Quantitative chemical exchange saturation transfer (qCEST) MRI – omega plot analysis of RF‐spillover‐corrected inverse CEST ratio asymmetry for simultaneous determination of labile proton ratio and exchange rate

Chemical exchange saturation transfer (CEST) MRI is sensitive to labile proton concentration and exchange rate, thus allowing measurement of dilute CEST agent and microenvironmental properties. However, CEST measurement depends not only on the CEST agent properties but also on the experimental conditions. Quantitative CEST (qCEST) analysis has been proposed to address the limitation of the commonly used simplistic CEST‐weighted calculation. Recent research has shown that the concomitant direct RF saturation (spillover) effect can be corrected using an inverse CEST ratio calculation. We postulated that a simplified qCEST analysis is feasible with omega plot analysis of the inverse CEST asymmetry calculation. Specifically, simulations showed that the numerically derived labile proton ratio and exchange rate were in good agreement with input values. In addition, the qCEST analysis was confirmed experimentally in a phantom with concurrent variation in CEST agent concentration and pH. Also, we demonstrated that the derived labile proton ratio increased linearly with creatine concentration (P < 0.01) while the pH‐dependent exchange rate followed a dominantly base‐catalyzed exchange relationship (P < 0.01). In summary, our study verified that a simplified qCEST analysis can simultaneously determine labile proton ratio and exchange rate in a relatively complex in vitro CEST system. Copyright © 2015 John Wiley & Sons, Ltd.     

Accuracy in the quantification of chemical exchange saturation transfer (CEST) and relayed nuclear Overhauser enhancement (rNOE) saturation transfer effects

Accurate quantification of chemical exchange saturation transfer (CEST) effects, including dipole–dipole mediated relayed nuclear Overhauser enhancement (rNOE) saturation transfer, is important for applications and studies of molecular concentration and transfer rate (and thereby pH or temperature). Although several quantification methods, such as Lorentzian difference (LD) analysis, multiple‐pool Lorentzian fits, and the three‐point method, have been extensively used in several preclinical and clinical applications, the accuracy of these methods has not been evaluated. Here we simulated multiple‐pool Z spectra containing the pools that contribute to the main CEST and rNOE saturation transfer signals in the brain, numerically fit them using the different methods, and then compared their derived CEST metrics with the known solute concentrations and exchange rates. Our results show that the LD analysis overestimates contributions from amide proton transfer (APT) and intermediate exchanging amine protons; the three‐point method significantly underestimates both APT and rNOE saturation transfer at ?3.5 ppm (NOE(?3.5)). The multiple‐pool Lorentzian fit is more accurate than the other two methods, but only at lower irradiation powers (≤1 μT at 9.4 T) within the range of our simulations. At higher irradiation powers, this method is also inaccurate because of the presence of a fast exchanging CEST signal that has a non‐Lorentzian lineshape. Quantitative parameters derived from in vivo images of rodent brain tumor obtained using an irradiation power of 1 μT were also compared. Our results demonstrate that all three quantification methods show similar contrasts between tumor and contralateral normal tissue for both APT and the NOE(?3.5). However, the quantified values of the three methods are significantly different. Our work provides insight into the fitting accuracy obtainable in a complex tissue model and provides guidelines for evaluating other newly developed quantification methods.     

CEST MRI of sepsis‐induced acute kidney injury

Sepsis‐induced acute kidney injury (SAKI) is a major complication of kidney disease associated with increased mortality and faster progression. Therefore, the development of imaging biomarkers to detect septic AKI is of great clinical interest. In this study, we aimed to characterize the endogenous chemical exchange saturation transfer (CEST) MRI contrast in the lipopolysaccharide (LPS)‐induced SAKI mouse model and to investigate the use of CEST MRI for detecting such injury. We used a SAKI mouse model that was generated by i.p. injection of 10 mg/kg LPS. The resulting kidney injury was confirmed by the elevation of serum creatinine and histology. MRI assessments were performed 24 h after LPS injection, including CEST MRI at different B₁ strengths (1, 1.8 and 3 μT), T₁ mapping, T₂ mapping and conventional magnetization transfer contrast (MTC) MRI. The CEST MRI results were analyzed using Z‐spectra, in which the normalized water signal saturation (S_sat/S₀) is measured as a function of saturation frequency. Substantial decreases in CEST contrast were observed at both 3.5 and ? 3.5 ppm frequency offset from water at all B₁ powers, with the most significant difference obtained at a B₁ of 1.8 μT. The average S_sat/S₀ differences between injured and normal kidneys were 0.07 (0.55 ± 0.04 versus 0.62 ± 0.04, P = 0.0028) and 0.07 (0.50 ± 0.04 versus 0.57 ± 0.03, P = 0.0008) for 3.5 and ? 3.5 ppm, respectively. In contrast, the T₁ and T₂ relaxation times and MTC contrast in the injured kidneys did not show a significant change compared with the normal control. Our results showed that CEST MRI is more sensitive to the pathological changes in injured kidneys than the changes in T₁, T₂ and MTC effect, indicating its potential clinical utility for molecular imaging of renal diseases.     

Aggregation‐induced changes in the chemical exchange saturation transfer (CEST) signals of proteins

Chemical exchange saturation transfer (CEST) is an MRI technique that allows mapping of biomolecules (small metabolites, proteins) with nearly the sensitivity of conventional water proton MRI. In living organisms, several tissue‐specific CEST effects have been observed and successfully applied to diagnostic imaging. In these studies, particularly the signals of proteins showed a distinct correlation with pathological changes. However, as CEST effects depend on various properties that determine and affect the chemical exchange processes, the origins of the observed signal changes remain to be understood. In this study, protein aggregation was identified as an additional process that is encoded in the CEST signals of proteins. Investigation of distinct proteins that are involved in pathological disorders, namely amyloid beta and huntingtin, revealed a significant decrease of all protein CEST signals upon controlled aggregation. This finding is of particular interest with regard to diagnostic imaging of patients with neurodegenerative diseases that involve amyloidogenesis, such as Alzheimer's or Huntington's disease. To investigate whether the observed CEST signal decrease also occurs in heterogeneous mixtures of aggregated cellular proteins, and thus prospectively in tissue, heat‐shocked yeast cell lysates were employed. Additionally, investigation of different cell compartments verified the assignment of the protein CEST signals to the soluble part of the proteome. The results of in vitro experiments demonstrate that aggregation affects the CEST signals of proteins. This observation can enable hypotheses for CEST imaging as a non‐invasive diagnostic tool for monitoring pathological alterations of the proteome in vivo.     

On the origins of chemical exchange saturation transfer (CEST) contrast in tumors at 9.4 T

Chemical exchange saturation transfer (CEST) provides an indirect means to detect exchangeable protons within tissues through their effects on the water signal. Previous studies have suggested that amide proton transfer (APT) imaging, a specific form of CEST, detects endogenous amide protons with a resonance frequency offset 3.5 ppm downfield from water, and thus may be sensitive to variations in mobile proteins/peptides in tumors. However, as CEST measurements are influenced by various confounding effects, such as spillover saturation, magnetization transfer (MT) and MT asymmetry, the mechanism or degree of increased APT signal in tumors is not certain. In addition to APT, nuclear Overhauser enhancement (NOE) effects upfield from water may also provide distinct information on tissue composition. In the current study, APT, NOE and several other MR parameters were measured and compared comprehensively in order to elucidate the origins of APT and NOE contrasts in tumors at 9.4 T. In addition to conventional CEST methods, a new intrinsic inverse metric was applied to correct for relaxation and other effects. After corrections for spillover, MT and T₁ effects, corrected APT in tumors was found not to be significantly different from that in normal tissues, but corrected NOE effects in tumors showed significant decreases compared with those in normal tissues. Biochemical measurements verified that there was no significant enhancement of protein contents in the tumors studied, consistent with the corrected APT measurements and previous literature, whereas quantitative MT data showed decreases in the fractions of immobile macromolecules in tumors. Our results may assist in the better understanding of the contrast depicted by CEST imaging in tumors, and in the development of improved APT and NOE measurements for cancer imaging. Copyright © 2014 John Wiley & Sons, Ltd.     

Towards the complex dependence of MTRasym on T1w in amide proton transfer (APT) imaging

Amide proton transfer (APT) imaging is a variation of chemical exchange saturation transfer MRI that has shown promise in diagnosing tumors, ischemic stroke, multiple sclerosis, traumatic brain injury, etc. Specific quantification of the APT effect is crucial for the interpretation of APT contrast in pathologies. Conventionally, magnetization transfer ratio with asymmetric analysis (MTR_asym) has been used to quantify the APT effect. However, some studies indicate that MTR_asym is contaminated by water longitudinal relaxation time (T_1w), and thus it is necessary to normalize T_1w in MTR_asym to obtain specific quantification of the APT effect. So far, whether to use MTR_asym or the T_1w‐normalized MTR_asym is still under debate in the field. In this paper, the influence of T_1w on the quantification of APT was evaluated through theoretical analysis, numerical simulations, and phantom studies for different experimental conditions. Results indicate that there are two types of T_1w effect (T_1w recovery and T_1w‐related saturation), which have inverse influences on the steady‐state MTR_asym. In situations with no or weak direct water saturation (DS) effect, there is only the T_1w recovery effect, and MTR_asym linearly depends on T_1w. In contrast, in situations with significant DS effects, the dependence of MTR_asym on T_1w is complex, and is dictated by the competition of these two T_1w effects. Therefore, by choosing appropriate irradiation powers, MTR_asym could be roughly insensitive to T_1w. Moreover, in non‐steady‐state acquisitions with very short irradiation time, MTR_asym is also roughly insensitive to T_1w. Therefore, for steady‐state APT imaging at high fields or with very low irradiation powers, where there are no significant DS effects, it is necessary to normalize T_1w to improve the specificity of MTR_asym. However, in clinical MRI systems (usually low fields or non‐steady‐state acquisitions), T_1w normalization may not be necessary when appropriate sequence parameters are chosen.