Quantitative Chemical Exchange Saturation Transfer Research Articles

PH Mapping of Gliomas Using Quantitative Chemical Exchange Saturation Transfer MRI: Quasi-Steady-State, Spillover-, and MT-Corrected Omega Plot Analysis.

Quantitative in-situ pH mapping of gliomas is important for therapeutic interventions, given its significant association with tumor progression, invasion, and metastasis. Although chemical exchange saturation transfer (CEST) offers a noninvasive way for pH imaging based on the pH-dependent exchange rate (ksw ), the reliable quantification of ksw in glioma remains constrained due to technical challenges. To quantify the pH of gliomas by measuring the proton exchange rate through optimized omega plot analysis. Prospective. Creatine and murine brain lysates phantoms, six rats with glioma xenograft model, and three patients with World Health Organization grade 2-4 gliomas. 11.7 T, 7.0 T, CEST imaging, T2 -weighted (T2 W) imaging, and T1 -mapping. Omega plot analysis, quasi-steady-state (QUASS) analysis, multi-pool Lorentzian fitting, amine and amide concentration-independent detection, pH enhanced method with the combination of amide and guanidyl (pHenh ), and magnetization transfer ratio (MTR) were utilized for pH metric quantification. The clinical outcomes were determined through radiologic follow-up and histopathological analysis. Mann-Whitney U test was performed to compare glioma with normal tissue, and Pearson's correlation analysis was used to assess the relationship between ksw and other parameters. In vitro experiments reveal that the determined ksw at 2 ppm increases exponentially with pH (creatine phantoms: ksw = 106 + 0.147 × 10(pH-4.198) ; lysates: ksw = 185.1 + 0.101 × 10(pH-3.914) ). Omega plot analysis exhibits a linear correlation between 1/MTRRex and 1/ω1 2 in the glioma xenografts (R2 > 0.98) and glioma patients (R2 > 0.99). The exchange rate in the rat glioma decreases compared to the contralateral normal tissue (349.46 ± 30.40 s-1 vs. 403.54 ± 51.01 s-1 , P = 0.025), while keeping independence from changes in concentration (r = 0.5037, P = 0.095). Similar pattern was observed in human data. Utilizing QUASS-based, spillover-, and MT-corrected omega plot analysis for the measurement of exchange rates, offers a feasible method for quantifying pH within glioma. NA TECHNICAL EFFICACY: Stage 1.

Numerical simulation-based assessment of pH-sensitive chemical exchange saturation transfer MRI quantification accuracy across field strengths.

Chemical exchange saturation transfer (CEST) MRI detects dilute labile protons via their exchange with bulk water, conferring pH sensitivity. Based on published exchange and relaxation properties, a 19-pool simulation was used to model the brain pH-dependent CEST effect and assess the accuracy of quantitative CEST (qCEST) analysis across magnetic field strengths under typical scan conditions. First, the optimal B1 amplitude was determined by maximizing pH-sensitive amide proton transfer (APT) contrast under the equilibrium condition. Apparent and quasi-steady-state (QUASS) CEST effects were then derived under the optimal B1 amplitude as functions of pH, RF saturation duration, relaxation delay, Ernst flip angle, and field strength. Finally, CEST effects, particularly the APT signal, were isolated with spinlock model-based Z-spectral fitting to evaluate the accuracy and consistency of CEST quantification. Our data showed that QUASS reconstruction significantly improved the consistency between simulated and equilibrium Z-spectra. The residual difference between QUASS and equilibrium CEST Z-spectra was, on average, 30 times less than that of the apparent CEST Z-spectra across field strengths, saturation, and repetition times. Also, the spinlock fitting of the QUASS CEST effect significantly reduced the residual errors 9-fold. Furthermore, the isolated APT amplitude from QUASS reconstruction was consistent and higher than the apparent CEST analysis under nonequilibrium conditions. To summarize, this study confirmed that QUASS reconstruction facilitates accurate determination of the CEST system under different scan protocols across field strengths, with the potential to help standardize CEST quantification.

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.

In vivo pH mapping with omega plot-based quantitative chemical exchange saturation transfer MRI.

Chemical exchange saturation transfer (CEST) MRI is promising for detecting dilute metabolites and microenvironment properties, which has been increasingly adopted in imaging disorders such as acute stroke and cancer. However, in vivo CEST MRI quantification remains challenging because routine asymmetry analysis (MTRasym ) or Lorentzian decoupling measures a combined effect of the labile proton concentration and its exchange rate. Therefore, our study aimed to quantify amide proton concentration and exchange rate independently in a cardiac arrest-induced global ischemia rat model. The amide proton CEST (APT) effect was decoupled from tissue water, macromolecular magnetization transfer, nuclear Overhauser enhancement, guanidinium, and amine protons using the image downsampling expedited adaptive least-squares (IDEAL) fitting algorithm on Z-spectra obtained under multiple RF saturation power levels, before and after global ischemia. Omega plot analysis was applied to determine amide proton concentration and exchange rate simultaneously. Global ischemia induces a significant APT signal drop from intact tissue. Using the modified omega plot analysis, we found that the amide proton exchange rate decreased from 29.6 ± 5.6 to 12.1 ± 1.3s-1 (P < 0.001), whereas the amide proton concentration showed little change (0.241 ± 0.035% vs. 0.202 ± 0.034%, P=0.074) following global ischemia. Our study determined the labile proton concentration and exchange rate underlying the in vivo APT MRI. The significant change in the exchange rate, but not the concentration of amide proton demonstrated that the pH effect dominates the APT contrast during tissue ischemia.

Quantitative Chemical Exchange Saturation Transfer Imaging of Amide Proton Transfer Differentiates between Cerebellopontine Angle Schwannoma and Meningioma: Preliminary Results.

Vestibular schwannomas are the most common tumor at the common cerebellopontine angle, followed by meningiomas. Differentiation of these tumors is critical because of the different surgical approaches required for treatment. Recent studies have demonstrated the utility of amide proton transfer (APT)-chemical exchange saturation transfer (CEST) imaging in evaluating malignant brain tumors. However, APT imaging has not been applied in benign tumors. Here, we explored the potential of APT in differentiating between schwannomas and meningiomas at the cerebellopontine angle. We retrospectively evaluated nine patients with schwannoma and nine patients with meningioma who underwent APT-CEST MRI from November 2020 to April 2022 pre-operation. All 18 tumors were histologically diagnosed. There was a significant difference in magnetization transfer ratio asymmetry (MTRasym) values (0.033 ± 0.012 vs. 0.021 ± 0.004; p = 0.007) between the schwannoma and meningioma groups. Receiver operative curve analysis showed that MTRasym values clearly differentiated between the schwannoma and meningioma groups. At an MTRasym value threshold of 0.024, the diagnostic sensitivity, specificity, positive predictive value, and negative predictive values for MTRasym were 88.9%, 77.8%, 80.0%, and 87.5%, respectively. Our results demonstrated the ability of MTRasym values on APT-CEST imaging to discriminate patients with schwannomas from patients with meningiomas.

Lorentzian-Corrected Apparent Exchange-Dependent Relaxation (LAREX) Ω-Plot Analysis-An Adaptation for qCEST in a Multi-Pool System: Comprehensive In Silico, In Situ, and In Vivo Studies.

Based on in silico, in situ, and in vivo studies, this study aims to develop a new method for the quantitative chemical exchange saturation transfer (qCEST) technique considering multi-pool systems. To this end, we extended the state-of-the-art apparent exchange-dependent relaxation (AREX) method with a Lorentzian correction (LAREX). We then validated this new method with in situ and in vivo experiments on human intervertebral discs (IVDs) using the Kendall-Tau correlation coefficient. In the in silico experiments, we observed significant deviations of the AREX method as a function of the underlying exchange rate (kba) and fractional concentration (fb) compared to the ground truth due to the influence of other exchange pools. In comparison to AREX, the LAREX-based Ω-plot approach yielded a substantial improvement. In the subsequent in situ and in vivo experiments on human IVDs, no correlation to the histological reference standard or Pfirrmann classification could be found for the fb (in situ: τ = −0.17 p = 0.51; in vivo: τ = 0.13 p = 0.30) and kba (in situ: τ = 0.042 p = 0.87; in vivo: τ = −0.26 p = 0.04) of Glycosaminoglycan (GAG) with AREX. In contrast, the influence of interfering pools could be corrected by LAREX, and a moderate to strong correlation was observed for the fractional concentration of GAG for both in situ (τ = −0.71 p = 0.005) and in vivo (τ = −0.49 p < 0.001) experiments. The study presented here is the first to introduce a new qCEST method that enables qCEST imaging in systems with multiple proton pools.

Quantitative chemical exchange saturation transfer imaging of nuclear overhauser effects in acute ischemic stroke.

PurposeIn chemical exchange saturation transfer imaging, saturation effects between −2 to −5 ppm (nuclear Overhauser effects, NOEs) have been shown to exhibit contrast in preclinical stroke models. Our previous work on NOEs in human stroke used an analysis model that combined NOEs and semisolid MT; however their combination might feasibly have reduced sensitivity to changes in NOEs. The aim of this study was to explore the information a 4‐pool Bloch–McConnell model provides about the NOE contribution in ischemic stroke, contrasting that with an intentionally approximate 3‐pool model.MethodsMRI data from 12 patients presenting with ischemic stroke were retrospectively analyzed, as well as from six animals induced with an ischemic lesion. Two Bloch–McConnell models (4 pools, and a 3‐pool approximation) were compared for their ability to distinguish pathological tissue in acute stroke. The association of NOEs with pH was also explored, using pH phantoms that mimic the intracellular environment of naïve mouse brain.ResultsThe 4‐pool measure of NOEs exhibited a different association with tissue outcome compared to 3‐pool approximation in the ischemic core and in tissue that underwent delayed infarction. In the ischemic core, the 4‐pool measure was elevated in patient white matter (1.20±0.20) and in animals (1.27±0.20). In the naïve brain pH phantoms, significant positive correlation between the NOE and pH was observed.ConclusionAssociations of NOEs with tissue pathology were found using the 4‐pool metric that were not observed using the 3‐pool approximation. The 4‐pool model more adequately captured in vivo changes in NOEs and revealed trends depending on tissue pathology in stroke.

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.

An end-to-end AI-based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST).

PurposeTo develop an automated machine‐learning‐based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols.MethodsAn MR physics‐governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative reconstruction neural network. The system (termed AutoCEST) is composed of a CEST saturation block, a spin dynamics module, and a deep reconstruction network, all differentiable and jointly connected. The method was validated using a variety of chemical exchange phantoms and in vivo mouse brains at 9.4T.ResultsThe acquisition times for AutoCEST optimized schedules ranged from 35 to 71 s, with a quantitative image reconstruction time of only 29 ms. The resulting exchangeable proton concentration maps for the phantoms were in good agreement with the known solute concentrations for AutoCEST sequences (mean absolute error = 2.42 mM; Pearson’s r=0.992, p<0.0001), but not for an unoptimized sequence (mean absolute error = 65.19 mM; Pearson’s r=‐0.161, p=0.522). Similarly, improved exchange rate agreement was observed between AutoCEST and quantification of exchange using saturation power (QUESP) methods (mean absolute error: 35.8 Hz, Pearson’s r=0.971, p<0.0001) compared to an unoptimized schedule and QUESP (mean absolute error = 58.2 Hz; Pearson’s r=0.959, p<0.0001). The AutoCEST in vivo mouse brain semi‐solid proton volume fractions were lower in the cortex (12.77% ± 0.75%) compared to the white matter (19.80% ± 0.50%), as expected.ConclusionAutoCEST can automatically generate optimized CEST/MT acquisition protocols that can be rapidly reconstructed into quantitative exchange parameter maps.

Intradiscal quantitative chemical exchange saturation transfer MRI signal correlates with discogenic pain in human patients

Low back pain (LBP) is often a result of a degenerative process in the intervertebral disc. The precise origin of discogenic pain is diagnosed by the invasive procedure of provocative discography (PD). Previously, we developed quantitative chemical exchange saturation transfer (qCEST) magnetic resonance imaging (MRI) to detect pH as a biomarker for discogenic pain. Based on these findings we initiated a clinical study with the goal to evaluate the correlation between qCEST values and PD results in LBP patients. Twenty five volunteers with chronic low back pain were subjected to T2-weighted (T2w) and qCEST MRI scans followed by PD. A total of 72 discs were analyzed. The average qCEST signal value of painful discs was significantly higher than non-painful discs (p = 0.012). The ratio between qCEST and normalized T2w was found to be significantly higher in painful discs compared to non-painful discs (p = 0.0022). A receiver operating characteristics (ROC) analysis indicated that qCEST/T2w ratio could be used to differentiate between painful and non-painful discs with 78% sensitivity and 81% specificity. The results of the study suggest that qCEST could be used for the diagnosis of discogenic pain, in conjunction with the commonly used T2w scan.

Analysis Protocol for the Quantification of Renal pH Using Chemical Exchange Saturation Transfer (CEST) MRI.

The kidney plays a major role in maintaining body pH homeostasis. Renal pH, in particular, changes immediately following injuries such as intoxication and ischemia, making pH an early biomarker for kidney injury before the symptom onset and complementary to well-established laboratory tests. Because of this, it is imperative to develop minimally invasive renal pH imaging exams and test pH as a new diagnostic biomarker in animal models of kidney injury before clinical translation. Briefly, iodinated contrast agents approved by the US Food and Drug Administration (FDA) for computed tomography (CT) have demonstrated promise as novel chemical exchange saturation transfer (CEST) MRI agents for pH-sensitive imaging. The generalized ratiometric iopamidol CEST MRI analysis enables concentration-independent pH measurement, which simplifies in vivo renal pH mapping. This chapter describes quantitative CEST MRI analysis for preclinical renal pH mapping, and their application in rodents, including normal conditions and acute kidney injury.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.

A deep learning approach for magnetization transfer contrast MR fingerprinting and chemical exchange saturation transfer imaging

Semisolid magnetization transfer contrast (MTC) and chemical exchange saturation transfer (CEST) MRI based on MT phenomenon have shown potential to evaluate brain development, neurological, psychiatric, and neurodegenerative diseases. However, a qualitative MT ratio (MTR) metric commonly used in conventional MTC imaging is limited in the assessment of quantitative semisolid macromolecular proton exchange rates and concentrations. In addition, CEST signals measured by MTR asymmetry analysis are unavoidably contaminated by upfield nuclear Overhauser enhancement (NOE) signals of mobile and semisolid macromolecules. To address these issues, we developed an MTC-MR fingerprinting (MTC-MRF) technique to quantify tissue parameters, which further allows an estimation of accurate MTC signals at a certain CEST frequency offset. A pseudorandomized RF saturation scheme was used to generate unique MTC signal evolutions for different tissues and a supervised deep neural network was designed to extract tissue properties from measured MTC-MRF signals. Through detailed Bloch equation-based digital phantom and in vivo studies, we demonstrated that the MTC-MRF can quantify MTC characteristics with high accuracy and computational efficiency, compared to a conventional Bloch equation fitting approach, and provide baseline reference signals for CEST and NOE imaging. For validation, MTC-MRF images were synthesized using the tissue parameters estimated from the deep-learning method and compared with experimentally acquired MTC-MRF images as the reference standard. The proposed MTC-MRF framework can provide quantitative 3D MTC, CEST, and NOE imaging of the human brain within a clinically acceptable scan time.

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer.

PurposeChemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low‐concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements.MethodsCEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two‐pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates.ResultsWhen all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis.ConclusionsThese results indicate that current practices of simultaneously fitting both CEST and MT effects in model‐based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.

Proton exchange in aqueous urea solutions measured by water-exchange (WEX) NMR spectroscopy and chemical exchange saturation transfer (CEST) imaging in vitro.

To characterize the proton exchange in aqueous urea solutions using a modified version of the WEX II filter at high magnetic field, and to assess the feasibility of performing quantitative urea CEST MRI on a 3T clinical MR system. In order to study the dependence of the exchange-rate constant of urea as a function of pH and T, the WEX-spectra were acquired at 600 MHz from urea solutions in a pH range from 6.4 to 8.0 and a temperature range from to . The CEST experiments were performed on a 3T MRI scanner by applying a train of 50 Gaussian-shaped pulses, each 100-millisecond long with a spacing of 100 milliseconds, for saturation. Exchange rates of urea were calculated using the (extended) AREX metric. The results showed that proton exchange in aqueous urea solutions is acid and base catalyzed with the rate constants: l/(mol·s) and l/(mol·s), respectively. Since the urea protons undergo a slow exchange with water protons, the CEST effect of urea can be observed efficiently at 3T. However, in neutral solutions the exchange rate of urea is minimal and cannot be estimated using the quantitative CEST approach. By means of the WEX-spectroscopy, the kinetic parameters of the proton exchange in urea solutions have been determined. It was also possible to estimate the exchange rates of urea in a broad range of pH values using the CEST method at a clinical scanner.

Analysis of chemical exchange saturation transfer contributions from brain metabolites to the Z-spectra at various field strengths and pH

Chemical exchange saturation transfer (CEST) exploits the chemical exchange of labile protons of an endogenous or exogenous compound with water to image the former indirectly through the water signal. Z-spectra of the brain have traditionally been analyzed for two most common saturation phenomena: downfield amide proton transfer (APT) and upfield nuclear Overhauser enhancement (NOE). However, a great body of brain metabolites, many of interest in neurology and oncology, contributes to the downfield saturation in Z-spectra. The extraction of these “hidden” metabolites from Z-spectra requires careful design of CEST sequences and data processing models, which is only possible by first obtaining CEST signatures of the brain metabolites possessing labile protons. In this work, we measured exchange rates of all major-for-CEST brain metabolites in the physiological pH range at 37 °C. Analysis of their contributions to Z-spectra revealed that regardless of the main magnetic field strength and pH, five main contributors, i.e. myo-inositol, creatine, phosphocreatine, glutamate, and mobile (poly)peptides, account for ca. 90% of downfield CEST effect. The fundamental CEST parameters presented in this study can be exploited in the design of novel CEST sequences and Z-spectra processing models, which will enable simultaneous and quantitative CEST imaging of multiple metabolites: multicolor CEST.

Molecular pain markers correlate with pH-sensitive MRI signal in a pig model of disc degeneration

Intervertebral disc (IVD) degeneration is a leading cause of chronic low back pain that affects millions of people every year. Yet identification of the specific IVD causing this pain is based on qualitative visual interpretation rather than objective findings. One possible approach to diagnosing pain-associated IVD could be to identify acidic IVDs, as decreased pH within an IVD has been postulated to mediate discogenic pain. We hypothesized that quantitative chemical exchange saturation transfer (qCEST) MRI could detect pH changes in IVDs, and thence be used to diagnose pathologically painful IVDs objectively and noninvasively. To test this hypothesis, a surgical model of IVD degeneration in Yucatan minipigs was used. Direct measurement of pH inside the degenerated IVDs revealed a significant drop in pH after degeneration, which correlated with a significant increase in the qCEST signal. Gene analysis of harvested degenerated IVDs revealed significant upregulation of pain-, nerve- and inflammatory-related markers after IVD degeneration. A strong positive correlation was observed between the expression of pain markers and the increase in the qCEST signal. Collectively, these findings suggest that this approach might be used to identify which IVD is causing low back pain, thereby providing valuable guidance for pain and surgical management.

Rapid and quantitative chemical exchange saturation transfer (CEST) imaging with magnetic resonance fingerprinting (MRF).

To develop a fast magnetic resonance fingerprinting (MRF) method for quantitative chemical exchange saturation transfer (CEST) imaging. We implemented a CEST-MRF method to quantify the chemical exchange rate and volume fraction of the Nα -amine protons of L-arginine (L-Arg) phantoms and the amide and semi-solid exchangeable protons of in vivo rat brain tissue. L-Arg phantoms were made with different concentrations (25-100 mM) and pH (pH 4-6). The MRF acquisition schedule varied the saturation power randomly for 30 iterations (phantom: 0-6 μT; in vivo: 0-4 μT) with a total acquisition time of ≤2 min. The signal trajectories were pattern-matched to a large dictionary of signal trajectories simulated using the Bloch-McConnell equations for different combinations of exchange rate, exchangeable proton volume fraction, and water T1 and T2 relaxation times. The chemical exchange rates of the Nα -amine protons of L-Arg were significantly (P < 0.0001) correlated with the rates measured with the quantitation of exchange using saturation power method. Similarly, the L-Arg concentrations determined using MRF were significantly (P < 0.0001) correlated with the known concentrations. The pH dependence of the exchange rate was well fit (R2 = 0.9186) by a base catalyzed exchange model. The amide proton exchange rate measured in rat brain cortex (34.8 ± 11.7 Hz) was in good agreement with that measured previously with the water exchange spectroscopy method (28.6 ± 7.4 Hz). The semi-solid proton volume fraction was elevated in white (12.2 ± 1.7%) compared to gray (8.1 ± 1.1%) matter brain regions in agreement with previous magnetization transfer studies. CEST-MRF provides a method for fast, quantitative CEST imaging.

PH-sensitive amide proton transfer effect dominates the magnetization transfer asymmetry contrast during acute ischemia-quantification of multipool contribution to in vivo CEST MRI.

To determine the origins of in vivo magnetization transfer asymmetry contrast during acute ischemic stroke, particularly in the diffusion lesion, perfusion lesion, and their mismatch using a middle cerebral artery occlusion rat model of acute stroke. Adult male Wistar rats underwent multiparametric MRI of diffusion, perfusion, T1 , and amide proton transfer (APT) imaging at 4.7 T following a middle cerebral artery occlusion procedure. A multipool Lorentzian model, including the nuclear Overhauser effect, magnetization transfer, direct water saturation, amine and amide chemical exchange saturation transfer effects, was applied for Z-spectrum fitting to determine the sources of in vivo magnetization transfer asymmetry following acute stroke. We showed that changes in amine chemical exchange saturation transfer (2 ppm) and APT (3.5 ppm) effects, particularly the APT MRI effect, dominate the commonly used magnetization transfer asymmetry analysis and hence confer pH sensitivity to APT imaging of acute stroke. Also, the nuclear Overhauser effect and magnetization transfer show small changes that counteracted each other, contributing less than 0.3% to magnetization transfer asymmetry at 3.5 ppm. Moreover, we showed that diffusion lesion had worsened acidosis from perfusion/diffusion lesion mismatch (P < 0.05). The study complements recent in vivo quantitative chemical exchange saturation transfer work to shed light on the sensitivity and specificity of endogenous APT MRI to tissue acidosis. Magn Reson Med 79:1602-1608, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

QUESP and QUEST revisited - fast and accurate quantitative CEST experiments.

Chemical exchange saturation transfer (CEST) NMR or MRI experiments allow detection of low concentrated molecules with enhanced sensitivity via their proton exchange with the abundant water pool. Be it endogenous metabolites or exogenous contrast agents, an exact quantification of the actual exchange rate is required to design optimal pulse sequences and/or specific sensitive agents. Refined analytical expressions allow deeper insight and improvement of accuracy for common quantification techniques. The accuracy of standard quantification methodologies, such as quantification of exchange rate using varying saturation power or varying saturation time, is improved especially for the case of nonequilibrium initial conditions and weak labeling conditions, meaning the saturation amplitude is smaller than the exchange rate (γB1 < k). The improved analytical 'quantification of exchange rate using varying saturation power/time' (QUESP/QUEST) equations allow for more accurate exchange rate determination, and provide clear insights on the general principles to execute the experiments and to perform numerical evaluation. The proposed methodology was evaluated on the large-shift regime of paramagnetic chemical-exchange-saturation-transfer agents using simulated data and data of the paramagnetic Eu(III) complex of DOTA-tetraglycineamide. The refined formulas yield improved exchange rate estimation. General convergence intervals of the methods that would apply for smaller shift agents are also discussed. Magn Reson Med 79:1708-1721, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Balanced Steady-State Free Precession (bSSFP) from an effective field perspective: Application to the detection of chemical exchange (bSSFPX)

Chemical exchange saturation transfer (CEST) is a novel contrast mechanism and it is gaining increasing popularity as many promising applications have been proposed and investigated. Fast and quantitative CEST imaging techniques are further needed in order to increase the applicability of CEST for clinical use as well as to derive quantitative physiological and biological information. Steady-state methods for fast CEST imaging have been reported recently. Here, we observe that an extreme case of these methods is a balanced steady-state free precession (bSSFP) sequence. The bSSFP in itself is sensitive to the exchange processes; hence, no additional saturation or preparation is needed for CEST-like data acquisition. The bSSFP experiment can be regarded as observation during saturation, without separate saturation and acquisition modules as used in standard CEST and similar experiments. One of the differences from standard CEST methods is that the bSSFP spectrum is an XY-spectrum not a Z-spectrum. As the first proof-of-principle step, we have implemented the steady-state bSSFP sequence for chemical exchange detection (bSSFPX) and verified its feasibility in phantom studies. These studies have shown that bSSFPX can achieve exchange-mediated contrast comparable to the standard CEST experiment. Therefore, the bSSFPX method has a potential for fast and quantitative CEST data acquisition.