Combined imaging and shimming with the dynamic multi-coil technique.

PURPOSE: Spatial encoding and shimming in MRI have traditionally been performed using dedicated coils that generate orthogonal spherical harmonic fields. The recently introduced multi-coil hardware has proven that MRI-relevant magnetic fields can also be created by a generic set of localized coils producing non-orthogonal fields. As a step towards establishing a purely multi-coil-based MRI field generation system, the feasibility of performing conventional Cartesian k-space encoding and echo-planar imaging (EPI), as well as concurrent encoding and shimming is demonstrated in this study. METHODS: We report the use of Dynamic Multi-Coil Technique (DYNAMITE) for combined Cartesian encoding and shimming, and EPI using a 48-channel multi-coil system. Experiments were performed on phantom objects and biological specimens in a 9.4 T pre-clinical scanner. Cartesian Fourier-encoded MRI and EPI were implemented whereby the magnetic fields required for encoding of the three orthogonal spatial dimensions were entirely based on linear combinations of multi-coil fields. Furthermore, DYNAMITE imaging was augmented by concurrent DYNAMITE shimming with the same hardware. RESULTS: DYNAMITE-based MR and echo-planar images were indistinguishable from those acquired with the conventional linear imaging gradients provided by the scanner. In experiments with concurrent DYNAMITE shimming and imaging, shim challenges that would result in extreme spatial distortion and signal loss were corrected very effectively with more than 92% signal recovery in case of extreme Z2 shim challenge that resulted in complete signal dephasing in most slices. CONCLUSIONS: We demonstrate the first successful implementation of combined DYNAMITE imaging and shimming and show the feasibility of performing EPI with DYNAMITE hardware. Our results substantiate the potential of multi-coil hardware as a full-fledged imaging and shimming system, with additional potential benefits of reduced echo-time and risk of peripheral nerve stimulation while performing EPI.

Improved estimation of MR relaxation parameters using complex-valued data.

PURPOSE: In MR image analysis, T1 , T2 , and T2* maps are generally calculated using magnitude MR data. Without knowledge of the underlying noise variance, parameter estimates at low signal to noise ratio (SNR) are usually biased. This leads to confounds in studies that compare parameters across SNRs and or across scanners. This article compares several estimation techniques which use real or complex-valued MR data to achieve unbiased estimation of MR relaxation parameters without the need for additional preprocessing. THEORY AND METHODS: Several existing and new techniques to estimate relaxation parameters using complex-valued data were compared with widely used magnitude-based techniques. Their bias, variance and processing times were studied using simulations covering various aspects of parameter variations. Validation on noise-degraded experimental measurements was also performed. RESULTS: Simulations and experiments demonstrated the superior performance of techniques based on complex-valued data, even in comparison with magnitude-based techniques that account for Rician noise characteristics. This was achieved with minor modifications to data modeling and at computational costs either comparable to or higher ( ≈two fold) than magnitude-based estimators. Theoretical analysis shows that estimators based on complex-valued data are statistically efficient. CONCLUSION: The estimation techniques that use complex-valued data provide minimum variance unbiased estimates of parametric maps and markedly outperform commonly used magnitude-based estimators under most conditions. They additionally provide phase maps and field maps, which are unavailable with magnitude-based methods. Magn Reson Med 77:385-397, 2017. © 2016 Wiley Periodicals, Inc.

Spreading depolarizations increase delayed brain injury in a rat model of subarachnoid hemorrhage.

Spreading depolarizations may contribute to delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage, but the effect of spreading depolarizations on brain lesion progression after subarachnoid hemorrhage has not yet been assessed directly. Therefore, we tested the hypothesis that artificially induced spreading depolarizations increase brain tissue damage in a rat model of subarachnoid hemorrhage. Subarachnoid hemorrhage was induced by endovascular puncture of the right internal carotid bifurcation. After one day, brain tissue damage was measured with T2-weighted MRI, followed by application of 1 M KCl (SD group, N = 16) or saline (no-SD group, N = 16) to the right cortex. Cortical laser-Doppler flowmetry was performed to record spreading depolarizations. MRI was repeated on day 3, after which brains were extracted for assessment of subarachnoid hemorrhage severity and histological damage. 5.0 ± 2.7 spreading depolarizations were recorded in the SD group. Subarachnoid hemorrhage severity and mortality were similar between the SD and no-SD groups. Subarachnoid hemorrhage-induced brain lesions expanded between days 1 and 3. This lesion growth was larger in the SD group (241 ± 233 mm(3)) than in the no-SD group (29 ± 54 mm(3)) (p = 0.001). We conclude that induction of spreading depolarizations significantly advances lesion growth after experimental subarachnoid hemorrhage. Our study underscores the pathophysiological consequence of spreading depolarizations in the development of delayed cerebral tissue injury after subarachnoid hemorrhage.

Dynamic multi-coil tailored excitation for transmit B1 correction at 7 Tesla.

PURPOSE: Tailored excitation (TEx) based on interspersing multiple radio frequency pulses with linear gradient and higher-order shim pulses can be used to obtain uniform flip angle in the presence of large radio frequency transmission (B 1+) inhomogeneity. Here, an implementation of dynamic, multislice tailored excitation using the recently developed multi-coil nonlinear shim hardware (MC-DTEx) is reported. METHODS: MC-DTEx was developed and tested both in a phantom and in vivo at 7 T, and its efficacy was quantitatively assessed. Predicted outcomes of MC-DTEx and DTEx based on spherical harmonic shims (SH-DTEx) were also compared. RESULTS: For a planned 30 ° flip angle, in a phantom, the standard deviation in excitation improved from 28% (regular excitation) to 12% with MC-DTEx. The SD in in vivo excitation improved from 22 to 12%. The improvements achieved with experimental MC-DTEx closely matched the theoretical predictions. Simulations further showed that MC-DTEx outperforms SH-DTEx for both scenarios. CONCLUSION: Successful implementation of multislice MC-DTEx is presented and is shown to be capable of homogenizing excitation over more than twofold B 1+ variations. Its benefits over SH-DTEx are also demonstrated. A distinct advantage of MC hardware over SH shim hardware is the absence of significant eddy current effects, which allows for a straightforward, multislice implementation of MC-DTEx. Magn Reson Med 76:83-93, 2016. © 2015 Wiley Periodicals, Inc.

Measurement of distinctive features of cortical spreading depolarizations with different MRI contrasts.

Growing clinical evidence suggests critical involvement of spreading depolarizations (SDs) in the pathophysiology of neurological disorders such as migraine and stroke. MRI provides powerful tools to detect and assess co-occurring cerebral hemodynamic and cellular changes during SDs. This study reports the feasibility and advantages of two MRI scans, based on balanced steady-state free precession (b-SSFP) and diffusion-weighted multi-spin-echo (DT2), heretofore unexplored for monitoring SDs. These were compared with gradient-echo MRI. SDs were induced by KCl application in rat brain. Known for high SNR, the T2- and T1-based b-SSFP contrast was hypothesized to provide higher spatiotemporal specificity than T2*-based gradient-echo scanning. DT2 scanning was designed to provide simultaneous T2 and apparent diffusion coefficient (ADC) measurements, thus enabling combined quantitative assessment of hemodynamic and cellular changes during SDs. Procedures were developed to automate identification of SD-induced responses in all the scans. These responses were analyzed to determine detection sensitivity and temporal characteristics of signals from each scanning method. Cluster analysis was performed to elucidate unique temporal patterns for each contrast. All scans allowed detection of SD-induced responses. b-SSFP scans showed significantly larger relative intensity changes, narrower peak widths and greater spatial specificity compared with gradient-echo MRI. SD-induced effects on ADC, calculated from DT2 scans, showed the most pronounced signal changes, displaying about 20% decrease, as against 10-15% signal increases observed with b-SSFP and gradient-echo scanning. Cluster analysis revealed additional temporal sub-patterns, such as an initial dip on gradient-echo scans and temporally shifted T2 and proton density changes in DT2 data. To summarize, b-SSFP and DT2 scanning provide distinct information on SDs compared with gradient-echo MRI. DT2 scanning, with its potential to simultaneously provide cellular and hemodynamic information, can offer unique information on the inter-relationship between these processes in pathologic brain, which may improve monitoring of spreading depolarizations in (pre)clinical settings.

Dynamic multi-coil technique (DYNAMITE) shimming for echo-planar imaging of the human brain at 7 Tesla.

Gradient-echo echo-planar imaging (EPI) is the primary method of choice in functional MRI and other methods relying on fast MRI to image brain activation and connectivity. However, the high susceptibility of EPI towards B0 magnetic field inhomogeneity poses serious challenges. Conventional magnetic field shimming with low-order spherical harmonic (SH) functions is capable of compensating shallow field distortions, but performs poorly for global brain shimming or on specific areas with strong susceptibility-induced B0 distortions such as the prefrontal cortex (PFC). Excellent B0 homogeneity has been demonstrated recently in the human brain at 7 Tesla with the DYNAmic Multi-coIl TEchnique (DYNAMITE) for magnetic field shimming (J Magn Reson (2011) 212:280-288). Here, we report the benefits of DYNAMITE shimming for multi-slice EPI and T2* mapping. A standard deviation of 13Hz was achieved for the residual B0 distribution in the human brain at 7 Tesla with DYNAMITE shimming and was 60% lower compared to conventional shimming that employs static zero through third order SH shapes. The residual field inhomogeneity with SH shimming led to an average 8mm shift at acquisition parameters commonly used for fMRI and was reduced to 1.5-3mm with DYNAMITE shimming. T2* values obtained from the prefrontal and temporal cortices with DYNAMITE shimming were 10-50% longer than those measured with SH shimming. The reduction of the confounding macroscopic B0 field gradients with DYNAMITE shimming thereby promises improved access to the relevant microscopic T2* effects. The combination of high spatial resolution and DYNAMITE shimming allows largely artifact-free EPI and T2* mapping throughout the brain, including prefrontal and temporal lobe areas. DYNAMITE shimming is expected to critically benefit a wide range of MRI applications that rely on excellent B0 magnetic field conditions including EPI-based fMRI to study various cognitive processes and assessing large-scale brain connectivity in vivo. As such, DYNAMITE shimming has the potential to replace conventional SH shim systems in human MR scanners.

Can diffusion kurtosis imaging improve the sensitivity and specificity of detecting microstructural alterations in brain tissue chronically after experimental stroke? Comparisons with diffusion tensor imaging and histology.

Imaging techniques that provide detailed insights into structural tissue changes after stroke can vitalize development of treatment strategies and diagnosis of disease. Diffusion-weighted MRI has been playing an important role in this regard. Diffusion kurtosis imaging (DKI), a recent addition to this repertoire, has opened up further possibilities in extending our knowledge about structural tissue changes related to injury as well as plasticity. In this study we sought to discern the microstructural alterations characterized by changes in diffusion tensor imaging (DTI) and DKI parameters at a chronic time point after experimental stroke. Of particular interest was the question of whether DKI parameters provide additional information in comparison to DTI parameters in understanding structural tissue changes, and if so, what their histological origins could be. Region-of-interest analysis and a data-driven approach to identify tissue abnormality were adopted to compare DTI- and DKI-based parameters in post mortem rat brain tissue, which were compared against immunohistochemistry of various cellular characteristics. The unilateral infarcted area encompassed the ventrolateral cortex and the lateral striatum. Results from region-of-interest analysis in the lesion borderzone and contralateral tissue revealed significant differences in DTI and DKI parameters between ipsi- and contralateral sensorimotor cortex, corpus callosum, internal capsule and striatum. This was reflected by a significant reduction in ipsilateral mean diffusivity (MD) and fractional anisotropy (FA) values, accompanied by significant increases in kurtosis parameters in these regions. Data-driven analysis to identify tissue abnormality revealed that the use of kurtosis-based parameters improved the detection of tissue changes in comparison with FA and MD, both in terms of dynamic range and in being able to detect changes to which DTI parameters were insensitive. This was observed in gray as well as white matter. Comparison against immunohistochemical stainings divulged no straightforward correlation between diffusion-based parameters and individual neuronal, glial or inflammatory tissue features. Our study demonstrates that DKI allows sensitive detection of structural tissue changes that reflect post-stroke tissue remodeling. However, our data also highlights the generic difficulty in unambiguously asserting specific causal relationships between tissue status and MR diffusion parameters.