Spin-lock imaging of early tissue pH changes in ischemic rat brain

Amide proton transfer MRI at 9.4 T for differentiating tissue acidosis in a rodent model of ischemic stroke

PURPOSE

Differentiating ischemic brain damage is critical for decision making in acute stroke treatment for better outcomes. We examined the sensitivity of amide proton transfer (APT) MRI, a pH-weighted imaging technique, to achieve this differentiation.

METHODS

In a rat stroke model, the ischemic core, oligemia, and the infarct-growth region (IGR) were identified by tracking the progression of the lesions. APT MRI signals were measured alongside ADC, T1, and T2 maps to evaluate their sensitivity in distinguishing ischemic tissues. Additionally, stroke under hyperglycemic conditions was studied.

RESULTS

The APT signal in the IGR decreased by about 10% shortly after stroke onset, and further decreased to 35% at 5 h, indicating a progression from mild to severe acidosis as the lesion evolved into infarction. Although ADC, T1, and T2 contrasts can only detect significant differences between the IGR and oligemia for a portion of the stroke duration, APT contrast consistently differentiates between them at all time points. However, the contrast to variation ratio at 1 h is only about 20% of the contrast to variation ratio between the core and normal tissues, indicating limited sensitivity. In the ischemic core, the APT signal decreases to about 45% and 33% of normal tissue level at 1 h for the normoglycemic and hyperglycemic groups, respectively, confirming more severe acidosis under hyperglycemia.

CONCLUSION

The sensitivity of APT MRI is high in detecting severe acidosis of the ischemic core but is much lower in detecting mild acidosis, which may affect the accuracy of differentiation between the IGR and oligemia.

Correction of errors in estimates of T1ρ at low spin-lock amplitudes in the presence of B0 and B1 inhomogeneities

Relaxation rates R1ρ in the rotating frame measured by spin-lock methods at very low locking amplitudes (≤ 100 Hz) are sensitive to the effects of water diffusion in intrinsic gradients and may provide information on tissue microvasculature, but accurate estimates are challenging in the presence of B0 and B1 inhomogeneities. Although composite pulse preparations have been developed to compensate for nonuniform fields, the transverse magnetization comprises different components and the spin-lock signals measured do not decay exponentially as a function of locking interval at low locking amplitudes. For example, during a typical preparation sequence, some of the magnetization in the transverse plane is nutated to the Z-axis and later tipped back, and so does not experience R1ρ relaxation. As a result, if the spin-lock signals are fit to a monoexponential decay with locking interval, there are residual errors in quantitative estimates of relaxation rates R1ρ and their dispersion with weak locking fields. We developed an approximate theoretical analysis to model the behaviors of the different components of the magnetization, which provides a means to correct these errors. The performance of this correction approach was evaluated both through numerical simulations and on human brain images at 3 T, and compared with a previous correction method using matrix multiplication. Our correction approach has better performance than the previous method at low locking amplitudes. Through careful shimming, the correction approach can be applied in studies using low spin-lock amplitudes to assess the contribution of diffusion to R1ρ dispersion and to derive estimates of microvascular sizes and spacings. The results of imaging eight healthy subjects suggest that R1ρ dispersion in human brain at low locking fields arises from diffusion among inhomogeneities that generate intrinsic gradients on a scale of capillaries (~7.4 ± 0.5 μm).

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) quantification of transient ischemia using a combination method of 5-pool Lorentzian fitting and inverse Z-spectrum analysis

Background

Chemical exchange saturation transfer (CEST) is a promising method for the detection of biochemical alterations in cancers and neurological diseases. However, the sensitivity of the currently existing quantitative method for detecting ischemia needs further improvement.

Methods

To further improve the quantification of the CEST signal and enhance the CEST detection for ischemia, we used a quantitative analysis method that combines an inverse Z-spectrum analysis and a 5-pool Lorentzian fitting. Specifically, a 5-pool Lorentzian simulation was conducted with the following brain tissue parameters: water, amide (3.5 ppm), amine (2.2 ppm), magnetization transfer (MT), and nuclear Overhauser enhancement (NOE; -3.5 ppm). The parameters were first calculated offline and stored as the initial value of the Z-spectrum fitting. Then, the measured Z-spectrum with the peak value set to 0 was fitted via the stored initial value, which yielded the reference Z-spectrum. Finally, the difference between the inverse of the Z-spectrum and the inverse of the reference Z-spectrum was used as the CEST definite spectrum.

Results

The simulation results demonstrated that the Z-spectra of the rat brain were well simulated by a 5-pool Lorentzian fitting. Further, the proposed method detected a larger difference than did either the saturation transfer difference or the 5-pool Lorentzian fitting, as demonstrated by simulations. According to the results of the cerebral ischemia rat model, the proposed method provided the highest contrast-to-noise ratio (CNR) between the contralateral and the ipsilateral striatum under various acquisition conditions. The results indicated that the difference of fitted amplitudes generated with a 5-pool Lorentzian fitting in amide at 3.5 ppm (6.04%±0.39%; 6.86%±0.39%) was decreased in a stroke lesion compared to the contralateral normal tissue. Moreover, the difference of the residual of inversed Z-spectra in which 5-pool Lorentzian fitting was used to calculate the reference Z-spectra ( M T R R e x 5 L ) amplitudes in amide at 3.5 ppm (13.83%±2.20%, 15.69%±1.99%) was reduced in a stroke lesion compared to the contralateral normal tissue.

Conclusions

M T R R e x 5 L is predominantly pH-sensitive and is suitable for detecting tissue acidosis following an acute stroke.

Demonstration of accurate multi-pool chemical exchange saturation transfer MRI quantification - Quasi-steady-state reconstruction empowered quantitative CEST analysis

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute labile protons and microenvironment properties, yet CEST quantification has been challenging. This difficulty is because the CEST measurement depends not only on the underlying CEST system but also on the scan protocols, including RF saturation amplitude, duration, and repetition time. In addition, T1 normalization is not straightforward under non-equilibrium conditions. Recently, a quasi-steady-state (QUASS) algorithm was established to reconstruct the desired equilibrium state from experimental measurements. Our study aimed to determine the accuracy of spinlock-model-based multi-pool CEST quantification using numerical simulations and phantom experiments. In short, CEST Z-spectra were simulated for a representative 3-pool model, and CEST amplitudes were solved with spinlock model-based multi-pool fitting and assessed as a function of RF saturation time (Ts), repetition time (TR), and T1. Although the apparent CEST signals showed significant T1 dependence, such relationships were not observed following QUASS reconstruction. To test the accuracy of T1 correction, a multi-vial phantom of nicotinamide and creatine was doped with manganese chloride, resulting in T1 ranging from 1 s to beyond 2 s. The multi-labile signals determined from the routine measurements showed significant dependence on Ts, TR, and T1. In contrast, CEST signals from the QUASS reconstruction showed consistent quantification independent of such variables. To summarize, our study demonstrated that accurate CEST quantification is feasible in multi-pool CEST systems with the spinlock-model-based fitting of QUASS CEST MRI.

Predicting a Favorable (mRS 0-2) or Unfavorable (mRS 3-6) Stroke Outcome by Arterial Spin Labeling and Amide Proton Transfer Imaging in Post-Thrombolysis Stroke Patients

(1) Background: The objective of this study was to determine whether arterial spin labeling (ASL), amide proton transfer (APT), or their combination could distinguish between patients with a low and high modified Rankin Scale (mRS) and forecast the effectiveness of the therapy; (2) Methods: Fifty-eight patients with subacute phase ischemic stroke were included in this study. Based on cerebral blood flow (CBF) and asymmetry magnetic transfer ratio (MTRasym) images, histogram analysis was performed on the ischemic area to acquire imaging biomarkers, and the contralateral area was used as a control. Imaging biomarkers were compared between the low (mRS 0-2) and high (mRS 3-6) mRS score groups using the Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the potential biomarkers in differentiating between the two groups; (3) Results: The rAPT 50th had an area under the ROC curve (AUC) of 0.728, with a sensitivity of 91.67% and a specificity of 61.76% for differentiating between patients with low and high mRS scores. Moreover, the AUC, sensitivity, and specificity of the rASL max were 0.926, 100%, and 82.4%, respectively. Combining the parameters with logistic regression could further improve the performance in predicting prognosis, leading to an AUC of 0.968, a sensitivity of 100%, and a specificity of 91.2%; (4) Conclusions: The combination of APT and ASL may be a potential imaging biomarker to reflect the effectiveness of thrombolytic therapy for stroke patients, assisting in guiding treatment approaches and identifying high-risk patients such as those with severe disability, paralysis, and cognitive impairment.

Quasi-steady-state amide proton transfer (QUASS APT) MRI enhances pH-weighted imaging of acute stroke

PURPOSE

Chemical exchange saturation transfer (CEST) imaging measurement depends not only on the labile proton concentration and pH-dependent exchange rate but also on experimental conditions, including the relaxation delay and radiofrequency (RF) saturation time. Our study aimed to extend a quasi-steady-state (QUASS) solution to a modified multi-slice CEST MRI sequence and test if it provides enhanced pH imaging after acute stroke.

METHODS

Our study derived the QUASS solution for a modified multislice CEST MRI sequence with an unevenly segmented RF saturation between image readout and signal averaging. Numerical simulation was performed to test if the generalized QUASS solution corrects the impact of insufficiently long relaxation delay, primary and secondary saturation times, and multi-slice readout. In addition, multiparametric MRI scans were obtained after middle cerebral artery occlusion, including relaxation and CEST Z-spectrum, to evaluate the performance of QUASS CEST MRI in a rodent acute stroke model. We also performed Lorentzian fitting to isolate multi-pool CEST contributions.

RESULTS

The QUASS analysis enhanced pH-weighted magnetization transfer asymmetry contrast over the routine apparent CEST measurements in both contralateral normal (-3.46% ± 0.62% (apparent) vs. -3.67% ± 0.66% (QUASS), P < 0.05) and ischemic tissue (-5.53% ± 0.68% (apparent) vs. -5.94% ± 0.73% (QUASS), P < 0.05). Lorentzian fitting also showed significant differences between routine and QUASS analysis of ischemia-induced changes in magnetization transfer, amide, amine, guanidyl CEST, and nuclear Overhauser enhancement (-1.6 parts per million) effects.

CONCLUSION

Our study demonstrated that generalized QUASS analysis enhanced pH MRI contrast and improved quantification of the underlying CEST contrast mechanism, promising for further in vivo applications.

Sensitivity schemes for dynamic glucose-enhanced magnetic resonance imaging to detect glucose uptake and clearance in mouse brain at 3 T

We investigated three dynamic glucose-enhanced (DGE) MRI methods for sensitively monitoring glucose uptake and clearance in both brain parenchyma and cerebrospinal fluid (CSF) at clinical field strength (3 T). By comparing three sequences, namely, Carr-Purcell-Meiboom-Gill (CPMG), on-resonance variable delay multipulse (onVDMP), and on-resonance spin-lock (onSL), a high-sensitivity DGE MRI scheme with truncated multilinear singular value decomposition (MLSVD) denoising was proposed. The CPMG method showed the highest sensitivity in detecting the parenchymal DGE signal among the three methods, while both onVDMP and onSL were more robust for CSF DGE imaging. Here, onVDMP was applied for CSF imaging, as it displayed the best stability of the DGE results in this study. The truncated MLSVD denoising method was incorporated to further improve the sensitivity. The proposed DGE MRI scheme was examined in mouse brain with 50%/25%/12.5% w/w D-glucose injections. The results showed that this combination could detect DGE signal changes from the brain parenchyma and CSF with as low as a 12.5% w/w D-glucose injection. The proposed DGE MRI schemes could sensitively detect the glucose signal change from brain parenchyma and CSF after D-glucose injection at a clinically relevant concentration, demonstrating high potential for clinical translation.

A Fully Convolutional Network (FCN) based Automated Ischemic Stroke Segment Method using Chemical Exchange Saturation Transfer Imaging

BACKGROUND

Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration. However, the accurate segmentation of pH-altered regions remains difficult due to the complicated sources in water signal changes of CEST MRI. Meanwhile, manual localization and quantification of stroke lesions are laborious and time-consuming, which cannot meet the urgent need for timely therapeutic interventions.

PURPOSE

The goal of this study was to develop an automatic lesion segmentation approach of ischemic region based on CEST MR images. A novel segmentation framework based on fully convolutional neural network was investigated for our task.

METHODS

Z-spectra from 10 rats were manually labeled as ground truth and split into two datasets, where the training dataset including 3 rats was used to generate a segmentation model, and the remaining rats were used as test datasets to evaluate the model's performance. Then a 1-D fully convolutional neural network equipped with bottleneck structures was set up, and a Grad-CAM approach was used to produce a coarse localization map, which can reflect the relevancy to the 'ischemia' class of each pixel.

RESULTS

As compared with the ground truth, the proposed network model achieved satisfying segmentation results with high values of evaluation metrics including specificity (SPE), sensitivity (SEN), accuracy (ACC), and Dice similarity coefficient (DSC), especially in some intractable situations where conventional MRI modalities and CEST quantitative method failed to distinguish between ischemic and normal tissues, and the model with augmentation was robust to input perturbations. The Grad-CAM maps performed clear tissue change distributions and interpreted the segmentations, and showed a strong correlation with the quantitative method, gave extended thinking to the function of networks.

CONCLUSIONS

The proposed method can segment ischemia region from CEST images, with the Grad-CAM maps give access to interpretative information about the segmentations, which demonstrates great potential in clinical routines. This article is protected by copyright. All rights reserved.

Metabolic Magnetic Resonance Imaging in Neuroimaging: Magnetic Resonance Spectroscopy, Sodium Magnetic Resonance Imaging and Chemical Exchange Saturation Transfer

Magnetic resonance (MR) is a powerful and versatile technique that offers much more beyond conventional anatomic imaging and has the potential of probing in vivo metabolism. Although MR spectroscopy (MRS) predates clinical MR imaging (MRI), its clinical application has been limited by technical and practical challenges. Other MR techniques actively being developed for in vivo metabolic imaging include sodium concentration imaging and chemical exchange saturation transfer. This article will review some of the practical aspects of MRS in neuroimaging, introduce sodium MRI and chemical exchange saturation transfer MRI, and highlight some of their emerging clinical applications.

Study of common quantification methods of amide proton transfer magnetic resonance imaging for ischemic stroke detection

PURPOSE

To assess the correlation and differences between common amide proton transfer (APT) quantification methods in the diagnosis of ischemic stroke.

METHODS

Five APT quantification methods, including asymmetry analysis and its variants as well as two Lorentzian model-based methods, were applied to data acquired from six rats that underwent middle cerebral artery occlusion scanned at 9.4T. Diffusion and perfusion-weighted images, and water relaxation time maps were also acquired to study the relationship of these conventional imaging modalities with the different APT quantification methods.

RESULTS

The APT ischemic area estimates had varying sizes (Jaccard index: 0.544 ≤ J ≤ 0.971) and had varying correlations in their distributions (Pearson correlation coefficient: 0.104 ≤ r ≤ 0.995), revealing discrepancies in the quantified ischemic areas. The Lorentzian methods produced the highest contrast-to-noise ratios (CNRs; 1.427 ≤ CNR ≤ 2.002), but generated APT ischemic areas that were comparable in size to the cerebral blood flow (CBF) deficit areas; asymmetry analysis and its variants produced APT ischemic areas that were smaller than the CBF deficit areas but larger than the apparent diffusion coefficient deficit areas, though having lower CNRs (0.561 ≤ CNR ≤ 1.083).

CONCLUSION

There is a need to further investigate the accuracy and correlation of each quantification method with the pathophysiology using a larger scale multi-imaging modality and multi-time-point clinical study. Future studies should include the magnetization transfer ratio asymmetry results alongside the findings of the study to facilitate the comparison of results between different centers and also the published literature.

R1ρ sensitivity to pH and other compounds at clinically accessible spin-lock fields in the presence of proteins

Numerous human diseases involve abnormal metabolism, and proton exchange is an effective source of magnetic resonance imaging (MRI) contrast for assessing metabolism. One MRI technique that capitalizes on proton exchange is R₁ relaxation in the rotating frame (R_1ρ ). Here, we investigated the sensitivity of R_1ρ to various proton-exchange mechanisms at spin-lock pulses within Food and Drug Administration (FDA) safety guidelines for radiofrequency-induced heating. We systematically varied pH known to change the rate of proton exchange as well as the glucose and lysine concentrations, thus changing the number of amide, hydroxyl and amine exchangeable sites in a series of egg-white albumin phantoms. The resulting effects on quantitative relaxation time measurements of R_1ρ , R₁ and R₂ were observed at 3 T. Using spin-lock amplitudes available for human imaging (less than 23.5 μT) at near physiologic temperatures, we found R_1ρ was more sensitive to physiologic changes in pH than to changes in glucose and lysine concentrations. In addition, R_1ρ was more sensitive to pH changes than R₁ and R₂ . Models of proton exchange fitted to the relaxation measurements suggest that amide groups were the primary source of pH sensitivity. Together, these experiments suggest an optimal spin-lock amplitude for measuring pH changes while not exceeding FDA-subject heating limitations.

Fast correction of B0 field inhomogeneity for pH-specific magnetization transfer and relaxation normalized amide proton transfer imaging of acute ischemic stroke without Z-spectrum

PURPOSE

The magnetization transfer and relaxation normalized amide proton transfer (MRAPT) analysis is promising to provide a highly pH-specific mapping of tissue acidosis, complementing commonly used CEST asymmetry analysis. We aimed to develop a fast B₀ inhomogeneity correction algorithm for acute stroke magnetization transfer and relaxation normalized amide proton transfer imaging without Z-spectral interpolation.

METHODS

The proposed fast field inhomogeneity correction describes B₀ artifacts with linear regression. We compared the new algorithm with the routine interpolation correction approach in CEST imaging of a dual-pH phantom. The fast B₀ correction was further evaluated in amide proton transfer imaging of normal and acute stroke rats.

RESULTS

Our phantom data showed that the proposed fast B₀ inhomogeneity correction significantly improved pH MRI contrast, recovering over 80% of the pH MRI contrast-to-noise-ratio difference between the raw magnetization transfer ratio asymmetry and that using the routine interpolation-based B₀ correction approach. In normal rat brains, the proposed fast B₀ correction improved pH-specific MRI uniformity across the intact tissue, with the ratio of magnetization transfer and relaxation normalized amide proton transfer ratio being 10% of that without B₀ inhomogeneity correction. In acute stroke rats, fast B₀ inhomogeneity-corrected pH MRI reveals substantially improved pH lesion conspicuity, particularly in regions with nonnegligible B₀ inhomogeneity. The pH MRI contrast-to-noise ratio between the ipsilateral diffusion lesion and contralateral normal tissue improved significantly with fast B₀ correction (from 1.88 ± 0.48 to 2.20 ± 0.44, P < .01).

CONCLUSIONS

Our study established an expedient B₀ inhomogeneity correction algorithm for fast pH imaging of acute ischemia.

Self-adapting multi-peak water-fat reconstruction for the removal of lipid artifacts in chemical exchange saturation transfer (CEST) imaging

PURPOSE

Artifacts caused by strong lipid signals pose challenges in body chemical exchange saturation transfer (CEST) imaging. This study aimed to develop an accurate water-fat reconstruction method based on the multi-echo Dixon technique to remove lipid artifacts in CEST imaging.

THEORY AND METHODS

It is well known that fat has multiple spectral peaks. Furthermore, RF pulses in CEST preparation saturate each fat peak at different levels, complicating fat modeling. Therefore, a self-adapting multi-peak model (SMPM) is proposed to update relative amplitudes of fat peaks using numerical calculation. With the SMPM-based updating, nonlinear least-squares fitting combined with IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation) algorithms was used for water-fat reconstruction and B₀ mapping. The proposed method was compared with the reported 3-point Dixon method and the fixed multi-peak model in a phantom study using a fat-free Z-spectrum obtained from MR spectroscopy acquisition as the ground truth. This method was also validated by in vivo experiments on human breast.

RESULTS

In the phantom experiments, the Z-spectrum from the SMPM-based method agreed well with the fat-free Z-spectrum from CEST-PRESS (point-resolved spectroscopy), validating the effective removal of lipid artifacts, while a decrease or a rise that appeared at -3.5 ppm was observed in the Z-spectrum from the 3-point method and the FMPM-based method, respectively. In the in vivo experiments, no lipid artifacts were observed in the Z-spectrum or the amide CEST map from the SMPM-based method in the fibro-glandular region of the breast with high fat fractions.

CONCLUSION

The SMPM-based method successfully removes lipid artifacts and significantly improves the accuracy of CEST contrast.

Evaluation of the sensitivity of R1ρ MRI to pH and macromolecular density

The tumor microenvironment is characteristically acidic and this extracellular acidosis is known to play a role in carcinogenesis and metastasis and can affect tumor chemosensitivity and radiosensitivity. Intracellular pH has been used as a possible biomarker of salvageable tissue in ischemic stroke. A non-invasive MRI-based approach for the determination and imaging of cerebral pH would be a powerful tool in cancer diagnosis and monitoring, as well as stroke treatment planning. Several pH-based MRI imaging approaches have been proposed but for these to be useful, disentangling the effects of pH from other parameters which may affect the measured MRI signal is crucial to ensure accuracy and specificity. R1 relaxation in the rotating frame (R1ρ) is an example of a method that has been proposed to probe pH in vivo using MRI. In this study, we have investigated the relationship between R1ρ, pH, and macromolecular density in vitro using phantoms and in human volunteers. Here we show that the rate of R1ρ relaxation (=1/T1ρ) varies with pH but only in the presence of macromolecules. At constant pH, phantom macromolecular density inversely correlated with R1ρ. R1ρ imaging of the normal human brain demonstrated regional heterogeneity with significant differences between structurally distinct regions, which are likely to be independent of pH. For example, R1ρ was higher in the basal ganglia compared to grey matter and higher in grey matter compared to white matter. We conclude that R1ρ cannot be reliably used to image tissue pH without deconvolution from the effects of local tissue macromolecular composition.

Mapping tissue pH in an experimental model of acute stroke - Determination of graded regional tissue pH changes with non-invasive quantitative amide proton transfer MRI

pH-weighted amide proton transfer (APT) MRI is sensitive to tissue pH change during acute ischemia, complementing conventional perfusion and diffusion stroke imaging. However, the currently used pH-weighted magnetization transfer (MT) ratio asymmetry (MTR_asym) analysis is of limited pH specificity. To overcome this, MT and relaxation normalized APT (MRAPT) analysis has been developed that to homogenize the background signal, thus providing highly pH conspicuous measurement. Our study aimed to calibrate MRAPT MRI toward absolute tissue pH mapping and determine regional pH changes during acute stroke. Using middle cerebral artery occlusion (MCAO) rats, we performed lactate MR spectroscopy and multi-parametric MRI. MRAPT MRI was calibrated against a region of interest (ROI)-based pH spectroscopy measurement (R² = 0.70, P < 0.001), showing noticeably higher correlation coefficient than the simplistic MTR_asym index. Capitalizing on this, we mapped brain tissue pH and semi-automatically segmented pH lesion, in addition to routine perfusion and diffusion lesions. Tissue pH from regions of the contralateral normal, perfusion/diffusion lesion mismatch and diffusion lesion was found to be 7.03 ± 0.04, 6.84 ± 0.10, 6.52 ± 0.19, respectively. Most importantly, we delineated the heterogeneous perfusion/diffusion lesion mismatch into perfusion/pH and pH/diffusion lesion mismatches, with their pH being 7.01 ± 0.04 and 6.71 ± 0.12, respectively (P < 0.05). To summarize, our study calibrated pH-sensitive MRAPT MRI toward absolute tissue pH mapping, semi-automatically segmented and determined graded tissue pH changes in ischemic tissue and demonstrated its feasibility for refined demarcation of heterogeneous metabolic disruption following acute stroke.