Optimal sampling schedule for chemical exchange saturation transfer

Detection of tissue pH with quantitative chemical exchange saturation transfer magnetic resonance imaging

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a novel means for sensitive detection of dilute labile protons and chemical exchange rates. By sensitizing to pH-dependent chemical exchange, CEST MRI has shown promising results in monitoring tissue statuses such as pH changes in disorders like acute stroke, tumor, and acute kidney injury. This article briefly reviews the basic principles for CEST imaging and quantitative measures, from the simplistic asymmetry analysis to multipool Lorentzian decoupling and quasi-steady-state reconstruction. In particular, the advantages and limitations of commonly used quantitative approaches for CEST applications are discussed.

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 7 T 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.

Quantitative chemical exchange saturation transfer imaging of nuclear overhauser effects in acute ischemic stroke

PURPOSE

In chemical exchange saturation transfer imaging, saturation effects between - 2 to - 5 ppm (nuclear Overhauser effects, NOEs) have been shown to exhibit contrast in preclinical stroke models. Our previous work on NOEs in human stroke used an analysis model that combined NOEs and semisolid MT; however their combination might feasibly have reduced sensitivity to changes in NOEs. The aim of this study was to explore the information a 4-pool Bloch-McConnell model provides about the NOE contribution in ischemic stroke, contrasting that with an intentionally approximate 3-pool model.

METHODS

MRI data from 12 patients presenting with ischemic stroke were retrospectively analyzed, as well as from six animals induced with an ischemic lesion. Two Bloch-McConnell models (4 pools, and a 3-pool approximation) were compared for their ability to distinguish pathological tissue in acute stroke. The association of NOEs with pH was also explored, using pH phantoms that mimic the intracellular environment of naïve mouse brain.

RESULTS

The 4-pool measure of NOEs exhibited a different association with tissue outcome compared to 3-pool approximation in the ischemic core and in tissue that underwent delayed infarction. In the ischemic core, the 4-pool measure was elevated in patient white matter ( 1 . 20 ± 0 . 20 ) and in animals ( 1 . 27 ± 0 . 20 ). In the naïve brain pH phantoms, significant positive correlation between the NOE and pH was observed.

CONCLUSION

Associations of NOEs with tissue pathology were found using the 4-pool metric that were not observed using the 3-pool approximation. The 4-pool model more adequately captured in vivo changes in NOEs and revealed trends depending on tissue pathology in stroke.

Clinical translation of amide proton transfer (APT) MRI for ischemic stroke: a systematic review (2003-2020)

Amide proton transfer (APT) magnetic resonance imaging (MRI) is a pH-sensitive imaging technique that can potentially complement existing clinical imaging protocol for the assessment of ischemic stroke. This review aims to summarize the developments in the clinical research of APT imaging of ischemic stroke after 17 years of progress since its first preclinical study in 2003. Three electronic databases: PubMed, Scopus, and Cochrane Library were systematically searched for articles reporting clinical studies on APT imaging of ischemic stroke. Only articles in English published between 2003 to 2020 that involved patients presenting ischemic stroke-like symptoms that underwent APT MRI were included. Of 1,093 articles screened, 14 articles met the inclusion criteria with a total of 282 patients that had been scanned using APT imaging. Generally, the clinical studies agreed APT effect to be hypointense in ischemic tissue compared to healthy tissue, allowing for the detection of ischemic stroke. Other uses of APT imaging have also been investigated in the studies, including penumbra identification, predicting long term clinical outcome, and serving as a biomarker for supportive treatment monitoring. The published results demonstrated the potential of APT imaging in these applications, but further investigations and larger trials are needed for conclusive evidence. Future studies are recommended to report the result of asymmetry analysis at 3.5 ppm along with the findings of the study to reduce this contribution to the heterogeneity of experimental methods observed and to facilitate effective comparison of results between studies and centers. In addition, it is important to focus on the development of fast 3D imaging for full volumetric ischemic tissue assessment for clinical translation.

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

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

Partial volume correction for quantitative CEST imaging of acute ischemic stroke

Purpose

Contributions of cerebrospinal fluid (CSF) have not been previously taken into account in the quantification of APT CEST effects, and correction for the dilution of CEST effects by CSF may allow for more robust measurement of CEST signals. The objective of this study was to compare the robustness of a partial volume (PV) correction model against a standard (4‐pool) multi‐pool model as far as their ability to quantify CEST effects in healthy, normal, and pathological tissue.

Methods

MRI data from 12 patients presenting with ischemic stroke, and 6 healthy subjects, were retrospectively analyzed. CEST signals derived from a 4‐pool model and a PV correction model were compared for repeatability and pathological tissue contrast. The effect of PV correction (PVC) was assessed within 3 ranges of tissue PV estimate (PVE): high PVE voxels, low PVE voxels, and the whole slice.

Results

In voxels with a high tissue PVE, PV correction did not make a significant difference to absolute APTR*. In low PVE voxels, the PVC model exhibited a significantly decreased ischemic core signal. The PVC measures exhibited higher repeatability between healthy subjects (4 pools: 3.4%, PVC: 2.4%) while maintaining a similar ischemic core CNR (0.7) to the 4‐pool model. In whole slice analysis it was found that both models exhibited similar results.

Conclusions

PV correction yielded a measure of APT effects that was more repeatable than standard 4‐pool analysis while achieving a similar CNR in pathological tissue, suggesting that PV‐corrected analysis was more robust at low values of tissue PVE.

Quantitative CEST imaging of amide proton transfer in acute ischaemic stroke

BACKGROUND

Amide proton transfer (APT) imaging may help identify the ischaemic penumbra in stroke patients, the classical definition of which is a region of tissue around the ischaemic core that is hypoperfused and metabolically stressed. Given the potential of APT imaging to complement existing imaging techniques to provide clinically-relevant information, there is a need to develop analysis techniques that deliver a robust and repeatable APT metric. The challenge to accurate quantification of an APT metric has been the heterogeneous in-vivo environment of human tissue, which exhibits several confounding magnetisation transfer effects including spectrally-asymmetric nuclear Overhauser effects (NOEs). The recent literature has introduced various model-free and model-based approaches to analysis that seek to overcome these limitations.

OBJECTIVES

The objective of this work was to compare quantification techniques for CEST imaging that specifically separate APT and NOE effects for application in the clinical setting. Towards this end a methodological comparison of different CEST quantification techniques was undertaken in healthy subjects, and around clinical endpoints in a cohort of acute stroke patients.

METHODS

MRI data from 12 patients presenting with ischaemic stroke were retrospectively analysed. Six APT quantification techniques, comprising model-based and model-free techniques, were compared for repeatability and ability for APT to distinguish pathological tissue in acute stroke.

RESULTS

Robustness analysis of six quantification techniques indicated that the multi-pool model-based technique had the smallest contrast between grey and white matter (2%), whereas model-free techniques exhibited the highest contrast (>30%). Model-based techniques also exhibited the lowest spatial variability, of which 4-pool APTR∗ was by far the most uniform (10% coefficient of variation, CoV), followed by 3-pool analysis (20%). Four-pool analysis yielded the highest ischaemic core contrast-to-noise ratio (0.74). Four-pool modelling of APT effects was more repeatable (3.2% CoV) than 3-pool modelling (4.6% CoV), but this appears to come at the cost of reduced contrast between infarct growth tissue and normal tissue.

CONCLUSION

The multi-pool measures performed best across the analyses of repeatability, spatial variability, contrast-to-noise ratio, and grey matter-white matter contrast, and might therefore be more suitable for use in clinical imaging of acute stroke. Addition of a fourth pool that separates NOEs and semisolid effects appeared to be more biophysically accurate and provided better separation of the APT signal compared to the 3-pool equivalent, but this improvement appeared be accompanied by reduced contrast between infarct growth tissue and normal tissue.

Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) imaging

Fitting a model based on the Bloch-McConnell (BM) equations to Chemical Exchange Saturation Transfer (CEST) spectra allows for the quantification of metabolite concentration and exchange rate as well as simultaneous correction of field inhomogeneity, direct water saturation and magnetization transfer. Employing a Bayesian fitting approach permits the integration of prior information into the analysis to incorporate expected parameter distributions and to prevent over-fitting. However, the analysis can be time consuming if a general numerical solution of the BM equations is applied. In this study, we combined a Bayesian fitting algorithm with approximate analytical solutions of the BM equations to achieve feasible computational times. To evaluate the accuracy and speed of the suggested approach, phantoms including Iodipamide, Taurine and Creatine were tested in addition to simulated data with continuous-wave (CW) and pulsed saturation with Gaussian pulses. A significant reduction of computational time was achieved when fitting CW data (about 50-fold) and pulsed saturation data (more than 100-fold) with the analytical model while the estimated parameters were largely consistent with the parameters from the general numerical solution. The increased speed of the algorithm facilitates the Bayesian analysis of CEST data within clinically feasible processing times. Other analytical models valid for different parameter regimes may be employed to extend the applicability to a wider range of CEST agents.

Investigation of the performance of variable-density Z-spectrum acquisition scheme in MR chemical exchange saturation transfer effect quantification

Chemical exchange saturation transfer (CEST) MRI emerges as a powerful imaging method to probe chemical exchange between bulk water and labile protons. Conventional CEST imaging needs detailed Z-spectrum acquisition, even at frequencies with limited information for CEST parameter quantification, which harms imaging efficiency and is not favorable in practical applications. In this study, a variable-density Z-spectrum acquisition scheme was proposed. Data with saturation frequencies close to water, labile protons and their negative frequency offset was densely sampled, while the remaining part was sparsely acquired. The accuracy of the proposed method in CEST ratio measurement was investigated with numerical simulation. Compared to the conventionally evenly distributed Z-spectrum acquisition method, the proposed scheme showed significant improvement of CEST ratio characterization with existence of noise and static magnetic field inhomogeneity. With the additional advantage of easy implementation, the developed Z-spectrum acquisition scheme provides a useful framework for accurate CEST parameter quantification without compromising the imaging time.

UCEPR: Ultrafast localized CEST-spectroscopy with PRESS in phantoms and in vivo

PURPOSE

Chemical exchange saturation transfer (CEST) is a contrast mechanism enhancing low-concentration molecules through saturation transfer from their exchangeable protons to bulk water. Often many scans are acquired to form a Z-spectrum, making the CEST method time-consuming. Here, an ultrafast localized CEST-spectroscopy with PRESS (UCEPR) is proposed to obtain the entire Z-spectrum of a voxel using only two scans, significantly accelerating CEST.

THEORY AND METHODS

The approach combines ultrafast nonlocalized CEST spectroscopy with localization using PRESS. A field gradient is applied concurrently with the saturation pulse producing simultaneous saturation of all Z-spectrum frequencies that are also spatially encoded. A readout gradient during data acquisition resolves the spatial dependence of the CEST responses into frequency. UCEPR was tested on a 3T scanner both in phantoms and in vivo.

RESULTS

In phantoms, a fast Z-spectroscopy acquisition of multiple pH-variant iopamidol samples was achieved with four- to seven-fold acceleration as compared to the conventional CEST methods. In vivo, amide proton transfer (APT) in white matter of healthy human brain was measured rapidly in 48 s and with high frequency resolution (≤ 0.2 ppm).

CONCLUSION

Compared with conventional CEST methods, UCEPR has the advantage of rapidly acquiring high-resolution Z-spectra. Potential in vivo applications include ultrafast localized Z-spectroscopy, quantitative, or dynamic CEST studies.

Fast simulation and optimization of pulse-train chemical exchange saturation transfer (CEST) imaging

Chemical exchange saturation transfer (CEST) MRI has been increasingly applied to detect dilute solutes and physicochemical properties, with promising in vivo applications. Whereas CEST imaging has been implemented with continuous wave (CW) radio-frequency irradiation on preclinical scanners, pulse-train irradiation is often chosen on clinical systems. Therefore, it is necessary to optimize pulse-train CEST imaging, particularly important for translational studies. Because conventional Bloch-McConnell formulas are not in the form of homogeneous differential equations, the routine simulation approach simulates the evolving magnetization step by step, which is time consuming. Herein we developed a computationally efficient numerical solution using matrix iterative analysis of homogeneous Bloch-McConnell equations. The proposed algorithm requires simulation of pulse-train CEST MRI magnetization within one irradiation repeat, with 99% computation time reduction from that of conventional approach under typical experimental conditions. The proposed solution enables determination of labile proton ratio and exchange rate from pulse-train CEST MRI experiment, within 5% from those determined from quantitative CW-CEST MRI. In addition, the structural similarity index analysis shows that the dependence of CEST contrast on saturation pulse flip angle and duration between simulation and experiment was 0.98 ± 0.01, indicating that the proposed simulation algorithm permits fast optimization and quantification of pulse-train CEST MRI.

Identifying the ischaemic penumbra using pH-weighted magnetic resonance imaging

The original concept of the ischaemic penumbra suggested imaging of regional cerebral blood flow and metabolism would be required to identify tissue that may benefit from intervention. Amide proton transfer magnetic resonance imaging, a chemical exchange saturation transfer technique, has been used to derive cerebral intracellular pH in preclinical stroke models and has been proposed as a metabolic marker of ischaemic penumbra. In this proof of principle clinical study, we explored the potential of this pH-weighted magnetic resonance imaging technique at tissue-level. Detailed voxel-wise analysis was performed on data from a prospective cohort of 12 patients with acute ischaemic stroke. Voxels within ischaemic core had a more severe intracellular acidosis than hypoperfused tissue recruited to the final infarct (P < 0.0001), which in turn was more acidotic than hypoperfused tissue that survived (P < 0.0001). In addition, when confined to the grey matter perfusion deficit, intracellular pH (P < 0.0001), but not cerebral blood flow (P = 0.31), differed between tissue that infarcted and tissue that survived. Within the presenting apparent diffusion coefficient lesion, intracellular pH differed between tissue with early apparent diffusion lesion pseudonormalization and tissue with true radiographic recovery. These findings support the need for further investigation of pH-weighted imaging in patients with acute ischaemic stroke.

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

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

A review of optimization and quantification techniques for chemical exchange saturation transfer MRI toward sensitive in vivo imaging

Chemical exchange saturation transfer (CEST) MRI is a versatile imaging method that probes the chemical exchange between bulk water and exchangeable protons. CEST imaging indirectly detects dilute labile protons via bulk water signal changes following selective saturation of exchangeable protons, which offers substantial sensitivity enhancement and has sparked numerous biomedical applications. Over the past decade, CEST imaging techniques have rapidly evolved owing to contributions from multiple domains, including the development of CEST mathematical models, innovative contrast agent designs, sensitive data acquisition schemes, efficient field inhomogeneity correction algorithms, and quantitative CEST (qCEST) analysis. The CEST system that underlies the apparent CEST-weighted effect, however, is complex. The experimentally measurable CEST effect depends not only on parameters such as CEST agent concentration, pH and temperature, but also on relaxation rate, magnetic field strength and more importantly, experimental parameters including repetition time, RF irradiation amplitude and scheme, and image readout. Thorough understanding of the underlying CEST system using qCEST analysis may augment the diagnostic capability of conventional imaging. In this review, we provide a concise explanation of CEST acquisition methods and processing algorithms, including their advantages and limitations, for optimization and quantification of CEST MRI experiments.

Quantitative chemical exchange saturation transfer (qCEST) MRI--RF spillover effect-corrected omega plot for simultaneous determination of labile proton fraction ratio and exchange rate

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute proteins and peptides as well as microenvironmental properties. However, the complexity of the CEST MRI effect, which varies with the labile proton content, exchange rate and experimental conditions, underscores the need for developing quantitative CEST (qCEST) analysis. Towards this goal, it has been shown that omega plot is capable of quantifying paramagnetic CEST MRI. However, the use of the omega plot is somewhat limited for diamagnetic CEST (DIACEST) MRI because it is more susceptible to direct radio frequency (RF) saturation (spillover) owing to the relatively small chemical shift. Recently, it has been found that, for dilute DIACEST agents that undergo slow to intermediate chemical exchange, the spillover effect varies little with the labile proton ratio and exchange rate. Therefore, we postulated that the omega plot analysis can be improved if RF spillover effect could be estimated and taken into account. Specifically, simulation showed that both labile proton ratio and exchange rate derived using the spillover effect-corrected omega plot were in good agreement with simulated values. In addition, the modified omega plot was confirmed experimentally, and we showed that the derived labile proton ratio increased linearly with creatine concentration (p < 0.01), with little difference in their exchange rate (p = 0.32). In summary, our study extends the conventional omega plot for quantitative analysis of DIACEST MRI.

Amide proton transfer-weighted imaging of the head and neck at 3 T: a feasibility study on healthy human subjects and patients with head and neck cancer

The aim of this study was to explore the feasibility and repeatability of amide proton transfer-weighted (APTw) MRI for the head and neck on clinical MRI scanners. Six healthy volunteers and four patients with head and neck tumors underwent APTw MRI scanning at 3 T. The APTw signal was quantified by the asymmetric magnetization transfer ratio (MTRasym) at 3.5 ppm. Z spectra of normal tissues in the head and neck (masseter muscle, parotid glands, submandibular glands and thyroid glands) were analyzed in healthy volunteers. Inter-scan repeatability of APTw MRI was evaluated in six healthy volunteers. Z spectra of patients with head and neck tumors were produced and APTw signals in these tumors were analyzed. APTw MRI scanning was successful for all 10 subjects. The parotid glands showed the highest APTw signal (~7.6% average), whereas the APTw signals in other tissues were relatively moderate. The repeatability of APTw signals from the masseter muscle, parotid gland, submandibular gland and thyroid gland of healthy volunteers was established. Four head and neck tumors showed positive mean APTw ranging from 1.2% to 3.2%, distinguishable from surrounding normal tissues. APTw MRI was feasible for use in the head and neck regions at 3 T. The preliminary results on patients with head and neck tumors indicated the potential of APTw MRI for clinical applications.

Comparing different analysis methods for quantifying the MRI amide proton transfer (APT) effect in hyperacute stroke patients

Amide proton transfer (APT) imaging is a pH mapping method based on the chemical exchange saturation transfer phenomenon that has potential for penumbra identification following stroke. The majority of the literature thus far has focused on generating pH-weighted contrast using magnetization transfer ratio asymmetry analysis instead of quantitative pH mapping. In this study, the widely used asymmetry analysis and a model-based analysis were both assessed on APT data collected from healthy subjects (n = 2) and hyperacute stroke patients (n = 6, median imaging time after onset = 2 hours 59 minutes). It was found that the model-based approach was able to quantify the APT effect with the lowest variation in grey and white matter (≤ 13.8 %) and the smallest average contrast between these two tissue types (3.48 %) in the healthy volunteers. The model-based approach also performed quantitatively better than the other measures in the hyperacute stroke patient APT data, where the quantified APT effect in the infarct core was consistently lower than in the contralateral normal appearing tissue for all the patients recruited, with the group average of the quantified APT effect being 1.5 ± 0.3 % (infarct core) and 1.9 ± 0.4 % (contralateral). Based on the fitted parameters from the model-based analysis and a previously published pH and amide proton exchange rate relationship, quantitative pH maps for hyperacute stroke patients were generated, for the first time, using APT imaging.

Quantification of amide proton transfer effect pre- and post-gadolinium contrast agent administration

PURPOSE

To compare quantification of the amide proton transfer (APT) effect pre- and post-gadolinium contrast agent (Gd) administration in order to establish to what extent Gd alters quantification of the APT effect.

MATERIALS AND METHODS

Four patients with internal carotid stenosis were recruited. APT imaging was acquired pre- and post-contrast in two sessions (before and after surgery) to assess the extent of relaxation time, T1 , change on APT effect calculated using magnetization transfer ratio asymmetry analysis at offsets of ±3.5 ppm relative to water resonance. Statistical and modeling evaluations were performed on the pre- and post-contrast APT effect to study the sensitivity to contrast administration.

RESULTS

Before surgery, the post-contrast T1 was estimated to drop <10% of the pre-value for the majority of the patients. After surgery, higher post-contrast T1 reductions were observed in all the patients (maximum decrease was about 20% of the pre-value). Consistent differences between pre- and post-contrast were seen in the APT effect quantified using the asymmetry measure in most regions of the brain, with significant differences found in the white matter at the group level and in 25% of the individual patient results.

CONCLUSION

APT imaging should be performed prior to Gd administration to avoid potential misinterpretation of the APT effect.