Enhanced and robust contrast in CEST MRI: Saturation pulse shape design via optimal control.

PURPOSE: To employ optimal control for the numerical design of Chemical Exchange Saturation Transfer (CEST) saturation pulses to maximize contrast and stability against B 0 $$ {\mathrm{B}}_0 $$ inhomogeneities. THEORY AND METHODS: We applied an optimal control framework for the design pulse shapes for CEST saturation pulse trains. The cost functional minimized both the pulse energy and the discrepancy between the corresponding CEST spectrum and the target spectrum based on a continuous radiofrequency (RF) pulse. The optimization is subject to hardware limitations. In measurements on a 7 T preclinical scanner, the optimal control pulses were compared to continuous-wave and Gaussian saturation methods. We conducted a comparison of the optimal control pulses with Gaussian, block pulse trains, and adiabatic spin-lock pulses. RESULTS: The optimal control pulse train demonstrated saturation levels comparable to continuous-wave saturation and surpassed Gaussian saturation by up to 50 % in phantom measurements. In phantom measurements at 3 T the optimized pulses not only showcased the highest CEST contrast, but also the highest stability against field inhomogeneities. In contrast, block pulse saturation resulted in severe artifacts. Dynamic Bloch-McConnell simulations were employed to identify the source of these artifacts, and underscore the B 0 $$ {\mathrm{B}}_0 $$ robustness of the optimized pulses. CONCLUSION: In this work, it was shown that a substantial improvement in pulsed saturation CEST imaging can be achieved by using Optimal Control design principles. It is possible to overcome the sensitivity of saturation to B0 inhomogeneities while achieving CEST contrast close to continuous wave saturation.

Improved quantification in CEST-MRI by joint spatial total generalized variation.

PURPOSE: In this work, the use of joint Total Generalized Variation (TGV) regularization to improve Multipool-Lorentzian fitting of chemical exchange saturation transfer (CEST) Spectra in terms of stability and parameter signal-to-noise ratio (SNR) was investigated. THEORY AND METHODS: The joint TGV term was integrated into the nonlinear parameter fitting problem. To increase convergence and weight the gradients, preconditioning using a voxel-wise singular value decomposition was applied to the problem, which was then solved using the iteratively regularized Gauss-Newton method combined with a Primal-Dual splitting algorithm. The TGV method was evaluated on simulated numerical phantoms, 3T phantom data and 7T in vivo data with respect to systematic errors and robustness. Three reference methods were also implemented: The standard nonlinear fitting, a method using a nonlocal-means filter for denoising and the pyramid scheme, which uses downsampled images to acquire accurate start values. RESULTS: The proposed regularized fitting method showed significantly improved robustness (compared to the reference methods). In testing, over a range of SNR values the TGV fit outperformed the other methods and showed accurate results even for large amounts of added noise. Parameter values found were closer or comparable to the ground truth. For in vivo datasets, the added regularization increased the parameter map SNR and prevented instabilities. CONCLUSION: The proposed fitting method using TGV regularization leads to improved results over a range of different data-sets and noise levels. Furthermore, it can be applied to all Z-spectrum data, with different amounts of pools, where the improved SNR and stability can increase diagnostic confidence.

MEndoB, a chimeric lysin featuring a novel domain architecture and superior activity for the treatment of staphylococcal infections.

Bacterial infections are a growing global healthcare concern, as an estimated annual 4.95 million deaths are associated with antimicrobial resistance (AMR). Methicillin-resistant Staphylococcus aureus is one of the deadliest pathogens and a high-priority pathogen according to the World Health Organization. Peptidoglycan hydrolases (PGHs) of phage origin have been postulated as a new class of antimicrobials for the treatment of bacterial infections, with a novel mechanism of action and no known resistances. The modular architecture of PGHs permits the creation of chimeric PGH libraries. In this study, the chimeric enzyme MEndoB was selected from a library of staphylococcal PGHs based on its rapid and sustained activity against staphylococci in human serum. The benefit of the presented screening approach was illustrated by the superiority of MEndoB in a head-to-head comparison with other PGHs intended for use against staphylococcal bacteremia. MEndoB displayed synergy with antibiotics and rapid killing in human whole blood with complete inhibition of re-growth over 24 h at low doses. Successful treatment of S. aureus-infected zebrafish larvae with MEndoB provided evidence for its in vivo effectiveness. This was further confirmed in a lethal systemic mouse infection model in which MEndoB significantly reduced S. aureus loads and tumor necrosis factor alpha levels in blood in a dose-dependent manner, which led to increased survival of the animals. Thus, the thorough lead candidate selection of MEndoB resulted in an outstanding second-generation PGH with in vitro, ex vivo, and in vivo results supporting further development.IMPORTANCEOne of the most pressing challenges of our era is the rising occurrence of bacteria that are resistant to antibiotics. Staphylococci are prominent pathogens in humans, which have developed multiple strategies to evade the effects of antibiotics. Infections caused by these bacteria have resulted in a high burden on the health care system and a significant loss of lives. In this study, we have successfully engineered lytic enzymes that exhibit an extraordinary ability to eradicate staphylococci. Our findings substantiate the importance of meticulous lead candidate selection to identify therapeutically promising peptidoglycan hydrolases with unprecedented activity. Hence, they offer a promising new avenue for treating staphylococcal infections.