{'fraction_non_alphanumeric': 0.03138337221874467, 'fraction_numerical': 0.01533602685938656, 'mean_word_length': 4.710316815597076, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 1, 'https://': 1, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A fast and novel method for amide proton transfer‐chemical exchange saturation transfer multislice imaging

Amide proton transfer‐chemical exchange saturation transfer (APT‐CEST) imaging provides important information for the diagnosis and monitoring of tumors. For such analysis, complete coverage of the brain is advantageous, especially when registration is performed with other magnetic resonance (MR) modalities, such as MR spectroscopy (MRS). However, the acquisition of Z‐spectra across several slices via multislice imaging may be time‐consuming. Therefore, in this paper, we present a new approach for fast multislice imaging, allowing us to acquire 16 slices per frequency offset within 8 s. The proposed fast CEST‐EPI sequence employs a presaturation module, which drives the magnetization into the steady‐state equilibrium for the first frequency offset. A second module, consisting of a single CEST pulse (for maintaining the steady‐state) followed by an EPI acquisition, passes through a loop to acquire multiple slices and adjacent frequency offsets. Thus, the whole Z‐spectrum can be recorded much faster than the conventional saturation scheme, which employs a presaturation for each single frequency offset. The validation of the CEST sequence parameters was performed by using the conventional saturation scheme. Subsequently, the proposed and a modified version of the conventional CEST sequence were compared in vitro on a phantom with different T1 times and in vivo on a brain tumor patient. No significant differences between both sequences could be found in vitro. The in vivo data yielded almost identical MTRasym contrasts for the white and gray matter as well as for tumor tissue. Our results show that the proposed fast CEST‐EPI sequence allows for rapid data acquisition and provides similar CEST contrasts as the modified conventional scheme while reducing the scanning time by approximately 50%.

Amide proton transfer-chemical exchange saturation transfer (APT-CEST) imaging provides important information for the diagnosis and monitoring of tumors. For such analysis, complete coverage of the brain is advantageous, especially when registration is performed with other magnetic resonance (MR) modalities, such as MR spectroscopy (MRS). However, the acquisition of Z-spectra across several slices via multislice imaging may be time-consuming. Therefore, in this paper, we present a new approach for fast multislice imaging, allowing us to acquire 16 slices per frequency offset within 8 s. The proposed fast CEST-EPI sequence employs a presaturation module, which drives the magnetization into the steady-state equilibrium for the first frequency offset. A second module, consisting of a single CEST pulse (for maintaining the steady-state) followed by an EPI acquisition, passes through a loop to acquire multiple slices and adjacent frequency offsets. Thus, the whole Z-spectrum can be recorded much faster than the conventional saturation scheme, which employs a presaturation for each single frequency offset. The validation of the CEST sequence parameters was performed by using the conventional saturation scheme. Subsequently, the proposed and a modified version of the conventional CEST sequence were compared in vitro on a phantom with different T1 times and in vivo on a brain tumor patient. No significant differences between both sequences could be found in vitro. The in vivo data yielded almost identical MTR asym contrasts for the white and gray matter as well as for tumor tissue. Our results show that the proposed fast CEST-EPI sequence allows for rapid data acquisition and provides similar CEST contrasts as the modified conventional scheme while reducing the scanning time by approximately 50%.

| INTRODUCTION
Amide proton transfer-chemical exchange saturation transfer (APT-CEST) represents a technique for the imaging of low-concentration compounds with exchangeable protons that provides a sensitive contrast towards the intracellular pH (pH i ), but also contain information about protein and peptide concentrations. [1][2][3][4][5][6] In a previous study, different APT-CEST metrics were compared with pH i maps, generated via 31 P-MRS to verify the pH dependence of the APT contrast. 7 To achieve a combined evaluation between both magnetic resonance (MR) modalities across several slices, sufficient coverage of the brain is required for CEST imaging to improve the coregistration. Since the acquisition of a full Z-spectrum is time-consuming, especially when several slices are recorded, different approaches have been proposed for clinical investigations, which allow the acquisition of CEST data in a clinically acceptable time, such as the acquisition of a few selected frequency offsets 8 or the implementation of keyhole techniques. 9 Another previous study modified the conventional multislice CEST sequence to shorten scanning time by dividing the radiofrequency (RF) irradiation scheme into a long and a short module. 10 While the long RF saturation module drives the magnetization into the steady state, the repetitive short RF irradiation module maintains the CEST contrast for multislice acquisition and measurement repetitions for a specific frequency offset. It could be demonstrated that this scheme provides almost identical CEST contrasts as a conventional multislice CEST technique, where one long RFirradiation module is used for the acquisition of each slice.
However, this scheme is still time-consuming due to the insertion of regular presaturation delays (for relaxation recovery) and the long primary saturation module prior to each new frequency offset. In this study, we modify the method of Sun et al. 10 and propose two schemes (dubbed "CEST SS " and "CEST fast ") that maintain the CEST contrast for multislice imaging. While the steady-state scheme (CEST SS ) is similar to the sequence presented by Sun et al, 10 the CEST fast sequence represents a new approach, which applies the long saturation module only for the first frequency offset and thus saves almost half of the measurement time. Both sequences were compared in vitro and in vivo.

| Phantom and subjects
A cylindrical phantom containing three 50-mL Falcon tubes was prepared for sequence comparison. Each tube contained a phosphate buffer solution doped with sodium chloride (NaCl) and 10 g of edible gelatin to provide proteins for the required CEST effect. In addition, all the tubes were set to different T1 values of approximately 450, 850 and 1300 ms by adapting the concentration of Gadovist, as described previously. 11,12 Before heating the solution in a microwave oven, the mixture in all tubes was stirred and the pH value was adjusted with a 1 mmoL/L solution of potassium hydroxide (KOH) to achieve a pH of approximately 7.0. After the preparation, the pH values in the gelled state were measured via pH strips and readjusted with KOH after previous heating, if necessary.
For in vivo measurements, a patient with a brain tumor (glioblastoma) was scanned, applying both CEST sequences, as described in the next section. The study was approved by the local ethics committee of the University Hospital, and the subject gave written informed consent before scanning.

| CEST sequences
The acquisition of a Z-spectrum requires the readout of the longitudinal magnetization after sufficient saturation via RF pulses with different frequency offsets. These offsets usually cover a range of several ppm symmetrically around the water signal. In our previous work, we applied a train of rectangular RF pulses with a total duration of 8 s prior to each single-slice echo-planar imaging (EPI) readout, which was repeated for several frequency offsets. 7 A similar scheme was used by Sun et al. 13 on a 4.7-T animal scanner, acquiring several consecutive EPI slices after the saturation period to obtain multislice data. However, this approach requires additional postprocessing to correct for the relaxation-induced loss of CEST contrast for each slice. Sun et al. further showed that a short additional saturation period for every single slice is sufficient to maintain a steadystate saturation, thus avoiding the requirement of a slice-specific correction via postprocessing. 10 Based on these findings, we designed the steady-state CEST-EPI (CEST SS ) sequence ( Figure 1A). The schematic representation shows an initial CEST saturation module (red) and an acquisition module (black).
The CEST saturation module executes repetitively a basic module, consisting of a single rectangular pulse of duration δ, followed by a delay time of equal duration. The delay further includes a spoiler gradient (S) to disperse transverse magnetization and a fat suppression (FS) module.
Assuming that FS does not interfere with the CEST saturation, repetitive application of this basic module can be used for establishing the steadystate magnetization for CEST imaging. Thus, the module is embedded in a dummy scan loop with N dummy repetitions, using for each RF pulse a constant amplitude of B 1 , which is sufficient to achieve the steady-state CEST contrast at a defined frequency offset (ω).
The acquisition module is similar to the basic module but includes a single-slice EPI readout after the FS in the delay. It is important to note that the modified delay with the inserted EPI readout has the same duration δ as the delay in the basic module, so timings in both modules (CEST saturation and acquisition) are identical, thus maintaining the steady state. Multislice imaging is achieved by embedding the acquisition module in a slice loop (N slices ) while maintaining the steady-state magnetization with a single RF saturation pulse.
In the CEST SS sequence ( Figure 1A), both the CEST saturation module and the subsequent acquisition module are repeated in a frequency offset loop, that is, for each frequency offset ω, the basic module is repeated N dummy times before multislice imaging is performed with the acquisition module across N slices at the same ω. Phase and read encodings are not shown in the figure for the sake of clarity.
To shorten the scanning time, the steady-state sequence is modified, as shown in the proposed scheme for the fast CEST-EPI (CEST fast ) sequence ( Figure 1B). Here, only the acquisition module is embedded in the frequency offset loop (i.e. the initial CEST saturation module is applied only for the first frequency offset to achieve the steady-state frequency-selective saturation). This is based on the assumption that the saturation pulse in the acquisition module is sufficient to maintain the steady state, provided the difference between subsequent values of ω is small and does not exceed 0.5 ppm (approximately 60 Hz). Thus, the acquisition module can be executed continuously for all slices and adjacent frequency offsets.
In this study, the CEST SS sequence was used as a reference method and compared with the proposed CEST fast sequence. The number of saturation pulses, as well as the irradiation power B 1 , were varied to achieve the optimal values for improving the saturation efficiency α. The corresponding results are presented in the supporting information ( Figures S.1-S.3). In addition, the Z-spectra of the multislice CEST fast sequence were simulated based on an analytical solution of the Bloch-McConnell equations. The Matlab code is provided by the project "CEST sources", which is available under https://www.cest-sources.org. The corresponding calculation of the longitudinal relaxation rate in the rotating frame can be found in the work of Zaiss and Bachert. 14 The modification and results of the simulation are shown in the supporting information.

| MRI experiments
Experiments were performed on a 3-T whole-body MRI system (MAGNETOM Prisma; Siemens Healthineers, Erlangen, Germany) using a body transmit and a 20-channel phase-array head/neck receive coil.
F I G U R E 1 Schematic depiction of the multislice chemical exchange saturation transfer (CEST) sequences (CEST SS and CEST fast ) with echoplanar imaging (EPI) acquisition. A, The steady-state CEST-EPI sequence employs a basic module embedded in a loop to achieve a sufficient number of dummy scans (N dummy ) to generate a steady-state saturation prior to each volume of data acquisition (CEST saturation module [red]). Each repetition of the dummy loop contains a single rectangular pulse of duration δ and a spoiler gradient S to disperse transverse magnetization, followed by a fat suppression (FS) module. The subsequent multislice acquisition module (black) comprises a single rectangular pulse followed by S, FS and an EPI readout within a slice loop ([N slices ]). Both loops (N dummy and N slices ) are repeated for each new frequency offset (ω). B, The proposed fast CEST-EPI sequence is similar to A except for different positioning of the frequency offset loop. In detail, the CEST saturation module is only performed once at the beginning for the first frequency offset. This initial dummy scan drives the magnetization into a steady state, which is then maintained throughout the N slices and Δω loops with the acquisition module T 1 mapping was based on the variable flip angle (VFA) method, [15][16][17] for which two three-dimensional RF-spoiled gradient echo (GE) datasets with different excitation angles (FA 1 , FA 2 ) were acquired. The following image parameters were used: isotropic spatial resolution of 1 x 1 x 1 mm 3 , field of view (FoV) = 256 x 224 x 160 mm 3 , TR/TE/FA 1 /FA 2 = 16.4/6.7 ms/4 /24 , bandwidth = 222 Hz/pixel. To correct T 1 for B 1 inhomogeneities, two additional datasets were acquired using two-dimensional GE with and without magnetization preparation via a 45 RF pulse. 18 For assessment of the tumor anatomy, T 2 -weighted turbo spin echo (TSE) data were acquired with: TE/TR = 102/4920 ms, FoV = 192 x 192 mm 2 , echo spacing = 16.9 ms, spatial resolution = 1.5 x 1.5 x 3 mm 3 and 25 slices.
For APT-CEST imaging, the two sequences (CEST SS , CEST fast ) as described above were employed. Sequence parameters related to the saturation were optimized on a phantom with the CEST SS sequence (as described in the supporting information), resulting in a rectangular pulse with B 1 = 1 μT, duration δ = 250 ms and N dummy = 16 for 8 s. The Z-spectra were acquired in the range from −8 to +8 ppm relative to the water signal according to the following scheme: 4. The spectral range from +3 to +4 ppm with an increment of 0.1 ppm (CEST SS : 2 min 58 s; CEST fast : 1 min 36 s).
Each step was performed twice successively, using two different echo times (TE 1 , TE 2 ) in the acquisition module and recording magnitude and phase data to perform a Dixon correction for the suppression of lipid artifacts in the EPI data. 19 A reference image (S 0 ) without RF irradiation (B 1 = 0 μT) was acquired additionally (an average of four measurement repetitions). Parameters for the image acquisition module were: While the acquisition of a volume with 16 slices via CEST SS takes 16 s, the CEST fast requires the same time only for the first frequency offset of a run. For each subsequent frequency offset, the time is reduced to 8 s, which corresponds to a time saving of almost 50%.

| Postprocessing
Image processing was performed in MATLAB (MathWorks, Natick, MA, USA) and with the software FSL version 6.0. 1. 20 First, EPI data were corrected for lipid artifacts by voxelwise addition of the complex (phase and magnitude) image data recorded with different TE, where the signals of water and fat are in-phase (TE 1 ) and 180 out-of-phase (TE 2 ). 21 Afterwards, all images were sorted according to the saturation frequency and merged along the fourth dimension for motion correction via FLIRT, 22 followed by brain extraction (for in vivo data) via BET. 23 The resulting images were divided by the motion-corrected and averaged reference dataset S 0 . Subsequently, Z-spectra were fitted with an inverted Lorentzian function from ω = −1 to +1 ppm, to detect the center of each Z-spectrum with the lowest signal intensity according to Equation ( Table 1). The Levenberg-Marquardt algorithm, as implemented in MATLAB's nonlinear curve fitting toolbox, was used to fit the data. A bisquare weighting was applied to reduce the impact of outliers on the fit.
To assess the quality of the inverted Lorentzian fit, the root-mean-square error (RMSE) was calculated for each voxel and plotted on a parametric RMSE map. After fitting the whole Z-spectrum with a four-pool model, the asymmetry MT ratio (MTR asym ) was calculated using Equation (3).
For the in vitro experiments, a region of interest (ROI) analysis was performed. The ROI was placed around the center of each tube, covering eight slices. Mean values and standard deviations (SD) were obtained for each slice and the entire volume as part of the sequence comparison. To estimate the sensitivity of each sequence, the contrast-to-noise ratio (CNR) was calculated according to Equation (4), where Sa and Sb are the signal intensities from two different tubes and σ is the SD of the background noise.
The evaluation of the in vitro data yielded B 0 -corrected Z-spectra and the calculated MTR asym values.
For the in vivo experiments, ROIs and volumes of interest (VOIs) were generated from quantitative T 1 (qT 1 ) data. For qT 1 mapping, the two GE datasets acquired at different flip angles were coregistered, subjected to brain extraction and tissue segmentation via BET 23 and FAST, 25 and processed as described in the literature to correct for insufficient RF spoiling 15 and B 1 inhomogeneities. 18 Subsequently, the unsaturated CEST reference was coregistered to the T 1 map with FLIRT, 22 employing the boundary-based registration via the white matter (WM) segmentation.
Afterwards, the WM and gray matter (GM) probability maps, derived from the T 1 map, were transferred back into the original space of the CEST data. For further evaluation, only voxels with a probability of at least 80% of belonging to the respective tissue type were considered. Additionally, a tumor VOI was defined by an experienced neuroradiologist based on the T 2 -weighted image, which was subsequently coregistered to the CEST space with FLIRT.
Quantitative comparison of the CEST SS and CEST fast sequences was performed on a representative slice with tumor tissue, according to the parameterized maps from Z B0 (+3.5 ppm), MTR asym (3.5 ppm) and the RMSE. In addition, subtraction maps between the two sequences were calculated based on the parameterized maps for Z B0 (+3.5 ppm) and MTR asym (  There is very good agreement between the Z-spectra obtained with the different sequences, independent from T 1 . In particular, comparison of both CEST SS data acquired with (blue) and without (red) the 10-s relaxation delay shows that omission of the delay does not affect the acquisition of subsequent frequency offsets. Furthermore, there is no significant difference between the data acquired with both CEST SS and the CEST fast sequence, which confirms the applicability of the proposed saturation scheme.
The data in Table 2 confirm these observations for Z B0 (+3.5 ppm), showing that all sequences yield nearly equal values within the image noise level (δ) of 0.005 = 0.5%, which is in agreement with the measured SD within the VOI.  Table 3 and confirm these observations. Figure 3B shows Z-spectra and MTR asym data for the tube with T 1 = 850 ms overlaid for all slices (different colors), both for CEST SS (left) and CEST fast (right). Both sequences yield almost identical results with rather marginal differences between the slices. Concerning MTR asym , minor differences can be found in the spectral range of Δω = 0-2 ppm, which can be attributed to insufficient B 0 correction. More details and further results for all three tubes are given in Table S.4. In summary, there is a high correlation between the MTR asym (3.5 ppm) results obtained with CEST SS and CEST fast (r = 0.94, p = .012), as well as contrast consistency across all slices.  shows regional differences in the area of GM ($0.01) or parts of tumor tissue ($0.05), while larger differences of 0.1-0.16 were observed for ventricular and cortical cerebrospinal fluid (CSF). Those observations may be attributed to partial volume effects from components with rather long T 1 or may arise from not fully relaxed equilibrium magnetization, due to the limited repetition time of 8 s.
For MTR asym , regional differences are significantly reduced since all effects that are symmetric regarding the water frequency are canceled during the calculation. The remaining contrast, which includes the APT-CEST effect, clearly indicates the tumor area. Average values for each tissue VOI within the slice are similar between sequences (GM steady-state/fast = −0.031 ± 0.021/-0.030 ± 0.019, WM steady-state/fast = −0.043 ± 0.016/ -0.041 ± 0.013, and tumor steady-state/fast = −0.014 ± 0.009/-0.010 ± 0.011). Consequently, the subtraction map shows relatively low residual differences, except for regions of cortical and ventricular CSF, as well as single voxels close to CSF compartments. In those areas, higher intensities of the RMSE maps indicate reduced fitting accuracy for the Z-spectra. Figure 5A shows the difference between MTR asym (3.  Figure 5B confirms the increased difference between the results obtained with both sequences in the frontal brain regions, while Figure 5C indicates distortions in these areas due to higher field inhomogeneities, which correlate with the larger deviations. Concerning tumor tissue, lower IQR (IQR tumor slice 4-11 ≈ 0.006) are revealed, corresponding to our findings via the subtraction map, in which the tumor is no longer visible.
F I G U R E 5 A, Boxplot analysis of the difference between MTR asym (3.5 ppm) values obtained with the CEST SS and CEST fast sequences for white matter (WM), gray matter (GM) and tumor tissue across all 16 slices. B, Corresponding subtraction map of MTR asym (3.5 ppm), indicating differences between both sequences. C, Corresponding unsaturated reference dataset (S 0 ) for structural information Figure 6A provides a sequence comparison via a Bland-Altman diagram, in which for each MTR asym (3.5 ppm) value, the difference of results obtained with both sequences is plotted versus the mutual mean. For this purpose, a ROI was created in slice 7, covering parts of WM, deeper GM and tumor tissue, as indicated by the red shaded area. The broad distribution of the mutual mean values on the x-axis represents WM and deeper GM on the left, and tumor on the right. The mean difference (M D ) is almost zero (M D = −0.007), indicating almost identical CEST contrasts for both sequences. In addition, the majority of the differences on the y-axis occur within the 95% confidence interval range (−0.021/+0.005), which is smaller than the expected CEST effect via MTR asym of 0.03-0.05. This criterion does not apply to the 7% of differences outside the confidence interval, due to residual artifacts induced by partial volume effects. A correlation between both methods in the selected ROI reveals good agreement between both sequences and no significant differences (r = 0.86, p < .001).
In addition, to check whether the contrast is preserved between tumor and WM or GM, Figure 6B shows MTR asym values for the respective tissue types. Comparable distributions and median values are shown for both sequences.

| DISCUSSION
In this study, a novel and fast scheme for APT-CEST multislice imaging was proposed to speed up measurement time by almost 50%, comprising a CEST saturation and an acquisition module. The CEST saturation part includes a basic module, embedded in a loop with N dummy repetitions, consisting of a rectangular saturation pulse of 250 ms duration (the longest pulse duration that was feasible on the respective MR system) followed by a delay of the same duration. The delay includes a crusher gradient followed by a FS module. The acquisition module is similar to the CEST saturation module, but contains a single-slice EPI acquisition after previous FS during the delay time. While the CEST saturation module is used to F I G U R E 6 Bland-Altman plot for data within a ROI consisting of white matter (WM), deeper gray matter (GM) and tumor tissue to investigate the correspondence between both sequences. While the mean value of the differences is close to zero (black line), 93% of the data are located within the confidence interval, which is two times the standard deviation (red lines) achieve the steady-state magnetization for the first frequency offset ω, the acquisition module maintains this state and performs the recording of several slices and adjacent frequency offsets. Thus, the CEST saturation module can be omitted for further Z-spectrum acquisition, which reduces the measurement time.
Previous research has already shown that it is uncritical to subdivide a long saturation pulse with a duration of 2-4 s into several short pulses that complement each other in sum. 13,26 Based on a duty cycle of 50% used in this study, the CEST effect would be initially reduced, so the steady-state and therefore also the APT-CEST effect gradually build up with each saturation pulse. It is also possible to acquire multiple slices, since the CEST effect increases with each additional pulse per slice. However, the first few slices may be discarded as the steady state has not yet been fully reached. Since this effect also depends on the sequence parameters, initial experiments were performed based on the CEST SS sequence with an additional relaxation delay of 10 s, which is almost similar to the method proposed by Sun et al. 10 As a minimum, eight saturation pulses with a duration of 250 ms each were sufficient to achieve the steady state for the maximum tested T 1 of 1300 ms. To account for the increased tumor T 1 , the number of saturation pulses was doubled from N dummy = 8 (duration = 4 s) to N dummy = 16 (duration = 8 s). Further, the optimal B 1 lay between 0.9 and 1.2 μT (Figures S.1 and S.2). While lower B 1 values led to an inferior saturation efficiency α, higher B 1 caused a broadening of the saturation peak of the amides in the Z-spectrum, accompanied by increased direct water saturation and thus a reduction of MTR asym values. 27,28 Therefore, a B 1 of 1 μT was chosen, yielding a saturation efficiency α of approximately 99%. This irradiation power has also been recommended for APT-CEST tumor imaging at 3 T to achieve the maximum contrast. 29 The in vitro results showed a perfect correlation of the Z-spectra obtained with both CEST SS sequences (with and without relaxation delay).
Although the acquisition for each new frequency offset did not start with a completely relaxed spin system in the case of CEST SS without relaxation delay, the data show that the achievement of full spin relaxation via adding a relaxation delay of 10 s does not affect the steady-state saturation and is therefore not required. Further, the Z-spectra show good agreement with the Z-spectra obtained with the CEST fast sequence, indicating that the frequency-selective presaturation can be omitted when using the proposed saturation scheme.
The visual inspection of parametrized MTR asym (3.5 ppm) maps revealed a good contrast in vitro as well as in vivo for tumor tissue versus WM for both sequences, without any significant differences between sequences in the subtraction maps. Residual contrast differences, in voxels containing CSF, were probably due to poor motion correction and a slow drift in scanner hardware, considering the total scanning time of 48 min 24 s. According to the manufacturer, the drift of the static magnetic field of the MR system used for this study is relatively low when using an EPI sequence. For a quantitative assessment, the method proposed by Windschuh et al. was applied, performing a linear interpolation between two B 0 maps, which were acquired at different time points. 30 In our study, the time difference between both images was 16 min, yielding an average drift of about 0.25 Hz/min within a VOI across the WM and GM. The resulting signal drift during the total measurement time of the sequence comparison ($48 min) was thus about 12 Hz (0.1 ppm), which can be deemed to be negligible.
However, motion-induced variations in CSF partial volumes at a spatial resolution of 3 x 3 x 4 mm 3 will have a noticeable impact on the subtraction maps. This might also explain the increased differences near the cortical structures (Figures 4 and 5).
In addition, Figure 5B shows higher MTR asym differences (>0.05) around the frontal brain within the first four slices, resulting from magnetic field distortions in anatomic regions that are typically affected by this effect. Those susceptibility artefacts can also be seen at almost the same positions in the unsaturated reference data S 0 ( Figure 5C), affecting the signal level, thus leading to inaccurate local B 0 -corrected values. Furthermore, it was shown in the simulation that there is a stronger pseudo-bleed-over effect for larger increments such as 0.5 ppm according to the CEST fast sequence for the first few slices, which hampers an adequate B 0 correction. As a result from both effects, this inaccuracy affects the difference between both calculated MTR asym maps. By excluding the first four slices, no significant differences could be found for WM and GM across the slices 5-16. Besides this artifact, the results indicate that at least 50% of the data deviated by less than 0.01 from the median value.
For tumor tissue, signal differences are smaller, which might be attributed to the fact that the respective VOI represents a smaller and more welldefined area.
Furthermore, a small but consistently negative median value was found for the subtraction maps in all VOIs and almost every slice, which is also visible in the Bland-Altman plot. However, Figures 5 and 6 show that this bias is negligible, residing in the range of the observed standard deviation for the in vitro data. In addition, Figure 6B shows that the contrast between tumor tissue and WM/GM is retained with both sequences.
Since the SNR efficiency is defined as the SNR per square root of the measurement time, the proposed fast sequence would increase the efficiency by about 40% compared with the standard sequence. In this study, the signal gain was calculated based on the mean signal of the images, since both sequences generated the same background noise levels. This may be due to the use of identical EPI acquisition parameters (e.g. matrix size, receiver bandwidth, spatial resolution, phase-encoding direction). According to a previous study, 31 image noise levels can in fact be expected to be similar for different sequences, provided all noise-relevant parameters are identical. Examination of the sensitivities of the sequences compared via CNR analysis indicates similar values for both CEST SS sequences (CNR = 1.6). However, the CEST fast sequence has a slightly increased CNR of 1.8, which suggests a slightly improved sensitivity.
To improve the SNR and CNR, an optimization of the flip angle during the EPI acquisition might be used in future studies. Such optimization may be essential because a large flip angle significantly perturbs the CEST steady state, which may not be fully recovered under a short duration of 0.5 s between subsequent RF pulses. 10 In addition, a further modification of the sequence is conceivable to acquire data for a specific frequency offset several times in succession.
The sequence design allows flexible adjustment of the RF irradiation in the CEST saturation and acquisition module for increased T 1 values.
For example, our current sequence settings would only allow for relaxation to about 93% of the equilibrium magnetization at a T 1 of 3000 ms for the TR chosen (8 s). By simply increasing the number of slices (N slices ), a longer TR could be achieved while further improving the saturation efficiency α with each additional slice. Apart from lengthening TR, the in-plane resolution can be further improved by increasing the matrix size, making use of the relatively long waiting time after each EPI readout. Moreover, the sequence allows the recording of certain spectral sections 50% faster compared with the conventional CEST SS sequence.
Results of the simulation show that a Z-spectrum with the interval of 0.1-0.25 ppm ($12-31 Hz) is highly suitable for the proposed sequence. Thus, for future studies, the measurement time might be further shortened by only recording necessary subranges of the Z-spectrum.
In the case of a larger increment (e.g. 0.5 ppm) between the offsets, it is recommended to simply acquire more slices and exclude the first few because of insufficient saturation. Alternatively, adjusting the number of pulses to the selected increment size before switching the frequency offset will be considered for future studies. Thus, if the data are recorded at higher field strengths such as 7 T, it is suggested to adjust the increment to 30 Hz for a fine sampling. However, this will almost double the number of offsets compared with 3 T, so the measurement would take longer.
Besides modifying the bandwidth of the increment, the acquisition of more slices due to longer T1 values might be a solution to compensate larger increments such as 60 Hz.
The advantage of the proposed sequence with the adjacent acquisition scheme depends on the number of points used to cover the APT-CEST region. In principle, there is no difference to the method of Sun et al. 10 compared with sampling just one point at +3.5 ppm and one at −3.5 ppm (which would require a robust B 0 correction), while for two points around +3.5 and −3.5 ppm, we almost gain 50% when a small step size is used.
With the proposed method and assuming a maximum step size of 0.2 ppm, one could divide the interval between 3 and 4 ppm by the number of averages required for sufficient accuracy (also taking into account outliers due to motion) and distribute them with equidistant increments across this interval. The total acquisition time would still match the time required for repetitive acquisition of 1 point, while the gain in accuracy due to a robust fit should at least compensate for the increased SNR obtained by repetitive sampling of just one point in the Z-spectrum.
A limitation may arise in multislice imaging, as each slice including the preceding saturation pulse requires 0.5 s, yielding a total of 8 s for each volume. In fact, any movement during volume acquisition can hamper adequate movement correction as it is applied in standard fMRI studies.
However, it should be taken into account that the proposed acquisition scheme also offers the opportunity to discard heavily blurred volumes and to compensate them on the basis of data fitting.

| CONCLUSION
In summary, we have shown that the proposed fast CEST-EPI sequence (CEST fast ) can be used for more rapid APT-CEST imaging. Compared with the modified conventional steady-state sequence (CEST SS ), this method offers a speeding up by almost 50% while providing similar MTR asym contrast.