Chemical Exchange Saturation Transfer Spectra Research Articles

Enhanced and robust contrast in CEST MRI: Saturation pulse shape design via optimal control.

To employ optimal control for the numerical design of Chemical Exchange Saturation Transfer (CEST) saturation pulses to maximize contrast and stability against inhomogeneities. We applied an optimal control framework for the design pulse shapes for CEST saturation pulse trains. The cost functional minimized both the pulse energy and the discrepancy between the corresponding CEST spectrum and the target spectrum based on a continuous radiofrequency (RF) pulse. The optimization is subject to hardware limitations. In measurements on a 7 T preclinical scanner, the optimal control pulses were compared to continuous-wave and Gaussian saturation methods. We conducted a comparison of the optimal control pulses with Gaussian, block pulse trains, and adiabatic spin-lock pulses. The optimal control pulse train demonstrated saturation levels comparable to continuous-wave saturation and surpassed Gaussian saturation by up to 50 % in phantom measurements. In phantom measurements at 3 T the optimized pulses not only showcased the highest CEST contrast, but also the highest stability against field inhomogeneities. In contrast, block pulse saturation resulted in severe artifacts. Dynamic Bloch-McConnell simulations were employed to identify the source of these artifacts, and underscore the robustness of the optimized pulses. In this work, it was shown that a substantial improvement in pulsed saturation CEST imaging can be achieved by using Optimal Control design principles. It is possible to overcome the sensitivity of saturation to B0 inhomogeneities while achieving CEST contrast close to continuous wave saturation.

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

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

Corrections for Rabi oscillations in cardiac chemical exchange saturation transfer MRI under the influence of very short preparation pulses.

Very short chemical exchange saturation transfer (CEST) pulses are beneficial in cardiac continuous wave (cw) CEST MRI, especially in small animals because of their rapid heartbeat; however, they result in signal modulations caused by Rabi oscillations. Therefore, we implemented two different filter techniques, DOwnsampling by SEparation of CEST spectrum into two parts (DOSE) and time domain (TD)-based filtering, to correct for these signal corruptions, allowing a reliable quantification of glucose-weighted CEST (glucoCEST) MRI contrast. In our study, cw CEST measurements were performed on a 9.4-T small animal BioSpec system using CEST pulses in the range of 10 to 200 ms. Experimental dependencies of Rabi oscillations on key MRI parameters were validated by Bloch-McConnell (BM) simulations. Filter efficiency was explored in a glucose concentration series as well as in the myocardium of healthy mice (n = 8), and glucoCEST contrast was subsequently quantified. The experimental results showed that the impact of Rabi oscillations on CEST spectra increased with decreasing CEST pulse length, optimized B0 homogeneity, and shorter T2 relaxation time, in accordance with results from BM simulations. Both investigated filter techniques reduced these signal modulations significantly, with DOSE filtering preserving the amplitude and TD filtering the spectral information of CEST data more accurately. Upon filter application, a significant decrease in glucoCEST contrast in the myocardium of healthy mice was observed after glucose infusion (pTD = 0.0079, pDOSE = 0.0044). To conclude, this study offers comprehensive experimental insights into Rabi oscillations within CEST MRI data along with methodological considerations that could be further advanced into a robust and precise cardiac cw CEST protocol by integrating DOSE and TD filtering into the standard CEST analysis pipeline.

A machine learning approach that measures pH using acidoCEST MRI of iopamidol.

Tumor acidosis is an important biomarker for aggressive tumors, and extracellular pH (pHe) of the tumor microenvironment can be used to predict and evaluate tumor responses to chemotherapy and immunotherapy. AcidoCEST MRI measures tumor pHe by exploiting the pH-dependent chemical exchange saturation transfer (CEST) effect of iopamidol, an exogenous CT agent repurposed for CEST MRI. However, all pH fitting methodologies for acidoCEST MRI data have limitations. Herein we present results of the application of machine learning for extracting pH values from CEST Z-spectra of iopamidol. We acquired 36,000 experimental CEST spectra from 200 phantoms of iopamidol prepared at five concentrations, five T1 values, and eight pH values at five temperatures, acquired at six saturation powers and six saturation times. We also acquired T1 , T2 , B1 RF power, and B0 magnetic field strength supplementary MR information. These MR images were used to train and validate machine learning models for the tasks of pH classification and pH regression. Specifically, we tested the L1-penalized logistic regression classification (LRC) model and the random forest classification (RFC) model for classifying the CEST Z-spectra for thresholds at pH 6.5 and 7.0. Our results showed that both RFC and LRC were effective for pH classification, although the RFC model achieved higher predictive value, and improved the accuracy of classification accuracy with CEST Z-spectra with a more limited set of saturation frequencies. Furthermore, we used LASSO and random forest regression (RFR) models to explore pH regression, which showed that the RFR model achieved higher accuracy and precision for estimating pH across the entire pH range of 6.2-7.3, especially when using a more limited set of features. Based on these results, machine learning for analysis of acidoCEST MRI is promising for eventual in vivo determination of tumor pHe.

Multiple CEST contrast imaging of nose-to-brain drug delivery using iohexol liposomes at 3T MRI.

Image guided nose-to-brain drug delivery provides a non-invasive way to monitor drug delivered to the brain, and the intranasal administration could increase effective dose via bypassing Blood Brain Barrier (BBB). Here, we investigated the imaging of liposome-based drug delivery to the brain via intranasal administration, in which the liposome could penetrate mucus and could be detected by chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) at 3T field strength. Liposomes were loaded with a computed tomography (CT) contrast agent, iohexol (Ioh-Lipo), which has specific amide protons exchanging at 4.3ppm of Z-spectrum (or CEST spectrum). Ioh-Lipo generated CEST contrasts of 35.4% at 4.3ppm, 1.8% at -3.4ppm and 20.6% at 1.2ppm in vitro. After intranasal administration, these specific CEST contrasts were observed in both olfactory bulb (OB) and frontal lobe (FL) in the case of 10% polyethylene glycol (PEG) Ioh-Lipo. We observed obvious increases in CEST contrast in OB half an hour after the injection of 10% PEG Ioh-Lipo, with a percentage increase of 62.0% at 4.3ppm, 10.9% at -3.4ppm and 25.7% at 1.2ppm. Interestingly, the CEST map at 4.3ppm was distinctive from that at -3.4pm and 1.2ppm. The highest contrast of 4.3ppm was at the external plexiform layer (EPL) and the region between left and right OB (LROB), while the CEST contrast at -3.4ppm had no significant difference among all investigated regions with slightly higher signal in olfactory limbus (OL, between OB and FL) and FL, as validated with histology. While no substantial increase of CEST contrast at 4.3ppm, -3.4ppm or 1.2ppm was observed in OB and FL when 1% PEG Ioh-Lipo was administered. We demonstrated for the first time the feasibility of non-invasively detecting the nose-to-brain delivery of liposomes using CEST MRI. This multiple-contrast approach is necessary to image the specific distribution of iohexol and liposome simultaneously and independently, especially when designing drug carriers for nose-to-brain drug delivery.

Ultrafast CEST line scanning as a method to quantify mutarotation kinetics

The process of mutarotation of sugars caused by a balanced reaction between their corresponding α and β isomers, has been known for almost 200 years. Still, it remains essential in modern biochemical research, as enzymatic reactions catalyzed by mutarotases are crucial for various pathways in the energy metabolism.In our study a fast magnetic resonance technique based on chemical exchange saturation transfer (CEST) line scanning (LS) was implemented as a method to measure mutarotation kinetics on a 9.4 T small animal MRI scanner. As proof of concept, the isomeric conversion of two hexoses (glucose and galactose) and pentoses (xylose and arabinose) was investigated in an aqueous solution over time. The technique allowed for ultrafast data acquisition without the implementation of complicated encoding schemes and acceleration procedures. Thus, CEST LS provided complete CEST spectra with a frequency step size of 19.6 Hz in less than one minute.For the mutarotation analysis, CEST spectra were acquired over a time duration of four hours and analyzed with four established CEST quantification approaches - based on either asymmetry of CEST spectra or a multi-pool Lorentzian fit. The isomer ratios of the different sugars at equilibrium were determined with an overall accuracy of 94 %, using an adapted 2-side chemical exchange (CE) model. The estimated mutarotation rate constants at 22 °C were in good agreement with conventionally measured reference values, derived from optical and spectroscopic techniques.

Breast cancer imaging with glucosamine CEST (chemical exchange saturation transfer) MRI: first human experience.

This study aims to evaluate the feasibility of imaging breast cancer with glucosamine (GlcN) chemical exchange saturation transfer (CEST) MRI technique to distinguish between tumor and surrounding tissue, compared to the conventional MRI method. Twelve patients with newly diagnosed breast tumors (median age, 53 years) were recruited in this prospective IRB-approved study, between August 2019 and March 2020. Informed consent was obtained from all patients. All MRI measurements were performed on a 3-T clinical MRI scanner. For CEST imaging, a fat-suppressed 3D RF-spoiled gradient echo sequence with saturation pulse train was applied. CEST signals were quantified in the tumor and in the surrounding tissue based on magnetization transfer ratio asymmetry (MTRasym) and a multi-Gaussian fitting. GlcN CEST MRI revealed higher signal intensities in the tumor tissue compared to the surrounding breast tissue (MTRasym effect of 8.12 ± 4.09%, N = 12, p = 2.2 E-03) with the incremental increase due to GlcN uptake of 3.41 ± 0.79% (N = 12, p = 2.2 E-03), which is in line with tumor location as demonstrated by T1W and T2W MRI. GlcN CEST spectra comprise distinct peaks corresponding to proton exchange between free water and hydroxyl and amide/amine groups, and relayed nuclear Overhauser enhancement (NOE) from aliphatic groups, all yielded larger CEST integrals in the tumor tissue after GlcN uptake by an averaged factor of 2.2 ± 1.2 (p = 3.38 E-03), 1.4 ± 0.4 (p =9.88 E-03), and 1.6 ± 0.6 (p = 2.09 E-02), respectively. The results of this initial feasibility study indicate the potential of GlcN CEST MRI to diagnose breast cancer in a clinical setup. • GlcN CEST MRI method is demonstrated for its the ability to differentiate between breast tumor lesions and the surrounding tissue, based on the differential accumulation of the GlcN in the tumors. • GlcN CEST imaging may be used to identify metabolic active malignant breast tumors without using a Gd contrast agent. • The GlcN CEST MRI method may be considered for use in a clinical setup for breast cancer detection and should be tested as a complementary method to conventional clinical MRI methods.

Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.

PEAKIT: A Gaussian Process regression analysis tool for chemical exchange saturation transfer spectra

Chemical Exchange Saturation Transfer (CEST) is a powerful technique for metabolic imaging, capable of exploring concentrations in the μM to mM range. However, extracting quantitative information from Z-spectra can be challenging due to the non-CEST contributions present and the limited knowledge about the exchanging pools. The PEAKIT tool is proposed as an alternative approach to quantifying CEST peaks, which requires no prior assumptions about the frequency offset or the underlying shape of the baseline. Specifically, the tool takes as input an experimental Z-spectrum and proceeds to identify peak candidates. After a baseline estimation based on Gaussian Process regression, PEAKIT outputs the chemical shift offsets, the areas, the heights and the statistical significance of the detected peaks. The performance and limitations of the PEAKIT tool are discussed for in vitro and in vivo applications.

Accelerating CEST MRI in the mouse brain at 9.4 T by exploiting sparsity in the Z-spectrum domain.

Chemical exchange saturation transfer (CEST) is an MR contrast modality offering an enhanced sensitivity for the detection of dilute metabolites with exchangeable protons. Quantitative analysis requires the acquisition of a number of images (usually between 20 and 50 RF offsets) per Z-spectrum, leading to long acquisition times of the order of 5-40 min in practice. In this work, we explore the possibility of employing sparsity in the Z-spectrum domain (irradiation offset dimension) to provide an accelerated acquisition scheme without compromising the quality of reconstructed CEST spectra. Ex vivo and in vivo data were acquired on an experimental, small animal 9.4 T system. Three different reconstruction methods were tested: k-Z SPARSE, k-Z SLR and k-Z principal component analysis (PCA) using retrospective undersampling with net acceleration factors R = 2, 3, 5. The quality of the reconstructed data was compared with respect to CEST spectra and full magnetization transfer ratio (MTR) asymmetry maps. In both phantom and in vivo data, CEST spectra and the resulting MTR asymmetry maps were reconstructed without significant deterioration in data quality. For a low acceleration factor (R = 2, 3) all applied methods resulted in similar data quality, while for high acceleration factor (R = 5) only k-Z PCA and k-Z SLR could be used. Loss in spatial resolution was observed in reconstruction with k-Z PCA for all acceleration factors. An example of prospective undersampling with acceleration factor R = 3 and k-Z PCA reconstruction demonstrates improved CEST maps when compared with fully sampled data acquisition with either three times longer scan duration or threefold prolonged acquisition window per frequency offset. The acquisition time of CEST spectra can be significantly accelerated by exploiting the sparsity of the Z-domain. For prospective and retrospective analysis using k-Z PCA, an acceleration factor of up to R = 3 can be used without significant loss in data quality.

Amplified detection of phosphocreatine and creatine after supplementation using CEST MRI at high and ultrahigh magnetic fields

Creatine is an important metabolite involved in muscle contraction. Administration of exogenous creatine (Cr) or phosphocreatine (PCr) has been used for improving exercise performance and protecting the heart during surgery including during valve replacements, coronary artery bypass grafting and repair of congenital heart defects. In this work we investigate whether it is possible to use chemical exchange saturation transfer (CEST) MRI to monitor uptake and clearance of exogenous creatine and phosphocreatine following supplementation. We were furthermore interested in determining the limiting conditions for distinguishing between creatine (1.9 ppm) and phosphocreatine (2.6 ppm) signals at ultra-high fields (21 T) and determine their concentrations could be reliably obtained using Bloch equation fits of the experimental CEST spectra. We have tested these items by performing CEST MRI of hind limb muscle and kidneys at 11.7 T and 21.1 T both before and after intravenous administration of PCr. We observed up to 4% increase in contrast in the kidneys at 2.6 ppm which peaked ~30 min after administration and a relative ratio of 1.3 in PCr:Cr signal. Overall, these results demonstrate the feasibility of independent monitoring of PCr and Cr concentration changes using CEST MRI.

Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP) for Z-spectra fitting in chemical exchange saturation transfer (CEST) MRI.

Chemical exchange saturation transfer (CEST) MRI is a promising approach for detecting biochemical alterations in cancers and neurological diseases, but the quantification can be challenging. Among numerous quantification methods, Lorentzian difference (LD) is relatively simple and widely used, which employs Lorentzian line-shape as a reference to describe the direct saturation (DS) of water and takes account of difference against experimental CEST spectra data. However, LD often overestimates CEST and nuclear overhauser enhancement (NOE) effects. Specifically, for fast-exchanging CEST species require higher saturation power (B1_sat) or in the presence of strong magnetization transfer (MT) contrast, Z-spectrum appears more like a Gaussian line-shape rather than a Lorentzian line-shape. To improve the conventional LD analysis, the present study developed and validated a novel fitting algorithm through a linear combination of Gaussian and Lorentzian function as the reference spectra, namely, Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP). The experimental Z-spectra were pre-fitted with Gaussian and Lorentzian method independently, in order to determine Lorentzian proportionality coefficient (a). To further compensate for the line-shape changes under different B1_sat's, a B1-dependent adjustment was applied to the experimental Z-spectra (Z_exp) according to the prior knowledge learned from 5-pool Bloch equation-based simulations at a range of B1_sat's. Then, the obtained Z-spectra (Z_B1adj) was fitted by the previously defined VOPVP function. Considering the asymmetric component of MT, the positive- and negative-side of Z-spectra were fitted separately, while the middle part (-0.6 to 0.6 ppm, consisted primarily of DS) was fitted using Lorentzian function. Finally, the difference between Z_VOPVP and Z_exp was defined as the CEST and NOE contrast. To validate our VOPVP method, an extensive simulation of CEST Z-spectra was performed using 5-pool model and 6-pool model with greater MT component. In comparison with LD approach, VOPVP exhibited lower sum of squares due to error (SSE) and higher goodness of fit (R-square) for the experimental Z-spectra at all B1_sat. Moreover, the results indicated that VOPVP fitting improved the overestimated contributions from amide proton transfer (APT) and NOE through LD at all B1_sat. Despite that the relationship for B1-dependent adjustment was pre-determined using a single 5-pool model, the VOPVP fittings obtained accurate quantification for multiple 6-pool models with a range of T1w's and T2w's. The robustness of VOPVP fitting was also proved by simulations using 3T parameters. Furthermore, we assessed VOPVP in vivo in a glioblastoma-bearing mouse. Compared to LD maps, VOPVP quantification maps displayed higher contrast-to-noise ratio between tumor and normal contralateral tissue for APT, glutamate and nuclear overhauser effect (NOE), when B1_sat >1 µT. As an improvement of LD method, VOPVP fitting can serve as a simple, robust and more accurate approach for quantifying CEST and NOE contrast.

Brain tumor acidification using drugs simultaneously targeting multiple pH regulatory mechanisms.

Non-invasively distinguishing aggressive from non-aggressive brain tumors is an important clinical challenge. Intracellular pH (pHi) regulation is essential for normal cell function and is normally maintained within a narrow range. Cancer cells are characterized by a reversed intracellular to extracellular pH gradient, compared to healthy cells, that is maintained by several distinct mechanisms. Previous studies have demonstrated acute pH modulation in glioblastoma detectable by chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) after blocking individual pH regulatory mechanisms. The purpose of the current study was to simultaneously block five pH regulatory mechanisms while also providing glucose as an energy substrate. We hypothesized that this approach would increase the acute pH modulation effect allowing the identification of aggressive cancer. Using a 9.4T MRI scanner, CEST spectra were acquired sensitive to pHi using amine/amide concentration independent detection (AACID). Twelve mice were scanned approximately 11 ± 1days after implanting 105 U87 human glioblastoma multiforme cells in the brain, before and after intraperitoneal injection of a combination of five drugs (quercetin, cariporide, dichloroacetate, acetazolamide, and pantoprazole) with and without glucose. Two hours after combination drug injection there was a significant 0.1 ± 0.03 increase in tumor AACIDvalue corresponding to a 0.4 decrease in pHi. After injecting the drug combination with glucose the AACID value increased by 0.18 ± 0.03 corresponding to a 0.72 decrease in pHi. AACID values were alsoslightly increased in contralateral tissue. The combined drug treatment with glucose produced a large acute CEST MRI contrast indicating tumor acidification, which could be used to help localize brain cancer and monitor tumor response to chemotherapy.

Adaptive denoising for chemical exchange saturation transfer MR imaging.

High image signal-to-noise ratio (SNR) is required to reliably detect the inherently small chemical exchange saturation transfer (CEST) effects in vivo. In this study, it was demonstrated that identifying spectral redundancies of CEST data by principal component analysis (PCA) in combination with an appropriate data-driven extraction of relevant information can be used for an effective and robust denoising of CEST spectra. The relationship between the number of relevant principal components and SNR was studied on fitted in vivo Z-spectra with artificially introduced noise. Three different data-driven criteria to automatically determine the optimal number of necessary components were investigated. In addition, these criteria facilitate straightforward assessment of data quality that could provide guidance for CEST MR protocols in terms of SNR. Insights were applied to achieve a robust denoising of highly sampled low power Z-spectra of the human brain at 3 and 7T. The median criterion provided the best estimation for the optimal number of components consistently for all three investigated artificial noise levels. Application of the denoising technique to in vivo data revealed a considerable increase in image quality for the amide and rNOE contrast with a considerable SNR gain. At 7T the denoising capability was quantified to be comparable or even superior to an averaging of six measurements. The proposed denoising algorithm enables an efficient and robust denoising of CEST data by combining PCA with appropriate data-driven truncation criteria. With this generally applicable technique at hand, small CEST effects can be reliably detected without the need for repeated measurements.

CEST-MRI for glioma pH quantification in mouse model: Validation by immunohistochemistry.

In glioma, the acidification of the extracellular tumor microenvironment drives proliferation, angiogenesis, immunosuppression, invasion and chemoresistance. Therefore, quantification of glioma extracellular pH (pHe) is of crucial importance. This study is focused on the application of the YbHPDO3A (ytterbium 1,4,7-triscarboxymethyl-1,4,7,10-tetraazacyclododecane) probe for in vivo glioma pHe quantification using chemical exchange saturation transfer (CEST)-MRI and its correlation with tumor metabolism assessed by immunohistochemistry. The U87 glioma mouse model was used (n=18) and MRI performed at 4.7T. CEST-MRI of YbHPDO3A solutions at different pH values showed two resolved CEST spectra at 71ppm and 99ppm, both sensitive to pH variations, allowing therefore calculation of the ratiometric curve for in vivo pH quantification. In vivo MRI sequences consisted of T2w for tumor localization, T2w * to assess YbHPDO3A biodistribution by exploiting its magnetic susceptibility effect and CEST for glioma pHe mapping. T2w * images show that YbHPDO3A extravasates in tumor in regions with damaged blood-brain barrier. The pHe is calculated only in these regions. Hematoxylin/eosin histology and Ki-67, CA-IX (carbonic anhydrase 9) and NHE-1 immunohistochemical staining were performed; their expression rates were compared with the in vivo pHe values. On the basis of the cell proliferation marker Ki-67, two groups were defined: one group with a lower mitotic index (MI%<20%=mean value) and a mean pHe value of 7.00 (low-proliferation/high-pH group) and the other with MI%>20% and an acidic pHe of 6.6 (high-proliferation/low-pH group). CA-IX and NHE-1 were over-expressed in the high-proliferation/low-pH group (CA-IX, 92±7% versus 30±13%; NHE-1, 84±8% versus 35±11%), indicating an acidic/hypoxic microenvironment. These immunohistochemical results are consistent with our pHe mapping (Pearson correlation coefficient>0.70) and provide evidence for the feasibility of the CEST-MRI method with the YbHPDO3A probe for glioma pHe quantification at 4.7T. Importantly, the YbHPDO3A probe has similar chemical and biological properties to the clinically approved MRI contrast agent GdHPDO3A. This makes the method promising for a clinical translation.

The Monocarboxylate transporter inhibitor Quercetin induces intracellular acidification in a mouse model of Glioblastoma Multiforme: in-vivo detection using magnetic resonance imaging.

The response of tumor intracellular pH to a pharmacological challenge could help identify aggressive cancer. Chemical exchange saturation transfer (CEST) is an MRI contrast mechanism that is dependent on intracellular pH (pHi). pHi is important in the maintenance of normal cell function and is normally maintained within a narrow range by the activity of transporters located at the plasma membrane. In cancer, changes in pHi have been correlated with both cell proliferation and cell death. Quercetin is a bioflavonoid and monocarboxylate transporter (MCT) inhibitor. Since MCTs plays a significant role in maintaining pH balance in the tumor microenvironment, we hypothesized that systemically administered quercetin could selectively acidify brain tumors. The goals of the current study were to determine whether CEST MRI measurements sensitive to tumor pH could detect acidification after quercetin injection and to measure the magnitude of the pH change (ΔpH). Using a 9.4T MRI, amine and amide concentration independent detection (AACID) CEST spectra were acquired in six mice approximately 15 ± 1days after implanting 105U87 human glioblastoma multiforme cells in the brain, before and after administration of quercetin (dose: 200mg/kg) by intraperitoneal injection. Three additional mice were studied as controls and received only vehicle dimethyl sulfoxide (DMSO) injection. Repeated measures t-test was used to compare AACID changes in tumor and contralateral tissue regions of interest. Two hours after quercetin injection there was a significant increase in tumor AACID by 0.07 ± 0.03 corresponding to a 0.27 decrease in pHi, and no change in AACID in contralateral tissue. There was also a small average increase in AACID in tumors within the three mice injected with DMSO only. The use of the natural compound quercetin in combination with pH weighted MRI represents a unique approach to cancer detection that does not require injection of an imaging contrast agent.

In vivo detection of acute intracellular acidification in glioblastoma multiforme following a single dose of cariporide.

Glioblastoma is an aggressive brain cancer that is very difficult to treat. Clinically, it is important to be able to distinguish aggressive from non-aggressive brain tumors. Previous studies have shown that some drugs can induce a rapid change in intracellular pH that could help to identify aggressive cancer. The sodium proton exchanger (NHE1) plays a significant role in maintaining pH balance in the tumor microenvironment. Cariporide is a sodium proton exchange inhibitor that is well tolerated by humans in cardiac applications. We hypothesized that cariporide could selectively acidify brain tumors. The purpose of this study was to determine whether amine/amide concentration-independent detection (AACID) chemical exchange saturation transfer (CEST) MRI measurement of tumor pHi could detect acidification after cariporide injection. Using a 9.4T MRI scanner, CEST spectra were acquired in six mice approximately 14days after implanting 105 U87 human glioblastoma multiforme cells in the brain, before and after administration of cariporide (dose: 6mg/kg) by intraperitoneal injection. Three additional mice were studied as controls and received only vehicle injection (DMSO + PBS). Repeated measures t test was used to examine changes in tumor and contralateral tissue regions of interest. Two hours after cariporide injection, there was a significant 0.12 ± 0.03 increase in tumor AACID value corresponding to a 0.48 decrease in pHi and no change in AACID value in contralateral tissue. A small but significant increase of 0.04 ± 0.017 in tumor AACID value was also observed following vehicle injection. This study demonstrates that acute CEST MRI contrast changes, indicative of intracellular acidification, after administration of cariporide could help localize glioblastoma.

Imaging Lung Cancer by Using Chemical Exchange Saturation Transfer MRI With Retrospective Respiration Gating.

Performing chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) in lung tissue is difficult because of motion artifacts. We, therefore, developed a CEST MRI acquisition and analysis method that performs retrospective respiration gating. Our method used an acquisition scheme with a short 200-millisecond saturation pulse that can accommodate the timing of the breathing cycle, and with saturation applied at frequencies in 0.03-ppm intervals. The Fourier transform of each image was used to calculate the difference in phase angle between adjacent pixels in the longitudinal direction of the respiratory motion. Additional digital filtering techniques were used to evaluate the breathing cycle, which was used to construct CEST spectra from images during quiescent periods. Results from CEST MRI with and without respiration gating analysis were used to evaluate the asymmetry of the magnetization transfer ratio (MTRasym), a measure of CEST, for an egg white phantom that underwent cyclic motion, in the liver of healthy patients, as well as liver and tumor tissues of patients diagnosed with lung cancer. Retrospective respiration gating analysis produced more precise measurements in all cases with significant motion compared with nongated analysis methods. Finally, a preliminary clinical study with the same respiration-gated CEST MRI method showed a large increase in MTRasym after radiation therapy, a small increase or decrease in MTRasym after chemotherapy, and mixed results with combined chemoradiation therapy. Therefore, our retrospective respiration-gated method can improve CEST MRI evaluations of tumors and organs that are affected by respiratory motion.

Dichloroacetate induced intracellular acidification in glioblastoma: in vivo detection using AACID-CEST MRI at 9.4Tesla.

Intracellular pH (pHi) plays an important role in the maintenance of normal cell function, and is maintained within a narrow range by the activity of transporters located at the plasma membrane. Modulation of tumor pHi may influence proliferation, apoptosis, chemotherapy resistance, and thermosensitivity. Chemical exchange saturation transfer (CEST) is a novel MRI contrast mechanism that is dependent on cellular pH. Amine and amide concentration-independent detection (AACID) is a recently developed CEST contrast method that is intracellular pH (pHi) weighted. Dichloroacetate (DCA) can alter tumor pHi by inhibiting the enzyme pyruvate dehydrogenase kinase causing reduced lactate (increasing pHi), or by decreasing the expression of monocarboxylate transporters and vacuolar ATPase leading to reduced pHi. Since the net in vivo effect of DCA on pHi is difficult to predict, the purpose of this study was to quantify the magnitude of acute pHi change in glioblastoma after a single DCA injection using AACID CEST MRI. Using a 9.4T MRI scanner, CEST spectra were acquired in six mice approximately 14 days after implanting 105 U87 human glioblastoma multiforme (GBM) cells in the brain, before and after intravenous injection of DCA (dose: 200mg/kg). Three additional mice received only phosphate buffered saline (PBS) injection and were studied as controls. Repeated measures t test was used to compare AACID changes in tumor and contralateral tissue regions of interest. One hour after DCA injection there was a significant increase in tumor AACID level by 0.04 ± 0.01 corresponding to a 0.16 decrease in pHi, and no change in AACID in contralateral tissue. Inspection of AACID maps following PBS injection showed no differences. The use of DCA to induce a tumor specific pH change detectable by AACID CEST MRI is consistent with previous studies that have shown similar effects for lonidamine and topiramate. This study demonstrates that a single dose of DCA can be used as a pharmacological challenge to induced rapid tumor intracellular acidification.

Detection and Quantification of Hydrogen Peroxide in Aqueous Solutions Using Chemical Exchange Saturation Transfer.

The development of new analytical methods to accurately quantify hydrogen peroxide is of great interest. In the current study, we developed a new magnetic resonance (MR) method for noninvasively quantifying hydrogen peroxide (H2O2) in aqueous solutions based on chemical exchange saturation transfer (CEST), an emerging MRI contrast mechanism. Our method can detect H2O2 by its specific CEST signal at ∼6.2 ppm downfield from water resonance, with more than 1000 times signal amplification compared to the direct NMR detection. To improve the accuracy of quantification, we comprehensively investigated the effects of sample properties on CEST detection, including pH, temperature, and relaxation times. To accelerate the NMR measurement, we implemented an ultrafast Z-spectroscopic (UFZ) CEST method to boost the acquisition speed to 2 s per CEST spectrum. To accurately quantify H2O2 in unknown samples, we also implemented a standard addition method, which eliminated the need for predetermined calibration curves. Our results clearly demonstrate that the presented CEST-based technique is a simple, noninvasive, quick, and accurate method for quantifying H2O2 in aqueous solutions.