Sidebands in CEST MR-How to recognize and avoid them.

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 out with Pulseq-CEST, while measurements were 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.

Snapshot CEST++: Advancing rapid whole-brain APTw-CEST MRI at 3 T.

APTw CEST MRI suffers from long preparation times and consequently long acquisition times (~5 min). Recently, a consensus on the preparation module for clinical APTw CEST at 3 T was found in the community, and we present a fast whole-brain APTw CEST MRI sequence following this consensus preparation of pulsed RF irradiation of 2 s duration at 90% RF duty-cycle and a B1,rms of 2 µT. After optimization of the snapshot CEST approach for APTw imaging regarding flip angle, voxel size and frequency offset sampling, we extend it by undersampled GRE acquisition and compressed sensing reconstruction. This allows 2 mm isotropic whole-brain APTw imaging for clinical research at 3 T below 2 min. With this sequence, a fast snapshot APTw imaging method is now available for larger clinical studies of brain tumors.

7 tricks for 7 T CEST: Improving the reproducibility of multipool evaluation provides insights into the effects of age and the early stages of Parkinson's disease.

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, B 1 + -homogeneous parallel transmit protocol was used. The postprocessing, consisting of motion correction, smoothing, B 0 -correction, normalization, denoising, B 1 + -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), B 0 correction of the Z-spectrum with moderate spline smoothing (4), denoising using principal component analysis preserving the 11 highest intensity components (5), B 1 + 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.

DeepCEST 7 T: Fast and homogeneous mapping of 7 T CEST MRI parameters and their uncertainty quantification.

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.

Linear projection-based chemical exchange saturation transfer parameter estimation.

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.

Accelerated and quantitative three-dimensional molecular MRI using a generative adversarial network.

PURPOSE: To substantially shorten the acquisition time required for quantitative three-dimensional (3D) chemical exchange saturation transfer (CEST) and semisolid magnetization transfer (MT) imaging and allow for rapid chemical exchange parameter map reconstruction. METHODS: Three-dimensional CEST and MT magnetic resonance fingerprinting (MRF) datasets of L-arginine phantoms, whole-brains, and calf muscles from healthy volunteers, cancer patients, and cardiac patients were acquired using 3T clinical scanners at three different sites, using three different scanner models and coils. A saturation transfer-oriented generative adversarial network (GAN-ST) supervised framework was then designed and trained to learn the mapping from a reduced input data space to the quantitative exchange parameter space, while preserving perceptual and quantitative content. RESULTS: The GAN-ST 3D acquisition time was 42-52 s, 70% shorter than CEST-MRF. The quantitative reconstruction of the entire brain took 0.8 s. An excellent agreement was observed between the ground truth and GAN-based L-arginine concentration and pH values (Pearson's r > 0.95, ICC > 0.88, NRMSE < 3%). GAN-ST images from a brain-tumor subject yielded a semi-solid volume fraction and exchange rate NRMSE of 3 . 8 ± 1 . 3 % $$ 3.8\pm 1.3\% $$ and 4 . 6 ± 1 . 3 % $$ 4.6\pm 1.3\% $$ , respectively, and SSIM of 96 . 3 ± 1 . 6 % $$ 96.3\pm 1.6\% $$ and 95 . 0 ± 2 . 4 % $$ 95.0\pm 2.4\% $$ , respectively. The mapping of the calf-muscle exchange parameters in a cardiac patient, yielded NRMSE < 7% and SSIM > 94% for the semi-solid exchange parameters. In regions with large susceptibility artifacts, GAN-ST has demonstrated improved performance and reduced noise compared to MRF. CONCLUSION: GAN-ST can substantially reduce the acquisition time for quantitative semi-solid MT/CEST mapping, while retaining performance even when facing pathologies and scanner models that were not available during training.

MR-double-zero - Proof-of-concept for a framework to autonomously discover MRI contrasts.

PURPOSE: A framework for supervised design of MR sequences for any given target contrast is proposed, based on fully automatic acquisition and reconstruction of MR data on a real MR scanner. The proposed method does not require any modeling of MR physics and thus allows even unknown contrast mechanisms to be addressed. METHODS: A derivative-free optimization algorithm is set up to repeatedly update and execute a parametrized sequence on the MR scanner to acquire data. In each iteration, the acquired data are mapped to a given target contrast by linear regression. RESULTS: It is shown that with the proposed framework it is possible to find an MR sequence that yields a predefined target contrast. In the present case, as a proof-of principle, a sequence mapping absolute creatine concentration, which cannot be extracted from T1 or T2-weighted scans directly, is discovered. The sequence was designed in a comparatively short time and with no human interaction. CONCLUSIONS: New MR contrasts for mapping a given target can be discovered by derivative-free optimization of parametrized sequences that are directly executed on a real MRI scanner. This is demonstrated by 're-discovery' of a chemical exchange weighted sequence. The proposed method is considered to be a paradigm shift towards autonomous, model-free and target-driven sequence design.

What do we know about dynamic glucose-enhanced (DGE) MRI and how close is it to the clinics? Horizon 2020 GLINT consortium report.

Cancer is one of the most devastating diseases that the world is currently facing, accounting for 10 million deaths in 2020 (WHO). In the last two decades, advanced medical imaging has played an ever more important role in the early detection of the disease, as it increases the chances of survival and the potential for full recovery. To date, dynamic glucose-enhanced (DGE) MRI using glucose-based chemical exchange saturation transfer (glucoCEST) has demonstrated the sensitivity to detect both D-glucose and glucose analogs, such as 3-oxy-methyl-D-glucose (3OMG) uptake in tumors. As one of the recent international efforts aiming at pushing the boundaries of translation of the DGE MRI technique into clinical practice, a multidisciplinary team of eight partners came together to form the "glucoCEST Imaging of Neoplastic Tumors (GLINT)" consortium, funded by the Horizon 2020 European Commission. This paper summarizes the progress made to date both by these groups and others in increasing our knowledge of the underlying mechanisms related to this technique as well as translating it into clinical practice.

Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning.

Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with glioblastoma multiforme, the early apoptotic responses to oncolytic virotherapy (characterized by decreased cytosolic pH and reduced protein synthesis) can be rapidly detected via chemical-exchange-saturation-transfer magnetic resonance fingerprinting (CEST-MRF) aided by deep learning. By leveraging a deep neural network trained with simulated magnetic resonance fingerprints, CEST-MRF can generate quantitative maps of intratumoural pH and of protein and lipid concentrations by selectively labelling the exchangeable amide protons of endogenous proteins and the exchangeable macromolecule protons of lipids, without requiring exogenous contrast agents. We also show that in a healthy volunteer, CEST-MRF yielded molecular parameters that are in good agreement with values from the literature. Deep-learning-aided CEST-MRF may also be amenable to the characterization of host responses to other cancer therapies and to the detection of cardiac and neurological pathologies.

GLINT: GlucoCEST in neoplastic tumors at 3 T-clinical results of GlucoCEST in gliomas.

OBJECTIVE: Clinical relevance of dynamic glucose enhanced (DGE) chemical exchange saturation transfer (CEST) imaging has mostly been demonstrated at ultra-high field (UHF) due to low effect size. Results of a cohort study at clinical field strength are shown herein. MATERIALS AND METHODS: Motion and field inhomogeneity corrected T1ρ-based DGE (DGE⍴) images were acquired before, during and after a D-glucose injection with 6.3 s temporal resolution to detect accumulation in the brain. Six glioma patients with clear blood-brain barrier (BBB) leakage, two glioma patients with suspected BBB leakage, and three glioma patients without BBB leakage were scanned at 3 T. RESULTS: In high-grade gliomas with BBB leakage, D-glucose uptake could be detected in the gadolinium (Gd) enhancing region as well as in the tumor necrosis with a maximum increase of ∆DGE⍴ around 0.25%, whereas unaffected white matter did not show any significant DGE⍴ increase. Glioma patients without Gd enhancement showed no detectable DGE⍴ effect within the tumor. CONCLUSION: First application of DGE⍴ in a patient cohort shows an association between BBB leakage and DGE signal irrespective of the tumor grade. This indicates that glucoCEST corresponds more to the disruptions of BBB with Gd uptake than to the molecular tumor profile or tumor grading.

Pulseq-CEST: Towards multi-site multi-vendor compatibility and reproducibility of CEST experiments using an open-source sequence standard.

PURPOSE: As the field of CEST grows, various novel preparation periods using different parameters are being introduced. At the same time, large, multisite clinical studies require clearly defined protocols, especially across different vendors. Here, we propose a CEST definition standard using the open Pulseq format for a shareable, simple, and exact definition of CEST protocols. METHODS: We present the benefits of such a standard in three ways: (1) an open database on GitHub, where fully defined, human-readable CEST protocols can be shared; (2) an open-source Bloch-McConnell simulation to test and optimize CEST preparation periods in silico; and (3) a hybrid MR sequence that plays out the CEST preparation period and can be combined with any existing readout module. RESULTS: The exact definition of the CEST preparation period, in combination with the flexible simulation, leads to a good match between simulations and measurements. The standard allowed finding consensus on three amide proton transfer-weighted protocols that could be compared in healthy subjects and a tumor patient. In addition, we could show coherent multisite results for a sophisticated CEST method, highlighting the benefits regarding protocol sharing and reproducibility. CONCLUSION: With Pulseq-CEST, we provide a straightforward approach to standardize, share, simulate, and measure different CEST preparation schemes, which are inherently completely defined.

CEST MR-Fingerprinting: Practical considerations and insights for acquisition schedule design and improved reconstruction.

PURPOSE: To understand the influence of various acquisition parameters on the ability of CEST MR-Fingerprinting (MRF) to discriminate different chemical exchange parameters and to provide tools for optimal acquisition schedule design and parameter map reconstruction. METHODS: Numerical simulations were conducted using a parallel computing implementation of the Bloch-McConnell equations, examining the effect of TR, TE, flip-angle, water T1 and T2 , saturation-pulse duration, power, and frequency on the discrimination ability of CEST-MRF. A modified Euclidean distance matching metric was evaluated and compared to traditional dot product matching. L-Arginine phantoms of various concentrations and pH were scanned at 4.7T and the results compared to numerical findings. RESULTS: Simulations for dot product matching demonstrated that the optimal flip-angle and saturation times are 30∘ and 1100 ms, respectively. The optimal maximal saturation power was 3.4 µT for concentrated solutes with a slow exchange rate, and 5.2 µT for dilute solutes with medium-to-fast exchange rates. Using the Euclidean distance matching metric, much lower maximum saturation powers were required (1.6 and 2.4 µT, respectively), with a slightly longer saturation time (1500 ms) and 90∘ flip-angle. For both matching metrics, the discrimination ability increased with the repetition time. The experimental results were in agreement with simulations, demonstrating that more than a 50% reduction in scan-time can be achieved by Euclidean distance-based matching. CONCLUSIONS: Optimization of the CEST-MRF acquisition schedule is critical for obtaining the best exchange parameter accuracy. The use of Euclidean distance-based matching of signal trajectories simultaneously improved the discrimination ability and reduced the scan time and maximal saturation power required.

DeepCEST 3T: Robust MRI parameter determination and uncertainty quantification with neural networks-application to CEST imaging of the human brain at 3T.

PURPOSE: Calculation of sophisticated MR contrasts often requires complex mathematical modeling. Data evaluation is computationally expensive, vulnerable to artifacts, and often sensitive to fit algorithm parameters. In this work, we investigate whether neural networks can provide not only fast model fitting results, but also a quality metric for the predicted values, so called uncertainty quantification, investigated here in the context of multi-pool Lorentzian fitting of CEST MRI spectra at 3T. METHODS: A deep feed-forward neural network including a probabilistic output layer allowing for uncertainty quantification was set up to take uncorrected CEST-spectra as input and predict 3T Lorentzian parameters of a 4-pool model (water, semisolid MT, amide CEST, NOE CEST), including the B0 inhomogeneity. Networks were trained on data from 3 subjects with and without data augmentation, and applied to untrained data from 1 additional subject and 1 brain tumor patient. Comparison to conventional Lorentzian fitting was performed on different perturbations of input data. RESULTS: The deepCEST 3T networks provided fast and accurate predictions of all Lorentzian parameters and were robust to input perturbations because of noise or B0 artifacts. The uncertainty quantification detected fluctuations in input data by increase of the uncertainty intervals. The method generalized to unseen brain tumor patient CEST data. CONCLUSIONS: The deepCEST 3T neural network provides fast and robust estimation of CEST parameters, enabling online reconstruction of sophisticated CEST contrast images without the typical computational cost. Moreover, the uncertainty quantification indicates if the predictions are trustworthy, enabling confident interpretation of contrast changes.

Structure or Exchange? On the Feasibility of Chemical Exchange Detection with Balanced Steady-State Free Precession in Tissue - An In Vitro Study.

Balanced steady-state free precession imaging has recently been suggested for chemical exchange detection (bSSFPX). The objective of this work is to investigate the contributions of microstructural, chemical shift and chemical exchange effects to the asymmetry of the bSSFP profile at field strengths of 3 T and 9.4 T. To this end, in vitro bSSFPX experiments are performed for a range of repetition times and flip angles in glucose water solutions with different MnCl2 concentrations and tissue homogenates obtained from the brainstem of pig brains. The experimental results are compared to multi-pool Bloch-McConnell simulations. Additionally, the influence of white matter tract geometry is analyzed ex vivo in pig brain hemispheres measured at two different angles with respect to B0 . The detectable bSSFP profile asymmetry in glucose solutions with tissue-like relaxation times and white matter homogenates was consistent with Bloch-McConnell simulations but relatively small. In intact white matter tracts, the asymmetry was dominated by structural effects with a strong dependency on tract orientation relative to B0 . In tracts perpendicular to B0 , the asymmetry was ≈ 3-4 times higher than in the homogenates, thus barely affected by chemical exchange effects. In conclusion, chemical exchange-related bSSFP profile asymmetries are detectable in tissue homogenates, however, the observed asymmetry level is generally low and prone to confounding structural effects rendering in vivo chemical exchange detection with bSSFP challenging in the brain.

Quantification of hydroxyl exchange of D-Glucose at physiological conditions for optimization of glucoCEST MRI at 3, 7 and 9.4 Tesla.

AIMS: To determine individual glucose hydroxyl exchange rates at physiological conditions and use this information for numerical optimization of glucoCEST/CESL preparation. To give guidelines for in vivo glucoCEST/CESL measurement parameters at clinical and ultra-high field strengths. METHODS: Five glucose solution samples at different pH values were measured at 14.1 T at various B1 power levels. Multi-B1 -Z-spectra Bloch-McConnell fits at physiological pH were further improved by the fitting of Z-spectra of five pH values simultaneously. The obtained exchange rates were used in a six-pool Bloch-McConnell simulation including a tissue-like water pool and semi-solid MT pool with different CEST and CESL presaturation pulse trains. In vivo glucose injection experiments were performed in a tumor mouse model at 7 T. RESULTS AND DISCUSSION: Glucose Z-spectra could be fitted with four exchanging pools at 0.66, 1.28, 2.08 and 2.88 ppm. Corresponding hydroxyl exchange rates could be determined at pH = 7.2, T = 37°C and 1X PBS. Simulation of saturation transfer for this glucose system in a gray matter-like and a tumor-like system revealed optimal pulses at different field strengths of 9.4, 7 and 3 T. Different existing sequences and approaches are simulated and discussed. The optima found could be experimentally verified in an animal model at 7 T. CONCLUSION: For the determined fast exchange regime, presaturation pulses in the spin-lock regime (long recover time, short yet strong saturation) were found to be optimal. This study gives an estimation for optimization of the glucoCEST signal in vivo on the basis of glucose exchange rate at physiological conditions.

Adaptive denoising for chemical exchange saturation transfer MR imaging.

High image signal-to-noise ratio (SNR) is required to reliably detect the inherently small chemical exchange saturation transfer (CEST) effects in vivo. In this study, it was demonstrated that identifying spectral redundancies of CEST data by principal component analysis (PCA) in combination with an appropriate data-driven extraction of relevant information can be used for an effective and robust denoising of CEST spectra. The relationship between the number of relevant principal components and SNR was studied on fitted in vivo Z-spectra with artificially introduced noise. Three different data-driven criteria to automatically determine the optimal number of necessary components were investigated. In addition, these criteria facilitate straightforward assessment of data quality that could provide guidance for CEST MR protocols in terms of SNR. Insights were applied to achieve a robust denoising of highly sampled low power Z-spectra of the human brain at 3 and 7 T. The median criterion provided the best estimation for the optimal number of components consistently for all three investigated artificial noise levels. Application of the denoising technique to in vivo data revealed a considerable increase in image quality for the amide and rNOE contrast with a considerable SNR gain. At 7 T the denoising capability was quantified to be comparable or even superior to an averaging of six measurements. The proposed denoising algorithm enables an efficient and robust denoising of CEST data by combining PCA with appropriate data-driven truncation criteria. With this generally applicable technique at hand, small CEST effects can be reliably detected without the need for repeated measurements.

T1ρ-based dynamic glucose-enhanced (DGEρ) MRI at 3 T: method development and early clinical experience in the human brain.

PURPOSE: The aim of this study was to translate the T1 ρ-based dynamic glucose-enhanced (DGEρ) experiment from ultrahigh magnetic field strengths to a clinical field strength of 3 T. Although the protocol would seem to be as simple as gadolinium-enhanced imaging, several obstacles had to be addressed, including signal-to-noise ratio (SNR), robustness of contrast, and postprocessing, especially motion correction. METHODS: Spin-lock based presaturation and a 3D gradient-echo snapshot readout were optimized for 3 T with regard to robustness, chemical exchange saturation transfer effect strength, and SNR. Postprocessing steps, including dynamic B0 and motion correction, were analyzed and optimized in 7 healthy volunteers. The final protocol, including glucose injection, was applied to 3 glioblastoma patients. RESULTS: With appropriate postprocessing, motion-related artifacts could be drastically reduced, and an SNR of approximately 90 could be achieved for a single dynamic measurement. In 2 patients with blood-brain barrier breakdown, a significant glucose uptake could be observed with a DGEρ effect strength in the range of 0.4% of the water signal. Thorough analysis of possible residual motion revealed that the statistical evidence can decrease when tested against pseudo effects attributed to uncorrected motion. CONCLUSION: DGEρ imaging was optimized for clinical field strengths of 3 T, and a robust protocol was established for broader application. Early experience shows that DGEρ seems possible at 3 T and could not only be attributed to motion artifacts. Observed DGEρ maps showed unique patterns, partly matching with the T1 -ce tumor ring enhancement. However, effect sizes are small and careful clinical application is necessary.

Relaxation-compensated APT and rNOE CEST-MRI of human brain tumors at 3 T.

PURPOSE: Relaxation-compensated CEST-MRI (i.e., the inverse metrics magnetization transfer ratio and apparent exchange-dependent relaxation) has already been shown to provide valuable information for brain tumor diagnosis at ultrahigh magnetic field strengths. This study aims at translating the established acquisition protocol at 7 T to a clinically relevant magnetic field strength of 3 T. METHODS: Protein model solutions were analyzed at multiple magnetic field strengths to assess the spectral widths of the amide proton transfer and relayed nuclear Overhauser effect (rNOE) signals at 3 T. This prior knowledge of the spectral range of CEST signals enabled a reliable and stable Lorentzian-fitting also at 3 T where distinct peaks are no longer resolved in the Z-spectrum. In comparison to the established acquisition protocol at 7 T, also the image readout was extended to three dimensions. RESULTS: The observed spectral range of CEST signals at 3 T was approximately ±15 ppm. Final relaxation-compensated amide proton transfer and relayed nuclear Overhauser effect contrasts were in line with previous results at 7 T. Examination of a patient with glioblastoma demonstrated the applicability of this acquisition protocol in a clinical setting. CONCLUSION: The presented acquisition protocol allows relaxation-compensated CEST-MRI at 3 T with a 3D coverage of the human brain. Translation to a clinically relevant magnetic field strength of 3 T opens the door to trials with a large number of participants, thus enabling a comprehensive assessment of the clinical relevance of relaxation compensation in CEST-MRI.

DeepCEST: 9.4 T Chemical exchange saturation transfer MRI contrast predicted from 3 T data - a proof of concept study.

PURPOSE: To determine the feasibility of employing the prior knowledge of well-separated chemical exchange saturation transfer (CEST) signals in the 9.4 T Z-spectrum to separate overlapping CEST signals acquired at 3 T, using a deep learning approach trained with 3 T and 9.4 T CEST spectral data from brains of the same subjects. METHODS: Highly spectrally resolved Z-spectra from the same volunteer were acquired by 3D-snapshot CEST MRI at 3 T and 9.4 T at low saturation power of B1 = 0.6 µT. The volume-registered 3 T Z-spectra-stack was then used as input data for a three layer deep neural network with the volume-registered 9.4 T fitted parameter stack as target data. RESULTS: An optimized neural net architecture could be found and verified in healthy volunteers. The gray-/white-matter contrast of the different CEST effects was predicted with only small deviations (Pearson R = 0.89). The 9.4 T prediction was less noisy compared to the directly measured CEST maps, although at the cost of slightly lower tissue contrast. Application to an unseen tumor patient measured at 3 T and 9.4 T revealed that tumorous tissue Z-spectra and corresponding hyper-/hypointensities of different CEST effects can also be predicted (Pearson R = 0.84). CONCLUSION: The 9.4 T CEST signals acquired at low saturation power can be accurately estimated from CEST imaging at 3 T using a neural network trained with coregistered 3 T and 9.4 T data of healthy subjects. The deepCEST approach generalizes to Z-spectra of tumor areas and might indicate whether additional ultrahigh-field (UHF) scans will be beneficial.

Possible artifacts in dynamic CEST MRI due to motion and field alterations.

PURPOSE: Dynamic CEST studies such as dynamic glucose enhanced imaging, have gained a lot of attention recently. The expected CEST effects after injection are rather small in tissue especially at clinical field strengths (0.5-2%). Small movements during the dynamic CEST measurement together with a subtraction-based evaluation can lead to pseudo CEST effects of the same order of magnitude. These artifacts are studied herein. METHODS: A brain tumor patient 3D-CEST baseline scan without glucose injection performed at 3 T is used to generate a virtual dynamic measurement introducing different kinds of simulated motion and B0 shifts. RESULTS: Minor motion (0.6 mm translations) and B0 artifacts (7 Hz shift) can lead to pseudo effects in the order of 1% in dynamic CEST imaging. Especially around tissue interfaces such as CSF borders or tumor affected areas, the pseudo effect patterns are non-intuitive and can be mistaken as dynamic agent uptake. CONCLUSION: Correction or mitigation for small motions is crucial for dynamic CEST imaging, especially in subjects with lesions. Concomitant B0 alterations can as well induce pseudo CEST effects at 3 T.