Semi-solid Magnetization Transfer Research Articles

Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation.

To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5). 95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation. The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001). Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.

CEST and nuclear Overhauser enhancement imaging withdeep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility andreliability studies.

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

Dynamic and rapid deep synthesis of chemical exchange saturation transfer and semisolid magnetization transfer MRI signals

Model-driven analysis of biophysical phenomena is gaining increased attention and utility for medical imaging applications. In magnetic resonance imaging (MRI), the availability of well-established models for describing the relations between the nuclear magnetization, tissue properties, and the externally applied magnetic fields has enabled the prediction of image contrast and served as a powerful tool for designing the imaging protocols that are now routinely used in the clinic. Recently, various advanced imaging techniques have relied on these models for image reconstruction, quantitative tissue parameter extraction, and automatic optimization of acquisition protocols. In molecular MRI, however, the increased complexity of the imaging scenario, where the signals from various chemical compounds and multiple proton pools must be accounted for, results in exceedingly long model simulation times, severely hindering the progress of this approach and its dissemination for various clinical applications. Here, we show that a deep-learning-based system can capture the nonlinear relations embedded in the molecular MRI Bloch–McConnell model, enabling a rapid and accurate generation of biologically realistic synthetic data. The applicability of this simulated data for in-silico, in-vitro, and in-vivo imaging applications is then demonstrated for chemical exchange saturation transfer (CEST) and semisolid macromolecule magnetization transfer (MT) analysis and quantification. The proposed approach yielded 63–99% acceleration in data synthesis time while retaining excellent agreement with the ground truth (Pearson’s r > 0.99, p < 0.0001, normalized root mean square error < 3%).

Noninvasive Characterization of Metabolic Changes in Ischemic Stroke Using Z-spectrum-fitted Multiparametric Chemical Exchange Saturation Transfer-weighted Magnetic Resonance Imaging.

This study aimed to noninvasively characterize the metabolic alterations in ischemic brain tissues using Z-spectrum-fitted multiparametric chemical exchange saturation transfer-weighted magnetic resonance imaging (CEST-MRI). Three sets of Z-spectrum data with saturation power (B1) values of 1.5, 2.5, and 3.5 µT, respectively, were acquired from 17 patients with ischemic stroke. Multiple contrasts contributing to the Z-spectrum, including fitted amide proton transfer (APTfitted), +2 ppm peak (CEST@2ppm), concomitantly fitted APTfitted and CEST@2ppm (APT&CEST@2ppm), semisolid magnetization transfer contrast (MT), aliphatic nuclear Overhauser effect (NOE), and direct saturation of water (DSW), were fitted with 4 and 5 Lorentzian functions, respectively. The CEST metrics were compared between ischemic lesions and contralateral normal white matter (CNWM), and the correlation between the CEST metrics and the apparent diffusion coefficient (ADC) was assessed. The differences in the Z-spectrum metrics under varied B1 values were also investigated. Ischemic lesions showed increased APTfitted, CEST@2ppm, APT&CEST@2ppm, NOE, and DSW as well as decreased MT. APT&CEST@2ppm, MT, and DSW showed a significant correlation with ADC [APT&CEST@2ppm at the 3 B1 values: R=0.584/0.467/0.551; MT at the 3 B1 values: R=-0.717/-0.695/-0.762 (4-parameter fitting), R=-0.734/-0.711/-0.785 (5-parameter fitting); DSW of 4-/5-parameter fitting: R=0.794/0.811 (2.5 µT), R=0.800/0.790 (3.5 µT)]. However, the asymmetric analysis of amide proton transfer (APTasym) could not differentiate the lesions from CNWM and showed no correlation with ADC. Furthermore, the Z-spectrum contrasts varied with B1. The Z-spectrum-fitted multiparametric CEST-MRI can comprehensively detect metabolic alterations in ischemic brain tissues.

Post-Surgical Depositions of Blood Products Are No Major Confounder for the Diagnostic and Prognostic Performance of CEST MRI in Patients with Glioma.

Amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) imaging can predict clinical outcomes in patients with glioma. However, the treatment of brain tumors is accompanied by the deposition of blood products within the tumor area in most cases. For this reason, the objective was to assess whether the diagnostic interpretation of the APT and ssMT is affected by methemoglobin (mHb) and hemosiderin (Hs) depositions at the first follow-up MRI 4 to 6 weeks after the completion of radiotherapy. A total of 34 participants underwent APT and ssMT imaging by applying reconstruction methods described by Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT and MTRRexMT) and Mehrabian et al. (MTconst). Contrast-enhancing tumor (CE), whole tumor (WT), mHb and Hs were segmented on contrast-enhanced T1wCE, T2w-FLAIR, T1w and T2*w images. ROC-analysis, Kaplan-Meier analysis and the log rank test were used to test for the association of mean contrast values with therapy response and overall survival (OS) before (WT and CE) and after correcting tumor volumes for mHb and Hs (CEC and WTC). CEC showed higher associations of the MTRRexMT with therapy response (CE: AUC = 0.677, p = 0.081; CEC: AUC = 0.705, p = 0.044) and of the APTwasym with OS (CE: HR = 2.634, p = 0.040; CEC: HR = 2.240, p = 0.095). In contrast, WTC showed a lower association of the APTwasym with survival (WT: HR = 2.304, p = 0.0849; WTC: HR = 2.990, p = 0.020). Overall, a sophisticated correction for blood products did not substantially influence the clinical performance of APT and ssMT imaging in patients with glioma early after radiotherapy.

Comparison of model-free Lorentzian and spinlock model-based fittings in quantitative CEST imaging ofacutestroke.

CEST MRI detects complex tissue changes following acute stroke. Our study aimed to test if spinlock model-based fitting of the quasi-steady-state (QUASS)-reconstructed equilibrium CEST MRI improves the determination of multi-pool signal changes over the commonly-used model-free Lorentzian fitting in acute stroke. Multiple three-pool CEST Z-spectra were simulated using Bloch-McConnell equations for a range of T1 , relaxation delay, and saturation times. The multi-pool CEST signals were solved from the simulated Z-spectra to test the accuracy of routine Lorentzian (model-free) and spinlock (model-based) fittings without and with QUASS reconstruction. In addition, multiparametric MRI scans were obtained in rat models of acute stroke, including relaxation, diffusion, and CEST Z-spectrum. Finally, we compared model-free and model-based per-pixel CEST quantification in vivo. The spinlock model-based fitting of QUASS CEST MRI provided a nearly T1 -independent determination of multi-pool CEST signals, advantageous over the fittings of apparent CEST MRI (model-free and model-based). In vivo data also demonstrated that the spinlock model-based QUASS fitting captured significantly different changes in semisolid magnetization transfer (-0.9 ± 0.8 vs. 0.3 ± 0.8%), amide (-1.1 ± 0.4 vs. -0.5 ± 0.2%), and guanidyl (1.0 ± 0.4 vs. 0.7 ± 0.3%) signals over the model-free Lorentzian analysis. Our study demonstrated that spinlock model-based fitting of QUASS CEST MRI improved the determination of the underlying tissue changes following acute stroke, promising further clinical translation of quantitative CEST imaging.

Semi-solid MT and APTw CEST-MRI predict clinical outcome of patients with glioma early after radiotherapy.

The purpose of this study was to compare the potential of asymmetry-based (APTwasym ), Lorentzian-fit-based (PeakAreaAPT and MTconst ), and relaxation-compensated (MTRRex APT and MTRRex MT) CEST contrasts of the amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) for early response assessment and prediction of progression-free survival (PFS) in patients with glioma. Seventy-two study participants underwent CEST-MRI at 3T from July 2018 to December 2021 in a prospective clinical trial four to 6 wk after the completion of radiotherapy for diffuse glioma. Tumor segmentations were performed on T2w -FLAIR and contrast-enhanced T1w images. Therapy response assessment and determination of PFS were performed according to response assessment in neuro oncology (RANO) criteria using clinical follow-up data with a median observation time of 9.2 mo (range, 1.6-40.8) and compared to CEST MRI metrics. Statistical testing included receiver operating characteristic analyses, Mann-Whitney-U-test, Kaplan-Meier analyses, and logrank-test. MTconst (AUC = 0.79, p < 0.01) showed a stronger association with RANO response assessment compared to PeakAreaAPT (AUC = 0.71, p = 0.02) and MTRRex MT (AUC = 0.71, p = 0.02), and enabled differentiation of participants with pseudoprogression (n = 8) from those with true progression (AUC = 0.79, p = 0.02). Furthermore, MTconst (HR = 3.04, p = 0.01), PeakAreaAPT (HR = 0.39, p = 0.03), and APTwasym (HR = 2.63, p = 0.02) were associated with PFS. MTRRex APT was not associated with any outcome. MTconst , PeakAreaAPT, and APTwasym imaging predict clinical outcome by means of progression-free survival. Furthermore, MTconst enables differentiation of radiation-induced pseudoprogression from disease progression. Therefore, the assessed metrics may have synergistic potential for supporting clinical decision making during follow-up of patients with glioma.

Isolation of amide proton transfer effect and relayed nuclear Overhauser enhancement effect at -3.5ppm using CEST with double saturation powers.

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

CEST imaging of the APT and ssMT predict the overall survival of patients with glioma at the first follow-up after completion of radiotherapy at 3T

Background and purposeOutcome prediction of patients with glioma early after the completion of radiotherapy represents a major clinical challenge. Previously, the prognostic value of chemical exchange saturation transfer (CEST) imaging has been demonstrated in patients with newly diagnosed glioma. The objective of this study was to assess the potential of amide proton transfer (APT)-, relayed nuclear Overhauser effect (rNOE)- and semi-solid magnetization transfer (ssMT)-imaging according to Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT, MTRRexNOE and MTRRexMT) and Mehrabian et al. (PeakAreaAPT, PeakAreaNOE and MTconst) for the prognostication of the overall survival (OS) of patients with glioma at the first follow-up after the completion of radiotherapy. Materials and Methods49 of 72 participants with diffuse glioma, who underwent CEST MRI at 3T between July 2018 and December 2021 4 to 6 weeks after the completion of radiotherapy, were analyzed. Contrast-enhancing tumor (CE) and whole tumor (WT) volumes were segmented on T2w-FLAIR and contrast-enhanced T1w images. Kaplan-Meier analysis and logrank-test were used for statistical analyses. ResultsAPTw imaging demonstrated the strongest association with OS (HR = 4.66, p < 0.001). The MTconst (HR = 2.54, p = 0.044) was associated with the OS of participants with residual contrast-enhancing glioma tissue, whilst the MTRRexAPT (HR = 2.44, p = 0.056) showed a trend in this sub-cohort. The MTRRexNOE, MTRRexMT and PeakAreaNOE were not associated with survival. ConclusionImaging of the APT and ssMT at the first follow-up 4 to 6 weeks after the completion of radiotherapy at 3T were associated with the overall survival of study participants with glioma.

Numerical fitting of Extrapolated semisolid Magnetization transfer Reference (NEMR) signals: Improved detection of ischemic stroke.

To propose a novel Numerical fitting method of the Extrapolated semisolid Magnetization transfer Reference (NEMR) signal for quantifying the CEST effect. Modified two-pool Bloch-McConnell equations were used to numerically fit the magnetization transfer (MT) and direct water saturation (DS) signals at far off-resonance frequencies, which was subsequently extrapolated into the frequency range of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) pools. Then the subtraction of the fitted two-pool z-spectrum and the experimentally acquired z-spectrum yielded APT# and NOE# signals mostly free of MT and DS contamination. Several strategies were used to accelerate the NEMR fitting. Furthermore, the proposed NEMR method was compared with the conventional extrapolated semisolid magnetization transfer reference (EMR) and magnetization transfer ratio asymmetry (MTRasym ) methods in simulations and stroke patients. The combination of RF downsampling, MT lineshape look-up table, and conversion of MATLAB code to C code accelerated the NEMR fitting by over 2700-fold. Monte-Carlo simulations showed that NEMR had higher accuracy than EMR and eliminated the requirement of the steady-state condition. In ischemic stroke patients, the NEMR maps at 1 μT removed hypointense artifacts seen on EMR and MTRasym images, and better depicted stroke lesions than EMR. For NEMR, NOE# yielded significantly (p < 0.05) stronger signal contrast between stroke and normal tissues than APT# at 1 μT. The proposed NEMR method is suitable for arbitrary saturation settings and can remove MT and DS contamination from the CEST signal for improved detection of ischemic stroke.

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

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

Generalization of quasi-steady-state reconstruction to CEST MRI with two-tiered RF saturation and gradient-echo readout-Synergistic nuclear Overhauser enhancement contribution to brain tumor amide proton transfer-weighted MRI.

While amide proton transfer-weighted (APTw) MRI has been adopted in tumor imaging, there are concurrent APT, magnetization transfer, and nuclear Overhauser enhancement changes. Also, the APTw image is confounded by relaxation changes, particularly when the relaxation delay and saturation time are not sufficiently long. Our study aimed to extend a quasi-steady-state (QUASS) solution to determine the contribution of the multipool CEST signals to the observed tumor APTw contrast. Our study derived the QUASS solution for a multislice CEST-MRI sequence with an interleaved RF saturation and gradient-echo readout between signal averaging. Multiparametric MRI scans were obtained in rat brain tumor models, including T1 , T2 , diffusion, and CEST scans. Finally, we performed spinlock model-based multipool fitting to determine multiple concurrent CEST signal changes in the tumor. The QUASS APTw MRI showed small but significant differences in normal and tumor tissues and their contrast from the acquired asymmetry calculation. The spinlock model-based fitting showed significant differences in semisolid magnetization transfer, amide, and nuclear Overhauser enhancement effects between the apparent and QUASS CEST MRI. In addition, we determined that the tumor APTw contrast is due to synergistic APT increase (+3.5ppm) and NOE decrease (-3.5ppm), with their relative contribution being about one third and two thirds under a moderate B1 of 0.75 μT at 4.7 T. Our study generalized QUASS analysis to gradient-echo image readout and quantified the underlying tumor CEST signal changes, providing an improved elucidation of the commonly used APTw MRI.

A comparative study of quantitative metrics in chemical exchange saturation transfer imaging for grading gliomas in adults

PurposeTo evaluate the performance of different chemical exchange saturation transfer (CEST) metrics for grading gliomas with semiautomatically defined regions of interest (ROIs). MethodsThirty-eight adult subjects were included, including 23 high-grade gliomas and 15 low-grade gliomas confirmed by histopathology. The B0-corrected CEST z-spectra were first calculated with magnetization transfer ratio asymmetry (MTRasym) analysis at frequency offsets of 3.5, 3, 2.5, 2, 1.5, and 1 ppm to obtain the fit-free metrics and subsequently fitted with three Lorentzian functions denoting direct water saturation (DS), amide proton transfer (APT), and combined semisolid magnetization transfer and nuclear Overhauser enhancement (MT & NOE) effects to derive the fit-based metrics. Wilcoxon rank-sum test was performed to determine if a statistically significant difference was present in the CEST metrics between low- and high-grade gliomas. Receiver operating characteristic (ROC) curves were used to evaluate the differentiation of CEST metrics between low- and high-grade gliomas. Pearson correlation coefficients were employed to evaluate the correlations of CEST metrics. ResultsFor the fit-free metrics, the highest areas under the curve (AUCs) of 0.85, 0.88, and 0.88, corresponding to MTRasym, MTRnormref (normalization by the reference scan), and MTRRex (subtraction of inverse z-spectra), respectively, were obtained at 3 ppm across various frequency offsets. In addition, the AUCs generated from the fit-based metrics (0.88–0.90) were higher than those generated from the fit-free metrics at 3 ppm. ConclusionThe results of this preliminary study indicate that fit-free CEST metrics at 3 ppm are superior to the other frequency offsets for grading human brain gliomas. The fit-based metrics manifested improved differentiation between low- and high-grade gliomas compared to the fit-free CEST metrics.

Relaxation-Compensated Chemical Exchange Saturation Transfer MRI in the Brain at 7T: Application in Relapsing-Remitting Multiple Sclerosis.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) can probe tissue biochemistry in vivo with high resolution and sensitivity without requiring exogenous contrast agents. Applying CEST MRI at ultrahigh field provides advantages of increasing spectral resolution and improving sensitivity to metabolites with faster proton exchange rates such as glutamate, a critical neurotransmitter in the brain. Prior magnetic resonance spectroscopy and CEST MRI studies have revealed altered regulation of glutamate in patients with multiple sclerosis (MS). While CEST imaging facilitates new strategies for investigating the pathology underlying this complex and heterogeneous neurological disease, CEST signals are contaminated or diluted by concurrent effects (e.g., semi-solid magnetization transfer (MT) and direct water saturation) and are scaled by the T1 relaxation time of the free water pool which may also be altered in the context of disease. In this study of 20 relapsing-remitting MS patients and age- and sex-matched healthy volunteers, glutamate-weighted CEST data were acquired at 7.0 T. A Lorentzian fitting procedure was used to remove the asymmetric MT contribution from CEST z-spectra, and the apparent exchange-dependent relaxation (AREX) correction was applied using an R1 map derived from an inversion recovery sequence to further isolate glutamate-weighted CEST signals from concurrent effects. Associations between AREX and cognitive function were examined using the Minimal Assessment of Cognitive Function in MS battery. After isolating CEST effects from MT, direct water saturation, and T1 effects, glutamate-weighted AREX contrast remained higher in gray matter than in white matter, though the difference between these tissues decreased. Glutamate-weighted AREX in normal-appearing gray and white matter in MS patients did not differ from healthy gray and white matter but was significantly elevated in white matter lesions. AREX in some cortical regions and in white matter lesions correlated with disability and measures of cognitive function in MS patients. However, further studies with larger sample sizes are needed to confirm these relationships due to potential confounding effects. The application of MT and AREX corrections in this study demonstrates the importance of isolating CEST signals for more specific characterization of the contribution of metabolic changes to tissue pathology and symptoms in MS.

Chemical exchange saturation transfer imaging of creatine, phosphocreatine, and protein arginine residue in tissues.

Chemical exchange saturation transfer (CEST) MRI has become a promising technique to assay target proteins and metabolites through their exchangeable protons, noninvasively. The ubiquity of creatine (Cr) and phosphocreatine (PCr) due to their pivotal roles in energy homeostasis through the creatine phosphate pathway has made them prime targets for CEST in the diagnosis and monitoring of disease pathologies, particularly in tissues heavily dependent on the maintenance of rich energy reserves. Guanidinium CEST from protein arginine residues (i.e. arginine CEST) can also provide information about the protein profile in tissue. However, numerous obfuscating factors stand as obstacles to the specificity of arginine, Cr, and PCr imaging through CEST, such as semisolid magnetization transfer, fast chemical exchanges such as primary amines, and the effects of nuclear Overhauser enhancement from aromatic and amide protons. In this review, the specific exchange properties of protein arginine residues, Cr, and PCr, along with their validation, are discussed, including the considerations necessary to target and tune their signal effects through CEST imaging. Additionally, strategies that have been employed to enhance the specificity of these exchanges in CEST imaging are described, along with how they have opened up possible applications of protein arginine residues, Cr and PCr CEST imaging in the study and diagnosis of pathology. A clear understanding of the capabilities and caveats of using CEST to image these vital metabolites and mitigation strategies is crucial to expanding the possibilities of this promising technology.

Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients

To comprehensively and noninvasively risk-stratify glioma grade, isocitrate dehydrogenase (IDH) genotype, and 1p/19q codeletion status using multi-contrast Z-spectral magnetic resonance imaging (MRI). One hundred and thirteen patients with glioma were retrospectively included. Multiple contrasts contributing to Z-spectra, including direct saturation of water (DSW), semi-solid magnetization transfer contrast (MTC), amide proton transfer (APT) effect, aliphatic nuclear Overhauser effect, and the 2-ppm chemical exchange saturation transfer peak (CEST@2ppm), were fitted with five individual Lorentzian functions. Z-spectral contrasts were compared according to the three most important risk stratifications: tumor grade, IDH genotype, and 1p/19q codeletion status. We further investigated the differentiation of 1p/19q codeletion status within IDH mutant gliomas. The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic (ROC) analyses. DSW was significantly different within grade, IDH genotypes, and 1p/19q codeletion status. APT was significantly different with grade and IDH mutation, but not with 1p/19q subtypes. CEST@2ppm was only significantly different with 1p/19q codeletion subtypes. DSW and CEST@2ppm were the two Z-spectral contrasts able to differentiate 1p/19q codeletion subtypes within IDH mutant gliomas. For differentiating glioma grades using ROC analyses, DSW achieved the largest AUC. For differentiating IDH genotypes, DSW and APT achieved comparable AUCs. DSW was the best metric for differentiating 1p/19q codeletion status within all patients and within the IDH mutant patients. Combining all Z-spectral contrasts improved sensitivity and specificity for all risk stratifications. Multi-parametric Z-spectral MRI serves as a useful, comprehensive, and noninvasive imaging technique for glioma stratification in clinical patients. • Multiple contrasts contributing to Z-spectra were separately fitted with Lorentzian functions. • Z-spectral contrasts were compared within the three most important and common tumor risk stratifications for gliomas: tumor grade, IDH genotype, and 1p/19q codeletion status. • The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic analyses, which found Z-spectral MRI to be a useful and comprehensive imaging biomarker for glioma stratification.

Brain tissues have single-voxel signatures in multi-spectral MRI

Since the seminal works by Brodmann and contemporaries, it is well-known that different brain regions exhibit unique cytoarchitectonic and myeloarchitectonic features. Transferring the approach of classifying brain tissues – and other tissues – based on their intrinsic features to the realm of magnetic resonance (MR) is a longstanding endeavor. In the 1990s, atlas-based segmentation replaced earlier multi-spectral classification approaches because of the large overlap between the class distributions. Here, we explored the feasibility of performing global brain classification based on intrinsic MR features, and used several technological advances: ultra-high field MRI, q-space trajectory diffusion imaging revealing voxel-intrinsic diffusion properties, chemical exchange saturation transfer and semi-solid magnetization transfer imaging as a marker of myelination and neurochemistry, and current neural network architectures to analyze the data. In particular, we used the raw image data as well to increase the number of input features. We found that a global brain classification of roughly 97 brain regions was feasible with gross classification accuracy of 60%; and that mapping from voxel-intrinsic MR data to the brain region to which the data belongs is possible. This indicates the presence of unique MR signals of different brain regions, similar to their cytoarchitectonic and myeloarchitectonic fingerprints.

Characterization of microenvironmental changes in the intervertebral discs of patients with chronic low back pain using multiparametric MRI contrasts extracted from Z-spectrum

Z-spectral MRI data were analyzed to produce multiparametric metabolic and microenvironmental contrasts for identifying intervertebral discs with/without pain symptom and sore pain. Z-spectra data were collected from the lumbar discs of 26 patients with non-specific chronic low bck pain (CLBP) and 21 asymptomatic controls (AC) with a chemical exchange saturation transfer (CEST). Data were fitted to quantify the CEST effects from glycosaminoglycan, amide proton transfer (APT), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer contrast effects, and the direct saturation of water. Multiparametric maps were computed from the fitted peak amplitudes, and the average values were calculated from all five lumber discs. Those parameters were compared between the CLBP and AC groups and between the subgroups with and without (Nsore) sore pain. The discs in symptomatic patients have lower water content, collagen-bound water and collagen than the discs in AC (P < 0.05). Additionally, Z-sepctral MRI indicated that the discs in the sore subgroup had less water, collagen-bound water and collagen, and likely lower pH compared to the Nsore subgroup (P < 0.05). Lower pH as measured with reduced APT and NOE effects may be an important pathological factor causing sore pain of the back. Z-spectral MRI with its multiparametric metabolic and microenvironmental contrasts has been demonstrated to identify discs with and without pain symptom or sore pain, providing more important information of CLBP.

Sensitivity and specificity of CEST and NOE MRI in injured spinal cord in monkeys

PurposeThe sensitivity and accuracy of chemical exchange saturation transfer (CEST) and nuclear Overhauser enhancement (NOE) effects for assessing injury-associated changes in cervical spinal cords were evaluated in squirrel monkeys. Multiple interacting pools of protons, including one identified by an NOE at −1.6 ppm relative to water (NOE(-1.6)), were derived and quantified from fitting proton Z-spectra. The effects of down-sampled data acquisitions and corrections for non-specific factors including T1, semi-solid magnetization transfer, and direct saturation of free water (DS), were investigated. The overall goal is to develop a protocol for rapid data acquisition for assessing the molecular signatures of the injured spinal cord and its surrounding regions. MethodsMRI scans were recorded of anesthetized squirrel monkeys at 9.4 T, before and after a unilateral dorsal column sectioning of the cervical spinal cord. Z-spectral images at 51 different RF offsets were acquired. The amplitudes of CEST and NOE effects from multiple proton pools were quantified using a six-pool Lorenzian fitting of each Z-spectrum (MTRmfit). In addition, down-sampled data using reduced selections of RF offsets were analyzed and compared. An apparent exchange-dependent relaxation (AREXmfit) method was also used to correct for non-specific factors in quantifying regional spectra around lesion sites. ResultsThe parametric maps from multi-pool fitting using the complete sampling data (P51e) detected unilateral changes at and around the injury. The maps derived from selected twofold down-sampled data with appropriate interpolation (P26sI51) revealed quite similar spatial distributions of different pools as those obtained using P51e at each resonance shift. Across 10 subjects, both data acquisition schemes detected significant decreases in NOE(-3.5) and NOE(-1.6) and increases in DS(0.0) and CEST(3.5) at the lesion site relative to measures of the normal tissues before injury. AREXmfit of cysts and other abnormal tissues at and around the lesion site also exhibited significant changes, especially at 3.5, −1.6 and −3.5 ppm RF offsets. ConclusionThese results confirm that a reduced set of RF offsets and down sampling are adequate for CEST imaging of injured spinal cord and allow shorter imaging times and/or permit additional signal averaging. AREXmfit correction improved the accuracy of CEST and NOE measures. The results provide a rapid (~13 mins), sensitive, and accurate protocol for deriving multiple NOE and CEST effects simultaneously in spinal cord imaging at high field.

Novel proton exchange rate MRI presents unique contrast in brains of ischemic stroke patients

BackgroundTo map and quantify the proton exchange rate (kex) of brain tissues using improved omega plots in ischemic stroke patients and to investigate whether kex can serve as a potential endogenous surrogate imaging biomarker for detecting the metabolic state and the pathologic changes due to ischemic stroke. New MethodThree sets of Z-spectra were acquired from seventeen ischemic stroke patients using a spin echo-echo planar imaging sequence with pre-saturation chemical exchange saturation transfer (CEST) pulse at B1 of 1.5, 2.5, and 3.5 μT, respectively. Pixel-wise kex was calculated from improved omega plot of water direct saturation (DS)-removed Z-spectral signals. ResultsThe derived kex maps can differentiate infarcts from contralateral normal brain tissues with significantly increased signal (893 ± 52 s-1vs. 739 ± 34 s-1, P < 0.001). Comparison with Existing Method(s)The kex maps were found to be different from conventional contrasts from diffusion-weighted imaging (DWI), CEST, and semi-solid magnetization transfer (MT) MRI. In brief, kex MRI showed larger lesion areas than DWI with different degrees and different lesion contrast compared to CEST and MT. ConclusionsIn this preliminary translational research, the kex MRI based on DS-removed omega plots has been demonstrated for in vivo imaging of clinical ischemic stroke patients. As a noninvasive and unique MRI contrast, kex MRI at 3 T may serve as a potential surrogate imaging biomarker for the metabolic changes of stroke and help for monitoring the evolution and the treatment of stroke.