-convergence phenomenon and the stopping criterion. The dependence of convergence behavior on the undersampling rate and the noise level in samples is also qualitatively investigated.