Ratiometric NOE(-1.6) contrast in brain tumors

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

PURPOSE

To develop a SNR enhancement method for chemical exchange saturation transfer (CEST) imaging using a denoising convolutional autoencoder (DCAE), and compare its performance with state-of-the-art denoising methods.

METHOD

The DCAECEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z spectrum via a series of 1D convolutions, nonlinearity applications and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in-vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric.

RESULTS

In digital phantom experiments, the DCAECEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirms the effectiveness of the DCAECEST in denoising the APT and NOE maps when compared to other methods. While no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings.

CONCLUSION

The DCAECEST can learn the most important features of the CEST Z spectrum and provide the most effective denoising solution compared to other methods.

Specific and rapid guanidinium CEST imaging using double saturation power and QUASS analysis in a rodent model of global ischemia

PURPOSE

Guanidinium CEST is sensitive to metabolic changes and pH variation in ischemia, and it can offer advantages over conventional pH-sensitive amide proton transfer (APT) imaging by providing hyperintense contrast in stroke lesions. However, quantifying guanidinium CEST is challenging due to multiple overlapping components and a close frequency offset from water. This study aims to evaluate the applicability of a new rapid and model-free CEST quantification method using double saturation power, termed DSP-CEST, for isolating the guanidinium CEST effect from confounding factors in ischemia. To further reduce acquisition time, the DSP-CEST was combined with a quasi-steady state (QUASS) CEST technique to process non-steady-state CEST signals.

METHODS

The specificity and accuracy of the DSP-CEST method in quantifying the guanidinium CEST effect were assessed by comparing simulated CEST signals with/without the contribution from confounding factors. The feasibility of this method for quantifying guanidinium CEST was evaluated in a rat model of global ischemia induced by cardiac arrest and compared to a conventional multiple-pool Lorentzian fit method.

RESULTS

The DSP-CEST method was successful in removing all confounding components and quantifying the guanidinium CEST signal increase in ischemia. This suggests that the DSP-CEST has the potential to provide hyperintense contrast in stroke lesions. Additionally, the DSP-CEST was shown to be a rapid method that does not require the acquisition of the entire or a portion of the CEST Z-spectrum that is required in conventional model-based fitting approaches.

CONCLUSION

This study highlights the potential of DSP-CEST as a valuable tool for rapid and specific detection of viable tissues.

Nuclear Overhauser enhancement imaging at -1.6 ppm in rat brain at 4.7T

PURPOSE

A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer signal at around -1.6 ppm, termed NOE(-1.6), has been reported at high fields of 7T and 9.4T previously. This study aims to validate the presence of this signal at a relatively low field of 4.7T and evaluate its variations in different brain regions and tumors.

METHODS

Rats were injected with monocrystalline iron oxide nanoparticles to reduce the NOE(-1.6) signal. CEST signals were measured using different saturation powers before and after injection to assess the presence of this signal. Multiple-pool Lorentzian fits, with/without inclusion of the NOE(-1.6) pool, were performed on CEST Z-spectra obtained from healthy rat brains and rats with 9L tumors. These fits aimed to further validate the presence of the NOE(-1.6) signal and quantify its amplitude.

RESULTS

The NOE(-1.6) signal exhibited a dramatic change following the injection of monocrystalline iron oxide nanoparticles, confirming its presence at 4.7T. The NOE(-1.6) signal reached its peak at a saturation power of ∼0.75 μT, indicating an optimized power level. The multiple-pool Lorentzian fit without the NOE(-1.6) pool showed higher residuals around -1.6 ppm compared to the fit with this pool, further supporting the presence of this signal. The NOE(-1.6) signal did not exhibit significant variation in the corpus callosum and caudate putamen regions, but it showed a significant decrease in tumors, which aligns with previous findings at 9.4T.

CONCLUSION

This study successfully demonstrated the presence of the NOE(-1.6) signal at 4.7T, which provides valuable insights into its potential applications at lower field strengths.

Measuring chemical exchange saturation transfer exchange rates in the human brain using a particle swarm optimisation algorithm

The z-spectrum contains many pools with different exchange rates and T2 values, which can make it difficult to interpret in vivo data and complicates the design of experiments aimed at providing sensitivity to one pool. This work aims to characterise the main pools observable with MRI at 7T in the human brain. To achieve this, we acquired z-spectra at multiple saturation powers in the human brain at 7T. We used simulations to optimise the use of particle swarm optimisation (PSO) to fit these data, validating this approach using further simulations and creatine phantoms. We then used the PSO to fit data from grey and white matter for the pool size, exchange rate, and T2 of five proton pools (magnetisation transfer, amides, amines, nuclear Overhauser enhancement NOE-3.5ppm and NOE-1.7ppm in addition to water). We then devised an approach for using PSO to fit z-spectra while limiting the computational burden, and we investigated the sensitivity of the fit to T2 and k for three overlapping pools. We used this to measure the exchange rate of creatine and to show that it varied with temperature, as expected. In the brain we measured a significantly larger pool size in white matter than in grey matter for the magnetisation transfer pool and the NOE-3.5ppm pool. For all other parameters we found no significant difference between grey and white matter. We showed that PSO can be used to fit z-spectra acquired at a range of B1 to provide information about peak position, amplitude, exchange rate, and T2 in vivo in the human brain. These data could provide more sensitivity to change in some clinical conditions and will also provide key information for further experimental design.

Validation of the presence of fast exchanging amine CEST effect at low saturation powers and its influence on the quantification of APT

PURPOSE

Accurately quantifying the amide proton transfer (APT) effect and the underlying exchange parameters is crucial for its applications, but previous studies have reported conflicting results. In these quantifications, the CEST effect from the fast exchange amine was always ignored because it was considered weak with low saturation powers. This paper aims to evaluate the influence of the fast exchange amine CEST on the quantification of APT at low saturation powers.

METHODS

A quantification method with low and high saturation powers was used to distinguish APT from the fast exchange amine CEST effect. Simulations were conducted to assess the method's capability to separate APT from the fast exchange amine CEST effect. Animal experiments were performed to assess the relative contributions from the fast exchange amine and amide to CEST signals at 3.5 ppm. Three APT quantification methods, each with varying degrees of contamination from the fast exchange amine, were employed to process the animal data to assess the influence of the amine on the quantification of APT effect and the exchange parameters.

RESULTS

The relative size of the fast exchange amine CEST effect to APT effect gradually increases with increasing saturation power. At 9.4 T, it increases from approximately 20% to 40% of APT effect with a saturation power increase from 0.25 to 1 μT.

CONCLUSION

The fast exchange amine CEST effect leads overestimation of APT effect, fitted amide concentration, and amide-water exchange rate, potentially contributing to the conflicting results reported in previous studies.

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

PURPOSE

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.

METHODS

For CEST imaging with relatively low saturation powers (ω 1 2 $$ {\upomega}_1^2 $$ ), both the fast-exchange CEST effect and the semi-solid MT effect roughly depend onω 1 2 $$ {\upomega}_1^2 $$ , 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.

RESULTS

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.

CONCLUSION

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.

Assignment of molecular origins of NOE signal at -3.5 ppm in the brain

PURPOSE

Nuclear Overhauser enhancemen mediated saturation transfer effect, termed NOE (-3.5 ppm), is a major source of CEST MRI contrasts at 3.5 ppm in the brain. Previous phantom experiments have demonstrated that both proteins and lipids, two major components in tissues, have substantial contributions to NOE (-3.5 ppm) signals. Their relative contributions in tissues are informative for the interpretation of NOE (-3.5 ppm) contrasts that could provide potential imaging biomarkers for relevant diseases, which remain incompletely understood.

METHODS

Experiments on homogenates and supernatants of brain tissues collected from healthy rats, that could isolate proteins from lipids, were performed to evaluate the relative contribution of lipids to NOE (-3.5 ppm) signals. On the other hand, experiments on ghost membranes with varied pH, and reconstituted phospholipids with different chemical compositions were conducted to study the dependence of NOE (-3.5 ppm) on physiological conditions. Besides, CEST imaging on rat brains bearing 9 L tumors and healthy rat brains was performed to analyze the causes of the NOE (-3.5 ppm) contrast variations between tumors and normal tissues, and between gray matter and white matter.

RESULTS

Our experiments reveal that lipids have dominant contributions to the NOE (-3.5 ppm) signals. Further analysis suggests that decreased NOE (-3.5 ppm) signals in tumors and higher NOE (-3.5 ppm) signals in white matter than in gray matter are mainly explained by changes in membrane lipids, rather than proteins.

CONCLUSION

NOE (-3.5 ppm) could be exploited as a highly sensitive MRI contrast for imaging membrane lipids in the brain.

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.

Assignment of molecular origins of NOE signal at -3.5 ppm in the brain

Purpose

Nuclear Overhauser Enhancement mediated saturation transfer effect, termed NOE(-3.5 ppm), is a major source of chemical exchange saturation transfer (CEST) MRI contrasts at 3.5 ppm in the brain. Previous phantom experiments have demonstrated that both proteins and lipids, two major components in tissues, have substantial contributions to NOE(-3.5 ppm) signals. Their relative contributions in tissues are informative for the interpretation of NOE(-3.5 ppm) contrasts that could provide potential imaging biomarkers for relevant diseases, which remain incompletely understood.

Methods

Experiments on homogenates and supernatants of brain tissues collected from healthy rats, that could isolate proteins from lipids, were performed to evaluate the relative contribution of lipids to NOE(-3.5 ppm) signals. On the other hand, experiments on ghost membranes with varied pH, and reconstituted phospholipids with different chemical compositions were conducted to study the dependence of NOE(-3.5 ppm) on physiological conditions. Besides, CEST imaging on rat brains bearing 9L tumors and healthy rat brains was performed to analyze the causes of the NOE(-3.5 ppm) contrast variations between tumors and normal tissues, and between gray matter and white matter.

Results

Our experiments reveal that lipids have dominant contributions to the NOE (-3.5 ppm) signals. Further analysis suggests that decreased NOE(-3.5 ppm) signals in tumors and higher NOE(-3.5 ppm) signals in white matter than in gray matter are mainly explained by changes in membrane lipids, rather than proteins.

Conclusion

NOE(-3.5 ppm) could be exploited as a highly sensitive MRI contrast for imaging membrane lipids in the brain.

NOE-weighted imaging in tumors using low-duty-cycle 2π-CEST

PURPOSE

Nuclear Overhauser enhancement (NOE)-mediated CEST imaging at -3.5 ppm has shown clinical interest in diagnosing tumors. Multiple-pool Lorentzian fit has been used to quantify NOE, which, however, requires a long scan time. Asymmetric analysis of CEST signals could be a simple and fast method to quantify this NOE, but it has contamination from the amide proton transfer (APT) at 3.5 ppm. This work proposes a new method using an asymmetric analysis of a low-duty-cycle pulsed-CEST sequence with a flip angle of 360°, termed 2π-CEST, to reduce the contribution from APT.

METHODS

Simulations were used to evaluate the capability of the 2π-CEST to reduce APT. Experiments on animal tumor models were performed to show its advantages compared with the conventional asymmetric analysis. Samples of reconstituted phospholipids and proteins were used to evaluate the molecular origin of this NOE.

RESULTS

The 2π-CEST has reduced contribution from APT. In tumors where we show that the NOE is comparable to the APT effect, reducing the contamination from APT is crucial. The results show that the NOE signal obtained with 2π-CEST in tumor regions appears more homogeneous than that obtained with the conventional method. The phantom study showed that both phospholipids and proteins contribute to the NOE at -3.5 ppm.

CONCLUSION

The NOE at -3.5 ppm has a different contrast mechanism from APT and other CEST/NOE effects. The proposed 2π-CEST is more accurate than the conventional asymmetric analysis in detecting NOE, and requires much less scan time than the multiple-pool Lorentzian fit.

Noninvasively differentiating acute and chronic nephropathies via multiparametric urea-CEST, nuclear Overhauser enhancement-CEST, and quantitative magnetization transfer MRI

PURPOSE

Standardized blood tests often lack adequate sensitivity and specificity to capture the gradual progression of renal injuries. We suggest a multiparametric molecular MRI approach as a noninvasive tool for monitoring renal function loss and distinguishing different types of renal injuries.

METHODS

CEST and quantitative magnetization transfer (qMT) imaging were performed on cisplatin (n = 16) and aristolochic acid (AA)-induced nephropathy (n = 22) mouse models at 7T with an infusion of either saline or urea. Seven-pool Lorentzian fitting was applied for the analysis of CEST Z-spectra, and the T1 -corrected CEST contrast apparent exchange-dependent relaxation (AREX) from urea (+1 ppm) and two nuclear Overhauser enhancement (NOE) pools (-1.6 and -3.5 ppm) were measured. Similarly, qMT spectra were fitted into two-pool Ramani equation and the relative semi-solid macromolecular pool-size ratio was measured. Histology of mouse kidneys was performed to validate the MR findings.

RESULTS

AA model showed disrupted spatial gradients of urea in the kidney and significantly decreased NOE CEST and qMT contrast. The cisplatin model showed slightly decreased qMT contrast only. The orrelation of MR parameters to histological features showed that NOE CEST and qMT imaging are sensitive to both acute and chronic injuries, whereas urea CEST shows a significant correlation only to acute injuries.

CONCLUSION

These results indicate that our multiparametric approach allows comprehensive and totally noninvasive monitoring of renal function and histological changes for distinguishing different nephropathies.

Chemical Exchange Saturation Transfer (CEST) Signal at −1.6 ppm and Its Application for Imaging a C6 Glioma Model

The chemical exchange saturation transfer (CEST) signal at −1.6 ppm is attributed to the choline methyl on phosphatidylcholines and results from the relayed nuclear Overhauser effect (rNOE), that is, rNOE(−1.6). The formation of rNOE(−1.6) involving the cholesterol hydroxyl is shown in liposome models. We aimed to confirm the correlation between cholesterol content and rNOE(−1.6) in cell cultures, tissues, and animals. C57BL/6 mice (N = 9) bearing the C6 glioma tumor were imaged in a 7 T MRI scanner, and their rNOE(−1.6) images were cross-validated through cholesterol staining with filipin. Cholesterol quantification was obtained using an 18.8-T NMR spectrometer from the lipid extracts of the brain tissues from another group of mice (N = 3). The cholesterol content in the cultured cells was manipulated using methyl-β-cyclodextrin and a complex of cholesterol and methyl-β-cyclodextrin. The rNOE(−1.6) of the cell homogenates and their cholesterol levels were measured using a 9.4-T NMR spectrometer. The rNOE(−1.6) signal is hypointense in the C6 tumors of mice, which matches the filipin staining results, suggesting that their tumor region is cholesterol deficient. The tissue extracts also indicate less cholesterol and phosphatidylcholine contents in tumors than in normal brain tissues. The amplitude of rNOE(−1.6) is positively correlated with the cholesterol concentration in the cholesterol-manipulated cell cultures. Our results indicate that the cholesterol dependence of rNOE(−1.6) occurs in cell cultures and solid tumors of C6 glioma. Furthermore, when the concentration of phosphatidylcholine is carefully considered, rNOE(−1.6) can be developed as a cholesterol-weighted imaging technique.

Contribution of blood to nuclear Overhauser effect at -1.6 ppm

PURPOSE

A relayed nuclear Overhauser enhancement (rNOE) saturation transfer effect at around -1.6 ppm from water, termed NOE(-1.6), was previously reported in rat and human brain, and some publications suggest that it may be related to blood. Here, we studied whether the NOE(-1.6) arises from blood through in vivo and ex vivo experiments.

METHODS

To evaluate the contribution from in vivo blood to NOE(-1.6), intravascular signals in rat brain were suppressed by two approaches: (1) signal acquisition with a diffusion-weighting of b = 400 s/mm2 ; (2) intravascular injection of 5 mg/kg monocrystalline iron oxide nanoparticle (MION). Ex vivo blood sample was also prepared. The signals were acquired using a chemical exchange saturation transfer (CEST) pulse sequence. Multiple-pool Lorentzian fitting of CEST Z-spectra was performed to quantify the NOE(-1.6) signal.

RESULTS

There are no significant variations in the fitted in vivo NOE(-1.6) signals when measured with or without diffusion-weighting, but significant signal decease does occur after injection of MION. The NOE(-1.6) signal from ex vivo blood is weaker than that from in vivo tissues.

CONCLUSION

Considering the relatively small volume of blood in brain, the in vivo experiments with diffusion weighting and the ex vivo experiments both suggest that the NOE(-1.6) is not mainly from blood. The mechanism for the in vivo experiments with MION are less clear. MION not only suppresses MR signals from intravascular space, but changes the susceptibility in the perivascular space. This result suggests that although the NOE(-1.6) is not mainly from blood, it may be vasculature dependent.

Mapping intracellular pH in tumors using amide and guanidyl CEST-MRI at 9.4 T

PURPOSE

In principle, non-invasive mapping of the intracellular pH (pH_i ) in vivo is possible using endogenous chemical exchange saturation transfer (CEST)-MRI of the amide and guanidyl signals. However, the application for cancer imaging is still impeded, as current state-of-the-art approaches do not allow for simultaneous compensation of concomitant effects that vary within tumors. In this study, we present a novel method for absolute pH_i mapping using endogenous CEST-MRI, which simultaneously compensates for concentration changes, superimposing CEST signals, magnetization transfer contrast, and spillover dilution.

THEORY AND METHODS

Compensation of the concomitant effects was achieved by a ratiometric approach (i.e. the ratio of one CEST signal at different B₁ ) in combination with the relaxation-compensated inverse magnetization transfer ratio MTR_Rex and a separate first-order polynomial-Lorentzian fit of the amide and guanidyl signals at 9.4 T. Calibration of pH values was accomplished using in vivo-like model suspensions from porcine brain lysates. Applicability of the presented method in vivo was demonstrated in n = 19 tumor-bearing mice.

RESULTS

In porcine brain lysates, measurement of pH was feasible over a broad range of physiologically relevant pH values of 6.2 to 8.0, while being independent of changes in concentration. A median pH_i of approximately 7.2 was found in the lesions of 19 tumor-bearing mice.

CONCLUSION

The presented method enables non-invasive mapping of absolute pH_i values in tumors using CEST-MRI, which was so far prevented by concomitant effects. Consequently, pre-clinical studies on pH_i changes in tumors are possible allowing the assessment of pH_i in vivo as a biomarker for cancer diagnosis or treatment monitoring.

Comparative evaluation of polynomial and Lorentzian lineshape-fitted amine CEST imaging in acute ischemic stroke

Purpose

Chemical exchange saturation transfer signals from amines are sensitive to pH, and detection of these signals can serve as an alternative pH imaging method to amide proton transfer (APT). However, conflicting results regarding amine CEST imaging at 2 ppm in ischemic stroke have been reported. Here, we correlated amine CEST with APT in animal stroke models to evaluate its specificity to pH, and investigated the reason for the different results through simulations and sample studies.

Methods

A three‐point quantification method was used to quantify APT. A polynomial fit method and a multiple‐pool Lorentzian fit method were used to quantify amine CEST. Samples of creatine and glutamate were prepared to study the different CEST effects from arginine amine and fast exchanging pools. Samples of tissue homogenates with different pH were prepared to study the variation in CEST signals due only to changes in pH.

Results

The polynomial fit of amine CEST at 2 ppm had a significant correlation with APT, whereas the Lorentzian fit did not. Further studies showed that arginine amine contributed to the polynomial fit, whereas both the arginine amine and the fast exchanging pools contributed to the Lorentzian fit with their CEST effects varying in opposite directions after stroke. The CEST signal from the fast exchanging pool decreased, probably due to the reduced pool concentration but not pH.

Conclusion

The variation in opposite directions led to an insignificant correlation of the Lorentzian fit of amine CEST with APT and the different results in different experimental conditions.

Role of the cholesterol hydroxyl group in the chemical exchange saturation transfer signal at -1.6 ppm

Chemical exchange saturation transfer (CEST) can provide metabolite-weighted images in the clinical setting; therefore, understanding the origin of each CEST signal is essential to revealing the changes in diseases at the molecular level, which would provide further insight for diagnoses and treatments. The CEST signal at -1.6 ppm is attributed to the choline methyl group of phosphatidylcholines. The methyl groups have no exchangeable protons, so the corresponding CEST signals must result from the relayed nuclear Overhauser effect (rNOE); however, the detailed mechanism remains unclear. Cholesterol is a major component of biological membranes, and its content is closely related to the dynamics and phases of these lipids. However, cholesterol has a hydroxyl group, which could participate in proton exchange to complete the rNOE process. In this study, we used liposomes containing cholesterol and its analogs (5α-cholestane and progesterone), which presumably have similar capabilities of influencing lipid bilayers, and found that the steroid hydroxyl group is the key to inducing the rNOE at -1.6 ppm. Our results suggest that the origin of the rNOE at -1.6 ppm likely requires an intermolecular NOE between the proton of the choline methyl group and that of the cholesterol hydroxyl group, and a chemical exchange between the cholesterol hydroxyl group and bulk water. However, the phenomenon in which the rNOE at -1.6 ppm appears when the cholesterol concentration is high seems to contradict the in vivo results, suggesting a more complicated mechanism associated with the rNOE at -1.6 ppm in biological membranes.

Analysis of model-based and model-free CEST effect quantification methods for different medical applications

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) holds great potential to provide new metabolic information for clinical applications such as tumor, stroke and Parkinson's Disease diagnosis. Many active research and developments have been conducted to translate this emerging MRI technique for routine clinical applications. In general, there are two CEST quantification techniques: (i) model-free and (ii) model-based techniques. The reliability of these quantification techniques depends heavily on the experimental conditions and quality of the collected data. Errors such as noise may lead to misleading quantification results and thus inaccurate diagnosis when CEST imaging becomes a standard or routine imaging scan in the future. This paper investigates the accuracy and robustness of these quantification techniques under different signal-to-noise (SNR) levels and magnetic field strengths. The quantified CEST effect before and after adding random Gaussian White Noise using model-free and model-based quantification techniques were compared. It was found that the model-free technique consistently yielded larger average percentage error across all tested parameters compared to its model-based counterpart, and that the model-based technique could withstand SNR of about 3 times lower than the model-free technique. When applied on noisy brain tumor, ischemic stroke, and Parkinson's Disease clinical data, the model-free technique failed to produce significant differences between normal and abnormal tissue whereas the model-based technique consistently generated significant differences. Although the model-free technique was less accurate and robust, its simplicity and thus speed would still make it a good approximate when the SNR was high (>50) or when the CEST effect was large and well-defined. For more accurate CEST quantification, model-based techniques should be considered. When SNR was low (<50) and the CEST effect was small such as those acquired from clinical field strength scanners, which are generally 3T and below, model-based techniques should be considered over model-free counterpart to maintain an average percentage error of less than 44% even under very noisy condition as tested in this work.