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Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.
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Disfunção Cognitiva , Substância Branca , Humanos , Idoso , Substância Branca/diagnóstico por imagem , Reprodutibilidade dos Testes , Mapeamento Encefálico , Envelhecimento , Encéfalo/diagnóstico por imagem , Cognição , Imageamento por Ressonância Magnética , Disfunção Cognitiva/diagnóstico por imagemRESUMO
PURPOSE: To evaluate the assumption in amide proton transfer weighted (APTw) imaging that the APT dominates over the relayed nuclear Overhauser enhancement (rNOE) and other CEST effects such as those from amines/guanidines, thereby providing imaging of mobile proteins/peptides. METHODS: We introduced two auxiliary asymmetric analysis metrics that can vary the relative contributions from amine/guanidinium CEST and other effects. By comparing these metrics with the conventional asymmetric analysis metric on healthy rat brains, we can approximately assess the contribution from amines/guanidines to APTw and determine whether the APT dominates over the rNOE effect. To further investigate the molecular origin of APTw, we used samples of dialyzed tissue homogenates to eliminate small metabolites and supernatants of homogenates to separate lipids from other components. RESULTS: When the APTw signal is positive using high saturation amplitudes (e.g., 2-3 µT), the contributions from amines/guanidines are significant and cannot be ignored. The APTw signal from the dialyzed homogenates and the controls has negligible changes, indicating that it primarily originates from macromolecules rather than small metabolites. Additionally, the APTw signals with low saturation amplitudes (e.g., 1 µT) were negative in tissue homogenates but positive in their supernatants, suggesting that proteins contribute positively to APTw signals, whereas lipids contribute negatively to it. CONCLUSION: The positive APTw signal using high saturation amplitudes could have significant contributions from soluble proteins through CEST, including amide/amine/guanidine proton transfer effects. In contrast, the negative APTw signal using low saturation amplitudes has significant contribution from lipids through rNOE.
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Imageamento por Ressonância Magnética , Prótons , Ratos , Animais , Imageamento por Ressonância Magnética/métodos , Amidas , Aminas , Guanidinas , LipídeosRESUMO
PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods. METHOD: The DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of one-dimensional convolutions, nonlinearity applications, and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis-processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric. RESULTS: In digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirm the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared with other methods. Although no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings. CONCLUSION: The DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared with other methods.
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PURPOSE: A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer signal at around -1.6 ppm, termed NOE(-1.6), has been reported at high fields of 7T and 9.4T previously. This study aims to validate the presence of this signal at a relatively low field of 4.7T and evaluate its variations in different brain regions and tumors. METHODS: Rats were injected with monocrystalline iron oxide nanoparticles to reduce the NOE(-1.6) signal. CEST signals were measured using different saturation powers before and after injection to assess the presence of this signal. Multiple-pool Lorentzian fits, with/without inclusion of the NOE(-1.6) pool, were performed on CEST Z-spectra obtained from healthy rat brains and rats with 9L tumors. These fits aimed to further validate the presence of the NOE(-1.6) signal and quantify its amplitude. RESULTS: The NOE(-1.6) signal exhibited a dramatic change following the injection of monocrystalline iron oxide nanoparticles, confirming its presence at 4.7T. The NOE(-1.6) signal reached its peak at a saturation power of â¼0.75 µT, indicating an optimized power level. The multiple-pool Lorentzian fit without the NOE(-1.6) pool showed higher residuals around -1.6 ppm compared to the fit with this pool, further supporting the presence of this signal. The NOE(-1.6) signal did not exhibit significant variation in the corpus callosum and caudate putamen regions, but it showed a significant decrease in tumors, which aligns with previous findings at 9.4T. CONCLUSION: This study successfully demonstrated the presence of the NOE(-1.6) signal at 4.7T, which provides valuable insights into its potential applications at lower field strengths.
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Neoplasias Encefálicas , Glioma , Ratos , Animais , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Glioma/patologia , Imageamento por Ressonância Magnética/métodos , Interpretação de Imagem Assistida por Computador/métodos , Algoritmos , Sensibilidade e Especificidade , Encéfalo/diagnóstico por imagem , Encéfalo/patologiaRESUMO
PURPOSE: Machine learning (ML) has been increasingly used to quantify CEST effect. ML models are typically trained using either measured data or fully simulated data. However, training with measured data often lacks sufficient training data, whereas training with fully simulated data may introduce bias because of limited simulations pools. This study introduces a new platform that combines simulated and measured components to generate partially synthetic CEST data, and to evaluate its feasibility for training ML models to predict amide proton transfer (APT) effect. METHODS: Partially synthetic CEST signals were created using an inverse summation of APT effects from simulations and the other components from measurements. Training data were generated by varying APT simulation parameters and applying scaling factors to adjust the measured components, achieving a balance between simulation flexibility and fidelity. First, tissue-mimicking CEST signals along with ground truth information were created using multiple-pool model simulations to validate this method. Second, an ML model was trained individually on partially synthetic data, in vivo data, and fully simulated data, to predict APT effect in rat brains bearing 9 L tumors. RESULTS: Experiments on tissue-mimicking data suggest that the ML method using the partially synthetic data is accurate in predicting APT. In vivo experiments suggest that our method provides more accurate and robust prediction than the training using in vivo data and fully synthetic data. CONCLUSION: Partially synthetic CEST data can address the challenges in conventional ML methods.
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Neoplasias Encefálicas , Imageamento por Ressonância Magnética , Ratos , Animais , Imageamento por Ressonância Magnética/métodos , Prótons , Amidas , Interpretação de Imagem Assistida por Computador/métodosRESUMO
PURPOSE: Guanidinium CEST is sensitive to metabolic changes and pH variation in ischemia, and it can offer advantages over conventional pH-sensitive amide proton transfer (APT) imaging by providing hyperintense contrast in stroke lesions. However, quantifying guanidinium CEST is challenging due to multiple overlapping components and a close frequency offset from water. This study aims to evaluate the applicability of a new rapid and model-free CEST quantification method using double saturation power, termed DSP-CEST, for isolating the guanidinium CEST effect from confounding factors in ischemia. To further reduce acquisition time, the DSP-CEST was combined with a quasi-steady state (QUASS) CEST technique to process non-steady-state CEST signals. METHODS: The specificity and accuracy of the DSP-CEST method in quantifying the guanidinium CEST effect were assessed by comparing simulated CEST signals with/without the contribution from confounding factors. The feasibility of this method for quantifying guanidinium CEST was evaluated in a rat model of global ischemia induced by cardiac arrest and compared to a conventional multiple-pool Lorentzian fit method. RESULTS: The DSP-CEST method was successful in removing all confounding components and quantifying the guanidinium CEST signal increase in ischemia. This suggests that the DSP-CEST has the potential to provide hyperintense contrast in stroke lesions. Additionally, the DSP-CEST was shown to be a rapid method that does not require the acquisition of the entire or a portion of the CEST Z-spectrum that is required in conventional model-based fitting approaches. CONCLUSION: This study highlights the potential of DSP-CEST as a valuable tool for rapid and specific detection of viable tissues.
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Encéfalo , Acidente Vascular Cerebral , Ratos , Animais , Encéfalo/metabolismo , Imageamento por Ressonância Magnética/métodos , Guanidina/metabolismo , Roedores , Isquemia/diagnóstico por imagem , Isquemia/metabolismo , Amidas/metabolismoRESUMO
PURPOSE: This study aims to assess how T2 heterogeneity biases IMPULSED-derived metrics of tissue microstructure in solid tumors and evaluate the potential of estimating multi-compartmental T2 and microstructural parameters simultaneously. METHODS: This study quantifies the impact of T2 relaxation on IMPULSED-derived microstructural parameters using computer simulations and in vivo multi-TE IMPULSED MRI in five tumor models, including brain, breast, prostate, melanoma, and colon cancer. A comprehensive T2 + IMPULSED method was developed to fit multi-compartmental T2 and microstructural parameters simultaneously. A Bayesian model selection approach was carried out voxel-wisely to determine if the T2 heterogeneity needs to be included in IMPULSED MRI in cancer. RESULTS: Simulations suggest that T2 heterogeneity has a minor effect on the estimation of d in tissues with intermediate or high cell density, but significantly biases the estimation of v in $$ {v}_{in} $$ with low cell density. For the in vivo animal experiments, all IMPULSED metrics except v in $$ {v}_{in} $$ are statistically independent on TE. For B16 tumors, the IMPULSED-derived v in $$ {v}_{in} $$ exhibited a notable increase with longer TEs. For MDA-MB-231 tumors, IMPULSED-derived v in $$ {v}_{in} $$ showed a significant increase with increasing TEs. The T2 + IMPULSED-derived T 2 in $$ {T}_2^{in} $$ of all five tumor models are consistently smaller than T 2 ex $$ {T}_2^{ex} $$ . CONCLUSIONS: The findings from this study highlight two key observations: (i) TE has a negligible impact on IMPULSED-derived cell sizes, and (ii) the TE-dependence of IMPULSED-derived intracellular volume fractions used in T2 + IMPULSED modeling to estimate T 2 in $$ {T}_2^{in} $$ and T 2 ex $$ {T}_2^{ex} $$ . These insights contribute to the ongoing development and refinement of non-invasive MRI techniques for measuring cell sizes.
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Monitoring the variation in phosphocreatine (PCr) levels following exercise provides valuable insights into muscle function. Chemical exchange saturation transfer (CEST) has emerged as a sensitive method with which to measure PCr levels in muscle, surpassing conventional MR spectroscopy. However, existing approaches for quantifying PCr CEST signals rely on time-consuming fitting methods that require the acquisition of the entire or a section of the CEST Z-spectrum. Additionally, traditional fitting methods often necessitate clear CEST peaks, which may be challenging to obtain at low magnetic fields. This paper evaluated the application of a new model-free method using double saturation power (DSP), termed DSP-CEST, to estimate the PCr CEST signal in muscle. The DSP-CEST method requires the acquisition of only two or a few CEST signals at the PCr frequency offset with two different saturation powers, enabling rapid dynamic imaging. Additionally, the DSP-CEST approach inherently eliminates confounding signals, offering enhanced robustness compared with fitting methods. Furthermore, DSP-CEST does not demand clear CEST peaks, making it suitable for low-field applications. We evaluated the capability of DSP-CEST to enhance the specificity of PCr CEST imaging through simulations and experiments on muscle tissue phantoms at 4.7 T. Furthermore, we applied DSP-CEST to animal leg muscle both before and after euthanasia and observed successful reduction of confounding signals. The DSP-CEST signal still has contaminations from a residual magnetization transfer (MT) effect and an aromatic nuclear Overhauser enhancement effect, and thus only provides a PCr-weighted imaging. The residual MT effect can be reduced by a subtraction of DSP-CEST signals at 2.6 and 5 ppm. Results show that the residual MT-corrected DSP-CEST signal at 2.6 ppm has significant variation in postmortem tissues. By contrast, both the CEST signal at 2.6 ppm and a conventional Lorentzian difference analysis of CEST signal at 2.6 ppm demonstrate no significant variation in postmortem tissues.
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Imageamento por Ressonância Magnética , Músculo Esquelético , Animais , Imageamento por Ressonância Magnética/métodos , Fosfocreatina , Espectroscopia de Ressonância Magnética/métodos , Músculo Esquelético/diagnóstico por imagem , Aumento da Imagem/métodosRESUMO
PURPOSE: Nuclear Overhauser enhancement (NOE)-mediated CEST imaging at -3.5 ppm has shown clinical interest in diagnosing tumors. Multiple-pool Lorentzian fit has been used to quantify NOE, which, however, requires a long scan time. Asymmetric analysis of CEST signals could be a simple and fast method to quantify this NOE, but it has contamination from the amide proton transfer (APT) at 3.5 ppm. This work proposes a new method using an asymmetric analysis of a low-duty-cycle pulsed-CEST sequence with a flip angle of 360°, termed 2π-CEST, to reduce the contribution from APT. METHODS: Simulations were used to evaluate the capability of the 2π-CEST to reduce APT. Experiments on animal tumor models were performed to show its advantages compared with the conventional asymmetric analysis. Samples of reconstituted phospholipids and proteins were used to evaluate the molecular origin of this NOE. RESULTS: The 2π-CEST has reduced contribution from APT. In tumors where we show that the NOE is comparable to the APT effect, reducing the contamination from APT is crucial. The results show that the NOE signal obtained with 2π-CEST in tumor regions appears more homogeneous than that obtained with the conventional method. The phantom study showed that both phospholipids and proteins contribute to the NOE at -3.5 ppm. CONCLUSION: The NOE at -3.5 ppm has a different contrast mechanism from APT and other CEST/NOE effects. The proposed 2π-CEST is more accurate than the conventional asymmetric analysis in detecting NOE, and requires much less scan time than the multiple-pool Lorentzian fit.
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Neoplasias Encefálicas , Animais , Neoplasias Encefálicas/patologia , Imageamento por Ressonância Magnética/métodos , Interpretação de Imagem Assistida por Computador/métodos , Prótons , Amidas/metabolismo , FosfolipídeosRESUMO
PURPOSE: Nuclear Overhauser enhancemen mediated saturation transfer effect, termed NOE (-3.5 ppm), is a major source of CEST MRI contrasts at 3.5 ppm in the brain. Previous phantom experiments have demonstrated that both proteins and lipids, two major components in tissues, have substantial contributions to NOE (-3.5 ppm) signals. Their relative contributions in tissues are informative for the interpretation of NOE (-3.5 ppm) contrasts that could provide potential imaging biomarkers for relevant diseases, which remain incompletely understood. METHODS: Experiments on homogenates and supernatants of brain tissues collected from healthy rats, that could isolate proteins from lipids, were performed to evaluate the relative contribution of lipids to NOE (-3.5 ppm) signals. On the other hand, experiments on ghost membranes with varied pH, and reconstituted phospholipids with different chemical compositions were conducted to study the dependence of NOE (-3.5 ppm) on physiological conditions. Besides, CEST imaging on rat brains bearing 9 L tumors and healthy rat brains was performed to analyze the causes of the NOE (-3.5 ppm) contrast variations between tumors and normal tissues, and between gray matter and white matter. RESULTS: Our experiments reveal that lipids have dominant contributions to the NOE (-3.5 ppm) signals. Further analysis suggests that decreased NOE (-3.5 ppm) signals in tumors and higher NOE (-3.5 ppm) signals in white matter than in gray matter are mainly explained by changes in membrane lipids, rather than proteins. CONCLUSION: NOE (-3.5 ppm) could be exploited as a highly sensitive MRI contrast for imaging membrane lipids in the brain.
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Neoplasias Encefálicas , Ratos , Animais , Neoplasias Encefálicas/metabolismo , Algoritmos , Prótons , Encéfalo/metabolismo , Imageamento por Ressonância Magnética/métodos , Lipídeos de MembranaRESUMO
PURPOSE: Accurately quantifying the amide proton transfer (APT) effect and the underlying exchange parameters is crucial for its applications, but previous studies have reported conflicting results. In these quantifications, the CEST effect from the fast exchange amine was always ignored because it was considered weak with low saturation powers. This paper aims to evaluate the influence of the fast exchange amine CEST on the quantification of APT at low saturation powers. METHODS: A quantification method with low and high saturation powers was used to distinguish APT from the fast exchange amine CEST effect. Simulations were conducted to assess the method's capability to separate APT from the fast exchange amine CEST effect. Animal experiments were performed to assess the relative contributions from the fast exchange amine and amide to CEST signals at 3.5 ppm. Three APT quantification methods, each with varying degrees of contamination from the fast exchange amine, were employed to process the animal data to assess the influence of the amine on the quantification of APT effect and the exchange parameters. RESULTS: The relative size of the fast exchange amine CEST effect to APT effect gradually increases with increasing saturation power. At 9.4 T, it increases from approximately 20% to 40% of APT effect with a saturation power increase from 0.25 to 1 µT. CONCLUSION: The fast exchange amine CEST effect leads overestimation of APT effect, fitted amide concentration, and amide-water exchange rate, potentially contributing to the conflicting results reported in previous studies.
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Imageamento por Ressonância Magnética , Prótons , Animais , Imageamento por Ressonância Magnética/métodos , Amidas , Aminas , ÁguaRESUMO
PURPOSE: Quantifications of amide proton transfer (APT) and nuclear Overhauser enhancement (rNOE(-3.5)) mediated saturation transfer with high specificity are challenging because their signals measured in a Z-spectrum are overlapped with confounding signals from direct water saturation (DS), semi-solid magnetization transfer (MT), and CEST of fast-exchange pools. In this study, based on two canonical CEST acquisitions with double saturation powers (DSP), a new data-postprocessing method is proposed to specifically quantify the effects of APT and rNOE. METHODS: For CEST imaging with relatively low saturation powers ( ω 1 2 $$ {\upomega}_1^2 $$ ), both the fast-exchange CEST effect and the semi-solid MT effect roughly depend on ω 1 2 $$ {\upomega}_1^2 $$ , whereas the slow-exchange APT/rNOE(-3.5) effect do not, which is exploited to isolate a part of the APT and rNOE effects from the confounding signals in this study. After a mathematical derivation for the establishment of the proposed method, numerical simulations based on Bloch equations are then performed to demonstrate its specificity to detections of the APT and rNOE effects. Finally, an in vivo validation of the proposed method is conducted using an animal tumor model at a 4.7 T MRI scanner. RESULTS: The simulations show that DSP-CEST can quantify the effects of APT and rNOE and substantially eliminate the confounding signals. The in vivo experiments demonstrate that the proposed DSP-CEST method is feasible for the imaging of tumors. CONCLUSION: The data-postprocessing method proposed in this study can quantify the APT and rNOE effects with considerably increased specificities and a reduced cost of imaging time.
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Amidas , Imagem Ecoplanar , Animais , Prótons , Neoplasias/diagnóstico por imagem , Imageamento por Ressonância MagnéticaRESUMO
PURPOSE: The purpose is to evaluate the relative contribution from confounding factors (T1 weighting and magnetization transfer) to the CEST ratio (CESTR)-quantified amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) (-3.5) in tumors as well as whether the CESTR can reflect the distribution of the solute concentration (fs ). METHODS: We first provided a signal model that shows the separate dependence of CESTR on these confounding factors and the clean CEST/NOE effects quantified by an apparent exchange-dependent relaxation (AREX) method. We then measured the change in these effects in the 9-L tumor model in rats, through which we calculated the relative contribution of each confounding factor. fs was also fitted, and its correlations with the CESTR and AREX were assessed to evaluate their capabilities to reflect fs . RESULTS: The CESTR-quantified APT shows "positive" contrast in tumors, which arises primarily from R1w at low powers and both R1w and magnetization transfer at high powers. CESTR-quantified NOE (-3.5) shows no or weak contrast in tumors, which is due to the cancelation of R1w and NOE (-3.5), which have opposite contributions. CESTR-quantified APT has a stronger correlation with APT fs than AREX-quantified APT. CESTR-quantified NOE (-3.5) has a weaker correlation with NOE (-3.5) fs than AREX-quantified NOE (-3.5). CONCLUSION: CESTR reflects a combined effect of T1 weighting and CEST/NOE. Both factors depend on fs , which contributes positively to the dependence of CESTR on fs in APT imaging and enhances its correlation with fs . In contrast, these factors have opposite contributions to its dependence on fs in NOE (-3.5) imaging, thereby weakening the correlation.
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Neoplasias Encefálicas , Ratos , Animais , Neoplasias Encefálicas/patologia , Prótons , Imageamento por Ressonância Magnética/métodos , Amidas , Aumento da Imagem/métodosRESUMO
PURPOSE: We aimed to compare multiple MRI parameters, including relaxation rates ( R 1 $$ {R}_1 $$ , R 2 $$ {R}_2 $$ , and R 1 ρ $$ {R}_{1\rho } $$ ), ADC from diffusion weighted imaging, pool size ratio (PSR) from quantitative magnetization transfer, and measures of exchange from spin-lock imaging ( S ρ $$ {S}_{\rho } $$ ), for assessing and predicting the severity of polycystic kidney disease (PKD) over time. METHODS: Pcy/Pcy mice with CD1 strain, a mouse model of autosomal dominant PKD, were imaged at 5, 9, and 26 wk of age using a 7T MRI system. Twelve-week normal CD1 mice were used as controls. Post-mortem paraffin tissue sections were stained using hematoxylin and eosin and picrosirius red to identify histological changes. RESULTS: Histology detected segmental cyst formation in the early stage (week 5) and progression of PKD over time in Pcy kidneys. In T 2 $$ {T}_2 $$ -weighted images, small cysts appeared locally in cystic kidneys in week 5 and gradually extended to the whole cortex and outer stripe of outer medulla region from week 5 to week 26. Regional PSR, R 1 $$ {R}_1 $$ , R 2 $$ {R}_2 $$ , and R 1 ρ $$ {R}_{1\rho } $$ decreased consistently over time compared to normal kidneys, with significant changes detected in week 5. Among all the MRI measures, R 2 $$ {R}_2 $$ and R 1 ρ $$ {R}_{1\rho } $$ allow highest detectability to PKD, while PSR and R 1 $$ {R}_1 $$ have highest correlation with pathological indices of PKD. Using optimum MRI parameters as regressors, multiple linear regression provides reliable prediction of PKD progression. CONCLUSION: R 2 $$ {R}_2 $$ , R 1 $$ {R}_1 $$ , and PSR are sensitive indicators of the presence of PKD. Multiparametric MRI allows a comprehensive analysis of renal changes caused by cyst formation and expansion.
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Cistos , Imageamento por Ressonância Magnética Multiparamétrica , Doenças Renais Policísticas , Camundongos , Animais , Doenças Renais Policísticas/diagnóstico por imagem , Doenças Renais Policísticas/patologia , Rim/diagnóstico por imagem , Rim/patologia , Imageamento por Ressonância Magnética , Cistos/patologia , Modelos Animais de DoençasRESUMO
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).
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A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change substantially. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.
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Substância Branca , Encéfalo , Mapeamento Encefálico/métodos , Substância Cinzenta/fisiologia , Humanos , Imageamento por Ressonância Magnética/métodos , Reprodutibilidade dos Testes , Substância Branca/diagnóstico por imagem , Substância Branca/fisiologiaRESUMO
PURPOSE: Chemical exchange saturation transfer signals from amines are sensitive to pH, and detection of these signals can serve as an alternative pH imaging method to amide proton transfer (APT). However, conflicting results regarding amine CEST imaging at 2 ppm in ischemic stroke have been reported. Here, we correlated amine CEST with APT in animal stroke models to evaluate its specificity to pH, and investigated the reason for the different results through simulations and sample studies. METHODS: A three-point quantification method was used to quantify APT. A polynomial fit method and a multiple-pool Lorentzian fit method were used to quantify amine CEST. Samples of creatine and glutamate were prepared to study the different CEST effects from arginine amine and fast exchanging pools. Samples of tissue homogenates with different pH were prepared to study the variation in CEST signals due only to changes in pH. RESULTS: The polynomial fit of amine CEST at 2 ppm had a significant correlation with APT, whereas the Lorentzian fit did not. Further studies showed that arginine amine contributed to the polynomial fit, whereas both the arginine amine and the fast exchanging pools contributed to the Lorentzian fit with their CEST effects varying in opposite directions after stroke. The CEST signal from the fast exchanging pool decreased, probably due to the reduced pool concentration but not pH. CONCLUSION: The variation in opposite directions led to an insignificant correlation of the Lorentzian fit of amine CEST with APT and the different results in different experimental conditions.
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Isquemia Encefálica , AVC Isquêmico , Acidente Vascular Cerebral , Aminas , Animais , Isquemia Encefálica/diagnóstico por imagem , Imageamento por Ressonância Magnética , Acidente Vascular Cerebral/diagnóstico por imagemRESUMO
PURPOSE: A relayed nuclear Overhauser enhancement (rNOE) saturation transfer effect at around -1.6 ppm from water, termed NOE(-1.6), was previously reported in rat and human brain, and some publications suggest that it may be related to blood. Here, we studied whether the NOE(-1.6) arises from blood through in vivo and ex vivo experiments. METHODS: To evaluate the contribution from in vivo blood to NOE(-1.6), intravascular signals in rat brain were suppressed by two approaches: (1) signal acquisition with a diffusion-weighting of b = 400 s/mm2 ; (2) intravascular injection of 5 mg/kg monocrystalline iron oxide nanoparticle (MION). Ex vivo blood sample was also prepared. The signals were acquired using a chemical exchange saturation transfer (CEST) pulse sequence. Multiple-pool Lorentzian fitting of CEST Z-spectra was performed to quantify the NOE(-1.6) signal. RESULTS: There are no significant variations in the fitted in vivo NOE(-1.6) signals when measured with or without diffusion-weighting, but significant signal decease does occur after injection of MION. The NOE(-1.6) signal from ex vivo blood is weaker than that from in vivo tissues. CONCLUSION: Considering the relatively small volume of blood in brain, the in vivo experiments with diffusion weighting and the ex vivo experiments both suggest that the NOE(-1.6) is not mainly from blood. The mechanism for the in vivo experiments with MION are less clear. MION not only suppresses MR signals from intravascular space, but changes the susceptibility in the perivascular space. This result suggests that although the NOE(-1.6) is not mainly from blood, it may be vasculature dependent.
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Neoplasias Encefálicas , Imageamento por Ressonância Magnética , Algoritmos , Animais , Encéfalo/diagnóstico por imagem , Ratos , Sensibilidade e EspecificidadeRESUMO
Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.
Assuntos
Neoplasias Encefálicas , Amidas , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Consenso , Dimaprit/análogos & derivados , Humanos , Imageamento por Ressonância Magnética/métodos , PrótonsRESUMO
Chemical exchange saturation transfer (CEST) methods measure the effect of magnetization exchange between solutes and water. While CEST methods are often implemented using a train of off-resonant shaped RF pulses, they are typically analyzed as if the irradiation were continuous. This approximation does not account for exchange of rotated magnetization, unique to pulsed irradiation and exploited by chemical exchange rotation transfer methods. In this work, we derive and test an analytic solution for the steady-state water signal under pulsed irradiation by extending a previous work to include the effects of pulse shape. The solution is largely accurate at all offsets, but this accuracy diminishes at higher exchange rates and when applying pulse shapes with large root-mean-squared to mean ratios (such as multi-lobe sinc pulses).