Vectorial total generalized variation for accelerated multi-channel multi-contrast MRI.

PURPOSE: To develop and implement an efficient reconstruction technique to improve accelerated multi-channel multi-contrast MRI. THEORY AND METHODS: The vectorial total generalized variation (TGV) operator is used as a regularizer for the sensitivity encoding (SENSE) technique to improve image quality of multi-channel multi-contrast MRI. The alternating direction method of multipliers (ADMM) is used to efficiently reconstruct the data. The performance of the proposed method (MC-TGV-SENSE) is assessed on two healthy volunteers at several acceleration factors. RESULTS: As demonstrated on the in vivo results, MC-TGV-SENSE had the lowest root-mean-square error (RMSE), highest structural similarity index, and best visual quality at all acceleration factors, compared to other methods under consideration. MC-TGV-SENSE yielded up to 17.3% relative RMSE reduction compared to the widely used total variation regularized SENSE. Furthermore, we observed that the reconstruction time of MC-TGV-SENSE is reduced by approximately a factor of two with comparable RMSEs by using the proposed ADMM-based algorithm as opposed to the more commonly used Chambolle-Pock primal-dual algorithm for the TGV-based reconstruction. CONCLUSION: MC-TGV-SENSE is a better alternative than the existing reconstruction methods for accelerated multi-channel multi-contrast MRI. The proposed method exploits shared information among the images (MC), mitigates staircasing artifacts (TGV), and uses the encoding power of multiple receiver coils (SENSE).

Parallel transmission pulse design with explicit control for the specific absorption rate in the presence of radiofrequency errors.

PURPOSE: A new framework for the design of parallel transmit (pTx) pulses is presented introducing constraints for local and global specific absorption rate (SAR) in the presence of errors in the radiofrequency (RF) transmit chain. METHODS: The first step is the design of a pTx RF pulse with explicit constraints for global and local SAR. Then, the worst possible SAR associated with that pulse due to RF transmission errors ("worst-case SAR") is calculated. Finally, this information is used to re-calculate the pulse with lower SAR constraints, iterating this procedure until its worst-case SAR is within safety limits. RESULTS: Analysis of an actual pTx RF transmit chain revealed amplitude errors as high as 8% (20%) and phase errors above 3° (15°) for spokes (spiral) pulses. Simulations show that using the proposed framework, pulses can be designed with controlled "worst-case SAR" in the presence of errors of this magnitude at minor cost of the excitation profile quality. CONCLUSION: Our worst-case SAR-constrained pTx design strategy yields pulses with local and global SAR within the safety limits even in the presence of RF transmission errors. This strategy is a natural way to incorporate SAR safety factors in the design of pTx pulses. Magn Reson Med 75:2493-2504, 2016. © 2015 Wiley Periodicals, Inc.

SAR reduction in 7T C-spine imaging using a "dark modes" transmit array strategy.

PURPOSE: Local specific absorption rate (SAR) limits many applications of parallel transmit (pTx) in ultra high-field imaging. In this Note, we introduce the use of an array element, which is intentionally inefficient at generating spin excitation (a "dark mode") to attempt a partial cancellation of the electric field from those elements that do generate excitation. We show that adding dipole elements oriented orthogonal to their conventional orientation to a linear array of conventional loop elements can lower the local SAR hotspot in a C-spine array at 7 T. METHODS: We model electromagnetic fields in a head/torso model to calculate SAR and excitation B1 (+) patterns generated by conventional loop arrays and loop arrays with added electric dipole elements. We utilize the dark modes that are generated by the intentional and inefficient orientation of dipole elements in order to reduce peak 10g local SAR while maintaining excitation fidelity. RESULTS: For B1 (+) shimming in the spine, the addition of dipole elements did not significantly alter the B1 (+) spatial pattern but reduced local SAR by 36%. CONCLUSION: The dipole elements provide a sufficiently complimentary B1 (+) and electric field pattern to the loop array that can be exploited by the radiofrequency shimming algorithm to reduce local SAR.

Parallel transmit pulse design for patients with deep brain stimulation implants.

PURPOSE: Specific absorption rate (SAR) amplification around active implantable medical devices during diagnostic MRI procedures poses a potential risk for patient safety. In this study, we present a parallel transmit (pTx) strategy that can be used to safely scan patients with deep brain stimulation (DBS) implants. METHODS: We performed electromagnetic simulations at 3T using a uniform phantom and a multitissue realistic head model with a generic DBS implant. Our strategy is based on using implant-friendly modes, which are defined as the modes of an array that reduce the local SAR around the DBS lead tip. These modes are used in a spokes pulse design algorithm in order to produce highly uniform magnitude least-squares flip angle excitations. RESULTS: Local SAR (1 g) at the lead tip is reduced below 0.1 W/kg compared with 31.2 W/kg, which is obtained by a simple quadrature birdcage excitation without any sort of SAR mitigation. For the multitissue realistic head model, peak 10 g local SAR and global SAR are obtained as 4.52 W/kg and 0.48 W/kg, respectively. A uniform axial flip angle is also obtained (NRMSE <3%). CONCLUSION: Parallel transmit arrays can be used to generate implant-friendly modes and to reduce SAR around DBS implants while constraining peak local SAR and global SAR and maximizing flip angle homogeneity.

Box relaxation schemes in staggered discretizations for the dual formulation of total variation minimization.

In this paper, we propose some new box relaxation numerical schemes on staggered grids to solve the stationary system of partial differential equations arising from the dual minimization problem associated with the total variation operator. We present in detail the numerical schemes for the scalar case and its generalization to multichannel (vectorial) images. Then, we discuss their implementation in digital image denoising. The results outperform the resolution of the dual equation based on the gradient descent approach and pave the way for more advanced numerical strategies.