Search

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. [ABSTRACT FROM AUTHOR]

Dimethyl sulfoxide (DMSO) has wide biomedical applications such as cryoprotectant and hydrophobic drug carrier. Here, we report for the first time that DMSO can generate a distinctive chemical exchange saturation transfer (CEST) signal at around −2 ppm. Structural analogs of DMSO, including aprotic and protic solvents, also demonstrated CEST signals from −1.4 to −3.8 ppm. When CEST detectable barbituric acid (BA) was dissolved in DMSO solution and was co‐loaded to liposome, two obvious peaks at 5 and −2 ppm were observed, indicating that DMSO and related solvent system can be monitored in a label‐free manner via CEST, which can be further applied to imaging drug nanocarriers. With reference to previous studies, there could be molecular interactions or magnetization transfer pathways, such as the relayed nuclear Overhauser enhancement (rNOE), that lead to this detectable CEST contrast at negative offset frequencies of the Z‐spectrum. Our findings suggest that small molecules of organic solvents could be involved in magnetization transfer processes with water and readily detected by CEST magnetic resonance imaging (MRI), providing a new avenue for detecting solvent–water and solvent–drug interactions. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) MRI at 3 T suffers from low specificity due to overlapping CEST effects from multiple metabolites, while higher field strengths (B0) allow for better separation of Z‐spectral "peaks," aiding signal interpretation and quantification. However, data acquisition at higher B0 is restricted by equipment access, field inhomogeneity and safety issues. Herein, we aim to synthesize higher‐B0Z‐spectra from readily available data acquired with 3 T clinical scanners using a deep learning framework. Trained with simulation data using models based on Bloch–McConnell equations, this framework comprised two deep neural networks (DNNs) and a singular value decomposition (SVD) module. The first DNN identified B0 shifts in Z‐spectra and aligned them to correct frequencies. After B0 correction, the lower‐B0Z‐spectra were streamlined to the second DNN, casting into the key feature representations of higher‐B0Z‐spectra, obtained through SVD truncation. Finally, the complete higher‐B0Z‐spectra were recovered from inverse SVD, given the low‐rank property of Z‐spectra. This study constructed and validated two models, a phosphocreatine (PCr) model and a pseudo‐in‐vivo one. Each experimental dataset, including PCr phantoms, egg white phantoms, and in vivo rat brains, was sequentially acquired on a 3 T human and a 9.4 T animal scanner. Results demonstrated that the synthetic 9.4 T Z‐spectra were almost identical to the experimental ground truth, showing low RMSE (0.11% ± 0.0013% for seven PCr tubes, 1.8% ± 0.2% for three egg white tubes, and 0.79% ± 0.54% for three rat slices) and high R2 (>0.99). The synthesized amide and NOE contrast maps, calculated using the Lorentzian difference, were also well matched with the experiments. Additionally, the synthesis model exhibited robustness to B0 inhomogeneities, noise, and other acquisition imperfections. In conclusion, the proposed framework enables synthesis of higher‐B0Z‐spectra from lower‐B0 ones, which may facilitate CEST MRI quantification and applications. [ABSTRACT FROM AUTHOR]

Purpose: To implement rosette readout trajectories with compressed sensing reconstruction for fast and motion‐robust CEST and magnetization transfer contrast imaging with inherent correction of B0 inhomogeneity. Methods: A pulse sequence was developed for fast saturation transfer imaging using a stack of rosette trajectories with a higher sampling density near the k‐space center. Each rosette lobe was segmented into two halves to generate dual‐echo images. B0 inhomogeneities were estimated using the phase difference between the images and corrected subsequently. The rosette‐based imaging was evaluated in comparison to a fully sampled Cartesian trajectory and demonstrated on CEST phantoms (creatine solutions and egg white) and healthy volunteers at 3 T. Results: Compared with the conventional Cartesian acquisition, compressed sensing reconstructed rosette images provided image quality with overall higher contrast‐to‐noise ratio and significantly faster readout time. Accurate B0 map estimation was achieved from the rosette acquisition with a negligible bias of 0.01 Hz between the rosette and dual‐echo Cartesian gradient echo B0 maps, using the latter as ground truth. The water‐saturation spectra (Z‐spectra) and amide proton transfer weighted signals obtained from the rosette‐based sequence were well preserved compared with the fully sampled data, both in the phantom and human studies. Conclusions: Fast, motion‐robust, and inherent B0‐corrected CEST and magnetization transfer contrast imaging using rosette trajectories could improve subject comfort and compliance, contrast‐to‐noise ratio, and provide inherent B0 homogeneity information. This work is expected to significantly accelerate the translation of CEST‐MRI into a robust, clinically viable approach. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a novel MRI technology to image certain compounds at extremely low concentrations. Long acquisition time to measure signals at a set of offset frequencies of the Z-spectra and to repeat measurements to reduce noise pose significant challenges to its applications. This study explores correlations of CEST MR images along the spatial and Z-spectral dimensions to improve MR image quality and robustness of magnetization transfer ratio (MTR) asymmetry estimation via a joint k-ω reconstruction model. The model was formulated as an optimization problem with respect to MR images at all frequencies ω, while incorporating regularizations along the spatial and spectral dimensions. The solution was subject to a self-consistency condition that the Z-spectrum of each pixel follows a multi-peak data fitting model corresponding to different CEST pools. The optimization problem was solved using the alternating direction method of multipliers. The proposed joint reconstruction method was evaluated on a simulated CEST MRI phantom and semi-experimentally on choline and iopamidol phantoms with added Gaussian noise of various levels. Results demonstrated that the joint reconstruction method was more tolerable to noise and reduction in number of offset frequencies by improving signal-to-noise ratio (SNR) of the reconstructed images and reducing uncertainty in MTR asymmetry estimation. In the choline and iopamidol phantom cases with 10.5% noise in the measurement data, our method achieved an averaged SNR of 31.0 dB and 32.2 dB compared to the SNR of 24.7 dB and 24.4 dB in the conventional reconstruction approach. It reduced uncertainty of the MTR asymmetry estimation over all regions of interest by 54.4% and 43.7%, from 1.71 and 2.38 to 0.78 and 1.71, respectively.

Purpose: Gene therapy using adeno‐associated virus (AAV) vector‐mediated gene delivery has undergone substantial growth in recent years with promising results in both preclinical and clinical studies, as well as emerging regulatory approval. However, the inability to quantify the efficacy of gene therapy from cellular delivery of gene‐editing technology to specific functional outcomes is an obstacle for efficient development of gene therapy treatments. Building on prior works that used the CEST reporter gene lysine rich protein, we hypothesized that AAV viral capsids may generate endogenous CEST contrast from an abundance of surface lysine residues. Methods: NMR experiments were performed on isolated solutions of AAV serotypes 1–9 on a Bruker 800‐MHz vertical scanner. In vitro experiments were performed for testing of CEST‐NMR contrast of AAV2 capsids under varying pH, density, biological transduction stage, and across multiple serotypes and mixed biological media. Reverse transcriptase–polymerase chain reaction was used to quantify virus concentration. Subsequent experiments at 7 T optimized CEST saturation schemes for AAV contrast detection and detected AAV2 particles encapsulated in a biocompatible hydrogel administered in the hind limb of mice. Results: CEST‐NMR experiments revealed CEST contrast up to 52% for AAV2 viral capsids between 0.6 and 0.8 ppm. CEST contrast generated by AAV2 demonstrated high levels of CEST contrast across a variety of chemical environments, concentrations, and saturation schemes. AAV2 CEST contrast displayed significant positive correlations with capsid density (R2 > 0.99, p < 0.001), pH (R2 = 0.97, p = 0.01), and viral titer per cell count (R2 = 0.92, p < 0.001). Transition to a preclinical field strength yielded up to 11.8% CEST contrast following optimization of saturation parameters. In vivo detection revealed statistically significant molecular contrast between viral and empty hydrogels using both mean values (4.67 ± 0.75% AAV2 vs. 3.47 ± 0.87% empty hydrogel, p = 0.02) and quantile analysis. Conclusion: AAV2 viral capsids exhibit strong capacity as an endogenous CEST contrast agent and can potentially be used for monitoring and evaluation of AAV vector‐mediated gene therapy protocols. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a novel MRI technology to image certain compounds at extremely low concentrations. Long acquisition time to measure signals at a set of offset frequencies of the Z-spectra and to repeat measurements to reduce noise pose significant challenges to its applications. This study explores correlations of CEST MR images along the spatial and Z-spectral dimensions to improve MR image quality and robustness of magnetization transfer ratio (MTR) asymmetry estimation via a joint k- ω reconstruction model. The model was formulated as an optimization problem with respect to MR images at all frequencies ω , while incorporating regularizations along the spatial and spectral dimensions. The solution was subject to a self-consistency condition that the Z-spectrum of each pixel follows a multi-peak data fitting model corresponding to different CEST pools. The optimization problem was solved using the alternating direction method of multipliers. The proposed joint reconstruction method was evaluated on a simulated CEST MRI phantom and semi-experimentally on choline and iopamidol phantoms with added Gaussian noise of various levels. Results demonstrated that the joint reconstruction method was more tolerable to noise and reduction in number of offset frequencies by improving signal-to-noise ratio (SNR) of the reconstructed images and reducing uncertainty in MTR asymmetry estimation. In the choline and iopamidol phantom cases with 10.5% noise in the measurement data, our method achieved an averaged SNR of 31.0 dB and 32.2 dB compared to the SNR of 24.7 dB and 24.4 dB in the conventional reconstruction approach. It reduced uncertainty of the MTR asymmetry estimation over all regions of interest by 54.4% and 43.7%, from 1.71 and 2.38 to 0.78 and 1.71, respectively. [ABSTRACT FROM AUTHOR]

Proton exchange underpins essential mechanisms in diverse MR imaging contrasts. Omega plots have proven effective in mapping proton exchange rates (k ex) in live human brains, enabling the differentiation of MS lesion activities and characterization of ischemic stroke. However, Omega plots require extended saturation durations (typically 5 to 10 s), resulting in high specific absorption rates (SAR) that can hinder clinical feasibility. In this study, we introduce a novel k ex mapping approach, named induced Saturation Transfer Recovery Steady-States (iSTRESS). iSTRESS integrates an excitation flip angle pulse prior to chemical exchange saturation transfer (CEST) saturation, effectively aligning the magnetization with its steady-state value. This innovation reduces saturation times and mitigates SAR concerns. The formula for iSTRESS-based k ex quantification was derived theoretically, involving two measurements with distinct excitation flip angles and saturation B 1 values. Bloch-McConnell simulations confirmed that iSTRESS-based k ex values closely matched input values (R2 > 0.99). An iSTRESS MRI sequence was implemented on a 9.4 T preclinical MRI, imaging protein phantoms with pH values ranging from 6.2 to 7.4 (n = 4). Z -spectra were acquired using excitation flip angles of 30° and 60°, followed by CEST saturation at powers of 30 and 120 Hz respectively, with a total saturation time of <1 s, resulting in two iSTRESS states for k ex mapping. k ex maps derived from the phantom study exhibited a linear correlation (R2 > 0.99) with Omega plot results. The developed iSTRESS method allows for k ex quantification with significantly reduced saturation times, effectively minimizing SAR concerns. [ABSTRACT FROM AUTHOR]

Purpose: Clinical scanners require pulsed CEST sequences to maintain amplifier and specific absorption rate limits. During off-resonant RF irradiation and interpulse delay, the magnetization can accumulate specific relative phases within the pulse train. In this work, we show that these phases are important to consider, as they can lead to unexpected artifacts when no interpulse gradient spoiling is performed during the saturation train. Methods: We investigated sideband artifacts using a CEST-3D snapshot gradient-echo sequence at 3 T. Initially, Bloch-McConnell simulations were carried outwith Pulseq-CEST, while measurementswere performed in vitro and in vivo. Results: Sidebands can be hidden in Z-spectra, and their structure becomes clearly visible only at high sampling. Sidebands are further influenced by B0 inhomogeneities and the RF phase cycling within the pulse train. In vivo, sidebands are mostly visible in liquid compartments such as CSF. Multi-pulse sidebands can be suppressed by interpulse gradient spoiling. Conclusion:We provide new insights into sidebands occurring in pulsed CEST experiments and show that, similar as in imaging sequences, gradient and RF spoiling play an important role. Gradient spoiling avoids misinterpretations of sidebands as CEST effects especially in liquid environments including pathological tissue or for CEST resonances close to water. It is recommended to simulate pulsed CEST sequences in advance to avoid artifacts. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) is a magnetic resonance (MR) imaging method providing molecular image contrasts based on indirect detection of low concentrated solutes. Previous CEST studies focused predominantly on the imaging of single CEST exchange regimes (e.g., slow, intermediate or fast exchanging groups). In this work, we aim to establish a so‐called comprehensive CEST protocol for 7 T, covering the different exchange regimes by three saturation B1 amplitude regimes: low, intermediate and high. We used the results of previous publications and our own simulations in pulseq‐CEST to produce a 7 T CEST protocol that has sensitivity to these three B1 regimes. With postprocessing optimization (simultaneous mapping of water shift and B1, B0‐fitting, multiple interleaved mode saturation B1 correction, neural network employment (deepCEST) and analytical input feature reduction), we are able to shorten our initially 40 min protocol to 15 min and generate six CEST contrast maps simultaneously. With this protocol, we measured four healthy subjects and one patient with a brain tumor. We established a comprehensive CEST protocol for clinical 7 T MRI, covering three different B1 amplitude regimes. We were able to reduce the acquisition time significantly by more than 50%, while still maintaining decent image quality and contrast in healthy subjects and one patient with a tumor. Our protocol paves the way to perform comprehensive CEST studies in clinical scan times for hypothesis generation regarding molecular properties of certain pathologies, for example, ischemic stroke or high‐grade brain tumours. [ABSTRACT FROM AUTHOR]

Purpose: To develop a novel MR physics‐driven, deep‐learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR. Methods: A neural network was designed to predict a direct water saturation and MTC‐dominated signal at a certain CEST frequency offset using a few high‐frequency offset features in the Z‐spectrum. The accuracy, scan‐rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics. Results: The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190‐fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR‐based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 μT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema. Conclusion: The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross‐sectional studies with low scan‐rescan variability. [ABSTRACT FROM AUTHOR]

Purpose: Endogenous CEST signal usually has low specificity due to contaminations from the magnetization transfer contrast (MTC) and other labile protons with overlapping or close Larmor frequencies. We propose to improve CEST signal specificity with adjustment of rotation and saturation effects (AROSE). Methods: The AROSE approach measures the difference between CEST signals acquired with the same average irradiation power but largely different duty cycles, for example, a continuous wave or a high duty cycle pulse train versus a low duty cycle pulse train with a flip angle φ. Simulation, phantom, and in vivo rodent studies were performed to evaluate the characteristics of the AROSEφ signal. Results: Simulation and experimental results show that AROSE2π is a low‐pass filter that can suppress fast exchanging processes (e.g., >3000 s−1), whereas AROSEπ is a band‐pass filter suppressing both fast and slow exchange (e.g., <30 s−1) rates. For other φ angles, the sensitivity and the exchange‐rate filtering effect of AROSEφ falls between AROSEπ and AROSE2π. AROSE can also minimize MTC and improve the Larmor frequency selectivity of the CEST signal. The linewidth of the AROSE1.5π spectrum is about 60% to 65% when compared to the CEST spectrum measured by continuous wave. Depending on the needs of an application, the sensitivity, exchange‐rate filtering, and Larmor frequency selectivity can be adjusted by varying the flip angle, duty cycle, and average irradiation power. Conclusion: Compared to conventional CEST signals, AROSE can minimize MTC and improve exchange rate filtering and Larmor frequency specificity. [ABSTRACT FROM AUTHOR]

Although NMR spectroscopy is routinely used to study the conformational dynamics of biomolecules, robust analyses of the data are challenged in cases where exchange is more complex than two-state, such as when a 'visible' major conformer exchanges with two 'invisible' minor states on the millisecond timescale. It is becoming increasingly clear that chemical exchange saturation transfer (CEST) NMR experiments that were initially developed to study systems undergoing slow interconversion are also sensitive to intermediate—fast timescale biomolecular conformational exchange. Here we investigate the utility of the amide 15N CEST experiment to characterise protein three-state exchange occurring on the millisecond timescale by studying the interconversion between the folded (F) state of the FF domain from human HYPA/FBP11 (WT FF) and two of its folding intermediates I1 and I2. Although 15N CPMG experiments are consistent with the F state interconverting with a single minor state on the millisecond timescale, 15N CEST data clearly establish an exchange process between F and a pair of minor states. A unique three-state exchange model cannot be obtained by analysis of 15N CEST data recorded at a single temperature. However, including the relative sign of the difference in the chemical shifts of the two minor states based on a simple two-state analysis of CEST data recorded at multiple temperatures, results in a robust three-state model in which the F, I1 and I2 states interconvert with each other on the millisecond timescale ( k e x , F I 1 ~ 550 s−1, k e x , F I 2 ~ 1200 s−1, k e x , I 1 I 2 ~ 5000 s−1), with I1 and I2 sparsely populated at ~ 0.15% and ~ 0.35%, respectively, at 15 °C. A computationally demanding grid-search of exchange parameter space is not required to extract the best-fit exchange parameters from the CEST data. The utility of the CEST experiment, thus, extends well beyond studies of conformers in slow exchange on the NMR chemical shift timescale, to include systems with interconversion rates on the order of thousands/second. [ABSTRACT FROM AUTHOR]

Abstract In recent years, the use of light to selectively and precisely activate drugs has been developed along the fundamental concepts of photopharmacology. One of the key methods in this field relies on transiently silencing the drug activity with photocleavable protecting groups (PPGs). To effectively utilize light‐activated drugs in future medical applications, physicians will require a reliable method to assess whether light penetrates deep enough into the tissues to activate the photoresponsive theragnostic agents. Here, we describe the development and evaluation of magnetic resonance (MR) imaging agents that allow for the detection of light penetration and drug activation in the tissues using non‐invasive whole‐body magnetic resonance imaging (MRI) and chemical exchange saturation transfer (CEST)‐MRI modalities. The approach relies on the use of PPG‐protected MR contrast agents, which upon irradiation with light change their imaging signal. A Gadolinium(III)‐based MRI contrast agent is presented that undergoes a significant change in relaxivity (25%) upon uncaging, providing a reliable indicator of light‐induced cargo release. Additionally, we introduce the first light‐responsive CEST‐MRI imaging agent, enabling positive signal enhancement (off‐to‐on) upon light activation, offering a novel approach to visualize the activation of photoactive agents in living tissues. This research provides a proof‐of‐principle for the non‐invasive, whole‐body imaging of light penetration and drug activation with high temporal resolution characteristic of MR methods.

Phosphate is an essential anion in the human body, comprising approximately 1% of the total body weight, and playing a vital role in metabolism, cell membranes, and bone formation. We have recently provided spectroscopic, microscopic, and computational evidence indicating that phosphates can aggregate much more readily in solution than previously thought. This prior work provided indirect evidence through the observation of unusual 31P NMR relaxation and line‐broadening effects with increasing temperature. Here, we show that, under conditions of slow exchange and selective RF saturation, additional features become visible in chemical exchange saturation transfer (CEST) experiments, which appear to be related to the previously reported phosphate clustering. In particular, CEST shows pronounced dips several ppm upfield of the main phosphate resonance at low temperatures, while direct 31P spectroscopy does not produce any signals in that range. We study the pH dependence of these new spectroscopic features and present exchange and spectroscopic parameters based on fitting the CEST data. These findings could be of importance in the investigation of phosphate dynamics, especially in the biological milieu. [ABSTRACT FROM AUTHOR]

Purpose: A new nuclear Overhauser enhancement (NOE)‐mediated saturation transfer signal at around −1.6 ppm, termed NOE(−1.6), has been reported at high fields of 7T and 9.4T previously. This study aims to validate the presence of this signal at a relatively low field of 4.7T and evaluate its variations in different brain regions and tumors. Methods: Rats were injected with monocrystalline iron oxide nanoparticles to reduce the NOE(−1.6) signal. CEST signals were measured using different saturation powers before and after injection to assess the presence of this signal. Multiple‐pool Lorentzian fits, with/without inclusion of the NOE(−1.6) pool, were performed on CEST Z‐spectra obtained from healthy rat brains and rats with 9L tumors. These fits aimed to further validate the presence of the NOE(−1.6) signal and quantify its amplitude. Results: The NOE(−1.6) signal exhibited a dramatic change following the injection of monocrystalline iron oxide nanoparticles, confirming its presence at 4.7T. The NOE(−1.6) signal reached its peak at a saturation power of ∼0.75 μT, indicating an optimized power level. The multiple‐pool Lorentzian fit without the NOE(−1.6) pool showed higher residuals around −1.6 ppm compared to the fit with this pool, further supporting the presence of this signal. The NOE(−1.6) signal did not exhibit significant variation in the corpus callosum and caudate putamen regions, but it showed a significant decrease in tumors, which aligns with previous findings at 9.4T. Conclusion: This study successfully demonstrated the presence of the NOE(−1.6) signal at 4.7T, which provides valuable insights into its potential applications at lower field strengths. [ABSTRACT FROM AUTHOR]

Purpose: To develop a model‐based deep neural network for high‐quality image reconstruction of undersampled multi‐coil CEST data. Theory and Methods: Inspired by the variational network (VN), the CEST image reconstruction equation is unrolled into a deep neural network (CEST‐VN) with a k‐space data‐sharing block that takes advantage of the inherent redundancy in adjacent CEST frames and 3D spatial–frequential convolution kernels that exploit correlations in the x‐ω domain. Additionally, a new pipeline based on multiple‐pool Bloch–McConnell simulations is devised to synthesize multi‐coil CEST data from publicly available anatomical MRI data. The proposed network is trained on simulated data with a CEST‐specific loss function that jointly measures the structural and CEST contrast. The performance of CEST‐VN was evaluated on four healthy volunteers and five brain tumor patients using retrospectively or prospectively undersampled data with various acceleration factors, and then compared with other conventional and state‐of‐the‐art reconstruction methods. Results: The proposed CEST‐VN method generated high‐quality CEST source images and amide proton transfer‐weighted maps in healthy and brain tumor subjects, consistently outperforming GRAPPA, blind compressed sensing, and the original VN. With the acceleration factors increasing from 3 to 6, CEST‐VN with the same hyperparameters yielded similar and accurate reconstruction without apparent loss of details or increase of artifacts. The ablation studies confirmed the effectiveness of the CEST‐specific loss function and data‐sharing block used. Conclusions: The proposed CEST‐VN method can offer high‐quality CEST source images and amide proton transfer‐weighted maps from highly undersampled multi‐coil data by integrating the deep learning prior and multi‐coil sensitivity encoding model. [ABSTRACT FROM AUTHOR]

Purpose: CEST MRI is influenced by fat signal, which can reduce the apparent CEST contrast or lead to pseudo‐CEST effects. Our goal was to develop a fat artifact correction based on multi‐echo fat–water separation that functions stably for 7 T knee MRI data. Methods: Our proposed algorithm utilizes the full complex data and a phase demodulation with an off‐resonance map estimation based on the Z‐spectra prior to fat–water separation to achieve stable fat artifact correction. Our method was validated and compared to multi‐echo–based methods originally proposed for 3 T by Bloch–McConnell simulations and phantom measurements. Moreover, the method was applied to in vivo 7 T knee MRI examinations and compared to Gaussian fat saturation and a published single‐echo Z‐spectrum–based fat artifact correction method. Results: Phase demodulation prior to fat–water separation reduced the occurrence of fat–water swaps. Utilizing the complex signal data led to more stable correction results than working with magnitude data, as was proposed for 3 T. Our approach reduced pseudo‐nuclear Overhauser effects compared to the other correction methods. Thus, the mean asymmetry contrast at 3.5 ppm in cartilage over five volunteers increased from −9.2% (uncorrected) and −10.6% (Z‐spectrum–based) to −1.5%. Results showed higher spatial stability than with the fat saturation pulse. Conclusion: Our work demonstrates the feasibility of multi‐echo–based fat–water separation with an adaptive fat model for fat artifact correction for CEST MRI at 7 T. Our approach provided better fat artifact correction throughout the entire spectrum and image than the fat saturation pulse or Z‐spectrum–based correction method for both phantom and knee imaging results. [ABSTRACT FROM AUTHOR]

Purpose: Axillary lymph nodes (LNs) often present a reservoir for metastatic breast cancer, yet metastatic LN involvement cannot be discerned definitively using diagnostic imaging. This study investigated whether in vivo CEST may discriminate LNs with versus without metastatic involvement. Methods: 3T MRI was performed in patients with breast cancer before clinically‐indicated mastectomy or lumpectomy with LN removal, after which LN metastasic involvement was determined using histological evaluation. Non‐contrast anatomical imaging, as well as B0 and B1 field maps, were acquired in sequence with three‐point CEST‐Dixon (3D turbo‐gradient‐echo; factor = 25; TR/TE1/ΔTE = 851/1.35/1.1 ms; spatial‐resolution = 2.5 × 2.5 × 6 mm; slices = 10; four sinc‐gauss pulses with duty‐cycle = 0.5, total saturation duration = 701.7 ms; B1 = 1.5 μT; saturation offsets = −5.5 to +5.5 ppm; stepsize = 0.2 ppm; scan duration = 6 min 30 s). The mean z‐spectrum from LNs with (n = 20) versus without (n = 22) metastatic involvement were analyzed and a Wilcoxon rank‐sum test (significance: p < 0.05) was applied to evaluate differences in B0, B1, and magnetization transfer ratio (MTR) in differing spectral regions of known proton exchange (nuclear Overhauser effect [NOE], amide, amine, and hydroxyl) between cohorts. Results: No difference in axillary B1 (p = 0.634) or B0 (p = 0.689) was observed between cohorts. Elevated MTR was observed for the NOE (−1.7 ppm; MTR = 0.285 ± 0.075 vs. 0.248 ± 0.039; p = 0.048), amine (+2.5 ppm; MTR = 0.284 ± 0.067 vs. 0.234 ± 0.31; p = 0.005), and hydroxyl (+1 ppm; MTR = 0.394 ± 0.075 vs. 0.329 ± 0.055; p = 0.002) protons in LNs from participants with versus without metastatic involvement. Conclusions: Findings are consistent with a unique metastatic LN microenvironment detectable by CEST‐Dixon and suggest that CEST MRI may have potential for mapping LN metastasis non‐invasively in vivo. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) is a versatile technique that enables noninvasive detections of endogenous metabolites present in low concentrations in living tissue. However, CEST imaging suffers from an inherently low signal‐to‐noise ratio (SNR) due to the decreased water signal caused by the transfer of saturated spins. This limitation challenges the accuracy and reliability of quantification in CEST imaging. In this study, a novel spatial–spectral denoising method, called BOOST (suBspace denoising with nOnlocal lOw‐rank constraint and Spectral local‐smooThness regularization), was proposed to enhance the SNR of CEST images and boost quantification accuracy. More precisely, our method initially decomposes the noisy CEST images into a low‐dimensional subspace by leveraging the global spectral low‐rank prior. Subsequently, a spatial nonlocal self‐similarity prior is applied to the subspace‐based images. Simultaneously, the spectral local‐smoothness property of Z‐spectra is incorporated by imposing a weighted spectral total variation constraint. The efficiency and robustness of BOOST were validated in various scenarios, including numerical simulations and preclinical and clinical conditions, spanning magnetic field strengths from 3.0 to 11.7 T. The results demonstrated that BOOST outperforms state‐of‐the‐art algorithms in terms of noise elimination. As a cost‐effective and widely available post‐processing method, BOOST can be easily integrated into existing CEST protocols, consequently promoting accuracy and reliability in detecting subtle CEST effects. [ABSTRACT FROM AUTHOR]

Purpose: pH enhanced (pHenh) CEST imaging combines the pH sensitivity from amide and guanidino signals, but the saturation parameters have not been optimized. We propose pHdual as a variant of pHenh that suppresses background signal variations, while enhancing pH sensitivity and potential for imaging ischemic brain injury of stroke. Methods: Simulation and in vivo rodent stroke experiments of pHenh MRI were performed with varied RF saturation powers for both amide and guanidino protons to optimize the contrast between lesion/normal tissues, while simultaneously minimizing signal variations across different types of normal tissues. In acute stroke, contrast and volume ratio measured by pHdual imaging were compared with an amide‐CEST approach, and perfusion and diffusion MRI. Results: Simulation experiments indicated that amide and guanidino CEST signals exhibit unique sensitivities across different pH ranges, with pHenh producing greater sensitivity over a broader pH regime. The pHenh data of rodent stroke brain demonstrated that the lesion/normal tissue contrast was maximized for an RF saturation power pair of 0.5 μT at 2.0 ppm and 1.0 μT at 3.6 ppm, whereas an optimal contrast‐to‐variation ratio (CVR) was obtained with a 0.7 μT saturation at 2.0 ppm and 0.8 μT at 3.6 ppm. In acute stroke, CVR optimized pHenh (i.e., pHdual) achieved a higher sensitivity than the three‐point amide‐CEST approach, and distinct patterns of lesion tissue compared to diffusion and perfusion MRI. Conclusion: pHdual MRI improves the sensitivity of pH‐weighted imaging and will be a valuable tool for assessing tissue viability in stroke. [ABSTRACT FROM AUTHOR]

Purpose: CEST MRI has been used to probe changes in cardiac metabolism via assessment of CEST contrast from Cr. However, B1 variation across the myocardium leads to spatially variable Cr CEST contrast in healthy myocardium. Methods: We developed a spatial–spectral (SPSP) saturation pulsed CEST protocol to compensate for B1 variation. Flip angle maps were used to individually tailor SPSP pulses comprised of a train of one‐dimensional spatially selective subpulses selective along the principal B1 gradient dimension. Complete Z‐spectra in the hearts of (n = 10) healthy individuals were acquired using conventional Gaussian saturation and SPSP schemes and supported by phantom studies. Results: In simulations, the use of SPSP pulses reduced the average SD of the effective saturation B1 values within the myocardium (n = 10) from 0.12 ± 0.02 μT to 0.05 ± 0.01 μT (p < 0.01) and reduced the average SD of Cr CEST contrast in vivo from 10.0 ± 4.3% to 6.1 ± 3.5% (p < 0.05). Results from the hearts of human subjects showed a significant reduction of CEST contrast distribution at 2 ppm, as well as amplitude, when using SPSP saturation. Corresponding phantom experiments revealed PCr‐specific contrast generation at body temperature when SPSP saturation was used but combined PCr and Cr contrast generation when Gaussian saturation was used. Conclusion: The use of SPSP saturation pulsed CEST resulted in PCr‐specific contrast generation and enabled ratiometric mapping of PCr to total Cr CEST contrast in the human heart at 3T. [ABSTRACT FROM AUTHOR]

Abstract Background With metabolic alterations of the tumor microenvironment (TME) contributing to cancer progression, metastatic spread and response to targeted therapies, non-invasive and repetitive imaging of tumor metabolism is of major importance. The purpose of this study was to investigate whether multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST-MRI) allows to detect differences in the metabolic profiles of the TME in murine breast cancer models with divergent degrees of malignancy and to assess their response to immunotherapy. Methods Tumor characteristics of highly malignant 4T1 and low malignant 67NR murine breast cancer models were investigated, and their changes during tumor progression and immune checkpoint inhibitor (ICI) treatment were evaluated. For simultaneous analysis of different metabolites, multiparametric CEST-MRI with calculation of asymmetric magnetization transfer ratio (MTRasym) at 1.2 to 2.0 ppm for glucose-weighted, 2.0 ppm for creatine-weighted and 3.2 to 3.6 ppm for amide proton transfer- (APT-) weighted CEST contrast was conducted. Ex vivo validation of MRI results was achieved by 1H nuclear magnetic resonance spectroscopy, matrix-assisted laser desorption/ionization mass spectrometry imaging with laser postionization and immunohistochemistry. Results During tumor progression, the two tumor models showed divergent trends for all examined CEST contrasts: While glucose- and APT-weighted CEST contrast decreased and creatine-weighted CEST contrast increased over time in the 4T1 model, 67NR tumors exhibited increased glucose- and APT-weighted CEST contrast during disease progression, accompanied by decreased creatine-weighted CEST contrast. Already three days after treatment initiation, CEST contrasts captured response to ICI therapy in both tumor models. Conclusion Multiparametric CEST-MRI enables non-invasive assessment of metabolic signatures of the TME, allowing both for estimation of the degree of tumor malignancy and for assessment of early response to immune checkpoint inhibition.

Novel MRI contrast methods, such as Chemical Exchange Saturation Transfer (CEST), rely on previously developed theory and approaches, often introduced first in solidstate NMR. Understanding or at least connecting the basic principles and original works to the modern-day contrast methods in MRI is instructive. The work brings together concepts in relaxation, saturation, and spin lock experiments in the dynamic (exchanging) systems. The work describes how basic principles and theory are translated and being applied to MRI contrast, including MT and CEST. Finally, we review select papers generalizing concepts of relaxation under periodic RF.

Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) provides a novel method for analyzing biomolecule concentrations in tissues without exogenous contrast agents. Despite its potential, achieving a high signal-to-noise ratio (SNR) is imperative for detecting small CEST effects. Traditional metrics such as Magnetization Transfer Ratio Asymmetry (MTRasym) and Lorentzian analyses are vulnerable to image noise, hampering their precision in quantitative concentration estimations. Recent noise-reduction algorithms like principal component analysis (PCA), nonlocal mean filtering (NLM), and block matching combined with 3D filtering (BM3D) have shown promise, as there is a burgeoning interest in the utilization of neural networks (NNs), particularly autoencoders, for imaging denoising. This study uses the Bloch–McConnell equations, which allow for the synthetic generation of CEST images and explores NNs efficacy in denoising these images. Using synthetically generated phantoms, autoencoders were created, and their performance was compared with traditional denoising methods using various datasets. The results underscored the superior performance of NNs, notably the ResUNet architectures, in noise identification and abatement compared to analytical approaches across a wide noise gamut. This superiority was particularly pronounced at elevated noise intensities in the in vitro data. Notably, the neural architectures significantly improved the PSNR values, achieving up to 35.0, while some traditional methods struggled, especially in low-noise reduction scenarios. However, the application to the in vivo data presented challenges due to varying noise profiles. This study accentuates the potential of NNs as robust denoising tools, but their translation to clinical settings warrants further investigation. [ABSTRACT FROM AUTHOR]

The z‐spectrum contains many pools with different exchange rates and T2 values, which can make it difficult to interpret in vivo data and complicates the design of experiments aimed at providing sensitivity to one pool. This work aims to characterise the main pools observable with MRI at 7T in the human brain. To achieve this, we acquired z‐spectra at multiple saturation powers in the human brain at 7T. We used simulations to optimise the use of particle swarm optimisation (PSO) to fit these data, validating this approach using further simulations and creatine phantoms. We then used the PSO to fit data from grey and white matter for the pool size, exchange rate, and T2 of five proton pools (magnetisation transfer, amides, amines, nuclear Overhauser enhancement NOE−3.5ppm and NOE−1.7ppm in addition to water). We then devised an approach for using PSO to fit z‐spectra while limiting the computational burden, and we investigated the sensitivity of the fit to T2 and k for three overlapping pools. We used this to measure the exchange rate of creatine and to show that it varied with temperature, as expected. In the brain we measured a significantly larger pool size in white matter than in grey matter for the magnetisation transfer pool and the NOE−3.5ppm pool. For all other parameters we found no significant difference between grey and white matter. We showed that PSO can be used to fit z‐spectra acquired at a range of B1 to provide information about peak position, amplitude, exchange rate, and T2 in vivo in the human brain. These data could provide more sensitivity to change in some clinical conditions and will also provide key information for further experimental design. [ABSTRACT FROM AUTHOR]

Non-invasive methods of detecting early-stage Alzheimer's disease (AD) can provide valuable insight into disease pathology, improving the diagnosis and treatment of AD. Nuclear Overhauser enhancement (NOE) MRI is a technique that provides image contrast sensitive to lipid and protein content in the brain. These macromolecules have been shown to be altered in Alzheimer's pathology, with early disruptions in cell membrane integrity and signaling pathways leading to the buildup of amyloid-beta plaques and neurofibrillary tangles. We used template-based analyzes of NOE MRI data and the characteristic Z-spectrum, with parameters optimized for increase specificity to NOE, to detect changes in lipids and proteins in an AD mouse model that recapitulates features of human AD. We find changes in NOE contrast in the hippocampus, hypothalamus, entorhinal cortex, and fimbria, with these changes likely attributed to disruptions in the phospholipid bilayer of cell membranes in both gray and white matter regions. This study suggests that NOE MRI may be a useful tool for monitoring early-stage changes in lipid-mediated metabolism in AD and other disorders with high spatial resolution. [ABSTRACT FROM AUTHOR]

The molecular imaging of biomarkers plays an increasing role in medical diagnostics. In particular, the imaging of enzyme activity is a promising approach, as it enables the use of its inherent catalytic activity for the amplification of an imaging signal. The increased activity of a sulfatase enzyme has been observed in several types of cancers. We describe the development and in vitro evaluation of molecular imaging agents that allow for the detection of sulfatase activity using the whole-body, non-invasive MRI and CEST imaging methods. This approach relies on a responsive ligand that features a sulfate ester moiety, which upon sulfatase-catalyzed hydrolysis undergoes an elimination process that changes the functional group, coordinating with the metal ion. When Gd3+ is used as the metal, the complex can be used for MRI, showing a 25% decrease at 0.23T and a 42% decrease at 4.7T in magnetic relaxivity after enzymatic conversion, thus providing a "switch-off" contrast agent. Conversely, the use of Yb3+ as the metal leads to a "switch-on" effect in the CEST imaging of sulfatase activity. Altogether, the results presented here provide a molecular basis and a proof-of-principle for the magnetic imaging of the activity of a key cancer biomarker. [ABSTRACT FROM AUTHOR]

Multi-parametric MRI (mpMRI) technology enables non-invasive and quantitative assessments of the structural, molecular, and functional characteristics of various neurological diseases. Despite the recognized importance of studying spinal cord pathology, mpMRI applications in spinal cord research have been somewhat limited, partly due to technical challenges associated with spine imaging. However, advances in imaging techniques and improved image quality now allow longitudinal investigations of a comprehensive range of spinal cord pathological features by exploiting different endogenous MRI contrasts. This review summarizes the use of mpMRI techniques including blood oxygenation level-dependent (BOLD) functional MRI (fMRI), diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST) MRI in monitoring different aspects of spinal cord pathology. These aspects include cyst formation and axonal disruption, demyelination and remyelination, changes in the excitability of spinal grey matter and the integrity of intrinsic functional circuits, and non-specific molecular changes associated with secondary injury and neuroinflammation. These approaches are illustrated with reference to a nonhuman primate (NHP) model of traumatic cervical spinal cord injuries (SCI). We highlight the benefits of using NHP SCI models to guide future studies of human spinal cord pathology, and demonstrate how mpMRI can capture distinctive features of spinal cord pathology that were previously inaccessible. Furthermore, the development of mechanism-based MRI biomarkers from mpMRI studies can provide clinically useful imaging indices for understanding the mechanisms by which injured spinal cords progress and repair. These biomarkers can assist in the diagnosis, prognosis, and evaluation of therapies for SCI patients, potentially leading to improved outcomes. [ABSTRACT FROM AUTHOR]

CEST MRI methods, such as APT and NOE imaging reveal biomarkers with significant diagnostic potential due to their ability to access molecular tissue information. Regardless of the technique used, CEST MRI data are affected by static magnetic B 0 and radiofrequency B 1 field inhomogeneities that degrade their contrast. For this reason, the correction of B 0 field-induced artefacts is essential, whereas accounting for B 1 field inhomogeneities have shown significant improvements in image readability. In a previous work, an MRI protocol called WASABI was presented, which can map simultaneously B 0 and B 1 field inhomogeneities, while maintaining the same sequence and readout types as used for CEST MRI. Despite the highly satisfactory quality of B 0 and B 1 maps computed from the WASABI data, the post-processing method is based on an exhaustive search of a four-parameter space and an additional four-parameter non-linear model fitting step. This leads to long post-processing times that are prohibitive in clinical practice. This work provides a new method for fast post-processing of WASABI data with outstanding acceleration of the parameter estimation procedure and without compromising its stability. The resulting computational acceleration makes the WASABI technique suitable for clinical use. The stability of the method is demonstrated on phantom data and clinical 3 Tesla in vivo data. • We propose a new fast and analytical post-processing method for WASABI data. • Method to obtain B 0 and B 1 inhomogeneity maps in few seconds • Its outstanding acceleration permits its use in clinical routine. • Accurate parameter estimation in good agreement with the original method • Method validation on numerical phantoms and on 10 clinical datasets [ABSTRACT FROM AUTHOR]

Purpose: To develop a unified deep‐learning framework by combining an ultrafast Bloch simulator and a semisolid macromolecular magnetization transfer contrast (MTC) MR fingerprinting (MRF) reconstruction for estimation of MTC effects. Methods: The Bloch simulator and MRF reconstruction architectures were designed with recurrent neural networks and convolutional neural networks, evaluated with numerical phantoms with known ground truths and cross‐linked bovine serum albumin phantoms, and demonstrated in the brain of healthy volunteers at 3 T. In addition, the inherent magnetization‐transfer ratio asymmetry effect was evaluated in MTC‐MRF, CEST, and relayed nuclear Overhauser enhancement imaging. A test–retest study was performed to evaluate the repeatability of MTC parameters, CEST, and relayed nuclear Overhauser enhancement signals estimated by the unified deep‐learning framework. Results: Compared with a conventional Bloch simulation, the deep Bloch simulator for generation of the MTC‐MRF dictionary or a training data set reduced the computation time by 181‐fold, without compromising MRF profile accuracy. The recurrent neural network–based MRF reconstruction outperformed existing methods in terms of reconstruction accuracy and noise robustness. Using the proposed MTC‐MRF framework for tissue‐parameter quantification, the test–retest study showed a high degree of repeatability in which the coefficients of variance were less than 7% for all tissue parameters. Conclusion: Bloch simulator–driven, deep‐learning MTC‐MRF can provide robust and repeatable multiple‐tissue parameter quantification in a clinically feasible scan time on a 3T scanner. [ABSTRACT FROM AUTHOR]

Purpose: Quantifications of amide proton transfer (APT) and nuclear Overhauser enhancement (rNOE(−3.5)) mediated saturation transfer with high specificity are challenging because their signals measured in a Z‐spectrum are overlapped with confounding signals from direct water saturation (DS), semi‐solid magnetization transfer (MT), and CEST of fast‐exchange pools. In this study, based on two canonical CEST acquisitions with double saturation powers (DSP), a new data‐postprocessing method is proposed to specifically quantify the effects of APT and rNOE. Methods: For CEST imaging with relatively low saturation powers (ω12$$ {\upomega}_1^2 $$), both the fast‐exchange CEST effect and the semi‐solid MT effect roughly depend on ω12$$ {\upomega}_1^2 $$, whereas the slow‐exchange APT/rNOE(−3.5) effect do not, which is exploited to isolate a part of the APT and rNOE effects from the confounding signals in this study. After a mathematical derivation for the establishment of the proposed method, numerical simulations based on Bloch equations are then performed to demonstrate its specificity to detections of the APT and rNOE effects. Finally, an in vivo validation of the proposed method is conducted using an animal tumor model at a 4.7 T MRI scanner. Results: The simulations show that DSP‐CEST can quantify the effects of APT and rNOE and substantially eliminate the confounding signals. The in vivo experiments demonstrate that the proposed DSP‐CEST method is feasible for the imaging of tumors. Conclusion: The data‐postprocessing method proposed in this study can quantify the APT and rNOE effects with considerably increased specificities and a reduced cost of imaging time. [ABSTRACT FROM AUTHOR]

PurposeTo evaluate the influence of phosphate on amine, amide, and hydroxyl CEST contrast using Bloch-McConnell simulations applied to physical phantom data.MethodsPhantom solutions of 4 representative metabolites with exchangeable protons-glycine (α-amine protons), Cr (η-amine protons), egg white protein (amide protons), and glucose (hydroxyl protons)-were prepared at different pH levels (5.6 to 8.9) and phosphate concentrations (5 to 80 mM). CEST images of the phantom were collected with CEST-EPI sequence at 3 tesla. The CEST data were then fitted to full Bloch-McConnell equation simulations to estimate the exchange rate constants. With the fitted parameters, simulations were performed to evaluate the intracellular and extracellular contributions of CEST signals in normal brain tissue and brain tumors, as well as in dynamic glucose-enhanced experiments.ResultsThe exchange rates of α-amine and hydroxyl protons were found to be highly dependent on both pH and phosphate concentrations, whereas the exchange rates of η-amine and amide protons were pH-dependent, albeit not catalyzed by phosphate. With phosphate being predominantly intracellular, CEST contrast of α-amine exhibited a higher sensitivity to changes in the extracellular microenvironment. Simulations of dynamic glucose-enhanced signals demonstrated that the contrast between normal and tumor tissue was mostly due to the extracellular CEST effect.ConclusionThe proton exchange rates in some metabolites can be greatly catalyzed by the presence of phosphate at physiological concentrations, which substantially alters the CEST contrast. Catalytic agents should be considered as confounding factors in future CEST-MRI research. This new dimension may also benefit the development of novel phosphate-sensitive imaging methods.

Non-invasive methods of detecting early-stage Alzheimer’s disease (AD) can provide valuable insight into disease pathology, improving the diagnosis and treatment of AD. Nuclear Overhauser enhancement (NOE) MRI is a technique that provides image contrast sensitive to lipid and protein content in the brain. These macromolecules have been shown to be altered in Alzheimer’s pathology, with early disruptions in cell membrane integrity and signaling pathways leading to the buildup of amyloid-beta plaques and neurofibrillary tangles. We used template-based analyzes of NOE MRI data and the characteristic Z-spectrum, with parameters optimized for increase specificity to NOE, to detect changes in lipids and proteins in an AD mouse model that recapitulates features of human AD. We find changes in NOE contrast in the hippocampus, hypothalamus, entorhinal cortex, and fimbria, with these changes likely attributed to disruptions in the phospholipid bilayer of cell membranes in both gray and white matter regions. This study suggests that NOE MRI may be a useful tool for monitoring early-stage changes in lipid-mediated metabolism in AD and other disorders with high spatial resolution.

Background: With metabolic alterations of the tumor microenvironment (TME) contributing to cancer progression, metastatic spread and response to targeted therapies, non-invasive and repetitive imaging of tumor metabolism is of major importance. The purpose of this study was to investigate whether multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST-MRI) allows to detect differences in the metabolic profiles of the TME in murine breast cancer models with divergent degrees of malignancy and to assess their response to immunotherapy. Methods: Tumor characteristics of highly malignant 4T1 and low malignant 67NR murine breast cancer models were investigated, and their changes during tumor progression and immune checkpoint inhibitor (ICI) treatment were evaluated. For simultaneous analysis of different metabolites, multiparametric CEST-MRI with calculation of asymmetric magnetization transfer ratio (MTRasym) at 1.2 to 2.0 ppm for glucose-weighted, 2.0 ppm for creatine-weighted and 3.2 to 3.6 ppm for amide proton transfer- (APT-) weighted CEST contrast was conducted. Ex vivo validation of MRI results was achieved by 1H nuclear magnetic resonance spectroscopy, matrix-assisted laser desorption/ionization mass spectrometry imaging with laser postionization and immunohistochemistry. Results: During tumor progression, the two tumor models showed divergent trends for all examined CEST contrasts: While glucose- and APT-weighted CEST contrast decreased and creatine-weighted CEST contrast increased over time in the 4T1 model, 67NR tumors exhibited increased glucose- and APT-weighted CEST contrast during disease progression, accompanied by decreased creatine-weighted CEST contrast. Already three days after treatment initiation, CEST contrasts captured response to ICI therapy in both tumor models. Conclusion: Multiparametric CEST-MRI enables non-invasive assessment of metabolic signatures of the TME, allowing both for estimation of the degree of tumor malignancy and for assessment of early response to immune checkpoint inhibition. [ABSTRACT FROM AUTHOR]

Over the last decade amide 15N CEST experiments have emerged as a popular tool to study protein dynamics that involves exchange between a 'visible' major state and sparsely populated 'invisible' minor states. Although initially introduced to study exchange between states that are in slow exchange with each other (typical exchange rates of, 10 to 400 s−1), they are now used to study interconversion between states on the intermediate to fast exchange timescale while still using low to moderate (5 to 350 Hz) 'saturating' B1 fields. The 15N CEST experiment is very sensitive to exchange as the exchange delay TEX can be quite long (~0.5 s) allowing for a large number of exchange events to occur making it a very powerful tool to detect minor sates populated ( p minor ) to as low as 1%. When systems are in fast exchange and the 15N CEST data has to be described using a model that contains exchange, the exchange parameters are often poorly defined because the χ red 2 versus p minor and χ red 2 versus exchange rate ( k ex ) plots can be quite flat with shallow or no minima and the analysis of such 15N CEST data can lead to wrong estimates of the exchange parameters due to the presence of 'spurious' minima. Here we show that the inclusion of experimentally derived constraints on the intrinsic transverse relaxation rates and the inclusion of visible state peak-positions during the analysis of amide 15N CEST data acquired with moderate B1 values (~50 to ~350 Hz) results in convincing minima in the χ red 2 versus p minor and the χ red 2 versus k ex plots even when exchange occurs on the 100 μs timescale. The utility of this strategy is demonstrated on the fast-folding Bacillus stearothermophilus peripheral subunit binding domain that folds with a rate constant ~104 s−1. Here the analysis of 15N CEST data alone results in χ red 2 versus p minor and χ red 2 versus k ex plots that contain shallow minima, but the inclusion of visible-state peak positions and restraints on the intrinsic transverse relaxation rates of both states during the analysis of the 15N CEST data results in pronounced minima in the χ red 2 versus p minor and χ red 2 versus k ex plots and precise exchange parameters even in the fast exchange regime ( k ex / | Δ ω | ~5). Using this strategy we find that the folding rate constant of PSBD is invariant (~10,500 s−1) from 33.2 to 42.9 °C while the unfolding rates (~70 to ~500 s−1) and unfolded state populations (~0.7 to ~4.3%) increase with temperature. The results presented here show that protein dynamics occurring on the 10 to 104 s−1 timescale can be studied using amide 15N CEST experiments. [ABSTRACT FROM AUTHOR]

Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT‐MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods. [ABSTRACT FROM AUTHOR]

The objective of the current study was to optimize the postprocessing pipeline of 7 T chemical exchange saturation transfer (CEST) imaging for reproducibility and to prove this optimization for the detection of age differences and differences between patients with Parkinson's disease versus normal subjects. The following 7 T CEST MRI experiments were analyzed: repeated measurements of a healthy subject, subjects of two age cohorts (14 older, seven younger subjects), and measurements of 12 patients with Parkinson's disease. A slab‐selective, B1+‐homogeneous parallel transmit protocol was used. The postprocessing, consisting of motion correction, smoothing, B0‐correction, normalization, denoising, B1+‐correction and Lorentzian fitting, was optimized regarding the intrasubject and intersubject coefficient of variation (CoV) of the amplitudes of the amide pool and the aliphatic relayed nuclear Overhauser effect (rNOE) pool within the brain. Seven "tricks" for postprocessing accomplished an improvement of the mean voxel CoV of the amide pool and the aliphatic rNOE pool amplitudes of less than 5% and 3%, respectively. These postprocessing steps are: motion correction with interpolation of the motion of low‐signal offsets (1) using the amide pool frequency offset image as reference (2), normalization of the Z‐spectrum using the outermost saturated measurements (3), B0 correction of the Z‐spectrum with moderate spline smoothing (4), denoising using principal component analysis preserving the 11 highest intensity components (5), B1+ correction using a linear fit (6) and Lorentzian fitting using the five‐pool fit model (7). With the optimized postprocessing pipeline, a significant age effect in the amide pool can be detected. Additionally, for the first time, an aliphatic rNOE contrast between subjects with Parkinson's disease and age‐matched healthy controls in the substantia nigra is detected. We propose an optimized postprocessing pipeline for CEST multipool evaluation. It is shown that by the use of these seven "tricks", the reproducibility and, thus, the statistical power of a CEST measurement, can be greatly improved and subtle changes can be detected. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST‐MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro‐oncology. The slower migration of CEST‐MRI to non‐neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST‐MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker. [ABSTRACT FROM AUTHOR]

The ability of CEST MRI to detect the presence of millimolar concentrations of non‐metallic contrast agents has made it possible to study, non‐invasively, important biological molecules such as proteins and sugars, as well as drugs already approved for clinical use. Here, we review efforts to use sugar and sugar polymers as exogenous contrast agents, which is possible based on the exchange of their hydroxyl protons with water protons. While this capability has raised early enthusiasm, for instance about the possibility of imaging D‐glucose metabolism with MRI in a way analogous to PET, experience over the past decade has shown that this is not trivial. On the other hand, many studies have confirmed the possibility of imaging a large variety of sugar analogues, each with potentially interesting applications to assess tissue physiology. Some promising applications are the study of (i) sugar delivery and transport to assess blood–brain barrier integrity and (ii) sugar uptake by cells for their characterization (e.g., cancer versus healthy), as well as (iii) clearance of sugars to assess tissue drainage—for instance, through the glymphatic system. To judge these opportunities and their challenges, especially in the clinic, it is necessary to understand the technical aspects of detecting the presence of rapidly exchanging protons through the water signal in MRI, especially as a function of magnetic field strength. We expect that novel approaches in terms of MRI detection (both saturation transfer and relaxation based), MRI data analysis, and sugar design will push this young field forward in the next decade. [ABSTRACT FROM AUTHOR]

Glutamate is the primary excitatory neurotransmitter in the mammalian central nervous system. As such, its proper regulation is essential to the healthy function of the human brain, and dysregulation of glutamate metabolism and compartmentalization underlies numerous neurological and neuropsychiatric pathologies. Glutamate‐weighted chemical exchange saturation transfer (gluCEST) MRI is one of the only ways to non‐invasively observe the relative concentration and spatial distribution of glutamate in the human brain. In the past 10 years, gluCEST has developed from a proof‐of‐concept experiment carried out in imaging phantoms and model systems to an increasingly sophisticated technique applied to reveal deviations from baseline neural metabolism in human beings, most notably in patients experiencing seizures of various origins or those on the psychosis spectrum. This article traces that progress, including in‐depth discussion of the technical specifics of gluCEST and potential challenges to performing these experiments rigorously. We discuss the neurobiological context of glutamate, including the widely accepted hypotheses and models in the literature regarding its involvement in neurodegenerative diseases and other pathology. We then review the state of the art of in vivo glutamate detection by magnetic resonance imaging and the limitations on this front of in vivo MR spectroscopy. The gluCEST experiment is introduced and its advantages, challenges and limitations are thoroughly explored, beginning with the phantom experiment results demonstrated in the initial publication, through the latest approaches to correcting human brain images for B1 inhomogeneity. We then give a comprehensive overview of preclinical applications demonstrated to date, including Alzheimer's disease, Parkinson's disease, Huntington's disease, Traumatic brain injury and cancer, followed by a similar discussion of human studies. Finally, we highlight emerging applications, and discuss technical improvements on the horizon that hold promise for improving the robustness and versatility of gluCEST and its increasing presence in the arena of translational and precision medicine. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast‐weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF) is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep‐learning algorithms have been developed to further boost the performance and speed of CEST and semi‐solid macromolecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST‐MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligence (AI)‐based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data. [ABSTRACT FROM AUTHOR]

Isolated evaluation of multiparametric in vivo chemical exchange saturation transfer (CEST) MRI often requires complex computational processing for both correction of B0 and B1 inhomogeneity and contrast generation. For that, sufficiently densely sampled Z‐spectra need to be acquired. The list of acquired frequency offsets largely determines the total CEST acquisition time, while potentially representing redundant information. In this work, a linear projection‐based multiparametric CEST evaluation method is introduced that offers fast B0 and B1 inhomogeneity correction, contrast generation and feature selection for CEST data, enabling reduction of the overall measurement time. To that end, CEST data acquired at 7 T in six healthy subjects and in one brain tumor patient were conventionally evaluated by interpolation‐based inhomogeneity correction and Lorentzian curve fitting. Linear regression was used to obtain coefficient vectors that directly map uncorrected data to corrected Lorentzian target parameters. L1‐regularization was applied to find subsets of the originally acquired CEST measurements that still allow for such a linear projection mapping. The linear projection method allows fast and interpretable mapping from acquired raw data to contrast parameters of interest, generalizing from healthy subject training data to unseen healthy test data and to the tumor patient dataset. The L1‐regularization method shows that a fraction of the acquired CEST measurements is sufficient to preserve tissue contrasts, offering up to a 2.8‐fold reduction of scan time. Similar observations as for the 7‐T data can be made for data from a clinical 3‐T scanner. Being a fast and interpretable computation step, the proposed method is complementary to neural networks that have recently been employed for similar purposes. The scan time acceleration offered by the L1‐regularization ("CEST‐LASSO") constitutes a step towards better applicability of multiparametric CEST protocols in a clinical context. [ABSTRACT FROM AUTHOR]

Purpose: Nuclear Overhauser effect (NOE) is based on dipolar cross‐relaxation mechanism that enables the indirect detection of aliphatic protons via the water proton signal. This work focuses on determining the reproducibility of NOE magnetization transfer ratio (NOEMTR) and isolated or relayed NOE (rNOE) contributions to the NOE MRI of the healthy human brain at 7 Tesla (T). Methods: We optimized the B1+$$ {\mathrm{B}}_1^{+} $$ amplitude and length of the saturation pulse by acquiring NOE images with different B1+$$ {\mathrm{B}}_1^{+} $$ values with multiple saturation lengths. Repeated NOE MRI measurements were made on five healthy volunteers by using optimized saturation pulse parameters including correction of B0 and B1+$$ {\mathrm{B}}_1^{+} $$ inhomogeneities. To isolate the individual contributions from z‐spectra, we have fit the NOE z‐spectra using multiple Lorentzians and calculated the total contribution from each pool contributing to the overall NOEMTR contrast. Results: We found that a saturation amplitude of 0.72 μT and a length of 3 s provided the highest contrast. We found that the mean NOEMTR value in gray matter (GM) was 26%, and in white matter (WM) was 33.3% across the 3D slab of the brain. The mean rNOE contributions from GM and WM values were 8.9% and 9.6%, which were ∼10% of the corresponding total NOEMTR signal. The intersubject coefficient of variations (CoVs) of NOEMTR from GM and WM were 4.5% and 6.5%, respectively, whereas the CoVs of rNOE were 4.8% and 5.6%, respectively. The intrasubject CoVs of the NOEMTR range was 2.1%–4.2%, and rNOE range was 2.9%–10.5%. Conclusion: This work has demonstrated an excellent reproducibility of both inter‐ and intrasubject NOEMTR and rNOE metrics in healthy human brains at 7 T. [ABSTRACT FROM AUTHOR]

Purpose: Dynamic glucose‐enhanced (DGE) MRI relates to a group of exchange‐based MRI techniques where the uptake of glucose analogues is studied dynamically. However, motion artifacts can be mistaken for true DGE effects, while motion correction may alter true signal effects. The aim was to design a numerical human brain phantom to simulate a realistic DGE MRI protocol at 3T that can be used to assess the influence of head movement on the signal before and after retrospective motion correction. Methods: MPRAGE data from a tumor patient were used to simulate dynamic Z‐spectra under the influence of motion. The DGE responses for different tissue types were simulated, creating a ground truth. Rigid head movement patterns were applied as well as physiological dilatation and pulsation of the lateral ventricles and head‐motion‐induced B0‐changes in presence of first‐order shimming. The effect of retrospective motion correction was evaluated. Results: Motion artifacts similar to those previously reported for in vivo DGE data could be reproduced. Head movement of 1 mm translation and 1.5 degrees rotation led to a pseudo‐DGE effect on the order of 1% signal change. B0 effects due to head motion altered DGE changes due to a shift in the water saturation spectrum. Pseudo DGE effects were partly reduced or enhanced by rigid motion correction depending on tissue location. Conclusion: DGE MRI studies can be corrupted by motion artifacts. Designing post‐processing methods using retrospective motion correction including B0 correction will be crucial for clinical implementation. The proposed phantom should be useful for evaluation and optimization of such techniques. [ABSTRACT FROM AUTHOR]

Purpose: In this work, we investigated the ability of neural networks to rapidly and robustly predict Lorentzian parameters of multi‐pool CEST MRI spectra at 7 T with corresponding uncertainty maps to make them quickly and easily available for routine clinical use. Methods: We developed a deepCEST 7 T approach that generates CEST contrasts from just 1 scan with robustness against B1 inhomogeneities. The input data for a neural feed‐forward network consisted of 7 T in vivo uncorrected Z‐spectra of a single B1 level, and a B1 map. The 7 T raw data were acquired using a 3D snapshot gradient echo multiple interleaved mode saturation CEST sequence. These inputs were mapped voxel‐wise to target data consisting of Lorentzian amplitudes generated conventionally by 5‐pool Lorentzian fitting of normalized, denoised, B0‐ and B1‐corrected Z‐spectra. The deepCEST network was trained with Gaussian negative log‐likelihood loss, providing an uncertainty quantification in addition to the Lorentzian amplitudes. Results: The deepCEST 7 T network provides fast and accurate prediction of all Lorentzian parameters also when only a single B1 level is used. The prediction was highly accurate with respect to the Lorentzian fit amplitudes, and both healthy tissues and hyperintensities in tumor areas are predicted with a low uncertainty. In corrupted cases, high uncertainty indicated wrong predictions reliably. Conclusion: The proposed deepCEST 7 T approach reduces scan time by 50% to now 6:42 min, but still delivers both B0‐ and B1‐corrected homogeneous CEST contrasts along with an uncertainty map, which can increase diagnostic confidence. Multiple accurate 7 T CEST contrasts are delivered within seconds. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) NMR is widely used for enhancing the sensitivity of low-abundance exchanging sites in general, and for the water-based detection of labile metabolite protons under in vivo conditions in particular. CEST, however, faces a number of limitations when targeting multiple metabolites, including a radiofrequency (RF)-induced broadening of the detected peaks, and relatively long acquisition times deriving from its continuous-wave nature. Methods have been proposed to overcome these limitations, including a Fourier-encoded version of CEST –the Frequency-Labeled EXchange (FLEX) experiment– and the incorporation of background gradients during the RF saturation time. This work explores an alternative avenue, based on spatiotemporally encoded ultrafast (UF) 2D NMR. UF NMR can compress the time-domain indirect-dimension encoding of 2D NMR into a single shot; to exploit these potential time savings, an UF version of the FLEX experiment was taken as starting point, and the multiple t1-incremented amplitude modulation cycles that the FLEX experiment normally requires were replaced by a single-shot spatiotemporal encoding. The ensuing UF 2D FLEX experiment was then used to monitor the spectral signatures of multiple moieties as they exchange with the solvent, by imprinting these onto the water resonance as in the original experiment –but now all within a single shot. Upon incorporating two-scan phase cycling and quadrature detection, the resulting method showed an experimental performance similar to t1-encoded FLEX, while providing significant time savings plus imaging information that could be of further use in in vivo studies. The main advantages, features and drawbacks observed for UF 2D FLEX are briefly discussed.

PurposeThe objective of the current study was to explore the efficacy of using pH-weighted amine CEST-EPI as a potential non-invasive imaging biomarker for treatment response and/or failure in recurrent GBM patients treated with bevacizumab.MethodA total of 11 patients with recurrent GBM treated with bevacizumab were included in this prospective study. CEST-EPI, perfusion MRI, and standardized anatomic MRI were obtained in patients before and after bevacizumab administration. CEST-EPI measures of magnetization transfer ratio asymmetry (MTRasym) at 3 ppm were used for pH-weighted imaging contrast. Multiple measures were examined for their association with progression-free survival (PFS).ResultTumor acidity, measured with MTRasym at 3 ppm, was significantly reduced in both contrast enhancing and non-enhancing tumor after bevacizumab (p = 0.0002 and p

Cerebral acidosis is a consequence of secondary injury mechanisms following traumatic brain injury (TBI), including excitotoxicity and ischemia, with potentially significant clinical implications. However, there remains an unmet clinical need for technology for non-invasive, high resolution pH imaging of human TBI for studying metabolic changes following injury. The current study examined 17 patients with TBI and 20 healthy controls using amine chemical exchange saturation transfer echoplanar imaging (CEST EPI), a novel pH-weighted molecular MR imaging technique, on a clinical 3T MR scanner. Results showed significantly elevated pH-weighted image contrast (MTRasym at 3 ppm) in areas of T2 hyperintensity or edema (P