CEST: from basic principles to applications, challenges and opportunities

The proton resonance enhancement for CEST imaging and shift exchange (PRECISE) family of RF pulse shapes for CEST MRI

PURPOSE

To optimize a 100 ms pulse for producing CEST MRI contrast and evaluate in mice.

METHODS

A gradient ascent algorithm was employed to generate a family of 100 point, 100 ms pulses for use in CEST pulse trains (proton resonance enhancement for CEST imaging and shift exchange). Gradient ascent optimizations were performed for exchange rates = 500, 1500, 2500, 3500, and 4500 s-1; and labile proton offsets (Δω) = 9.6, 7.8, 4.2, and 2.0 ppm. Seven proton resonance enhancement for CEST imaging and shift exchange pulse shapes were tested on an 11.7 T scanner using a phantom containing three representative CEST agents with peak saturation B1,peak = 4 μT. The pulse producing the most contrast in phantoms was then evaluated for CEST MRI pH mapping of the kidneys in healthy mice after iopamidol administration.

RESULTS

The most promising pulse in terms of contrast performance across all three phantoms was the 9.6 ppm, 2500 s-1 optimized pulse with ˜2.7 × increase in asymmetric magnetization transfer ratio (MTRasym) over Gaussian, and ˜ 1.3 times over Fermi pulses for the same B1,peak = 4 μT. This pulse also displayed a large improvement in contrast over the Gaussian pulse after administration of iopamidol in live mice.

CONCLUSION

A new 100-ms pulse was developed based on gradient ascent optimizations, which produced better contrast compared to standard Gaussian and Fermi pulses in phantoms. This shape also showed a substantial improvement for CEST MRI pH mapping in live mice over the Gaussian shape and appears promising for a wide range of CEST applications.

Saturation transfer MR fingerprinting for magnetization transfer contrast and chemical exchange saturation transfer quantification

PURPOSE

The aim of this study was to develop a saturation transfer MR fingerprinting (ST-MRF) technique using a biophysics model-driven deep learning approach.

METHODS

A deep learning-based quantitative saturation transfer framework was proposed to estimate water, magnetization transfer contrast, and amide proton transfer (APT) parameters plus B0 field inhomogeneity. This framework incorporated a Bloch-McConnell simulator during neural network training and enforced consistency between synthesized MRF signals and experimentally acquired ST-MRF signals. Ground-truth numerical phantoms were used to assess the accuracy of estimated tissue parameters, and in vivo tissue parameters were validated using synthetic MRI analysis.

RESULTS

The proposed ST-MRF reconstruction network achieved a normalized root mean square error (nRMSE) of 9.3% when tested against numerical phantoms with a signal-to-noise ratio of 46 dB, which outperformed conventional Bloch-McConnell fitting (nRMSE of 15.3%) and dictionary-matching approaches (nRMSE of 19.5%). Synthetic MRI analysis indicated excellent similarity (RMSE = 3.2%) between acquired and synthesized ST-MRF images, demonstrating high in vivo reconstruction accuracy. In healthy human brains, the APT pool size ratios for gray and white matter were 0.16 ± 0.02% and 0.13 ± 0.02%, respectively, and the exchange rates for gray and white matter were 101 ± 25 Hz and 131 ± 27 Hz, respectively. The reconstruction network processed the eight tissue parameter maps in approximately 27 s for ST-MRF data sized at 256 × 256 × 9 × 103.

CONCLUSION

This study highlights the feasibility of the deep learning-based ST-MRF imaging for rapid and accurate quantification of free bulk water, magnetization transfer contrast, APT parameters, and B0 field inhomogeneity.

Synthesis, Characterization, Magnetic Properties, and Applications of Carbon Dots as Diamagnetic Chemical Exchange Saturation Transfer Magnetic Resonance Imaging Contrast Agents: A Review

Carbon dots (CDs) are metal-free carbon-based nanoparticles. They possess excellent photoluminescent properties, various physical properties, good chemical stability, high water solubility, high biocompatibility, and tunable surface functionalities, suitable for biomedical applications. Their properties are subject to synthetic conditions such as pH, reaction time, temperature, precursor, and solvent. Until now, a large number of articles on the synthesis and biomedical applications of CDs using their photoluminescent properties have been reported. However, their research on magnetic properties and especially, diamagnetic chemical exchange saturation transfer (diaCEST) in magnetic resonance imaging (MRI) is very poor. The diaCEST MRI contrast agents are based on exchangeable protons of materials with bulk water protons and thus, different from conventional MRI contrast agents, which are based on enhancements of proton spin relaxations of bulk water and tissue. In this review, various syntheses, characterizations, magnetic properties, and potential applications of CDs as diaCEST MRI contrast agents are reviewed. Finally, future perspectives of CDs as the next-generation diaCEST MRI contrast agents are discussed.

Quantitative molecular imaging using deep magnetic resonance fingerprinting

Deep learning-based saturation transfer magnetic resonance fingerprinting (MRF) is an emerging approach for noninvasive in vivo imaging of proteins, metabolites and pH. It involves a series of steps, including sample/participant preparation, image acquisition schedule design, biophysical model formulation and artificial intelligence and computational model training, followed by image acquisition, deep reconstruction and analysis. Saturation transfer-based molecular MRI has been slow to reach clinical maturity and adoption for clinical practice due to its technical complexity, semi-quantitative contrast-weighted nature and long scan times needed for the extraction of quantitative molecular biomarkers. Deep MRF provides solutions to these challenges by providing a quantitative and rapid framework for extracting biologically and clinically meaningful molecular information. Here we define a complete protocol for quantitative molecular MRI using deep MRF. We describe in vitro sample preparation and animal and human scan considerations, and provide intuition behind the acquisition protocol design and optimization of chemical exchange saturation transfer (CEST) and semi-solid magnetization transfer (MT) quantitative imaging. We then extensively describe the building blocks for several artificial intelligence models and demonstrate their performance for different applications, including cancer monitoring, brain myelin imaging and pH quantification. Finally, we provide guidelines to further modify and expand the pipeline for imaging a variety of other pathologies (such as neurodegeneration, stroke and cardiac disease), accompanied by the related open-source code and sample data. The procedure takes between 48 min (for two proton pools or in vitro imaging) and 57 h (for complex multi-proton pool in vivo imaging) to complete and is suitable for graduate student-level users.

Prospective acceleration of whole-brain CEST imaging by golden-angle view ordering in Cartesian coordinates and joint k-space and image-space parallel imaging (KIPI)

PURPOSE

To prospectively accelerate whole-brain CEST acquisition by joint k-space and image-space parallel imaging (KIPI) with a proposed golden-angle view ordering technique (GAVOT) in Cartesian coordinates.

THEORY AND METHODS

The T2-decay effect will vary across frames with variable acceleration factors (AF) in the prospective acquisition using sequences with long echo trains. The GAVOT method uses a subset strategy to eliminate the T2-decay inconsistency, where all frames use a subset of shots from the calibration frame to form their k-space view ordering. The golden-angle rule is adapted to ensure uniform k-space coverage for arbitrary AFs in Cartesian coordinates. Phantom and in vivo studies were conducted on a 3 T scanner.

RESULTS

The GAVOT view ordering yielded a higher g-factor than conventional uniformly centric ordering, whereas the noise propagation in amide proton transfer (APT) weighted images was similar between different view ordering. Compared to centric ordering, GAVOT successfully eliminated the T2-decay inconsistency across all frames, resulting in fewer image artifacts for both KIPI and conventional parallel imaging methods. The synergy of GAVOT and KIPI mitigated strong aliasing artifacts and achieved high-quality reconstruction of prospective variable-AF datasets. GAVOT-KIPI reduced the scan time to 2.1 min for whole-brain APT weighted imaging and 4.7 min for quantitative APT signal (APT#) mapping.

CONCLUSION

GAVOT makes the prospective variable AF strategy flexible and practical, and, in conjunction with KIPI, ensures high-quality reconstruction from highly undersampled data, facilitating the clinical translation of whole-brain CEST imaging.

Interphase Design for Lithium-Metal Anodes

Electrode-electrolyte interphases are critical determinants of the reversibility and longevity of lithium (Li)-metal batteries (LMBs). However, upon cycling, the inherently delicate interphases, formed from electrolyte decomposition, become vulnerable to chemomechanical degradation and corrosion, resulting in rapid capacity loss and thus short battery life. Here, we present a comprehensive analysis of the complex interplay between the thermodynamic and kinetic properties of interphases on Li-metal anodes, providing insights into interphase design to address these challenges. Direct measurements of ion-transport kinetics across various electrolyte chemistries reveal that interphases with high Li-ion mobility are essential for achieving dense Li deposits. Conversely, sluggish ion transport generates high-surface-area Li deposits that induce Li random stripping and the accumulation of isolated Li deposits. Surprisingly, interphases that support long cycle life do not necessarily require the formation of dense Li deposits but must avoid possible electrochemical/chemical reactions between the Li-metal deposits and electrolytes' components. By that, in some specific electrolyte systems, isolated Li deposits can recover and electrically rejoin the active Li anodes' mass. These findings challenge conventional understanding and establish new principles for designing durable LMBs, demonstrating that even with commercial carbonate-based electrolytes, LiNi0.8Co0.1Mn0.1O2||Cu cells can achieve high reversibility.

Gadolinium-Based Contrast Agents (GBCAs) for MRI: A Benefit-Risk Balance Analysis from a Chemical, Biomedical, and Environmental Point of View

Gadolinium-based contrast agents (GBCAs) have revolutionized medical imaging, enhancing the accuracy and diagnostic value of magnetic resonance imaging (MRI). The increasing use of GBCAs has raised concerns about the release of gadolinium (Gd)(III) into the environment and potential risks for human health. Initially, multiple administrations of GBCAs were associated only with nephrogenic system fibrosis disease in individuals with impaired kidney function. Even if the Gd(III) retention in tissues has not yet been correlated with any specific disease, caution is required for the extensive use of GBCAs. The concerns related to the employment of GBCAs, due to the possible deposition and retention, should be extended also to healthy individuals without renal impairments. To ensure the well-being of patients, there is a need to develop even more stable and better-performing GBCAs, new MRI approaches requiring lower doses of GBCAs and, finally, innovative methods for recovering Gd(III) from both patients' urines and the environment. This can have strong advantages for human health and for environmental sustainability, also considering Gd(III) scarcity, being a rare earth element, and the shared guideline to reduce, as much as possible, the use of rare metals.

Evaluation of Brain Impairment Using Proton Exchange Rate MRI in a Kainic Acid-Induced Rat Model of Epilepsy

PURPOSE

Proton exchange rate (Kex) is a valuable biophysical metric. Kex MRI may augment conventional structural MRI by revealing brain impairments at the molecular level. This study aimed to investigate the feasibility of Kex MRI in evaluating brain injuries at multiple epilepsy stages.

PROCEDURES

Six adult rats with epilepsy induced by intra-amygdalae administration of kainic acid (KA) underwent MRI experiment at 11.7 T. Two MRI scans, including T1 mapping and CEST imaging under three B1 amplitudes of 0.75, 1.0, and 1.5 μT, were conducted before and 2, 7, and 28 days after KA injection. Quasi-steady-state analysis was performed to reconstruct equilibrium Z spectra. Direct saturation was resolved using a multi-pool Lorentzian model and removed from Z spectra. The residual spectral signal (ΔZ) was used to construct the omega plot of (1-ΔZ)/ΔZ as a linear function of 1/ ω 1 2 , from which Kex was quantified from the X-axis intercept. One-way ANOVA or two-tailed paired student's t-test was employed with P < 0.05 as statistically significant.

RESULTS

All animals exhibited repetitive status epilepticus with IV to V seizure stages after KA injection. At day 28, Kex values in the hippocampus and cerebral cortex at the surgical hemisphere with KA injection were significantly higher than that at the time points of control and/or day 2 in the same regions (P < 0.01). Moreover, the values were significantly higher than that in respective contralateral regions at day 28 (P < 0.02). No substantial changes of Kex were seen in bilateral thalamus or contralateral hemisphere among time points (all P > 0.05).

CONCLUSIONS

Kex increase significantly in the cerebral cortex and hippocampus at the surgical hemisphere, especially at day 28, likely due to substantial alterations at chronic epilepsy stage. Kex MRI is promising to evaluate brain impairment, facilitating the diagnosis and evaluation of neurological disorders.

Detection of breast cancer lesions using APT weighted MRI: a systematic review

Amide proton transfer (APT) is a novel magnetic resonance imaging (MRI) technique that has shown promising ability to study cancers. This paper systematically reviewed the literature on the use of APT MRI in the prognosis of breast cancer. A literature search was conducted on Pubmed and Embase and a total of 14 articles comprising 775 patients were included in the review. APT MRI had the ability to distinguish between benign and malignant lesions with an AUC as high as 0.959. There is a positive correlation between APT signal intensity and tumor grade/stage as well as Ki-67, whereas no correlation was found with ER/PR/Her-2 receptor status. There was a greater decrease in APT signal intensity after neoadjuvant chemotherapy (NAC) in responders compared to non-responders, suggesting that APT MRI may serve as a valuable supplemental tool in the early identification of chemotherapy response. APT has the potential to complement with other imaging methods in the diagnosis, prognosis, treatment monitoring, and management of breast cancer. Additional studies and standardization of APT acquisition methods are needed.

Visualizing Preosteoarthritis: Updates on UTE-Based Compositional MRI and Deep Learning Algorithms

Osteoarthritis (OA) is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Detecting OA before the onset of irreversible changes is crucial for early proactive management and limit growing disease burden. The more recent advanced quantitative imaging techniques and deep learning (DL) algorithms in musculoskeletal imaging have shown great potential for visualizing "pre-OA." In this review, we first focus on ultrashort echo time-based magnetic resonance imaging (MRI) techniques for direct visualization as well as quantitative morphological and compositional assessment of both short- and long-T2 musculoskeletal tissues, and second explore how DL revolutionize the way of MRI analysis (eg, automatic tissue segmentation and extraction of quantitative image biomarkers) and the classification, prediction, and management of OA. PLAIN LANGUAGE SUMMARY: Detecting osteoarthritis (OA) before the onset of irreversible changes is crucial for early proactive management. OA is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Ultrashort echo time-based magnetic resonance imaging (MRI), in particular, enables direct visualization and quantitative compositional assessment of short-T2 tissues. Deep learning is revolutionizing the way of MRI analysis (eg, automatic tissue segmentation and extraction of quantitative image biomarkers) and the detection, classification, and prediction of disease. They together have made further advances toward identification of imaging biomarkers/features for pre-OA. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Physics-guided multi-dimensional scan optimization and quasi-steady-state reconstruction to enhance CEST MRI sensitivity efficiency and quantification accuracy

Chemical exchange saturation transfer (CEST) MRI has become increasingly utilized for detecting dilute labile protons and characterizing microenvironment properties. However, the CEST MRI effect is only a few percent, and there is a need for a systematic approach to optimize scan parameters for sensitive and accurate CEST quantification. We propose multi-dimensional adjustments of key parameters such as the repetition time (TR) and RF duty cycle to optimize CEST MRI sensitivity per unit of time and utilization of quasi-steady-state (QUASS) reconstruction to recover the full CEST effect during postprocessing. Our work herein derived the CEST effect based on the generalized spin-lock CEST model and determined the interdependency of the optimal RF duty cycle and TR, showing the optimal TR decreases with the RF duty cycle but plateaus beyond 60-80 %. The accuracy of the solution was validated with both numerical simulations and CEST MRI experiments on a dual pH creatine gel phantom. The desired equilibrium CEST effect was further reconstructed with the QUASS algorithm from the optimized CEST MRI scan. In summary, our study establishes a workflow for CEST MRI scan optimization and postprocessing analysis, providing a framework to boost both the sensitivity of CEST MRI scans and the accuracy of CEST quantification. This approach holds promise for future in vivo validation and translation.

PET, SPECT, and MRI imaging for evaluation of Parkinson's disease

This review assesses the primary neuroimaging techniques used to evaluate Parkinson's disease (PD) - a neurological condition characterized by gradual dopamine-producing nerve cell degeneration. The neuroimaging techniques explored include positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI). These modalities offer varying degrees of insights into PD pathophysiology, diagnostic accuracy, specificity by way of exclusion of other Parkinsonian syndromes, and monitoring of disease progression. Neuroimaging is thus crucial for diagnosing and managing PD, with integrated multimodal approaches and novel techniques further enhancing early detection and treatment evaluation.

Multiparametric Chemical Exchange Saturation Transfer MRI Detects Metabolic Changes in Mild Cognitive Impairment Cases at 3.0 Tesla

This study aimed to assess the potential of multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) for MCI detection. Twenty-eight patients with MCI and 31 age- and gender-matched normal controls (NCs) were enrolled. CEST MRI was performed with a gradient and spin-echo sequence on a 3T scanner. Multi-parametric CEST parameters were analyzed, such as amide CEST, amine CEST, amine and amide concentration independent assay (AACID), magnetization transfer ratio yielding rex (MTRrex-amide), and downfield rNOE suppressed apparent exchange-dependent relaxation amide proton (DNS-AREX-amide). Statistical analyses of CEST parameters were performed to evaluate group differences, their correlations with Montreal cognitive assessment (MoCA) score, and diagnostic performance for MCI. Compared with NC group, amide CEST as well as MTRrex-amide decreased in the left hippocampus and amine CEST as well as AACID increased in the right hippocampus in the MCI group; In both hippocampi, the DNS-AREX-amide were significantly lower in the MCI group versus the NC group (all P < 0.05). Amine CEST in the right hippocampus was negatively correlated with MoCA score (r = - 0.457, p = 0.017); DNS-AREX-amide in the bilateral hippocampus was positively correlated with MoCA score (left: r = 0.449, P = 0.019; right: AUC = 0.529, P = 0.05). DNS-AREX-amide in the bilateral hippocampus have a good ability to identify MCI (left: AUC = 0.756, P < 0.01; right: AUC = 0.762, P < 0.01). CEST MRI provides a potential imaging diagnostic strategy for MCI, which may promote early detection of MCI and provide novel insights into the pathological progress toward AD.

Synthesis of higher-B0 CEST Z-spectra from lower-B0 data via deep learning and singular value decomposition

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-B0 Z-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-B0 Z-spectra were streamlined to the second DNN, casting into the key feature representations of higher-B0 Z-spectra, obtained through SVD truncation. Finally, the complete higher-B0 Z-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-B0 Z-spectra from lower-B0 ones, which may facilitate CEST MRI quantification and applications.

Grain-Boundary-Rich Interphases for Rechargeable Batteries

The formation of stable interphases on the electrodes is crucial for rechargeable lithium (Li) batteries. However, next-generation high-energy batteries face challenges in controlling interphase formation due to the high reactivity and structural changes of electrodes, leading to reduced stability and slow ion transport, which accelerate battery degradation. Here, we report an approach to address these issues by introducing multicomponent grain-boundary-rich interphase that boosts the rapid transport of ions and enhances passivation toward prolonged lifespan. This is guided by fundamental principles of solid-state ionics and geological crystallization differentiation theory, achieved through improved solvation chemistry. Demonstrations showcase how the introduction of the interphase substantially impacts the Li-ion transport across the interphase and the electrode-electrolyte compatibility in cost-effective electrolyte solutions optimized with multiple Li salts. The resulting interphases feature microstructures rich in inorganic grain boundaries with a diverse array of nanosized grains, presenting enhanced Li-ion transport. Comprehensive analyses revealed that this realizes remarkable electrochemical stability over extended cycling periods by inhibiting electrode corrosion, thus holding promise for high-capacity thin-Li-metal, Si-based anodes, and even Li-free anodes when paired with high-capacity oxide cathodes. This work opens new avenues to customize protective interphases on high-capacity electrodes, promoting the development of batteries with the highest energy density using cost-effective electrolytes.

In vivo mapping of the chemical exchange relayed nuclear Overhauser effect using deep magnetic resonance fingerprinting

Noninvasive magnetic resonance imaging (MRI) of the relayed nuclear Overhauser effect (rNOE) constitutes a promising approach for gaining biological insights into various pathologies, including brain cancer, kidney injury, ischemic stroke, and liver disease. However, rNOE imaging is time-consuming and prone to biases stemming from the water T1 and the semisolid magnetization transfer (MT) contrasts. Here, we developed a rapid rNOE quantification approach, combining magnetic resonance fingerprinting (MRF) acquisition with deep-learning-based reconstruction. The method was systematically validated using tissue-mimicking phantoms, wild-type mice (n = 7), and healthy human volunteers (n = 5). In vitro rNOE parameter maps generated by MRF were highly correlated with ground truth (r > 0.98, p < 0.001). Simultaneous mapping of the rNOE and the semisolid MT exchange parameters in mice and humans were in agreement with previously reported literature values. Whole-brain 3D parameter mapping in humans took less than 5 min (282 s for acquisition and less than 2 s for reconstruction). With its demonstrated ability to rapidly extract quantitative molecular maps, deep rNOE-MRF can potentially serve as a valuable tool for the characterization and detection of molecular abnormalities in vivo.

Quantitative in Vivo Molecular MRI

Molecular magnetic resonance imaging (MRI) combines chemistry, chemical biology, and imaging techniques to track molecular events non-invasively. Quantitative molecular MRI aims to provide meaningful, reproducible numerical measurements of molecular processes or biochemical targets within the body. In this review, the classifications of molecular MRI probes based on their signal-generating mechanism and functionality are first described. From there, the primary considerations for in vitro characterization and in vivo validation of molecular MRI probes, including how to avoid pitfalls and biases are discussed. Then, recommendations on imaging acquisition protocols and analysis methods to establish quantitative relationships between MRI signal change induced by the probes and the molecular processes of interest are provided. Finally, several representative case studies are highlighted that incorporate these features. Quantitative molecular MRI is a multidisciplinary research area incorporating expertise in chemical biology, inorganic chemistry, molecular probes, imaging physics, drug development, pathobiology, and medicine. The purpose of this review is to provide guidance to chemists developing MR imaging probes and methods in terms of in vitro and in vivo validation to accelerate the translation of these new quantitative tools for non-invasive imaging of biological processes.

Differentiation and characterization of healthy versus pathological tau using chemical exchange saturation transfer

Neurofibrillary tangles of tau constitute one of the key biological hallmarks of Alzheimer's disease. Currently, the assessment of regional tau accumulation requires intravenous administration of radioactive tracers for PET imaging. A noninvasive MRI-based solution would have significant clinical implications. Herein, we utilized an MRI technique known as chemical exchange saturation transfer (CEST) to determine the imaging signature of tau in both its monomeric and pathologic fibrillated conformations. Three sets of purified recombinant full-length (4R) tau protein were prepared for collection of CEST spectra using a 9.4 T NMR spectrometer at varying temperatures (25, 37, and 42 °C) and RF intensities (0.7, 1.0, 1.5, and 2.2 μT). Monomeric and fibrillated tau were readily distinguished based on their Z-spectrum profiles. Fibrillated tau demonstrated a less prominent peak at 3.5 ppm with additional peaks near 0.5 and 1.5 ppm. No significant differences were identified between fibrillated tau prepared using heparin versus seed-competent tau. In conclusion, monomeric and fibrillated tau can be readily detected and distinguished based on their CEST-derived Z-spectra, pointing to the potential utility of CEST-MRI as a noninvasive biomarker of regional pathologic tau accumulation in the brain. Further testing and validation in vitro and in vivo will be necessary before this can be applied clinically.

B1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T

PURPOSE

CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model.

METHODS

Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 μT at 5T. DS was resolved using a multi-pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/B 1 2 $$ {B}_1^2 $$ , from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach.

RESULTS

B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices.

CONCLUSION

The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisition of high-resolution images capable of accurately identifying subtle regional changes in vivo, while simultaneously maintaining a high level of spectral resolution. However, the acquisition of such high-resolution images is time consuming, presenting a challenge for practical implementation in clinical settings. Among several techniques that have been explored to reduce the acquisition time in MRI, deep-learning-based super-resolution (DLSR) is a promising approach to address this problem due to its adaptability to any acquisition sequence and hardware. However, its translation to CEST MRI has been hindered by the lack of the large CEST datasets required for network development. Thus, we aim to develop a DLSR method, named DLSR-CEST, to reduce the acquisition time for CEST MRI by reconstructing high-resolution images from fast low-resolution acquisitions. This is achieved by first pretraining the DLSR-CEST on human brain T1w and T2w images to initialize the weights of the network and then training the network on very small human and mouse brain CEST datasets to fine-tune the weights. Using the trained DLSR-CEST network, the reconstructed CEST source images exhibited improved spatial resolution in both peak signal-to-noise ratio and structural similarity index measure metrics at all downsampling factors (2-8). Moreover, amide CEST and relayed nuclear Overhauser effect maps extrapolated from the DLSR-CEST source images exhibited high spatial resolution and low normalized root mean square error, indicating a negligible loss in Z-spectrum information. Therefore, our DLSR-CEST demonstrated a robust reconstruction of high-resolution CEST source images from fast low-resolution acquisitions, thereby improving the spatial resolution and preserving most Z-spectrum information.

Imaging of adeno-associated viral capsids for purposes of gene editing using CEST NMR/MRI

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.

Highly-accelerated CEST MRI using frequency-offset-dependent k-space sampling and deep-learning reconstruction

PURPOSE

To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction.

METHODS

For k-space down-sampling, a customized pattern was proposed for CEST, with the randomized probability following a frequency-offset-dependent (FOD) function in the direction of saturation offset. For reconstruction, the convolution network (CNN) was enhanced with a Partially Separable (PS) function to optimize the spatial domain and frequency domain separately. Retrospective experiments on a self-acquired human brain dataset (13 healthy adults and 15 brain tumor patients) were conducted using k-space resampling. The prospective performance was also assessed on six healthy subjects.

RESULTS

In retrospective experiments, the combination of FOD sampling and PS network (FOD + PSN) showed the best quantitative metrics for reconstruction, outperforming three other combinations of conventional sampling with varying density and a regular CNN (nMSE and SSIM, p < 0.001 for healthy subjects). Across all acceleration factors from 4 to 14, the FOD + PSN approach consistently outperformed the comparative methods in four contrast maps including MTRasym, MTRrex, as well as the Lorentzian Difference maps of amide and nuclear Overhauser effect (NOE). In the subspace replacement experiment, the error distribution demonstrated the denoising benefits achieved in the spatial subspace. Finally, our prospective results obtained from healthy adults and brain tumor patients (14×) exhibited the initial feasibility of our method, albeit with less accurate reconstruction than retrospective ones.

CONCLUSION

The combination of FOD sampling and PSN reconstruction enabled highly accelerated CEST MRI acquisition, which may facilitate CEST metabolic MRI for brain tumor patients.

Development and Validation of Four Different Methods to Improve MRI-CEST Tumor pH Mapping in Presence of Fat

CEST-MRI is an emerging imaging technique suitable for various in vivo applications, including the quantification of tumor acidosis. Traditionally, CEST contrast is calculated by asymmetry analysis, but the presence of fat signals leads to wrong contrast quantification and hence to inaccurate pH measurements. In this study, we investigated four post-processing approaches to overcome fat signal influences and enable correct CEST contrast calculations and tumor pH measurements using iopamidol. The proposed methods involve replacing the Z-spectrum region affected by fat peaks by (i) using a linear interpolation of the fat frequencies, (ii) applying water pool Lorentzian fitting, (iii) considering only the positive part of the Z-spectrum, or (iv) calculating a correction factor for the ratiometric value. In vitro and in vivo studies demonstrated the possibility of using these approaches to calculate CEST contrast and then to measure tumor pH, even in the presence of moderate to high fat fraction values. However, only the method based on the water pool Lorentzian fitting produced highly accurate results in terms of pH measurement in tumor-bearing mice with low and high fat contents.

Hybrid PNA-peptide hydrogels as injectable CEST-MRI agents

The self-assembly of peptides and peptide analogues may be exploited to develop platforms for different biomedical applications, among which CEST-MRI (chemical exchange saturation transfer magnetic resonance imaging) represents one of the most attractive techniques to be explored as a novel metal-free contrast approach in imaging acquisitions. A lysine-containing peptide sequence (LIVAGK-NH2, named K2) was thus modified by insertion, at the N-terminus, of a peptide nucleic acid (PNA) base, leading to a primary amine suitable for the signal generation. a-K2, c-K2, g-K2 and t-K2 peptides were synthesized and characterized. The c-K2 sequence displayed gelling properties and the Watson and Crick pairing, arising from its combination with g-K2, allowed a significant increase in the mechanical responsivity of the hydrogel. These matrices were able to generate a CEST signal around 2.5 ppm from water and, after assessing their cytocompatibility on GL261 (murine glioma), TS/a (murine breast carcinoma), and 3T3-NIH (murine fibroblasts) cell lines, their capability to work as implants for in vivo detection, was proved by intratumor injection in Balb/c mice inoculated with TS/a murine breast cancer cells.

Intramolecular Hydrogen Bonding Based CEST MRI Contrast Agents As an Emerging Design Strategy: A Mini-Review

Intramolecular hydrogen bonding-based chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) contrast agents represent an innovative design strategy aiming to overcome limitations in diamagnetic CEST (diaCEST) MRI contrast agent specificity and also those associated with traditional metal-based MRI contrast agents. Ward and Balaban's proposal of small diamagnetic compounds marked a paradigm shift in contrast-based radiologic research, inspiring extensive investigations since 2000. These contrast agents leverage labile hydrogen bonds, serving as chemical exchange sites to induce saturation of water. The selective manipulation of radiofrequency (RF) allows for optimized signal contrast in soft tissue, with a significant signal amplification even at low probe concentrations, mitigating concerns about dose-dependent toxicities. This mini-review delves into the evolution of CEST MRI, its classification, and the strategic design principles of synthetic small molecules containing intramolecular hydrogen bonds. With a focus on applications and potential clinical relevance, the authors highlight the promising role of intramolecular hydrogen bonding-based CEST MRI in diverse medical contexts, especially renal imaging and pH mapping, paving the way for enhanced molecular imaging capabilities. Ongoing research endeavors aim to further optimize and expand the utility of these contrast agents, underscoring their transformative potential in clinical diagnostics and imaging.

The Proton Resonance Enhancement for CEST imaging and Shift Exchange (PRECISE) family of RF pulse shapes for Chemical Exchange Saturation Transfer MRI

Purpose

To optimize a 100 msec pulse for producing CEST MRI contrast and evaluate in mice.

Methods

A gradient ascent algorithm was employed to generate a family of 100 point, 100 msec pulses for use in CEST pulse trains ('PRECISE'). Gradient ascent optimizations were performed for exchange rates (k ca ) = 500 s -1 , 1,500 s -1 , 2,500 s -1 , 3,500 s -1 and 4,500 s -1 and offsets (Δω) = 9.6, 7.8, 4.2 and 2.0 ppm. 7 PRECISE pulse shapes were tested on an 11.7 T scanner using a phantom containing three representative CEST agents with peak saturation B 1 = 4 μT. The pulse producing the most contrast in phantoms was then evaluated for CEST MRI pH mapping of the kidneys in healthy mice after iopamidol administration.

Results

The most promising pulse in terms of contrast performance across all three phantoms was the 9.6 ppm, 2500 s -1 optimized pulse with ∼2.7 x improvement over Gaussian and ∼1.3x's over Fermi pulses. This pulse also displayed a large improvement in contrast over the Gaussian pulse after administration of iopamidol in live mice.

Conclusion

A new 100 msec pulse was developed based on gradient ascent optimizations which produced better contrast compared to standard Gaussian and Fermi pulses in phantoms. This shape also showed a substantial improvement for CEST MRI pH mapping in live mice over the Gaussian shape and appears promising for a wide range of CEST applications.

Induced saturation transfer recovery steady states (iSTRESS) for proton exchange rate mapping with CEST MRI, a preliminary study

Proton exchange underpins essential mechanisms in diverse MR imaging contrasts. Omega plots have proven effective in mapping proton exchange rates (kex) 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 kex 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 kex quantification was derived theoretically, involving two measurements with distinct excitation flip angles and saturation B1 values. Bloch-McConnell simulations confirmed that iSTRESS-based kex 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 kex mapping. kex maps derived from the phantom study exhibited a linear correlation (R2 > 0.99) with Omega plot results. The developed iSTRESS method allows for kex quantification with significantly reduced saturation times, effectively minimizing SAR concerns.

Quantum dipole interactions and transient hydrogen bond orientation order in cells, cellular membranes and myelin sheath: Implications for MRI signal relaxation, anisotropy, and T1 magnetic field dependence

PURPOSE

Despite significant impact on the study of human brain, MRI lacks a theory of signal formation that integrates quantum interactions involving proton dipoles (a primary MRI signal source) with brain intricate cellular environment. The purpose of the present study is developing such a theory.

METHODS

We introduce the Transient Hydrogen Bond (THB) model, where THB-mediated quantum dipole interactions between water and protons of hydrophilic heads of amphipathic biomolecules forming cells, cellular membranes and myelin sheath serve as a major source of MR signal relaxation.

RESULTS

The THB theory predicts the existence of a hydrogen-bond-driven structural order of dipole-dipole connections within THBs as a primary factor for the anisotropy observed in MRI signal relaxation. We have also demonstrated that the conventional Lorentzian spectral density function decreases too fast at high frequencies to adequately capture the field dependence of brain MRI signal relaxation. To bridge this gap, we introduced a stretched spectral density function that surpasses the limitations of Lorentzian dispersion. In human brain, our findings reveal that at any time point only about 4% to 7% of water protons are engaged in quantum encounters within THBs. These ultra-short (2 to 3 ns), but frequent quantum spin exchanges lead to gradual recovery of magnetization toward thermodynamic equilibrium, that is, relaxation of MRI signal.

CONCLUSION

By incorporating quantum proton interactions involved in brain imaging, the THB approach introduces new insights on the complex relationship between brain tissue cellular structure and MRI measurements, thus offering a promising new tool for better understanding of brain microstructure in health and disease.

Amide proton transfer-weighted imaging of the abdomen: Current progress and future directions

The chemical exchange saturation transfer technique serves as a valuable tool for generating in vivo image contrast based on the content of various proton groups, including amide protons, amine protons, and aliphatic protons. Among these, amide proton transfer-weighted (APTw) imaging has seen extensive development as a means to assess the biochemical status of lesions. The exchange from saturated amide protons to bulk water protons during and following the saturation ratio frequency pulse contributes to detectable APT signals. While APTw imaging has garnered significant attention in the central nervous system, demonstrating noteworthy findings in cerebral neoplasia, stroke, and Alzheimer's disease over the past decade, its application in the abdomen has been a relatively recent progression. Notably, studies have explored its utility in hepatocellular carcinoma, prostate cancer, and cervical carcinoma within the abdominal context. Despite these advancements, there is a paucity of reviews on APTw imaging in abdominal applications. This paper aims to fill this gap by providing a concise overview of the fundamental theories underpinning APTw imaging. Additionally, we systematically summarize its diverse clinical applications in the abdomen, with a particular focus on the digestive and urogenital systems. Finally, the manuscript concludes by discussing technical limitations and factors influencing APTw imaging in abdominal applications, along with prospects for future research.

A Magnetic Resonance Imaging-Chemical Exchange Saturation Transfer (MRI-CEST) Method for the Detection of Water Cycling across Cellular Membranes

Water cycling across the membrane transporters is considered a hallmark of cellular metabolism and it could be of high diagnostic relevance in the characterization of tumors and other diseases. The method relies on the response of intracellular proton exchanging molecules to the presence of extracellular Gd-based contrast agents (GBCAs). Paramagnetic GBCAs enhances the relaxation rate of water molecules in the extracellular compartment and, through membrane exchange, the relaxation enhancement is transferred to intracellular molecules. The effect is detected at the MRI-CEST (Magnetic Resonance Imaging - Chemical Exchange Saturation Transfer) signal of intracellular proton exchanging molecules. The magnitude of the change in the CEST response reports on water cycling across the membrane. The method has been tested on Red Blood Cells and on orthotopic murine models of breast cancer with different degree of malignancy (4T1, TS/A and 168FARN). The distribution of voxels reporting on membrane permeability fits well with the cells' aggressiveness and acts as an early reporter to monitor therapeutic treatments.

Fast and robust pulsed chemical exchange saturation transfer (CEST) MRI using a quasi-steady-state (QUASS) algorithm at 3 T

Chemical exchange saturation transfer (CEST) has emerged as a powerful technique to image dilute labile protons. However, its measurement depends on the RF saturation duration (Tsat) and relaxation delay (Trec). Although the recently developed quasi-steady-state (QUASS) solution can reconstruct equilibrium CEST effects under continuous-wave RF saturation, it does not apply to pulsed-CEST MRI on clinical scanners with restricted hardware or specific absorption rate limits. This study proposed a QUASS algorithm for pulsed-CEST MRI and evaluated its performance in muscle CEST measurement. An approximated expression of a steady-state pulsed-CEST signal was incorporated in the off-resonance spin-lock model, from which the QUASS pulsed-CEST effect was derived. Numerical simulation, creatine phantom, and healthy volunteer scans were conducted at 3 T. The CEST effect was quantified with asymmetry analysis in the simulation and phantom experiments. CEST effects of creatine, amide proton transfer, phosphocreatine, and combined magnetization transfer and nuclear Overhauser effects were isolated from a multi-pool Lorentzian model in muscles. Apparent and QUASS CEST measurements were compared under different Tsat/Trec and duty cycles. Paired Student's t-test was employed with P < 0.05 as statistically significant. The simulation, phantom, and human studies showed the strong impact of Tsat/Trec on apparent CEST measurements, which were significantly smaller than the corresponding QUASS CEST measures, especially under short Tsat/Trec times. In comparison, the QUASS algorithm mitigates such impact and enables accurate CEST measurements under short Tsat/Trec times. In conclusion, the QUASS algorithm can accelerate robust pulsed-CEST MRI, promising the efficient detection and evaluation of muscle diseases in clinical settings.

Repurposing of the PET Probe Prototype PiB for Label and Radiation-Free CEST MRI Molecular Imaging of Amyloid

Positron emission tomography (PET) probes are specific and sensitive while suffering from radiation risk. It is worthwhile to explore the chemical emission saturation transfer (CEST) effects of the probe prototypes and repurpose them for CEST imaging to avoid radiation. In this study, we used 11C-PiB as an example of a PET probe for detecting amyloid and tested the feasibility of repurposing this PET probe prototype, PiB, for CEST imaging. After optimizing the parameters through preliminary phantom experiments, we used APP/PS1 transgenic mice and age-matched C57 mice for in vivo CEST magnetic resonance imaging (MRI) of amyloid. Furthermore, the pathological assessment was conducted on the same brain slices to evaluate the correlation between the CEST MRI signal abnormality and β-amyloid deposition detected by immunohistochemical staining. In our results, the Z-spectra revealed an apparent CEST effect that peaked at approximately 6 ppm. APP/PS1 mice as young as 9 months injected with PiB showed a significantly higher CEST effect compared to the control groups. The hyperintense region was correlated with the Aβ deposition shown by pathological staining. In conclusion, repurposing the PET probe prototype for CEST MRI imaging is feasible and enables label- and radiation-free detection of the amyloid while maintaining the sensitivity and specificity of the ligand. This study opens the door to developing CEST probes based on PET probe prototypes.

Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI

PURPOSE

Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencing in chemical exchange saturation transfer (CEST) MRI. However, their analysis using least-squares (LS) Lorentzian fitting is time-consuming and prone to errors because of the unavoidable noise in vivo. A deep learning-based single Lorentzian Fitting Network (sLoFNet) is proposed to overcome these shortcomings.

METHODS

A neural network architecture was constructed and its hyperparameters optimized. Training was conducted on a simulated and in vivo-paired data sets of discrete signal values and their corresponding Lorentzian shape parameters. The sLoFNet performance was compared with LS on several WASSR data sets (both simulated and in vivo 3T brain scans). Prediction errors, robustness against noise, effects of sampling density, and time consumption were compared.

RESULTS

LS and sLoFNet performed comparably in terms of RMS error and mean absolute error on all in vivo data with no statistically significant difference. Although the LS method fitted well on samples with low noise, its error increased rapidly when increasing sample noise up to 4.5%, whereas the error of sLoFNet increased only marginally. With the reduction of Z-spectral sampling density, prediction errors increased for both methods, but the increase occurred earlier (at 25 vs. 15 frequency points) and was more pronounced for LS. Furthermore, sLoFNet performed, on average, 70 times faster than the LS-method.

CONCLUSION

Comparisons between LS and sLoFNet on simulated and in vivo WASSR MRI Z-spectra in terms of robustness against noise and decreased sample resolution, as well as time consumption, showed significant advantages for sLoFNet.

Contrasting Properties of Polymeric Nanocarriers for MRI-Guided Drug Delivery

Poor pharmacokinetics and low aqueous solubility combined with rapid clearance from the circulation of drugs result in their limited effectiveness and generally high therapeutic doses. The use of nanocarriers for drug delivery can prevent the rapid degradation of the drug, leading to its increased half-life. It can also improve the solubility and stability of drugs, advance their distribution and targeting, ensure a sustained release, and reduce drug resistance by delivering multiple therapeutic agents simultaneously. Furthermore, nanotechnology enables the combination of therapeutics with biomedical imaging agents and other treatment modalities to overcome the challenges of disease diagnosis and therapy. Such an approach is referred to as "theranostics" and aims to offer a more patient-specific approach through the observation of the distribution of contrast agents that are linked to therapeutics. The purpose of this paper is to present the recent scientific reports on polymeric nanocarriers for MRI-guided drug delivery. Polymeric nanocarriers are a very broad and versatile group of materials for drug delivery, providing high loading capacities, improved pharmacokinetics, and biocompatibility. The main focus was on the contrasting properties of proposed polymeric nanocarriers, which can be categorized into three main groups: polymeric nanocarriers (1) with relaxation-type contrast agents, (2) with chemical exchange saturation transfer (CEST) properties, and (3) with direct detection contrast agents based on fluorinated compounds. The importance of this aspect tends to be downplayed, despite its being essential for the successful design of applicable theranostic nanocarriers for image-guided drug delivery. If available, cytotoxicity and therapeutic effects were also summarized.

Chemical Exchange Saturation Transfer MRI: Capability for Predicting Therapeutic Effect of Chemoradiotherapy on Non-Small Cell Lung Cancer Patients

BACKGROUND

Amide proton transfer (APT) weighted chemical exchange saturation transfer CEST (APTw/CEST) magnetic resonance imaging (MRI) has been suggested as having the potential for assessing the therapeutic effect of brain tumors or rectal cancer. Moreover, diffusion-weighted imaging (DWI) and positron emission tomography fused with computed tomography by means of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG-PET/CT) have been suggested as useful in same setting.

PURPOSE

To compare the capability of APTw/CEST imaging, DWI, and FDG-PET/CT for predicting therapeutic effect of chemoradiotherapy (CRT) on stage III non-small cell lung cancer (NSCLC) patients.

STUDY TYPE

Prospective.

POPULATION

Eighty-four consecutive patients with Stage III NSCLC, 45 men (age range, 62-75 years; mean age, 71 years) and 39 women (age range, 57-75 years; mean age, 70 years). All patients were then divided into two groups (Response Evaluation Criteria in Solid Tumors [RECIST] responders, consisting of the complete response and partial response groups, and RECIST non-responders, consisting of the stable disease and progressive disease groups).

FIELD STRENGTH/SEQUENCE

3 T, echo planar imaging or fast advanced spin-echo (FASE) sequences for DWI and 2D half Fourier FASE sequences with magnetization transfer pulses for CEST imaging.

ASSESSMENT

Magnetization transfer ratio asymmetry (MTRasym ) at 3.5 ppm, apparent diffusion coefficient (ADC), and maximum standard uptake value (SUVmax, ) on PET/CT were assessed by means of region of interest (ROI) measurements at primary tumor.

STATISTICAL TESTS

Kaplan-Meier method followed by log-rank test and Cox proportional hazards regression analysis with multivariate analysis. A P value <0.05 was considered statistically significant.

RESULTS

Progression-free survival (PFS) and overall survival (OS) had significant difference between two groups. MTRasym at 3.5 ppm (hazard ratio [HR] = 0.70) and SUVmax (HR = 1.41) were identified as significant predictors for PFS. Tumor staging (HR = 0.57) was also significant predictors for OS.

DATA CONCLUSION

APTw/CEST imaging showed potential performance as DWI and FDG-PET/CT for predicting the therapeutic effect of CRT on stage III NSCLC patients.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

CEST 2022-three-dimensional amide proton transfer (APT) imaging can identify the changes of cerebral cortex in Parkinson's disease

PURPOSE

Amide proton transfer (APT) imaging has shown its diagnostic and predictive superiority in PD in our previous studies using 2D APT imaging based on deep nuclei. We hypothesized that the pathophysiological abnormality of PD will change the APT-related parameters in the cerebral cortex, and the signal changes can contribute to accurate diagnosis of Parkinson's disease.

METHODS

34 patients with sporadic Parkinson's disease (IPD) and 29 age- and sex-matched normal controls (NC) were enrolled in this prospective study. 3D-APT imaging and 3D-T1WI was performed in our participants. A volume-based morphometry algorithm was used and get automated cortical segmentations. Quantitative parameter maps of APT-related metrics were calculated by using SPM and MATLAB. The unpaired Student's t-test or Mann-Whitney U test was used for comparison of these values between IPD and NC groups. The associations between APT-related metrics and clinical assessments were investigated by Spearman correlation analysis. The receiver-operating characteristic (ROC) analysis was used to assess the diagnostic performances. The binary logistic regression model was used to combine the imaging parameters.

RESULTS

There wasn't any correlations between cortical APT-related signals and clinical assessment, including the H&Y scale, the disease duration, the UPDRS III scores and the MMSE scores. The MTRasym, CESTRnr and MTRRex had significantly higher values (p <0.001, corrected by Bonferroni methods) in the IPD group than NC groups in the region of bilateral and total temporal grey matter. The single parameters achieved the best diagnostic performance among all APT-related metrics was MTRRex on the right temporal grey matter, with an area under the ROC curve (AUC) of 0.865. The combined parameters achieved the highest diagnostic performance (AUC: 0.932).

CONCLUSIONS

3D-APT imaging could identify the changes of the cerebral cortex in Parkinson's disease. The cortical changes of APT-related parameters could potentially serve as imaging biomarkers to aid in the non-invasive diagnosis of PD.

CEST2022 - mapping multi-pool CEST signal changes in an animal model of brain tumor with quasi-steady-state reconstruction-empowered CEST quantification

Chemical exchange saturated transfer (CEST) MRI has biomarker potential to assess tissue microenvironment in brain tumors. Multi-pool Lorentzian or spinlock models provides useful insights into the CEST contrast mechanism. However, T₁ contribution to the complex overlapping effects of brain tumors is difficult under the non-equilibrium state. Therefore, this study evaluated T₁ contributions on multi-pool parameters with quasi-steady-state (QUASS) algorithm reconstructed equilibrium data. MRI scans were performed in rat brain tumor models, including relaxation, diffusion, and CEST imaging. A pixel-wise seven-pool spinlock-model was employed to fit QUASS reconstructed CEST Z-spectra and evaluated the magnetization transfer (MT), amide, amine, guanidyl, and nuclear-overhauled effect (NOE) signals in tumor and normal tissues. In addition, T₁ was estimated from the spinlock-model fitting and compared with measured T₁. We observed tumor had a statistically significant increase in the amide signal (p < 0.001) and decreases in the MT and NOE signals (p < 0.001). On the other hand, the differences in amine and guanidyl between the tumor and contralateral normal regions were not statistically significant. The differences between measured and estimated T₁ values were 8% in the normal tissue and 4% in the tumor. Furthermore, the isolated MT signal strongly correlated with R₁ (r = 0.96, P < 0.001). In summary, we successfully unraveled multi-factorial effects in the CEST signal using spinlock-model fitting and QUASS method and demonstrated the effect of T₁ relaxation on MT and NOE.

CEST 2022 - Differences in APT-weighted signal in T1 weighted isointense lesions, black holes and normal-appearing white matter in people with relapsing-remitting multiple sclerosis

PURPOSE

To evaluate amide proton transfer weighted (APTw) signal differences between multiple sclerosis (MS) lesions and contralateral normal-appearing white matter (cNAWM). Cellular changes during the demyelination process were also assessed by comparing APTw signal intensity in T1weighted isointense (ISO) and hypointense (black hole -BH) MS lesions in relation to cNAWM.

METHODS

Twenty-four people with relapsing-remitting MS (pw-RRMS) on stable therapy were recruited. MRI/APTw acquisitions were undertaken on a 3 T MRI scanner. The pre and post-processing, analysis, co-registration with structural MRI maps, and identification of regions of interest (ROIs) were all performed with Olea Sphere 3.0 software. Generalized linear model (GLM) univariate ANOVA was undertaken to test the hypotheses that differences in mean APTw were entered as dependent variables. ROIs were entered as random effect variables, which allowed all data to be included. Regions (lesions and cNAWM) and/or structure (ISO and BH) were the main factor variables. The models also included age, sex, disease duration, EDSS, and ROI volumes as covariates. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic performance of these comparisons.

RESULTS

A total of 502 MS lesions manually identified on T2-FLAIR from twenty-four pw-RRMS were subcategorized as 359 ISO and 143 BH with reference to the T1-MPRAGE cerebral cortex signal. Also, 490 ROIs of cNAWM were manually delineated to match the MS lesion positions. A two-tailed t-test showed that mean APTw values were higher in females than in males (t = 3.52, p < 0.001). Additionally, the mean APTw values of MS lesions were higher than those of cNAWM after accounting for covariates (mean lesion = 0.44, mean cNAWM = 0.13, F = 44.12, p < 0.001).The mean APTw values of ISO lesions were higher than those of cNAWM after accounting for covariates (mean ISO lesions = 0.42, mean cNAWM = 0.21, F = 12.12, p < 0.001). The mean APTw values of BH were also higher than those of cNAWM (mean BH lesions = 0.47, mean cNAWM = 0.033, F = 40.3, p < 0.001). The effect size (i.e., difference between lesion and cNAWM) for BH was found to be higher than for ISO (14 vs. 2). Diagnostic performance showed that APT was able to discriminate between all lesions and cNAWM with an accuracy of >75% (AUC = 0.79, SE = 0.014). Discrimination between ISO lesions and cNAWM was accomplished with an accuracy of >69% (AUC = 0.74, SE = 0.018), while discrimination between BH lesions and cNAWM was achieved at an accuracy of >80% (AUC = 0.87, SE = 0.021).

CONCLUSIONS

Our results highlight the potential of APTw imaging for use as a non-invasive technique that is able to provide essential molecular information to clinicians and researchers so that the stages of inflammation and degeneration in MS lesions can be better characterized.

Detection of tissue pH with quantitative chemical exchange saturation transfer magnetic resonance imaging

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a novel means for sensitive detection of dilute labile protons and chemical exchange rates. By sensitizing to pH-dependent chemical exchange, CEST MRI has shown promising results in monitoring tissue statuses such as pH changes in disorders like acute stroke, tumor, and acute kidney injury. This article briefly reviews the basic principles for CEST imaging and quantitative measures, from the simplistic asymmetry analysis to multipool Lorentzian decoupling and quasi-steady-state reconstruction. In particular, the advantages and limitations of commonly used quantitative approaches for CEST applications are discussed.

MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification

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.

Applications of chemical exchange saturation transfer magnetic resonance imaging in identifying genetic markers in gliomas

Chemical exchange saturation transfer (CEST) imaging is an important molecular magnetic resonance imaging technique that can image numerous low-concentration biomolecules with water-exchangeable protons (such as cellular proteins) and tissue pH. CEST, or more specially amide proton transfer-weighted imaging, has been widely used for the detection, diagnosis, and response assessment of brain tumors, and its feasibility in identifying molecular markers in gliomas has also been explored in recent years. In this paper, after briefing on the basic principles and quantification methods of CEST imaging, we review its early applications in identifying isocitrate dehydrogenase mutation status, MGMT methylation status, 1p/19q deletion status, and H3K27M mutation status in gliomas. Finally, we discuss the limitations or weaknesses in these studies.

Glutamate-weighted CEST (gluCEST) imaging for mapping neurometabolism: An update on the state of the art and emerging findings from in vivo applications

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.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Amide proton transfer imaging in stroke

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.

The relayed nuclear Overhauser effect in magnetization transfer and chemical exchange saturation transfer MRI

Magnetic resonance (MR) is a powerful technique for noninvasively probing molecular species in vivo but suffers from low signal sensitivity. Saturation transfer (ST) MRI approaches, including chemical exchange saturation transfer (CEST) and conventional magnetization transfer contrast (MTC), allow imaging of low-concentration molecular components with enhanced sensitivity using indirect detection via the abundant water proton pool. Several recent studies have shown the utility of chemical exchange relayed nuclear Overhauser effect (rNOE) contrast originating from nonexchangeable carbon-bound protons in mobile macromolecules in solution. In this review, we describe the mechanisms leading to the occurrence of rNOE-based signals in the water saturation spectrum (Z-spectrum), including those from mobile and immobile molecular sources and from molecular binding. While it is becoming clear that MTC is mainly an rNOE-based signal, we continue to use the classical MTC nomenclature to separate it from the rNOE signals of mobile macromolecules, which we will refer to as rNOEs. Some emerging applications of the use of rNOEs for probing macromolecular solution components such as proteins and carbohydrates in vivo or studying the binding of small substrates are discussed.

Dual-Peak Lorentzian CEST MRI for antiretroviral drug brain distribution

Objectives

Spatial-temporal biodistribution of antiretroviral drugs (ARVs) can now be achieved using MRI by utilizing chemical exchange saturation transfer (CEST) contrasts. However, the presence of biomolecules in tissue limits the specificity of current CEST methods. To overcome this limitation, a Lorentzian line-shape fitting algorithm was developed that simultaneously fits CEST peaks of ARV protons on its Z-spectrum.

Case presentation

This algorithm was tested on the common first line ARV, lamivudine (3TC), that has two peaks resulting from amino (-NH2) and hydroxyl (-OH) protons in 3TC. The developed dual-peak Lorentzian function fitted these two peaks simultaneously, and used the ratio of -NH2 and -OH CEST contrasts as a constraint parameter to measure 3TC presence in brains of drug-treated mice. 3TC biodistribution calculated using the new algorithm was compared against actual drug levels measured using UPLC-MS/MS. In comparison to the method that employs the -NH2 CEST peak only, the dual-peak Lorentzian fitting algorithm showed stronger correlation with brain tissue 3TC levels, signifying estimation of actual drug levels.

Conclusions

We concluded that 3TC levels can be extracted from confounding CEST effects of tissue biomolecules resulting in improved specificity for drug mapping. This algorithm can be expanded to measure a variety of ARVs using CEST MRI.

Demonstration of accurate multi-pool chemical exchange saturation transfer MRI quantification - Quasi-steady-state reconstruction empowered quantitative CEST analysis

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute labile protons and microenvironment properties, yet CEST quantification has been challenging. This difficulty is because the CEST measurement depends not only on the underlying CEST system but also on the scan protocols, including RF saturation amplitude, duration, and repetition time. In addition, T1 normalization is not straightforward under non-equilibrium conditions. Recently, a quasi-steady-state (QUASS) algorithm was established to reconstruct the desired equilibrium state from experimental measurements. Our study aimed to determine the accuracy of spinlock-model-based multi-pool CEST quantification using numerical simulations and phantom experiments. In short, CEST Z-spectra were simulated for a representative 3-pool model, and CEST amplitudes were solved with spinlock model-based multi-pool fitting and assessed as a function of RF saturation time (Ts), repetition time (TR), and T1. Although the apparent CEST signals showed significant T1 dependence, such relationships were not observed following QUASS reconstruction. To test the accuracy of T1 correction, a multi-vial phantom of nicotinamide and creatine was doped with manganese chloride, resulting in T1 ranging from 1 s to beyond 2 s. The multi-labile signals determined from the routine measurements showed significant dependence on Ts, TR, and T1. In contrast, CEST signals from the QUASS reconstruction showed consistent quantification independent of such variables. To summarize, our study demonstrated that accurate CEST quantification is feasible in multi-pool CEST systems with the spinlock-model-based fitting of QUASS CEST MRI.

Joint K-space and Image-space Parallel Imaging (KIPI) for accelerated chemical exchange saturation transfer acquisition

PURPOSE

To develop an auto-calibrated technique by joint K-space and Image-space Parallel Imaging (KIPI) for accelerated CEST acquisition.

THEORY AND METHODS

The KIPI method selects a calibration frame with a low acceleration factor (AF) and auto-calibration signals (ACS) acquired, from which the coil sensitivity profiles and artifact correction maps are calculated after restoring the k-space by GRAPPA. Then the other frames with high AF and without ACS can be reconstructed by SENSE and artifact suppression. The signal leakage due to the T₂ -decay filtering in k-space compromises the SENSE reconstruction, which can be corrected by the artifact suppression algorithm of KIPI. The 2D and 3D imaging experiments were done on the phantom, healthy volunteer, and brain tumor patient with a 3T scanner.

RESULTS

The proposed KIPI method was evaluated by retrospectively undersampled data with variable AFs and compared against existing parallel imaging methods (SENSE/auto, GRAPPA, and ESPIRiT). KIPI enabled CEST frames with random AFs to achieve similar image quality, eliminated the strong aliasing artifacts, and generated significantly smaller errors than the other methods (p < 0.01). The KIPI method permitted an AF up to 12-fold in both phase-encoding and slice-encoding directions for 3D CEST source images, achieving an overall 8.2-fold speedup in scan time.

CONCLUSION

KIPI is a novel auto-calibrated parallel imaging method that enables variable AFs for different CEST frames, achieves a significant reduction in scan time, and does not compromise the accuracy of CEST maps.

Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience

PURPOSE

Integrating magnetic resonance (MR) into radiotherapy planning has several advantages. This report details the clinical implementation of an MR simulation (MR-planning) program for external beam radiotherapy (EBRT) in one of North America's largest radiotherapy programs.

METHODS AND MATERIALS

An MR radiotherapy planning program was developed and implemented at Sunnybrook Health Sciences Center in 2016 with two dedicated wide-bore MR platforms (1.5 and 3.0 Tesla). Planning MR was sequentially implemented every 3 months for separate treatment sites, including the central nervous system (CNS), gynecologic (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus. Essential protocols and processes were detailed in this report, including clinical workflow, optimized MR-image acquisition protocols, MR-adapted patient setup, strategies to overcome risks and challenges, and an MR-planning quality assurance program. This study retrospectively reviewed simulation site data for all MR-planning sessions performed for EBRT over the past 5 years.

RESULTS

From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all computer tomography (CT) simulations (CT-planning) performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of planning MR/CT increased from 3% of all planning sessions in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%).

CONCLUSION

Detailed clinical processes and protocols of our MR-planning program were presented, which have been improved over more than 5 years of robust experience. Strategies to overcome risks and challenges in the implementation process are highlighted. Our work provides details that can be used by institutions interested in implementing an MR-planning program.