Accurate actual flip angle imaging (AFI) in the presence of fat.

PURPOSE: To investigate the effect of incomplete fat spoiling on the accuracy of B1 mapping with actual flip angle imaging (AFI) and to propose a method to minimize the errors using the chemical shift properties of fat. THEORY AND METHODS: Diffusion-based dephasing is the main spoiling mechanism exploited in AFI. However, a very low diffusion in fat may make the spoiling insufficient, leading to ghosts in the B1 maps. As the errors retain the chemical-shift signature of fat, their impact can be minimized using chemical-shift-based fat signal removal from AFI acquisition modified to include multi-echo readout. The source of the errors and the proposed correction were studied in simulations and phantom and in-vivo imaging experiments. RESULTS: Our results support that AFI artifacts are caused by the incomplete fat spoiling present in clinically attractive short TR acquisition regimes. The correction eliminated the ghosting and significantly improved the B1 mapping accuracy as well as the accuracy of R1 mapping performed with AFI-derived B1 maps. CONCLUSIONS: The incomplete fat signal spoiling may be a source of AFI B1 mapping errors, especially in subjects with high fat content. Achieving complete fat spoiling requires longer TR, which is undesirable in clinical applications. The proposed approach based on fat signal removal can reduce errors without significant prolongation of the AFI pulse sequence. We propose that, when attaining complete fat spoiling is not feasible, AFI mapping should be performed in a multi-echo regime with appropriate fat separation or suppression to minimize these errors.

Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping.

PURPOSE: To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM. METHODS: An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC). The proposed method was compared to the previously proposed and validated approach in liver QSM for two multi-echo spoiled gradient-recalled echo protocols with different acquisition parameters at 3T. Linear regression was used for evaluation of QSM methods against a reference FDA-approved R 2 $$ {R}_2 $$ -based LIC measure and R 2 ∗ $$ {R}_2^{\ast } $$ measurements; repeatability/reproducibility were assessed by Bland-Altman analysis. RESULTS: The data-adaptive method produced susceptibility maps with higher subjective quality due to reduced shading artifacts. For both acquisition protocols, higher linear correlation with both R 2 $$ {R}_2 $$ - and R 2 ∗ $$ {R}_2^{\ast } $$ -based measurements were observed for the data-adaptive method ( r 2 = 0 . 74 / 0 . 69 $$ {r}^2=0.74/0.69 $$ for R 2 $$ {R}_2 $$ , 0 . 97 / 0 . 95 $$ 0.97/0.95 $$ for R 2 ∗ $$ {R}_2^{\ast } $$ ) than the standard method ( r 2 = 0 . 60 / 0 . 66 $$ {r}^2=0.60/0.66 $$ and 0 . 79 / 0 . 88 $$ 0.79/0.88 $$ ). For both protocols, the data-adaptive method enabled better test-retest repeatability (repeatability coefficients 0.19/0.30 ppm for the data-adaptive method, 0.38/0.47 ppm for the standard method) and reproducibility across protocols (reproducibility coefficient 0.28 vs. 0.53ppm) than the standard method. CONCLUSIONS: The proposed data-adaptive QSM algorithm may enable quantification of LIC with improved repeatability/reproducibility across different acquisition parameters as 3T.

High-resolution dynamic susceptibility contrast perfusion imaging using higher-order temporal smoothness regularization.

PURPOSE: To improve image quality and resolution of dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) by developing acquisition and reconstruction methods exploiting the temporal regularity property of DSC-PWI signal. THEORY AND METHODS: A novel regularized reconstruction is proposed that recovers DSC-PWI series from interleaved segmented spiral k-space acquisition using higher order temporal smoothness (HOTS) properties of the DSC-PWI signal. The HOTS regularization is designed to tackle representational insufficiency of the standard first-order temporal regularizations for supporting higher accelerations. The higher accelerations allow for k-space coverage with shorter spiral interleaves resulting in improved acquisition point spread function, and acquisition of images at multiple TEs for more accurate DSC-PWI analysis. RESULTS: The methods were evaluated in simulated and in-vivo studies. HOTS regularization provided increasingly more accurate models for DSC-PWI than the standard first-order methods with either quadratic or robust norms at the expense of increased noise. HOTS DSC-PWI optimized for noise and accuracy demonstrated significant advantages over both spiral DSC-PWI without temporal regularization and traditional echo-planar DSC-PWI, improving resolution and mitigating image artifacts associated with long readout, including blurring and geometric distortions. In context of multi-echo DSC-PWI, the novel methods allowed ∼4.3× decrease of voxel volume, providing 2× number of TEs compared to the previously published results. CONCLUSIONS: Proposed HOTS reconstruction combined with dynamic spiral sampling represents a valid mechanism for improving image quality and resolution of DSC-PWI significantly beyond those available with established fast imaging techniques.

The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI.

Radial acquisition with MOCCO reconstruction has been previously proposed for high spatial and temporal resolution breast DCE imaging. In this work, we characterize MOCCO across a wide range of temporal contrast enhancement in a digital reference object (DRO). Time-resolved radial data was simulated using a DRO with lesions in different PK parameters. The under sampled data were reconstructed at 5 s temporal resolution using the data-driven low-rank temporal model for MOCCO, compressed sensing with temporal total variation (CS-TV) and more conventional low-rank reconstruction (PCB). Our results demonstrated that MOCCO was able to recover curves with Ktrans values ranging from 0.01 to 0.8 min-1 and fixed Ve = 0.3, where the fitted results are within a 10% bias error range. MOCCO reconstruction showed less impact on the selection of different temporal models than conventional low-rank reconstruction and the greater error was observed with PCB. CS-TV showed overall underestimation in both Ktrans and Ve. For the Monte-Carlo simulations, MOCCO was found to provide the most accurate reconstruction results for curves with intermediate lesion kinetics in the presence of noise. Initial in vivo experiences are reported in one patient volunteer. Overall, MOCCO was able to provide reconstructed time-series data that resulted in a more accurate measurement of PK parameters than PCB and CS-TV.

Correlation of Objective Endpoints and Subjective Patient-Reported Outcomes in NAFLD Treatment with Essential Phospholipids: Real-World Data Based on Pooled Analysis of Observational Studies.

BACKGROUND: While no "gold-standard" pharmacotherapy for nonalcoholic fatty liver disease (NAFLD) is yet established, essential phospholipids (EPLs) are reported to decrease steatosis and improve laboratory parameters. OBJECTIVE: This analysis evaluated adherence and satisfaction with EPL treatment as patient-reported outcomes and their relationship with changes in laboratory and ultrasound parameters among Russian patients with NAFLD. METHODS: Data were pooled from three observational Russian studies-MANPOWER (2015-2016), LIDER 1 (2012-2013), and LIDER 2 (2013)-in which EPLs were used for at least 12 weeks in the treatment of liver diseases and which measured both subjective and objective endpoints. Only patients who had NAFLD were included in this analysis. The main endpoints were to determine treatment adherence and satisfaction with 12 weeks of EPL therapy, relationship between adherence/satisfaction and changes in the laboratory and ultrasound parameters. A secondary subgroup analysis was performed to identify patients with NAFLD who responded better (or worse) to 24 weeks of adjunctive EPL treatment. RESULTS: Overall, 3384 patients were included. A total of 82.2% of patients were adherent to 12 weeks of EPL treatment; high/very high satisfaction was reported by 15.3%/65.9% of clinicians and 15.9%/64.4% of patients. There was positive correlation between patients' adherence and satisfaction and significant improvement in laboratory (transaminases, lipid profile; p < 0.001) and ultrasound (steatosis, p < 0.001) parameters, and improvement in symptoms (p < 0.001) after 24 weeks of EPL. Male patients, patients with unhealthy lifestyles, and those with more comorbidities showed a better response in laboratory and ultrasound parameters. CONCLUSIONS: Patients with NAFLD treated with adjunctive EPL therapy in real-world clinical practice in Russia showed good treatment adherence and treatment satisfaction. Improvements in laboratory and ultrasound parameters, as well as dynamics of patient symptoms, were positively correlated with adherence and satisfaction.

Nonalcoholic fatty liver disease (NAFLD) is a major cause of liver disease, and patients have a risk of liver cancer and needing transplantation. Patients with advanced NAFLD are usually recommended to use medication. Clinical trials in patients with NAFLD showed that essential phospholipids (EPLs) comprising phosphatidylcholine improved liver fat accumulation (known as steatosis), so treatment guidelines in several countries recommend they be added to the usual therapy. EPLs have been associated with both objective and subjective improvements. This real-world study evaluated three observational studies to assess how patient adherence and satisfaction with EPL treatment were related to changes in clinical parameters in 3384 Russian patients with NAFLD. Overall, 82.2% of patients were adherent with 12 weeks of EPL therapy, and almost two-thirds of patients (64.4%) and clinicians (65.9%) reported very high satisfaction with treatment. Patients' adherence and satisfaction increased alongside significant improvements in liver enzymes, lipid levels, liver fat content (steatosis), and fewer symptoms after 24 weeks of EPL therapy. Male patients, those with an unhealthy lifestyle, and those with other comorbid conditions had the best response to EPL therapy. This study shows that Russian patients with NAFLD have good adherence and satisfaction with EPL therapy in routine clinical practice and highlights the importance of adherence to EPL therapy in these patients.

Comparison of data-driven and general temporal constraints on compressed sensing for breast DCE MRI.

PURPOSE: Current breast DCE-MRI strategies provide high sensitivity for cancer detection but are known to be insufficient in fully capturing rapidly changing contrast kinetics at high spatial resolution across both breasts. Advanced acquisition and reconstruction strategies aim to improve spatial and temporal resolution and increase specificity for disease characterization. In this work, we evaluate the spatial and temporal fidelity of a modified data-driven low-rank-based model (known as MOCCO, model consistency condition) compressed-sensing (CS) reconstruction compared to CS with temporal total variation with radial acquisition for high spatial-temporal breast DCE MRI. METHODS: Reconstruction performance was characterized using numerical simulations of a golden-angle stack-of-stars breast DCE-MRI acquisition at 5-second temporal resolution. Specifically, MOCCO was compared with CS total variation and conventional SENSE reconstructions. The temporal model for MOCCO was prelearned over the source data, whereas CS total variation was performed using a first-order temporal gradient sparsity transform. RESULTS: The MOCCO reconstruction was able to capture rapid lesion kinetics while providing high image quality across a range of optimal regularization values. It also recovered kinetics in small lesions (1.5 mm) in line-profile analysis and error images, whereas g-factor maps showed relatively low and constant values with no significant artifacts. The CS-TV method demonstrated either recovery of high spatial resolution with reduced temporal accuracy using large regularization values, or recovery of rapid lesion kinetics with reduced image quality using low regularization values. CONCLUSION: Simulations demonstrated that MOCCO with radial acquisition provides a robust imaging technique for improving temporal fidelity, while maintaining high spatial resolution and image quality in the setting of bilateral breast DCE MRI.

Amyloid and Tau PET Imaging of Alzheimer Disease and Other Neurodegenerative Conditions.

Although diagnosing the syndrome of dementia is largely a clinical endeavor, neuroimaging plays an increasingly important role in accurately determining the underlying etiology, which extends beyond its traditional role in excluding other causes of altered cognition. New neuroimaging methods not only facilitate the diagnosis of the most common neurodegenerative conditions (particularly Alzheimer Disease [AD]) after symptom onset, but also show diagnostic promise even in the very early or presymptomatic phases of disease. Positron emission tomography (PET) is increasingly recognized as a key clinical tool for differentiating normal age-related changes in brain metabolism (using 18F-fluorodeoxyglucose [FDG]) from those seen in the earliest stages of specific forms of dementia. However, FDG PET only demonstrates nonspecific changes in altered parenchymal glucose uptake and not the specific etiologic proteinopathy causing the abnormal glucose uptake. A growing class of radiotracers targeting specific protein aggregates for amyloid-ß (Aß) and tau are changing the way AD is diagnosed, as these radiotracers directly label the underlying disease pathology. As these pathology-specific radiotracers are currently making their way to the clinic, it is important for the clinical neuroradiologist to understand the underlying patterns of Aß and tau deposition in the context of AD (across its clinical continuum) and in other causes of dementia, as well as understand the implications of current research.

A New, Non-Invasive Scale for Steatosis Developed Using Real-World Data From Russian Outpatients to Aid in the Diagnosis of Non-Alcoholic Fatty Liver Disease.

INTRODUCTION: The current non-invasive tools for the diagnosis of non-alcoholic fatty liver disease (NAFLD) have methodological limitations. We aimed to develop a non-invasive scale to assist in the diagnosis of NAFLD. To achieve our aim, we conducted a secondary analysis of data from a large observational study conducted in Russia. METHODS: This retrospective analysis assessed the frequency of NAFLD in the population of patients in the DIREG_L_06725 study, an epidemiological, observational, cross-sectional, multicenter study performed in 50,145 outpatients from 16 Russian cities. Among the cohort of patients diagnosed with NAFLD, we identified factors associated with the risk of NAFLD. To develop a non-invasive tool for diagnosing NAFLD, we also determined the frequency of steatohepatitis. RESULTS: Our analysis included 48,297 patients; NAFLD was present in 20,281 patients (42.0%). The majority (64.1%) were women (80.3% post-menopause), and 87% had a body mass index (BMI) > 27.0 kg/m2. We developed a fully non-invasive scale (St-index) that showed a specificity of 91.4% for ruling in steatosis, and a sensitivity of 93.8% for ruling out steatosis. Multivariate regression analyses conducted in the subgroups of patients aged ≥ 12 and < 18 years and those with BMI < 25.0 kg/m2 produced area under the receiver operating characteristic (AUROC) curve values of 0.8243 and 0.7054, respectively. The factors most strongly associated with the development of NAFLD were age > 35 years, presence of type 2 diabetes mellitus, and a waist circumference/height ratio > 0.54. CONCLUSION: Our non-invasive steatosis scale, St-index, can help physicians diagnose NAFLD in high-risk patients in the absence of ultrasound data.

Deep learning-based fully automatic segmentation of wrist cartilage in MR images.

The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensured optimal performance in the presence of a limited amount of training data. The CNN was trained and validated in 20 multi-slice MRI datasets acquired with two different coils in 11 subjects (healthy volunteers and patients). The validation included a comparison with the alternative state-of-the-art CNN methods for the segmentation of joints from MR images and the ground-truth manual segmentation. When trained on the limited training data, the CNN outperformed significantly image-based and PB-U-Net networks. Our PB-CNN also demonstrated a good agreement with manual segmentation (Sørensen-Dice similarity coefficient [DSC] = 0.81) in the representative (central coronal) slices with a large amount of cartilage tissue. Reduced performance of the network for slices with a very limited amount of cartilage tissue suggests the need for fully 3D convolutional networks to provide uniform performance across the joint. The study also assessed inter- and intra-observer variability of the manual wrist cartilage segmentation (DSC = 0.78-0.88 and 0.9, respectively). The proposed deep learning-based segmentation of the wrist cartilage from MRI could facilitate research of novel imaging markers of wrist osteoarthritis to characterize its progression and response to therapy.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed  âˆ¼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

Advancing RF pulse design using an open-competition format: Report from the 2015 ISMRM challenge.

PURPOSE: To advance the best solutions to two important RF pulse design problems with an open head-to-head competition. METHODS: Two sub-challenges were formulated in which contestants competed to design the shortest simultaneous multislice (SMS) refocusing pulses and slice-selective parallel transmission (pTx) excitation pulses, subject to realistic hardware and safety constraints. Short refocusing pulses are needed for spin echo SMS imaging at high multiband factors, and short slice-selective pTx pulses are needed for multislice imaging in ultra-high field MRI. Each sub-challenge comprised two phases, in which the first phase posed problems with a low barrier of entry, and the second phase encouraged solutions that performed well in general. The Challenge ran from October 2015 to May 2016. RESULTS: The pTx Challenge winners developed a spokes pulse design method that combined variable-rate selective excitation with an efficient method to enforce SAR constraints, which achieved 10.6 times shorter pulse durations than conventional approaches. The SMS Challenge winners developed a time-optimal control multiband pulse design algorithm that achieved 5.1 times shorter pulse durations than conventional approaches. CONCLUSION: The Challenge led to rapid step improvements in solutions to significant problems in RF excitation for SMS imaging and ultra-high field MRI. Magn Reson Med 78:1352-1361, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

PURPOSE: To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models preestimated from training data. THEORY: We introduce the model consistency condition (MOCCO) technique, which utilizes temporal models to regularize reconstruction without constraining the solution to be low-rank, as is performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. METHODS: Our method was compared with a standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE-MRA) and cardiac CINE imaging. We studied the sensitivity of all methods to rank reduction and temporal subspace modeling errors. RESULTS: MOCCO demonstrated reduced sensitivity to modeling errors compared with the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE-MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. CONCLUSIONS: MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data.

Removal of cerebrospinal fluid partial volume effects in quantitative magnetization transfer imaging using a three-pool model with nonexchanging water component.

PURPOSE: Parameters of the two-pool model describing magnetization transfer (MT) in macromolecule-rich tissues may be significantly biased in partial volume (PV) voxels containing cerebrospinal fluid (CSF). The purpose of this study was to develop a quantitative MT (qMT) method that provides indices insensitive to CSF PV averaging. THEORY AND METHODS: We propose a three-pool MT model, in which PV macro-compartment is modeled as an additional nonexchanging water pool. We demonstrate the feasibility of model parameter estimation from several MT-weighted spoiled gradient echo datasets. We validated the three-pool model in numerical, phantom, and in vivo studies. RESULTS: PV averaging with the free water compartment reduces all qMT parameters, most significantly affecting macromolecular proton fraction (MPF) and cross-relaxation rate. Monte-Carlo simulations confirmed stability of the three-pool model fit. Unlike the standard two-pool model, the three-pool model qMT parameters were not affected by PV averaging in simulations and phantom studies. The three-pool model fit allowed CSF PV correction in brain PV voxels and resulted in good correlation with standard two-pool model parameters in non-PV voxels. CONCLUSION: Quantitative MT imaging based on a three-pool model with a non-exchanging water component yields a set of CSF-insensitive qMT parameters, which may improve MPF-based assessment of myelination in structures strongly affected by CSF PV averaging such as brain gray matter.

Three-dimensional pulmonary perfusion MRI with radial ultrashort echo time and spatial-temporal constrained reconstruction.

PURPOSE: To assess the feasibility of spatial-temporal constrained reconstruction for accelerated regional lung perfusion using highly undersampled dynamic contrast-enhanced (DCE) three-dimensional (3D) radial MRI with ultrashort echo time (UTE). METHODS: A combined strategy was used to accelerate DCE MRI for 3D pulmonary perfusion with whole lung coverage. A highly undersampled 3D radial UTE MRI acquisition was combined with an iterative constrained reconstruction exploiting principal component analysis and wavelet soft-thresholding for dimensionality reduction in space and time. The performance of the method was evaluated using a 3D fractal-based DCE digital lung phantom. Simulated perfusion maps and contrast enhancement curves were compared with ground truth using the structural similarity index (SSIM) to determine robust threshold and regularization levels. Feasibility studies were then performed in a canine and a human subject with 3D radial UTE (TE=0.08 ms) acquisition to assess feasibility of mapping regional 3D perfusion. RESULTS: The method was able to accurately recover perfusion maps in the phantom with a nominal isotropic spatial resolution of 1.5 mm (SSIM of 0.949). The canine and human subject studies demonstrated feasibility for providing artifact-free perfusion maps in a simple 3D breath-held acquisition. CONCLUSION: The proposed method is promising for fast and flexible 3D pulmonary perfusion imaging. Magn Reson

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications.

Rapid measurement and correction of phase errors from B0 eddy currents: impact on image quality for non-Cartesian imaging.

Non-Cartesian imaging sequences and navigational methods can be more sensitive to scanner imperfections that have little impact on conventional clinical sequences, an issue which has repeatedly complicated the commercialization of these techniques by frustrating transitions to multicenter evaluations. One such imperfection is phase errors caused by resonant frequency shifts from eddy currents induced in the cryostat by time-varying gradients, a phenomenon known as B(0) eddy currents. These phase errors can have a substantial impact on sequences that use ramp sampling, bipolar gradients, and readouts at varying azimuthal angles. We present a method for measuring and correcting phase errors from B(0) eddy currents and examine the results on two different scanner models. This technique yields significant improvements in image quality for high-resolution joint imaging on certain scanners. This result suggests that correcting short-time B(0) eddy currents that do not affect conventional clinical sequences may simplify the adoption of non-Cartesian methods.

Simultaneous variable flip angle-actual flip angle imaging method for improved accuracy and precision of three-dimensional T1 and B1 measurements.

A new time-efficient and accurate technique for simultaneous mapping of T(1) and B(1) is proposed based on a combination of the actual flip angle (FA) imaging and variable FA methods. Variable FA-actual FA imaging utilizes a single actual FA imaging and one or more spoiled gradient-echo acquisitions with a simultaneous nonlinear fitting procedure to yield accurate T(1)/B(1) maps. The advantage of variable FA-actual FA imaging is high accuracy at either short T(1) times or long repetition times in the actual FA imaging sequence. Simulations show this method is accurate to 0.03% in FA and 0.07% in T(1) for ratios of repetition time to T1 time over the range of 0.01-0.45. We show for the case of brain imaging that it is sufficient to use only one small FA spoiled gradient-echo acquisition, which results in reduced spoiling requirements and a significant scan time reduction compared to the original variable FA method. In vivo validation yielded high-quality 3D T(1) maps and T(1) measurements within 10% of previously published values and within a clinically acceptable scan time. The variable FA-actual FA imaging method will increase the accuracy and clinical feasibility of many quantitative MRI methods requiring T(1)/B(1) mapping such as dynamic contrast enhanced perfusion and quantitative magnetization transfer imaging.

High b-value and diffusion tensor imaging in a canine model of dysmyelination and brain maturation.

Recent studies in rodents have demonstrated that diffusion imaging is highly sensitive to differences in myelination. These studies suggest that demyelination/dysmyelination cause increases in the radial diffusivity from diffusion tensor imaging (DTI) measurements and decreases in the restricted diffusion component from high b-value diffusion-weighted imaging experiments. In this study, the shaking pup (sh pup), a canine model of dysmyelination, was studied on a clinical MRI scanner using a combination of conventional diffusion tensor imaging and high b-value diffusion-weighted imaging methods. Diffusion measurements were compared between control dogs and sh pups in the age range 3 months to 16 months, which is similar to the period of early childhood through adolescence in humans. The study revealed significant group differences in nearly all diffusion measures with the largest differences in the zero-displacement probability (Po) from high b-value DWI and the radial diffusivity from DTI, which are consistent with the observations from the published rodent studies. Age-related changes in Po, FA, mean diffusivity, radial diffusivity and axial diffusivity were observed in whole brain white matter for the control dogs, but not the sh pups. Regionally, age-related changes in the sh pup white matter were observed for Po, mean diffusivity and radial diffusivity in the internal capsule, which may be indicative of mild myelination. These studies demonstrate that DWI may be used to study myelin abnormalities and brain development in large animal models on clinical MRI scanners, which are more amenable to translation to human studies.

Self-calibrated multiple-echo acquisition with radial trajectories using the conjugate gradient method (SMART-CG).

PURPOSE: To remove phase inconsistencies between multiple echoes, an algorithm using a radial acquisition to provide inherent phase and magnitude information for self correction was developed. The information also allows simultaneous support for parallel imaging for multiple coil acquisitions. MATERIALS AND METHODS: Without a separate field map acquisition, a phase estimate from each echo in multiple echo train was generated. When using a multiple channel coil, magnitude and phase estimates from each echo provide in vivo coil sensitivities. An algorithm based on the conjugate gradient method uses these estimates to simultaneously remove phase inconsistencies between echoes, and in the case of multiple coil acquisition, simultaneously provides parallel imaging benefits. The algorithm is demonstrated on single channel, multiple channel, and undersampled data. RESULTS: Substantial image quality improvements were demonstrated. Signal dropouts were completely removed and undersampling artifacts were well suppressed. CONCLUSION: The suggested algorithm is able to remove phase cancellation and undersampling artifacts simultaneously and to improve image quality of multiecho radial imaging, the important technique for fast three-dimensional MRI data acquisition.

Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains.

The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains.