Alexandre Vignaud

Purpose MP2RAGE parameter optimization is redefined to allow more time‐efficient MR acquisitions, whereas the T 1 ‐based synthetic imaging framework is used to obtain on‐demand T 1 ‐weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug‐and‐play parallel‐transmission brain imaging at 7 T. Methods A “time‐efficient” MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip‐angle values to maximize the gray–to–white‐matter contrast‐to‐noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWS MIN , FLAWS HCO ) were generated online based on the acquired T 1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time‐efficient and conventional MP2RAGE parameterizations. Results The proposed time‐efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm) 3 , (0.80 mm) 3 and (0.65 mm) 3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast‐to‐noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole‐brain (0.45 mm) 3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm) 3 time‐efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm) 3 protocol, while decreasing the scan time by 15%. Conclusion The proposed optimization, associated with T 1 ‐based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.

Purpose Patient‐induced inhomogeneities in the static magnetic field cause distortions and blurring (off‐resonance artifacts) during acquisitions with long readouts such as in SWI. Conventional versatile correction methods based on extended Fourier models are too slow for clinical practice in computationally demanding cases such as 3D high‐resolution non‐Cartesian multi‐coil acquisitions. Theory Most reconstruction methods can be accelerated when performing off‐resonance correction by reducing the number of iterations, compressed coils, and correction components. Recent state‐of‐the‐art unrolled deep learning architectures could help but are generally not adapted to corrupted measurements as they rely on the standard Fourier operator in the data consistency term. The combination of correction models and neural networks is therefore necessary to reduce reconstruction times. Methods Hybrid pipelines using UNets were trained stack‐by‐stack over 99 SWI 3D SPARKLING 20‐fold accelerated acquisitions at 0.6 mm isotropic resolution using different off‐resonance correction methods. Target images were obtained using slow model‐based corrections based on self‐estimated field maps. The proposed strategies, tested over 11 volumes, are compared to model‐only and network‐only pipelines. Results The proposed hybrid pipelines achieved scores competing with two to three times slower baseline methods, and neural networks were observed to contribute both as pre‐conditioner and through inter‐iteration memory by allowing more degrees of freedom over the model design. Conclusion A combination of model‐based and network‐based off‐resonance correction was proposed to significantly accelerate conventional methods. Different promising synergies were observed between acceleration factors (iterations, coils, correction) and model/network that could be expanded in the future.

Purpose To optimize the homogeneity of the presaturation module in a Chemical Exchange Saturation Transfer (CEST) acquisition at 7 T using parallel transmission (pTx). Theory and Methods An optimized pTx‐CEST presaturation scheme based on precomputed universal pulses was designed. The optimization was performed by minimizing the L2‐norm between the effective and a given target while imposing energy constraints under virtual observation points (VOPs) supervision. The proposed method was evaluated through simulations and experimentally, both in vitro, on a realistic human head phantom, and in vivo, on healthy volunteers. The results were compared with circular polarization (CP) presaturation and other pTx approaches previously proposed. All experiments were conducted on a 7 T MRI scanner using a commercial 8Tx/32Rx head coil. Results The simulations show that the proposed pTx strategy boosted with VOPs is superior to the CP mode and existent pTx approaches. While the best results are obtained with subject specific pulses, the gain provided by the use of VOPs renders the universal pulses superior to tailored pulses optimized under vendor provided Specific Absorption Rate (SAR) management. In the phantom, the glucose map was significantly more homogeneous than with CP (root mean square error [RMSE] 17% vs. 30%). The efficiency of the method for in vivo hydroxyl, glutamate and rNOE weighted CEST acquisitions was also demonstrated. Conclusion The use of a pTx presaturation scheme based on universal pulses optimized under VOP SAR management is significantly benefiting CEST imaging at high magnetic field.