Chemical Exchange Saturation Transfer Data Research Articles

Molecular Profiling to Understand Treatment Resistance and Response in Glioblastoma

INTRODUCTION: Patients with glioblastoma experience a wide variation in response to standard treatment, with nearly 30% experiencing tumour progression during treatment, and nearly 6% surviving more than 5 years. To date, there are few non-invasive clinical biomarkers to predict response to firstline treatment. Chemical exchange saturation transfer (CEST) MRI may have the potential to fill this gap. CEST MRI is sensitive to treatment-induced changes and changes in tumor metabolism1. Our team has obtained CEST data for patients before, during and after standard chemoradiation treatment, and found that CEST provides markers of early response and can identify early, standard and late progressors before treatment initiation.2 METHODS: Patients (n = 104) with primary, IDH wild-type glioblastoma were imaged with CEST-MRI at multiple time points throughout standard chemoradiation treatment. DNA and RNA were co-extracted from matched normal and tumour pairs and processed for whole genome sequencing and gene expression analysis using Nanostring. Clinical variables such as age, extent of resection, sex, ECOG status and MGMT promoter methylated were also collected. A survival analysis was conducted using the Kaplan-Meier method with log-rank tests. Univariate and multi-variate hazard ratios for clinical variables were calculated by fitting Cox Proportional Hazards Models. RESULTS: Early progressors reported a median progression-free survival (PFS) of 142 days compared to 296.5 in standard and 832 days in late progressors (p < 0.0001). Early progressors also harbored distinct and statistically significant differences in gene expression and genomic alterations, namely in DNA damage repair, glucose transport and arginine metabolism pathways. A gene signature was prognostic of PFS and overall survival in a Cox proportional hazards model. CONCLUSIONS: This data may serve as a radiogenomic biomarker to assess treatment response within early phases of treatment and allow for a personalized treatment plan.

A generalized QUCESOP method with evaluating CEST peak overlap.

The overlapping peaks of the target chemical exchange saturation transfer (CEST) solutes and other unknown CEST solutes affect the quantification results and accuracy of the chemical exchange parameters-the fractional concentration, , exchange rate, , and transverse relaxation rate, -for the target solutes. However, to date, no method has been established for assessing the overlapping peaks. This study aimed to develop a method for quantifying the , , and values of a specific CEST solute, as well as assessing the overlap between the CEST peaks of the specific solute(s) and other unknown solutes. A simplified model was proposed, assuming linear approximation of the other solutes' contributions to . A CEST data acquisition scheme was applied with various saturation offsets and saturation powers. In addition to fitting the , , and values of the specific solute, the overlapping condition was evaluated based on the root mean square error (RMSE) between the trajectories of the acquired and synthesized data. Single-solute and multi-solute phantoms with various phosphocreatine (PCr) concentrations and pH values were used to calculate the and of PCr and the corresponding RMSE. The feasibility of RMSE for evaluating the overlapping condition, and the accurate fitting of and in weak overlapping conditions, were verified. Furthermore, the method was employed to quantify the nuclear Overhauser effect signal in rat brains and the PCr signal in rat skeletal muscles, providing results that were consistent with those reported in previous studies. In summary, the proposed approach can be applied to evaluate the overlapping condition of CEST peaks and quantify the , , and values of specific solutes, if the weak overlapping condition is satisfied.

Deep learning for dense Z-spectra reconstruction from CEST images at sparse frequency offsets.

A direct way to reduce scan time for chemical exchange saturation transfer (CEST)-magnetic resonance imaging (MRI) is to reduce the number of CEST images acquired in experiments. In some scenarios, a sufficient number of CEST images acquired in experiments was needed to estimate parameters for quantitative analysis, and this prolonged the scan time. For that, we aim to develop a general deep-learning framework to reconstruct dense CEST Z-spectra from experimentally acquired images at sparse frequency offsets so as to reduce the number of experimentally acquired CEST images and achieve scan time reduction. The main innovation works are outlined as follows: (1) a general sequence-to-sequence (seq2seq) framework is proposed to reconstruct dense CEST Z-spectra from experimentally acquired images at sparse frequency offsets; (2) we create a training set from wide-ranging simulated Z-spectra instead of experimentally acquired CEST data, overcoming the limitation of the time and labor consumption in manual annotation; (3) a new seq2seq network that is capable of utilizing information from both short-range and long-range is developed to improve reconstruction ability. One of our intentions is to establish a simple and efficient framework, i.e., traditional seq2seq can solve the reconstruction task and obtain satisfactory results. In addition, we propose a new seq2seq network that includes the short- and long-range ability to boost dense CEST Z-spectra reconstruction. The experimental results demonstrate that the considered seq2seq models can accurately reconstruct dense CEST images from experimentally acquired images at 11 frequency offsets so as to reduce the scan time by at least 2/3, and our new seq2seq network contributes to competitive advantage.

Beyond slow two-state protein conformational exchange using CEST: applications to three-state protein interconversion on the millisecond timescale.

Although NMR spectroscopy is routinely used to study the conformational dynamics of biomolecules, robust analyses of the data are challenged in cases where exchange is more complex than two-state, such as when a 'visible' major conformer exchanges with two 'invisible' minor states on the millisecond timescale. It is becoming increasingly clear that chemical exchange saturation transfer (CEST) NMR experiments that were initially developed to study systems undergoing slow interconversion are also sensitive to intermediate-fast timescale biomolecular conformational exchange. Here we investigate the utility of the amide 15N CEST experiment to characterise protein three-state exchange occurring on the millisecond timescale by studying the interconversion between the folded (F) state of the FF domain from human HYPA/FBP11 (WT FF) and two of its folding intermediates I1 and I2. Although 15N CPMG experiments are consistent with the F state interconverting with a single minor state on the millisecond timescale, 15N CEST data clearly establish an exchange process between F and a pair of minor states. A unique three-state exchange model cannot be obtained by analysis of 15N CEST data recorded at a single temperature. However, including the relative sign of the difference in the chemical shifts of the two minor states based on a simple two-state analysis of CEST data recorded at multiple temperatures, results in a robust three-state model in which the F, I1 and I2 states interconvert with each other on the millisecond timescale ( ~ 550s-1, ~ 1200s-1, ~ 5000s-1), with I1 and I2 sparsely populated at ~ 0.15% and ~ 0.35%, respectively, at 15°C. A computationally demanding grid-search of exchange parameter space is not required to extract the best-fit exchange parameters from the CEST data. The utility of the CEST experiment, thus, extends well beyond studies of conformers in slow exchange on the NMR chemical shift timescale, to include systems with interconversion rates on the order of thousands/second.

Scan-specific Unsupervised Highly Accelerated Non-Cartesian CEST Imaging using Implicit Neural Representation and Explicit Sparse Prior.

Chemical exchange saturation transfer (CEST) is a promising magnetic resonance imaging (MRI) technique. CEST imaging usually requires a long scan time, and reducing acquisition time is highly desirable for clinical applications. A novel scan-specific unsupervised deep learning algorithm is proposed to accelerate steady-state pulsed CEST imaging with golden-angle stack-of-stars trajectory using hybrid-feature hash encoding implicit neural representation. Additionally, imaging quality is further improved by using the explicit prior knowledge of low rank and weighted joint sparsity in the spatial and Z-spectral domain of CEST data. In the retrospective acceleration experiment, the proposed method outperforms other state-of-the-art algorithms (TDDIP, LRTES, kt-SLR, NeRP, CRNN, and PBCS) for the in vivo human brain dataset under various acceleration rates. In the prospective acceleration experiment, the proposed algorithm can still obtain results close to the fully-sampled images. The hybrid-feature hash encoding implicit neural representation combined with explicit sparse prior (INRESP) can efficiently accelerate CEST imaging. The proposed algorithm achieves reduced error and improved image quality compared to several state-of-the-art algorithms at relatively high acceleration factors. The superior performance and the training database-free characteristic make the proposed algorithm promising for accelerating CEST imaging in various applications.

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.

Spectroscopically dark phosphate features revealed by chemical exchange saturation transfer.

Phosphate is an essential anion in the human body, comprising approximately 1% of the total body weight, and playing a vital role in metabolism, cell membranes, and bone formation. We have recently provided spectroscopic, microscopic, and computational evidence indicating that phosphates can aggregate much more readily in solution than previously thought. This prior work provided indirect evidence through the observation of unusual P NMR relaxation and line-broadening effects with increasing temperature. Here, we show that, under conditions of slow exchange and selective RF saturation, additional features become visible in chemical exchange saturation transfer (CEST) experiments, which appear to be related to the previously reported phosphate clustering. In particular, CEST shows pronounced dips several ppm upfield of the main phosphate resonance at low temperatures, while direct P spectroscopy does not produce any signals in that range. We study the pH dependence of these new spectroscopic features and present exchange and spectroscopic parameters based on fitting the CEST data. These findings could be of importance in the investigation of phosphate dynamics, especially in the biological milieu.

Feasibility of clinical studies of chemical exchange saturation transfer magnetic resonance imaging of prostate cancer at 7 T.

Chemical exchange saturation transfer (CEST) has been explored for differentiation between tumour and benign tissue in prostate cancer (PCa) patients. With ultrahigh field strengths such as 7-T, the increase of spectral resolution and sensitivity could allow for selective detection of amide proton transfer (APT) at 3.5 ppm and a group of compounds that resonate at 2 ppm (i.e., [poly]amines and/or creatine). The potential of 7-T multipool CEST analysis of the prostate and the detection of PCa was studied in patients with proven localised PCa who were scheduled to undergo robot-assisted radical prostatectomy (RARP). Twelve patients were prospectively included (mean age 68.0 years, mean serum prostate-specific antigen 7.8ng/mL). A total of 24 lesions larger than 2 mm were analysed. Used were 7-T T2-weighted (T2W) imaging and 48 spectral CEST points. Patients received 1.5-T/3-T prostate magnetic resonance imaging and galium-68-prostate-specific membrane antigen-positron emission tomography/computerised tomography to determine the location of the single-slice CEST. Based on the histopathological results after RARP, three regions of interest were drawn on the T2W images from a known malignant zone and benign zone in the central and peripheral zones. These areas were transposed to the CEST data, from which the APT and 2-ppm CEST were calculated. The statistical significance of the CEST between the central zone, the peripheral zone, and tumour was calculated using a Kruskal-Wallis test. The z-spectra showed that APT and even a distinct pool that resonated at 2 ppm were detectable. This study showed a difference trend in the APT levels, but no difference in the 2-ppm levels when tested between the central zone, the peripheral zone, and tumour (H(2) = 4.8, p= 0.093 and H(2) = 0.86, p= 0.651, respectively). Thus, to conclude, we could most likely detect APT and amines and/or creatine levels noninvasively in prostate using the CEST effect. At group level, CEST showed a higher level of APT in the peripheral versus the central zone; however, no differences of APT and 2-ppm levels were observed in tumours.

Calf – Software for CEST Analysis with Lorentzian Fitting

Analysis of chemical exchange saturation transfer (CEST) MRI data requires sophisticated methods to obtain reliable results about metabolites in the tissue under study. CEST generates z-spectra with multiple components, each originating from individual molecular groups. The individual lines with Lorentzian line shape are mostly overlapping and disturbed by various effects. We present an elaborate method based on an adaptive nonlinear least squares algorithm that provides robust quantification of z-spectra and incorporates prior knowledge in the fitting process. To disseminate CEST to the research community, we developed software as part of this study that runs on the Microsoft Windows operating system and will be made freely available to the community. Special attention has been paid to establish a low entrance threshold and high usability, so that even less experienced users can successfully analyze CEST data.

Enabling Characterisation of the NAD+ Biosynthesis Pathway via in vitro CEST MRI

AbstractBackgroundThe Chemical Exchange Saturation Transfer (CEST) MRI properties of six metabolites required for synthesis of coenzyme nicotinamide adenine dinucleotide (NAD+) and to evaluate the potential for clinical imaging of altered NAD+ regulation in neurodegenerative disordersMethodCEST images of metabolites in the NAD+ biosynthesis pathway were acquired at physiological temperature with high‐field MRI (9.4T) running a modified magnetisation transfer (MTR) prepared RARE sequence over a range of saturation powers and frequency ofsets, for pH values 5.5‐7.4. CEST data were fitted using spline interpolation, the exchange rate was calculated, and frequency specific MTR maps were generated using pixelwise analysis.ResultTryptophan, nicotinamide, nicotinic acid (NA), nicotinamide riboside (NR), nicotinamide mononucleotide (NMN) and NADH were evaluated. At pH 7.4, all molecules exhibited CEST contrast between 0.1 and 0.9 ppm, originating from the OH hydroxyl proton. NADH exhibited up to 15% CEST contrast in a B1 field of 2.4µT from its fast‐exchanging amine groups at 2 and 3 ppm, and showed a positive dependence of CEST efciency on pH. Tryptophan exhibited three independent peaks at 0.7, 2.6, and 5.4 ppm corresponding to pH 6.7, 5.5 and 7.4. NMN showed high CEST contrast at 0.7ppm originating from its phosphorous OH enabling higher CEST efciency due to enhanced charge delocalisation (Fig.1).ConclusionThis in vitro feasibility study demonstrates signal detection and characterization of NAD+ biosynthesis pathway precursor molecules over precise temperature, concentration and physiological pH ranges. All molecules exhibited a peak at 0.7 from the hydroxyl group with NMN showing highest CEST efficiency due to phosphate charge delocalisation. NADH showed a peak at 2 and 3ppm from amine group protons and a dependency on temperature and pH.

In vivo detection of carnosine and its derivatives using chemical exchange saturation transfer.

PurposeTo detect carnosine, anserine and homocarnosine in vivo with chemical exchange saturation transfer (CEST) at 17.2 T.MethodsCEST MR acquisitions were performed using a CEST‐linescan sequence developed in‐house and optimized for carnosine detection. In vivo CEST data were collected from three different regions of interest (the lower leg muscle, the olfactory bulb and the neocortex) of eight rats.ResultsThe CEST effect for carnosine, anserine and homocarnosine was characterized in phantoms, demonstrating the possibility to separate individual contributions by employing high spectral resolution (0.005 ppm) and low CEST saturation power (0.15 μT). The CEST signature of these peptides was evidenced, in vivo, in the rat brain and skeletal muscle. The presence of carnosine and anserine in the muscle was corroborated by in vivo localized spectroscopy (MRS). However, the sensitivity of MRS was insufficient for carnosine and homocarnosine detection in the brain. The absolute amounts of carnosine and derivatives in the investigated tissues were determined by liquid chromatography–electrospray ionization‐tandem mass spectrometry using isotopic dilution standard methods and were in agreement with the CEST results.ConclusionThe robustness of the CEST‐linescan approach and the favorable conditions for CEST at ultra‐high magnetic field allowed the in vivo CEST MR detection of carnosine and related peptides. This approach could be useful to investigate noninvasively the (patho)‐physiological roles of these molecules.

Two point Dixon-based chemical exchange saturation transfer (CEST) MRI in renal transplant patients on 3 T

PurposeTo assess the performance of two point (2-pt) Dixon-based chemical exchange saturation transfer (CEST) imaging for fat suppression in renal transplant patients. MethodsThe 2-pt Dixon-based CEST MRI was validated in an egg-phantom and in fourteen renal transplant recipients (5 females and 9 males; age range: 23–78 years; mean age: 51 ± 16.8). All CEST experiments were performed on a 3 T clinical MRI scanner using a dual-echo CEST sequence. The 2-pt Dixon technique was applied to generate water-only CEST images at different frequency offsets, which were further used to calculate the z-spectra. The magnetization transfer ratio asymmetry (MTRasym) values in the frequency ranges of hydroxyl, amine and amide protons were estimated in the renal cortex and medulla. ResultsResults of the in vitro experiments suggest that the 2-pt Dixon technique enables effective fat peak removal and does not introduce additional asymmetries to the z-spectrum. Accordingly, our results in vivo show that the fat-corrected amide proton transfer (APT) effect in the kidney is significantly higher compared to that obtained from the CEST data acquired close to the in-phase condition both in the renal cortex (−0.1 [0.7] vs. −0.7 [1.2], P = 0.029) and medulla (0.3 [0.8] vs. 0.01 [1.3], P = 0.049), indicating that the 2-pt Dixon-based CEST method increases the specificity of the APT contrast by correcting the fat-induced artifacts. ConclusionCombination of the dual-echo CEST acquisition with Dixon post-processing provides effective water-fat separation, allowing more accurate quantification of the APT CEST effect in the transplanted kidney.

Brain pH Measurement Using AACID CEST MRI Incorporating the 2 ppm Amine Resonance.

Many pathological conditions lead to altered intracellular pH (pHi) disrupting normal cellular functions. The chemical exchange saturation transfer (CEST) method, known as Amine and Amide Concentration Independent Detection (AACID), can produce image contrast that is predominantly dependent on tissue intracellular pHi. The AACID value is linearly related to the ratio of the 3.5 ppm amide CEST effect and the 2.75 ppm amine CEST effect in the physiological range. However, the amine CEST effect at 2 ppm is often more clearly defined in vivo, and may provide greater sensitivity to pH changes. The purpose of the current study was to compare AACID measurement precision utilizing the 2.0 and 2.75 ppm amine CEST effects. We hypothesized that the 2.0 ppm amine CEST resonance would produce measurements with greater sensitivity to pH changes. In the current study, we compare the range of the AACID values obtained in 24 mice with brain tumors and in normal tissue using the 2 ppm and 2.75 ppm amine resonances. All CEST data were acquired on a 9.4T MRI scanner. The AACID measurement range increased by 39% when using the 2 ppm amine resonance compared to the 2.75 ppm resonance, with decreased measurement variability across the brain. These data indicate that in vivo pH measurements made using AACID CEST can be enhanced by incorporating the 2 ppm amine resonance. This approach should be considered for pH measurements made over short intervals when no changes are expected in the concentration of metabolites that contribute to the 2 ppm amine resonance.

Linear projection-based chemical exchange saturation transfer parameter estimation.

Isolated evaluation of multiparametric in vivo chemical exchange saturation transfer (CEST) MRI often requires complex computational processing for both correction of B0 and B1 inhomogeneity and contrast generation. For that, sufficiently densely sampled Z-spectra need to be acquired. The list of acquired frequency offsets largely determines the total CEST acquisition time, while potentially representing redundant information. In this work, a linear projection-based multiparametric CEST evaluation method is introduced that offers fast B0 and B1 inhomogeneity correction, contrast generation and feature selection for CEST data, enabling reduction of the overall measurement time. To that end, CEST data acquired at 7T in six healthy subjects and in one brain tumor patient were conventionally evaluated by interpolation-based inhomogeneity correction and Lorentzian curve fitting. Linear regression was used to obtain coefficient vectors that directly map uncorrected data to corrected Lorentzian target parameters. L1-regularization was applied to find subsets of the originally acquired CEST measurements that still allow for such a linear projection mapping. The linear projection method allows fast and interpretable mapping from acquired raw data to contrast parameters of interest, generalizing from healthy subject training data to unseen healthy test data and to the tumor patient dataset. The L1-regularization method shows that a fraction of the acquired CEST measurements is sufficient to preserve tissue contrasts, offering up to a 2.8-fold reduction of scan time. Similar observations as for the 7-T data can be made for data from a clinical 3-T scanner. Being a fast and interpretable computation step, the proposed method is complementary to neural networks that have recently been employed for similar purposes. The scan time acceleration offered by the L1-regularization ("CEST-LASSO") constitutes a step towards better applicability of multiparametric CEST protocols in a clinical context.

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.

Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often required to extract the signal of interest. We investigated whether deep learning could help identify pertinent Z-spectral features for distinguishing tumor aggressiveness as well as the possibility of acquiring only the pertinent spectral regions for more efficient CEST acquisition. Human breast cancer cells, MDA-MB-231 and MCF-7, were used to establish bi-lateral tumor xenografts in mice to represent higher and lower aggressive tumors, respectively. A convolutional neural network (CNN)-based classification model, trained on simulated data, utilized Z-spectral features as input to predict labels of different tissue types, including MDA-MB-231, MCF-7, and muscle tissue. Saliency maps reported the influence of Z-spectral regions on classifying tissue types. The model was robust to noise with an accuracy of more than 91.5% for low and moderate noise levels in simulated testing data (SD of noise less than 2.0%). For in vivo CEST data acquired with a saturation pulse amplitude of 2.0 μT, the model had a superior ability to delineate tissue types compared with Lorentzian difference (LD) and magnetization transfer ratio asymmetry (MTRasym ) analysis, classifying tissues to the correct types with a mean accuracy of 85.7%, sensitivity of 81.1%, and specificity of 94.0%. The model's performance did not improve substantially when using data acquired at multiple saturation pulse amplitudes or when adding LD or MTRasym spectral features, and did not change when using saliency map-based partial or downsampled Z-spectra. This study demonstrates the potential of CNN-based classification to distinguish between different tumor types and muscle tissue, and speed up CEST acquisition protocols.

Clinical routine acquisition protocol for 3D relaxation-compensated APT and rNOE CEST-MRI of the human brain at 3T.

The value of relaxation-compensated amide proton transfer (APT) and relayed nuclear Overhauser effect (rNOE) chemical exchange saturation transfer (CEST)-MRI has already been demonstrated in various neuro-oncological clinical applications. Recently, we translated the approach from 7T to a clinically relevant magnetic field strength of 3T. However, the overall acquisition time was still too long for a broad application in the clinical setting. The aim of this study was to establish a shorter acquisition protocol whilst maintaining the contrast behavior and reproducibility. Ten patients with glioblastoma were examined using the previous state-of-the-art acquisition protocol at 3T. The acquired spectral data were retrospectively reduced to find the minimal amount of required information that allows obtaining the same contrast behavior. To further reduce the acquisition time, also the image readout was accelerated and the pre-saturation parameters were further optimized. In total, the overall acquisition time could be reduced from 19 min to under 7 min. One key finding was that, when evaluated by the relaxation-compensated inverse metric, a contrast correction for B1 -field inhomogeneities at 3T can also be achieved reliably with CEST data at only one B1 value. In contrast, a 1-point B1 -correction was not sufficient for the common linear difference evaluation. The reproducibility of the new clinical routine acquisition protocol was similar to the previous state-of-the-art protocol with limits of agreement below 20%. The substantial reduction in acquisition time by about 64% now allows the application of 3D relaxation-compensated APT and rNOE CEST-MRI for examinations of the human brain at 3T in clinical routine.

Effect of offset-frequency step size and interpolation methods on chemical exchange saturation transfer MRI computation in human brain.

Chemical exchange saturation transfer (CEST) MRI is a non-invasive molecular imaging technique with potential applications in pre-clinical and clinical studies. Applications of amide proton transfer-weighted (APT-w), glutamate-weighted (Glu-w) and creatine-weighted (Cr-w) CEST, among others, have been reported. In general, CEST data are acquired at multiple offset-frequencies. In reported studies, different offset-frequency step sizes and interpolation methods have been used during B0 inhomogeneity correction of data. The objective of the current study was to evaluate the effects of different step sizes and interpolation methods on CEST value computation. In the current study, simulation (Glu-w, Cr-w and APT-w) and experimental data from the brain were used. Experimental CEST data (Glu-w) were acquired from human volunteers at 7 T and brain tumor patients (APT-w) at 3 T. During B0 inhomogeneity correction, different interpolation methods (polynomial [degree-1, 2 and 3], cubic-Hermite, cubic-spline and smoothing-spline) were compared. CEST values were computed using asymmetry analysis. The effects of different step sizes and interpolation methods were evaluated using coefficient of variation (CV), normalized mean square error (nMSE) and coefficient of correlation parameters. Additionally, an optimum interpolation method for APT-w values was selected based upon fitting accuracy, T-test, receiver operating characteristic analysis, and its diagnostic performance in differentiating low-grade and high-grade tumors. CV and nMSE increase with an increase in step size irrespective of the interpolation method (except for cubic-Hermite and cubic-spline). The nMSE of Cr-w and Glu-w CEST values were least for polynomial (degree-2 and 3). The quality of Glu-w CEST maps became coarse with the increase in step size. There was a significant difference (P < .05) between low-grade and high-grade tumors using polynomial interpolation (degree-1, 2 and 3); however, linear interpolation outperforms other methods for APT-w data, providing the highest sensitivity and specificity. In conclusion, depending upon the saturation parameters and field strength, optimization of step size and interpolation should be carried out for different CEST metabolites/molecules. Glu-w, Cr-w and APT-w CEST data should be acquired with a step size of between 0.2 and 0.3 ppm. For B0 inhomogeneity correction, polynomial (degree-2) should be used for Glu-w and Cr-w CEST data at 7 T and linear interpolation should be used for APT-w data at 3 T for a limited frequency range.

Quantitative MRI (qMRI) Metrics of Response to Stereotactic Radiosurgery for Brain Metastases

Brain metastases (BM) occur in 20-40 % of all cancer patients and stereotactic radiosurgery (SRS) is an important tool for BM therapy. However, response to therapy after SRS may take several months and is based on tumor dimension change. This study evaluated the predictive capacity of quantitative MRI (qMRI) for response to SRS, using chemical exchange saturation transfer (CEST) and magnetization transfer (MT). Fifty-four BM patients with 61 BM consented to this IRB approved prospective study. qMRI was conducted prior to and at 1-week after SRS treatment (single and hypo-fractionated). Response to SRS was evaluated according to RANO-BM. Tumors with CR, PR, and SD were considered responders (n = 40); tumors with PD or if the patient expired within 2 months after SRS were considered non-responders (n = 21). A single slice through BM was MRI-scanned (CEST & MT) on a 3T Philips scanner. Tumor ROI was identified on the post-Gd T1w and registered to the CEST slice. MT analysis provided the amount of MT, RM0B/RA, and direct water saturation, 1/(RAT2A) parameters. CEST analysis provided MTRAmide (3.5 ppm) and MTRrNOE (-3.5 ppm) that represent the combination of MT, direct saturation and CEST effects. Thus, using the MT analysis results, pure CESTAmide and CESTrNOE signals were also calculated (by removing MT and direct saturation effects from CEST data). The median age of patients was 58 years (35 F, 19 M) with BM most commonly from lung (30), followed by breast (11), melanoma (8), renal (3), liver (2), colon (2), GBM (1), rectum (1), cervix (1), H&N (1) and endometrial (1) cancers. Treatment was delivered in a single fraction with 18-20 Gy (n = 21), 24 Gy in 3 fractions (n = 2) and 25-30 Gy in 5 fractions (n = 38). Responders had a significant reduction in CESTAmide (prior 3.7 ± 1.0 [%], 1-week 3.0 ± 0.9 [%], p = 0.008) and MTRAmide (prior 9.5 ±1.5 [%], 1-week 8.8 ± 1.4 [%], p = 0.048) suggesting a reduction in metabolism. No change was observed for non-responders in CESTAmide (prior 2.8 ± 0.9 [%], 1-week 2.7 ± 0.9 [%], p = 0.77) and MTRAmide (prior 8.8 ± 1.2 [%], 1-week 8.2 ± 1.5 [%], p = 0.22). No other CEST or MT metric differentiated the 2 cohorts. Furthermore, when considering the pre-treatment scans only, we observed significant differences in CESTAmide properties of responders (3.7 ± 1.0 [%]) and non-responders (2.8 ± 0.9 [%]) with p = 0.004. The tumors that responded to SRS showed statistically significantly higher CESTAmide at the pre-treatment scan suggesting the less metabolically active tumors were resistant to radiotherapy. Tumors that respond to SRS experience significant reduction in CESTAmide after SRS while it does not change for non-responders. We also observe that at baseline, qMRI can determine a priori which tumors will subsequently respond to SRS, as those with greater metabolic activity even before treatment (characterized by CESTAmide), suggesting CEST can characterize tumor aggressiveness. Such information may be useful in prescribing the optimal treatment plan.

Quantifying the fractional concentrations and exchange rates of small-linewidth CEST agents using the QUCESOP method under multi-solute conditions in MRI signals.

To develop a novel method for quantifying the fractional concentration (fb ) and the exchange rate (kb ) of a specific small-linewidth chemical exchange saturation transfer (CEST) solute in the presence of other unknown CEST solutes. A simplified R1ρ model was proposed assuming a small linewidth of the specific solute and a linear approximation of the other solutes' contribution to R1ρ . Two modes of CEST data acquisition, using various saturation offsets and various saturation powers, were used. The fb and kb of the specific solute could be fitted using the proposed model. In MRI experiments, using either single-solute or multi-solute phantoms with various creatine concentrations and pHs, the fb and kb values of creatine were calculated for each phantom; the fb and kb values of phosphocreatine in rats' skeletal muscles were also evaluated. The fitted fb value of creatine from the phantoms were in excellent agreement. The fitted kb value of creatine from the phantoms coincides with that from the literature, as do the fb and kb values of phosphocreatine in skeletal muscles. The proposed approach enables us to quantify the fb and kb values of a specific small-linewidth solute in the presence of other unknown solutes.