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Background: There is growing interest in understanding the dynamic functional connectivity (DFC) between distributed brain regions. However, it remains challenging to reliably estimate the temporal dynamics from resting-state functional magnetic resonance imaging (rs-fMRI) due to the limitations of current methods., New Methods: We propose a new model called HDP-HSMM-BPCA for sparse DFC analysis of high-dimensional rs-fMRI data, which is a temporal extension of probabilistic principal component analysis using Bayesian nonparametric hidden semi-Markov model (HSMM). Specifically, we utilize a hierarchical Dirichlet process (HDP) prior to remove the parametric assumption of the HMM framework, overcoming the limitations of the standard HMM. An attractive superiority is its ability to automatically infer the state-specific latent space dimensionality within the Bayesian formulation., Results: The experiment results of synthetic data show that our model outperforms the competitive models with relatively higher estimation accuracy. In addition, the proposed framework is applied to real rs-fMRI data to explore sparse DFC patterns. The findings indicate that there is a time-varying underlying structure and sparse DFC patterns in high-dimensional rs-fMRI data., Comparison With Existing Methods: Compared with the existing DFC approaches based on HMM, our method overcomes the limitations of standard HMM. The observation model of HDP-HSMM-BPCA can discover the underlying temporal structure of rs-fMRI data. Furthermore, the relevant sparse DFC construction algorithm provides a scheme for estimating sparse DFC., Conclusion: We describe a new computational framework for sparse DFC analysis to discover the underlying temporal structure of rs-fMRI data, which will facilitate the study of brain functional connectivity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To comprehensively assess the impact of aging, cigarette smoking, and chronic obstructive pulmonary disease (COPD) on pulmonary physiology using 129 Xe MR., Methods: A total of 90 subjects were categorized into four groups, including healthy young (HY, n = 20), age-matched control (AMC, n = 20), asymptomatic smokers (AS, n = 28), and COPD patients (n = 22). 129 Xe MR was utilized to obtain pulmonary physiological parameters, including ventilation defect percent (VDP), alveolar sleeve depth (h), apparent diffusion coefficient (ADC), total septal wall thickness (d), and ratio of xenon signal from red blood cells and interstitial tissue/plasma (RBC/TP)., Results: Significant differences were found in the measured VDP (p = 0.035), h (p = 0.003), and RBC/TP (p = 0.003) between the HY and AMC groups. Compared with the AMC group, higher VDP (p = 0.020) and d (p = 0.048) were found in the AS group; higher VDP (p < 0.001), d (p < 0.001) and ADC (p < 0.001), and lower h (p < 0.001) and RBC/TP (p < 0.001) were found in the COPD group. Moreover, significant differences were also found in the measured VDP (p < 0.001), h (p < 0.001), ADC (p < 0.001), d (p = 0.008), and RBC/TP (p = 0.032) between the AS and COPD groups., Conclusion: Our findings indicate that pulmonary structure and functional changes caused by aging, cigarette smoking, and COPD are various, and show a progressive deterioration with the accumulation of these risk factors, including cigarette smoking and COPD., Clinical Relevance Statement: Pathophysiological changes can be difficult to comprehensively understand due to limitations in common techniques and multifactorial etiologies. 129 Xe MRI can demonstrate structural and functional changes caused by several common factors and can be used to better understand patients' underlying pathology., Key Points: Standard techniques for assessing pathophysiological lung function changes, spirometry, and chest CT come with limitations. 129 Xe MR demonstrated progressive deterioration with accumulation of the investigated risk factors, without these limitations. 129 Xe MR can assess lung changes related to these risk factors to stage and evaluate the etiology of the disease., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

The brain exhibits intrinsic dynamics characterized by spontaneous spatiotemporal reorganization of neural activity or metastability, which is associated closely with functional integration and segregation. Compared to dynamic functional connectivity, state-dependent effective connectivity (i.e., dynamic effective connectivity) is more suitable for exploring the metastability as its ability to infer causalities between brain regions. However, methods for state-dependent effective connectivity are scarce and urgently needed. In this study, a novel data-driven computational framework, named NHSMM-MAR-sdNC integrating nonparametric hidden semi-Markov model combined with multivariate autoregressive model and state-dependent new causality, is proposed to investigate the state-dependent effective connectivity. The framework is not constrained by any biological assumptions. Furthermore, state number can be inferred from the observed data directly and the state duration distributions will be estimated explicitly rather than restricted by geometric form, which overcomes limitations of hidden Markov model. Experimental results of synthetic data show that the framework can identify the state number adaptively and the state-dependent causality networks accurately. The dynamics of state-related causality networks are also revealed by the new method on real-world resting-state fMRI data. Our method provides a new data-driven computational framework for identifying state-dependent effective connectivity, which will facilitate the identification and assessment of metastability and itinerant dynamics of the brain., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas exchange. Comprehensive evaluation of lung function cannot be obtained through chest X-ray and computed tomography. Proton-based lung MRI is particularly challenging due to low proton density within the lung tissue. In this review, we discuss an emerging technology--hyperpolarized gas MRI with inhaled 129 Xe, which provides functional and microstructural information and has the potential as a clinical tool for detecting the early stage and progression of certain lung diseases. We review the hyperpolarized 129 Xe MRI studies in patients with a range of pulmonary diseases, including chronic obstructive pulmonary disease, asthma, cystic fibrosis, pulmonary hypertension, radiation-induced lung injury and interstitial lung disease, and the applications of artificial intelligence were reviewed as well., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Purpose: To demonstrate the feasibility of zigzag sampling for 3D rapid hyperpolarized 129 Xe ventilation MRI in human., Methods: Zigzag sampling in one direction was combined with gradient-recalled echo sequence (GRE-zigzag-Y) to acquire hyperpolarized 129 Xe ventilation images. Image quality was compared with a balanced SSFP (bSSFP) sequence with the same spatial resolution for 12 healthy volunteers (HVs). For another 8 HVs and 9 discharged coronavirus disease 2019 subjects, isotropic resolution 129 Xe ventilation images were acquired using zigzag sampling in two directions through GRE-zigzag-YZ. 129 Xe ventilation defect percent (VDP) was quantified for GRE-zigzag-YZ and bSSFP acquisitions. Relationships and agreement between these VDP measurements were evaluated using Pearson correlation coefficient (r) and Bland-Altman analysis., Results: For 12 HVs, GRE-zigzag-Y and bSSFP required 2.2 s and 10.5 s, respectively, to acquire 129 Xe images with a spatial resolution of 3.96 × 3.96 × 10.5 mm 3 . Structural similarity index, mean absolute error, and Dice similarity coefficient between the two sets of images and ventilated lung regions were 0.85 ± 0.03, 0.0015 ± 0.0001, and 0.91 ± 0.02, respectively. For another 8 HVs and 9 coronavirus disease 2019 subjects, 129 Xe images with a nominal spatial resolution of 2.5 × 2.5 × 2.5 mm 3 were acquired within 5.5 s per subject using GRE-zigzag-YZ. VDP provided by GRE-zigzag-YZ was strongly correlated (R 2  = 0.93, p < 0.0001) with that generated by bSSFP with minimal biases (bias = -0.005%, 95% limit-of-agreement = [-0.414%, 0.424%])., Conclusion: Zigzag sampling combined with GRE sequence provides a way for rapid 129 Xe ventilation imaging., (© 2024 International Society for Magnetic Resonance in Medicine.)

Introduction: Many studies have found sex differences in alterations of brain function in cigarette-smoking adults from the perspective of functional activity or connectivity. However, no studies have systematically found different alteration patterns in brain functional topology of cigarette-smoking men and women from three perspectives: nodal and network efficiency and modular connections., Aims and Methods: Fifty-six tobacco use disorder (TUD) participants (25 women) and 66 non-TUD participants (28 women) underwent a resting-state functional magnetic resonance imaging scan. The whole-brain functional networks were constructed, and a two-way analysis of covariance with false discovery rate correction (q < 0.05) was performed to investigate whether men and women TUD participants had different alterations in the topological features at global, modular, and nodal levels., Results: Compared to non-TUD participants, men but not women TUD participants showed significantly lower global efficiency (lower intermodular connections between the visual and executive control and between the visual and subcortical modules did not pass the correction) and significantly lower nodal global efficiency in the right superior occipital gyrus, bilateral fusiform gyrus, the right pallidum, right putamen, the bilateral paracentral lobule, the postcentral gyrus, and lower nodal local efficiency in the left paracentral lobule., Conclusions: Men and women TUD participants have different topological properties of brain functional network, which may contribute to our understanding of neural mechanisms underlying sex differences in TUD., Implications: Compared to non-TUD participants, we found men but not women TUD participants with significantly lower network metrics at global, modular, and nodal levels, which could improve our understanding of neural mechanisms underlying sex differences in TUD and lay a solid foundation for future sex-based TUD prevention and treatment., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Assessing the effectiveness of nanomedicines involves evaluating the drug content at the target site. Currently, most research focuses on monitoring the signal responses from loaded drugs, neglecting the changes caused by the nanohosts. Here, we propose a strategy to quantitatively evaluate the content of loaded drugs by detecting the signal variations resulting from the alterations in the microenvironment of the nanohosts. Specifically, hyperpolarized (HP) 129 Xe atoms are employed as probes to sense the nanohosts' environment and generate a specific magnetic resonance (MR) signal that indicates their accessibility. The introduction of drugs reduces the available space in the nanohosts, leading to a crowded microenvironment that hinders the access of the 129 Xe atoms. By employing 129 Xe atoms as a signal source to detect the alterations in the microenvironment, we constructed a three-dimensional (3D) map that indicated the concentration of the nanohosts and established a linear relationship to quantitatively measure the drug content within the nanohosts based on the corresponding MR signals. Using the developed strategy, we successfully quantified the uptake of the nanohosts and drugs in living cells through HP 129 Xe MR imaging. Overall, the proposed HP 129 Xe atom-sensing approach can be used to monitor alterations in the microenvironment of nanohosts induced by loaded drugs and provides a new perspective for the quantitative evaluation of drug presence in various nanomedicines.

Early-onset mental disorders are associated with disrupted neurodevelopmental processes during adolescence. The methylazoxymethanol acetate (MAM) animal model, in which disruption in neurodevelopmental processes is induced, mimics the abnormal neurodevelopment associated with early-onset mental disorders from an etiological perspective. We conducted longitudinal structural magnetic resonance imaging (MRI) scans during childhood, adolescence, and adulthood in MAM rats to identify specific brain regions and critical windows for intervention. Then, the effect of repetitive transcranial magnetic stimulation (rTMS) intervention on the target brain region during the critical window was investigated. In addition, the efficacy of this intervention paradigm was tested in a group of adolescent patients with early-onset mental disorders (diagnosed with major depressive disorder or bipolar disorder) to evaluate its clinical translational potential. The results demonstrated that, compared to the control group, the MAM rats exhibited significantly lower striatal volume from childhood to adulthood (all P <0.001). In contrast, the volume of the hippocampus did not show significant differences during childhood (P >0.05) but was significantly lower than the control group from adolescence to adulthood (both P <0.001). Subsequently, rTMS was applied to the occipital cortex, which is anatomically connected to the hippocampus, in the MAM models during adolescence. The MAM-rTMS group showed a significant increase in hippocampal volume compared to the MAM-sham group (P <0.01), while the volume of the striatum remained unchanged (P >0.05). In the clinical trial, adolescents with early-onset mental disorders showed a significant increase in hippocampal volume after rTMS treatment compared to baseline (P <0.01), and these volumetric changes were associated with improvement in depressive symptoms (r = - 0.524, P = 0.018). These findings highlight the potential of targeting aberrant hippocampal development during adolescence as a viable intervention for early-onset mental disorders with neurodevelopmental etiology as well as the promise of rTMS as a therapeutic approach for mitigating aberrant neurodevelopmental processes and alleviating clinical symptoms., (© 2023. The Author(s).)

The immune checkpoint blockade strategy has improved the survival rate of late-stage lung cancer patients. However, the low immune response rate limits the immunotherapy efficiency. Here, we report a ROS-responsive Fe 3 O 4 -based nanoparticle that undergoes charge reversal and disassembly in the tumor microenvironment, enhancing the uptake of Fe 3 O 4 by tumor cells and triggering a more severe ferroptosis. In the tumor microenvironment, the nanoparticle rapidly disassembles and releases the loaded GOx and the immune-activating peptide Tuftsin under overexpressed H 2 O 2 . GOx can consume the glucose of tumor cells and generate more H 2 O 2 , promoting the disassembly of the nanoparticle and drug release, thereby enhancing the therapeutic effect of ferroptosis. Combined with Tuftsin, it can more effectively reverse the immune-suppressive microenvironment and promote the recruitment of effector T cells in tumor tissues. Ultimately, in combination with α-PD-L1, there is significant inhibition of the growth of lung metastases. Additionally, the hyperpolarized 129 Xe method has been used to evaluate the Fe 3 O 4 nanoparticle-mediated immunotherapy, where the ventilation defects in lung metastases have been significantly improved with complete lung structure and function recovered. The ferroptosis-enhanced immunotherapy combined with non-radiation evaluation methodology paves a new way for designing novel theranostic agents for cancer therapy., (© 2024 Wiley-VCH GmbH.)

Background: Ultra-high field 7T MRI can provide excellent tissue contrast and anatomical details, but is often cost prohibitive, and is not widely accessible in clinical practice., Purpose: To generate synthetic 7T images from widely acquired 3T images with deep learning and to evaluate the feasibility of this approach for brain imaging., Study Type: Prospective., Population: 33 healthy volunteers and 89 patients with brain diseases, divided into training, and evaluation datasets in the ratio 4:1., Sequence and Field Strength: T1-weighted nonenhanced or contrast-enhanced magnetization-prepared rapid acquisition gradient-echo sequence at both 3T and 7T., Assessment: A generative adversarial network (SynGAN) was developed to produce synthetic 7T images from 3T images as input. SynGAN training and evaluation were performed separately for nonenhanced and contrast-enhanced paired acquisitions. Qualitative image quality of acquired 3T and 7T images and of synthesized 7T images was evaluated by three radiologists in terms of overall image quality, artifacts, sharpness, contrast, and visualization of vessel using 5-point Likert scales., Statistical Tests: Wilcoxon signed rank tests to compare synthetic 7T images with acquired 7T and 3T images and intraclass correlation coefficients to evaluate interobserver variability. P < 0.05 was considered significant., Results: Of the 122 paired 3T and 7T MRI scans, 66 were acquired without contrast agent and 56 with contrast agent. The average time to generate synthetic images was ~11.4 msec per slice (2.95 sec per participant). The synthetic 7T images achieved significantly improved tissue contrast and sharpness in comparison to 3T images in both nonenhanced and contrast-enhanced subgroups. Meanwhile, there was no significant difference between acquired 7T and synthetic 7T images in terms of all the evaluation criteria for both nonenhanced and contrast-enhanced subgroups (P ≥ 0.180)., Data Conclusion: The deep learning model has potential to generate synthetic 7T images with similar image quality to acquired 7T images., Level of Evidence: 2 TECHNICAL EFFICACY: Stage 1., (© 2023 International Society for Magnetic Resonance in Medicine.)

Prognosticating acute lung injury (ALI) is challenging, in part because of a lack of sensitive biomarkers. Hyperpolarized gas magnetic resonance (MR) has unique advantages in pulmonary function measurement and can provide promising biomarkers for the assessment of lung injuries. Herein, we employ hyperpolarized 129 Xe MRI and generate a number of imaging biomarkers to detect the pulmonary physiological and morphological changes during the progression of ALI in an animal model. We find the measured ratio of 129 Xe in red blood cells to interstitial tissue/plasma (RBC/TP) is significantly lower in the ALI group on the second (0.32 ± 0.03, p = 0.004), seventh (0.23 ± 0.03, p < 0.001), and 14th (0.29 ± 0.04, p = 0.001) day after lipopolysaccharide treatment compared with that in the control group (0.41 ± 0.04). In addition, significant differences are also observed for RBC/TP measurements between the second and seventh day (p = 0.001) and between the seventh and 14th day (p = 0.018) in the ALI group after treatment. Besides RBC/TP, significant differences are also observed in the measured exchange time constant (T) on the second (p = 0.038) and seventh day (p = 0.009) and in the measured apparent diffusion coefficient (ADC) and alveolar surface-to-volume ratio (SVR) on the 14th day (ADC: p = 0.009 and SVR: p = 0.019) after treatment in the ALI group compared with that in the control group. These findings indicate that the parameters measured with 129 Xe MR can detect the dynamic changes in pulmonary structure and function in an ALI animal model., (© 2023 John Wiley & Sons, Ltd.)

We report a dual-signal chemical exchange saturation transfer (Dusi-CEST) strategy for drug delivery and detection in living cells. The two signals can be detected by operators in complex environments. This strategy is demonstrated on a cucurbit[6]uril (CB[6]) nanoparticle probe, as an example. The CB[6] probe is equipped with two kinds of hydrophobic cavities: one is found inside CB[6] itself, whereas the other exists inside the nanoparticle. When the probe is dispersed in aqueous solution as part of a hyperpolarized 129 Xe NMR experiment, two signals appear at two different chemical shifts (100 and 200 ppm). These two resonances correspond to the NMR signals of 129 Xe in the two different cavities. Upon loading with hydrophobic drugs, such as paclitaxel, for intracellular drug delivery, the two resonances undergo significant changes upon drug loading and cargo release, giving rise to a metric enabling the assessment of drug delivery success. The simultaneous change of Dusi-CEST likes a mobile phone that can receive both LTE and Wi-Fi signals, which can help reduce the occurrence of false positives and false negatives in complex biological environments and help improve the accuracy and sensitivity of single-shot detection.

Background: The ventral tegmental area (VTA) contains heterogeneous cell populations. The dopaminergic neurons in VTA play a central role in reward and cognition, while CamKIIα-positive neurons, composed mainly of glutamatergic and some dopaminergic neurons, participate in the reward learning and locomotor activity behaviors. The differences in brain-wide functional and structural networks between these two neuronal subtypes were comparatively elucidated., Methods: In this study, we applied a method combining Designer Receptors Exclusively Activated by Designer Drugs (DREADD) and fMRI to assess the cell type-specific modulation of whole-brain neural networks. rAAV encoding the cre-dependent hM3D was injected into the right VTA of DAT-cre or CamKIIα-cre transgenic rats. The global brain activities elicited by DREADD stimulation were then detected using BOLD-fMRI. Furthermore, the cre-dependent antegrade transsynaptic viral tracer H129ΔTK-TT was applied to label the outputs of VTA neurons., Results: We found that DREADD stimulation of dopaminergic neurons induced significant BOLD signal changes in the VTA and several VTA-related regions including mPFC, Cg and Septum. More regions responded to selective activation of VTA CamKIIα-positive neurons, resulting in increased BOLD signals in VTA, Insula, mPFC, MC&#95;R (Right), Cg, Septum, Hipp, TH&#95;R, PtA&#95;R, and ViC&#95;R. Along with DREADD-BOLD analysis, further neuronal tracing identified multiple cortical (MC, mPFC) and subcortical (Hipp, TH) brain regions that are structurally and functionally connected by VTA dopaminergic and CamKIIα-positive neurons., Conclusions: Our study dissects brain-wide structural and functional networks of two neuronal subtypes in VTA and advances our understanding of VTA functions., (© 2023. BioMed Central Ltd., part of Springer Nature.)

In NMR-based untargeted metabolomic studies, 1 H NMR spectra are usually divided into equal bins/buckets to diminish the effects of peak shift caused by sample status or instrument instability, and to reduce the number of variables used as input for the multivariate statistical analysis. It was noticed that the peaks near bin boundaries may cause significant changes in integral values of adjacent bins, and the weaker peak may be obscured if it is allocated in the same bin with intense peaks. Several efforts have been taken to improve the performance of binning. Here we propose an alternative method, named P-Bin, based on the combination of the classic peak-picking and binning procedures. The location of each peak defined by peak-picking is used as the center of the individual bin. P-Bin is expected to keep all spectral information associated with the peaks and significantly reduce the data size as the spectral regions without peaks are not considered. In addition, both peak-picking and binning are routine procedures, making P-Bin easy to be implemented. To verify the performance, two sets of experimental data from human plasma and Ganoderma lucidum (G. lucidum) extracts were processed using the conventional binning method and the proposed method, before the principal component analysis (PCA) and the orthogonal projection to latent structures discriminant analysis (OPLS-DA). The results indicate that the proposed method has improved both the clustering performance of PCA score plots and the interpretability of OPLS-DA loading plots, and P-Bin could be an improved version of data preparation for metabonomic study., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

In-cell NMR spectroscopy is an effective tool for observing proteins at atomic resolution in their native cellular environment. However, its utility is limited by its low sensitivity and the extensive line broadening caused by nonspecific interactions in the cells, which is even more pronounced in human cells due to the difficulty of overexpressing or delivering high concentrations of isotopically labeled proteins. Here, we present a high-sensitivity tag (wPSP-6F) containing two trifluoromethyl groups that can efficiently label globular proteins with molecular weights in the 6-40 kDa range under mild conditions. This tag allowed us to detect globular proteins in human cells at concentrations as low as 1.0 μM, which would not have been achievable with 15 N or 3-fluorotyrosine labeling. Moreover, we detected conformational changes and interactions of proteins in the cellular environment. The new sensitive 19 F NMR tag may significantly expand the scope of protein NMR in human cells., (© 2023 Wiley-VCH GmbH.)

The predicted age difference (PAD) between an individual's predicted brain age and chronological age has been commonly viewed as a meaningful phenotype relating to aging and brain diseases. However, the systematic bias appears in the PAD achieved using machine learning methods. Recent studies have designed diverse bias correction methods to eliminate it for further downstream studies. Strikingly, here we demonstrate that bias still exists in the PAD of samples with the same age even after kind of correction. Therefore, current PAD may not be taken as a reliable phenotype and more investigations are needed to solve this fundamental defect. To this end, we propose an age-level bias correction method and demonstrate its efficacy in numerical experiments., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Multishot scan magnetic resonance imaging (MRI) acquisition is inherently sensitive to motion, and motion artifact reduction is essential for improving the image quality in MRI. This work proposes and validates a new end-to-end motion-correction method for the multishot sequence that incorporates a conditional generative adversarial network with minimum entropy (cGANME) of MR images. The cGANME contains an encoder-decoder generator to obtain motion-corrected images and a PatchGAN discriminator to classify the image as either real (motion-free) or fake (motion-corrected). The entropy of the images is set as one loss item in the cGAN's loss as the entropy increases monotonically with the motion artifacts. An ablation experiment of the different weights of entropy loss was performed to evaluate the function of entropy loss. The preclinical dataset was acquired with a fast spin echo pulse sequence on a 7.0-T scanner. After the simulation, we had 10,080/2880/1440 slices for training, testing, and validating, respectively. The clinical dataset was downloaded from the Human Connection Project website, and 11,300/3500/2000 slices were used for training, testing, and validating after simulation, respectively. Extensive experiments for different motion patterns, motion levels, and protocol parameters demonstrate that cGANME outperforms traditional and some state-of-the-art, deep learning-based methods. In addition, we tested cGANME on in vivo awake rats and mitigated the motion artifacts, indicating that the model has some generalizability., (© 2022 John Wiley & Sons, Ltd.)

The article considers the problem of dividing the encephalography data into two time series, that generated by the brain and that generated by other electrical sources located in the human head. The magnetic encephalograms and magnetic resonance images of the head were recorded in the Center for Neuromagnetism at NYU Grossman School of Medicine. Data obtained at McGill University and Montreal University were also used. Recordings were made in a magnetically shielded room and the gradiometers were designed to suppress external noise, making it possible to eliminate them from the data analysis. Magnetic encephalograms were analyzed by the method of functional tomography, based on the Fourier transform and on the solution of inverse problem for all frequencies. In this method, one spatial position is assigned to each frequency component. Magnetic resonance images of the head were evaluated to annotate the space to be included in the analysis. The included space was divided into two parts: «brain» and «non-brain». The frequency components were classified by the feature of their inclusion in one or the other part. The set of frequencies, designated as «brain», represented the partial spectrum of the brain signal, while the set of frequencies designated as «non-brain», represented the partial spectrum of the physiological noise produced by the head. Both partial spectra shared the same frequency band. From the partial spectra, a time series of the «brain» area signal and «non-brain» area head noise were reconstructed. Summary spectral power of the signal was found to be ten times greater than the noise. The proposed method makes it possible to analyze in detail both the signal and the noise components of the encephalogram and to filter the magnetic encephalogram., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Llinás, Rykunov, Walton, Boyko and Ustinin.)

The long-range heteronuclear correlation remains a significant challenge in solid-state nuclear magnetic resonance (NMR), which is critical in the structural elucidation of biomolecular, material, and pharmaceutical solids. We propose a selective NMR method, heteronuclear selective phase-optimized recoupling (hetSPR), to selectively enhance long-range correlations of interest by utilizing characteristic chemical shifts. Compared to conventional methods, hetSPR can selectively enhance desired heteronuclear correlations (e.g., 1 H- 13 C and 1 H- 19 F) by factors up to 5 and largely suppress the unwanted ones. The method proves useful by enhancing the long-range correlation from an intermolecular 1 H- 19 F distance of 4.8 Å by a factor of 2.4 in a fluorinated pharmaceutical drug, bicalutamide, under fast magic-angle spinning. It does not use selective pulses and is thus user-friendly even for nonexperts. The new method is expected to boost solid-state NMR to elucidate the structures of various solids.

The investigation of neural circuits is important for interpreting both healthy brain function and psychiatric disorders. Currently, the architecture of neural circuits is always investigated with fluorescent protein encoding neurotropic virus and ex vivo fluorescent imaging technology. However, it is difficult to obtain a whole-brain neural circuit connection in living animals, due to the limited fluorescent imaging depth. Herein, the noninvasive, whole-brain imaging technique of MRI and the hypotoxicity virus vector AAV (adeno-associated virus) were combined to investigate the whole-brain neural circuits in vivo. AAV2-retro are an artificially-evolved virus vector that permits access to the terminal of neurons and retrograde transport to their cell bodies. By expressing the ferritin protein which could accumulate iron ions and influence the MRI contrast, the neurotropic virus can cause MRI signal changes in the infected regions. For mice injected with the ferritin-encoding virus vector (rAAV2-retro-CAG-Ferritin) in the caudate putamen (CPu), several regions showed significant changes in MRI contrasts, such as PFC (prefrontal cortex), HIP (hippocampus), Ins (insular cortex) and BLA (basolateral amygdala). The expression of ferritin in those regions was also verified with ex vivo fluorescence imaging. In addition, we demonstrated that changes in T2 relaxation time could be used to identify the spread area of the virus in the brain over time. Thus, the neural connections could be longitudinally detected with the in vivo MRI method. This novel technique could be utilized to observe the viral infection process and detect the neural circuits in a living animal., (© 2021 Innovation Academy for Precision Measurement Science and Technology. Human Brain Mapping published by Wiley Periodicals LLC.)

A novel approach, concentration-ordered NMR spectroscopy (CORDY), is being proposed based on the principle that the ratio of the NMR peak area to its associated number of spins is proportional to the concentration of the assigned compound. Besides, prior information of chemical shift distribution and line shape characteristics of different chemical groups is utilized to shrink the solution space. CORDY generates a pseudo-two-dimensional NMR spectrum with chemical shifts in one axis and concentrations in the other, resulting in both separation and quantitation of components in complex samples. The method was validated by application to three samples-a model mixture containing six amino acids, sugar-free Red Bull, and human urine. It was demonstrated that CORDY could successfully separate the components with up to 2 orders of magnitude in the concentration dimension for the samples used in the current study. In addition, a combination of CORDY and DOSY (CORDY-DOSY) has been found to be more efficient in resolving the molecules with similar concentrations or self-diffusion coefficients.

Quantitative magnetic resonance imaging (MRI) estimates magnetic parameters related to tissue, such as T1, T2 relaxation times and proton density. MR fingerprinting (MRF) is a new concept that uses pseudo-random, incoherent measurements to create a unique fingerprint for each tissue type to quantify magnet parameters. This paper aims to enhance MRF performance by investigating (i) the most suitable acquisition trajectory, and (ii) analytical transformations, suitable for radial acquisitions. Highly undersampled MRF brain (k, t)-space data have been simulated and non-linearly reconstructed to exploit the low-rank property of dynamic imaging. Based on our findings, the radial trajectory is the most suitable for MRF compared to Cartesian and spiral acquisitions. Perhaps this is due to the fact that its aliasing artifacts are more noise-like, and that unlike spiral trajectories, it can use analytical transformations that do not require re-gridding. One such analytical algorithm is the spline reconstruction technique (SRT) that is based on a novel numerical implementation of an analytic representation of the inverse Radon transform. Here, for the first time, this algorithm is applied to MR radial data. Reconstructions using SRT were compared to the ones using filtered back-projection. SRT provided images of higher contrast, lower bias, which resulted in more accurate T1, T2 values., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Compressed sensing (CS) theory can help accelerate magnetic resonance imaging (MRI) by sampling partial k-space measurements. However, conventional optimization-based CS-MRI methods are often time-consuming and are based on fixed transform or shallow image dictionaries, which limits modeling capabilities. Recently, deep learning models have been used to solve the CS-MRI problem. However, recent researches have focused on modeling in image domain, and the potential of k-space modeling capability has not been utilized seriously. In this paper, we propose a deep model called Dual Domain Dense network (Triple-D network), which consisted of some k-space and image domain sub-network. These sub-networks are connected with dense connections, which can utilize feature maps at different levels to enhance performance. To further promote model capabilities, we use two strategies: multi-supervision strategies, which can avoid loss of supervision information; channel-wise attention layer (CA layer), which can adaptively adjust the weight of the feature map. Experimental results show that the proposed Triple-D network provides promising performance in CS-MRI, and it can effectively work on different sampling trajectories and noisy settings., (Copyright © 2020. Published by Elsevier Inc.)

MRI with hyperpolarized 129 Xe can achieve low-concentration detection. Herein, nanoparticle-coated perfluorooctyl bromide (PFOB) was developed as a 129 Xe MRI contrast agent with a moderate exchange rate, sufficient stability and feasible surface modification. The α v β 3 integrin overexpressed by non-small-cell lung cancer A549 cells was successfully detected by 129 Xe MRI with high specificity through adequate surface modifications.

An enriched environment (EE) provides multi-dimensional stimuli to the brain. EE exposure for days to months induces functional and structural neuroplasticity. In this study, manganese-enhanced magnetic resonance imaging (MEMRI) was used to map the accumulative whole-brain activities associated with a 7-day EE exposure in freely-moving adult male mice, followed by c-Fos immunochemical assessments. Relative to the mice residing in a standard environment (SE), the mice subjected to EE treatment had significantly enhanced regional MEMRI signal intensities in the prefrontal cortex, somatosensory cortices, basal ganglia, amygdala, motor thalamus, lateral hypothalamus, ventral hippocampus and midbrain dopaminergic areas at the end of the 7-day exposure, likely attributing to enhanced Mn 2+ uptake/transport associated with brain activities at both the regional and macroscale network levels. Some of, but not all, the brain regions in the EE-treated mice showing enhanced MEMRI signal intensity had accompanying increases in c-Fos expression. The EE-treated mice were also found to have significantly increased overall amount of food consumption, decreased body weight gain and upregulated tyrosine hydroxylase (TH) expression in the midbrain dopaminergic areas. Taken together, these results demonstrated that the 7-day EE exposure was associated with elevated cumulative activities in the nigrostriatal, mesolimbic and corticostriatal circuits underpinning reward, motivation, cognition, motor control and appetite regulation. Such accumulative activities might have served as the substrate of EE-related neuroplasticity and the beneficial effects of EE treatment on neurological/psychiatric conditions including drug addiction, Parkinson's disease and eating disorder., Competing Interests: Declarations of competing interest None., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Monodisperse polyethylene glycols-modified (M-PEGylated) biomaterials exhibit high structural accuracy, biocompatibility, and fine-tunable physicochemical properties. To develop "smart" drug delivery systems in a controllable and convenient manner, a peptidic M-PEG "comb" with fluorinated L-lysine side chains and a fluorescent N-terminal is conveniently prepared as a 19 F magnetic resonance imaging ( 19 F MRI) and fluorescence dual-imaging traceable and thermo-responsive "add-on" module for liposomal theranostics in cancer therapy. The peptidic M-PEG "comb" has high biocompatibility, thermo-responsivity with a sharp lower critical solution temperature, an aggregation-induced emission fluorescence, and high 19 F MRI sensitivity. As a highly branched amphiphile, it self-assembles and firmly anchors on the doxorubicin-loaded liposomal nanoparticles, which M-PEGylates the liposomes and facilitates the thermo-responsive drug release and drug tracking with dual-imaging technologies. In a rodent xenograft model of human liver cancer HepG2 cells, the M-PEGylated liposomes exhibit long in vivo half time, low toxicity, high tumor accumulation, "hot spot" 19 F MRI, and therapeutic efficacy. With accurately programmable chemical structure, fine-tunable physicochemical and biological properties to meet the demands of diagnosis, drug delivery, and therapy, the M-PEG "comb" is promising as a versatile "add-on" module for rapid and convenient formulation of various "smart" theranostics., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Purpose: This study incorporates a gradient system imperfection model into an optimal control framework for radio frequency (RF) pulse design., Theory and Methods: The joint design of minimum-time RF and slice selective gradient shapes is posed as an optimal control problem. Hardware limitations such as maximal amplitudes for RF and slice selective gradient or its slew rate are included as hard constraints to assure practical applicability of the optimized waveforms. In order to guarantee the performance of the optimized waveform with possible gradient system disturbances such as limited system bandwidth and eddy currents, a measured gradient impulse response function (GIRF) for a specific system is integrated into the optimization., Results: The method generates optimized RF and pre-distorted slice selective gradient shapes for refocusing that are able to fully compensate the modeled imperfections of the gradient system under investigation. The results nearly regenerate the optimal results of an idealized gradient system. The numerical Bloch simulations are validated by phantom and in-vivo experiments on 2 3T scanners., Conclusions: The presented design approach demonstrates the successful correction of gradient system imperfections within an optimal control framework for RF pulse design., (© 2019 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Withdrawal plays a key role in the development of addiction, and several brain regions, such as the extended amygdala, are functional during this stage. Manganese-enhanced magnetic resonance imaging (MEMRI) is a promising method for directly studying neural activity during morphine withdrawal, versus functional MRI, which is based on hemodynamic alterations. The functional brain circuitry associated with morphine withdrawal has not been thoroughly investigated, and there are very few longitudinal studies utilizing MEMRI to explore brain activity during this stage. In our experiments, we revealed essential brain regions involved in morphine withdrawal by application of a novel dynamic MEMRI approach, and demonstrated dynamic alterations of functional brain activities in these associated brain regions. Our results demonstrate that the dynamic MEMRI approach is an effective method that may be applied to reveal dynamic alterations in functional brain activity during morphine withdrawal., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Motivation: Study of brain images of rodent animals is the most straightforward way to understand brain functions and neural basis of physiological functions. An important step in brain image analysis is to precisely assign signal labels to specified brain regions through matching brain images to standardized brain reference atlases. However, no significant effort has been made to match different types of brain images to atlas images due to influence of artifact operation during slice preparation, relatively low resolution of images and large structural variations in individual brains., Results: In this study, we develop a novel image sequence matching procedure, termed accurate and robust matching brain image sequences (ARMBIS), to match brain image sequences to established atlas image sequences. First, for a given query image sequence a scaling factor is estimated to match a reference image sequence by a curve fitting algorithm based on geometric features. Then, the texture features as well as the scale and rotation invariant shape features are extracted, and a dynamic programming-based procedure is designed to select optimal image subsequences. Finally, a hierarchical decision approach is employed to find the best matched subsequence using regional textures. Our simulation studies show that ARMBIS is effective and robust to image deformations such as linear or non-linear scaling, 2D or 3D rotations, tissue tear and tissue loss. We demonstrate the superior performance of ARMBIS on three types of brain images including magnetic resonance imaging, mCherry with 4',6-diamidino-2-phenylindole (DAPI) staining and green fluorescent protein without DAPI staining images., Availability and Implementation: The R software package is freely available at https://www.synapse.org/#!Synapse:syn18638510/wiki/591054 for Not-For-Profit Institutions. If you are a For-Profit Institution, please contact the corresponding author., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: To fast and accurately reconstruct human lung gas MRI from highly undersampled k-space using deep learning., Methods: The scheme was comprised of coarse-to-fine nets (C-net and F-net). Zero-filling images from retrospectively undersampled k-space at an acceleration factor of 4 were used as input for C-net, and then output intermediate results which were fed into F-net. During training, a L2 loss function was adopted in C-net, while a function that united L2 loss with proton prior knowledge was used in F-net. The 871 hyperpolarized 129 Xe pulmonary ventilation images from 72 volunteers were randomly arranged as training (90%) and testing (10%) data. Ventilation defect percentage comparisons were implemented using a paired 2-tailed Student's t-test and correlation analysis. Furthermore, prospective acquisitions were demonstrated in 5 healthy subjects and 5 asymptomatic smokers., Results: Each image with size of 96 × 84 could be reconstructed within 31 ms (mean absolute error was 4.35% and structural similarity was 0.7558). Compared with conventional compressed sensing MRI, the mean absolute error decreased by 17.92%, but the structural similarity increased by 6.33%. For ventilation defect percentage, there were no significant differences between the fully sampled and reconstructed images through the proposed algorithm (P = 0.932), but had significant correlations (r = 0.975; P < 0.001). The prospectively undersampled results validated a good agreement with fully sampled images, with no significant differences in ventilation defect percentage but significantly higher signal-to-noise ratio values., Conclusion: The proposed algorithm outperformed classical undersampling methods, paving the way for future use of deep learning in real-time and accurate reconstruction of gas MRI., (© 2019 International Society for Magnetic Resonance in Medicine.)

The elucidation of neural networks is essential to understanding the mechanisms of brain functions and brain disorders. Neurotropic virus-based trans-synaptic tracing tools have become an effective method for dissecting the structure and analyzing the function of neural-circuitry. However, these tracing systems rely on fluorescent signals, making it hard to visualize the panorama of the labeled networks in mammalian brain in vivo. One MRI method, Diffusion Tensor Imaging (DTI), is capable of imaging the networks of the whole brain in live animals but without information of anatomical connections through synapses. In this report, a chimeric gene coding for ferritin and enhanced green fluorescent protein (EGFP) was integrated into Vesicular stomatitis virus (VSV), a neurotropic virus that is able to spread anterogradely in synaptically connected networks. After the animal was injected with the recombinant VSV (rVSV), rVSV-Ferritin-EGFP, into the somatosensory cortex (SC) for four days, the labeled neural-network was visualized in the postmortem whole brain with a T2-weighted MRI sequence. The modified virus transmitted from SC to synaptically connected downstream regions. The results demonstrate that rVSV-Ferritin-EGFP could be used as a bimodal imaging vector for detecting synaptically connected neural-network with both ex vivo MRI and fluorescent imaging. The strategy in the current study has the potential to longitudinally monitor the global structure of a given neural-network in living animals., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background and Purpose: We investigated the baseline demographics of patients with severe unilateral atherosclerotic stenosis of the middle cerebral artery (MCA) using multimodal MRI and evaluated the haemodynamic impairments and plaque characteristics of patients who had a recurrent stroke., Materials and Methods: We retrospectively recruited consecutive patients with severe unilateral atherosclerotic MCA stenosis who underwent arterial spin labelling (ASL) with postlabelling delay (PLD) of 1.5 and 2.5 s, and vessel wall MRI. For each PLD, cerebral blood flow (CBF) maps were generated. Hypoperfusion volume ratio (HVR) from 2 PLD CBF was calculated. An HVR value ≥50% was considered as severe HVR. Plaque areas, plaque burden, plaque length and remodelling index were measured. Plaque enhancement at maximal lumen narrowing site were graded. Baseline clinical and imaging characteristics were compared between patients with (event+) and without (event-) 1 year ischaemic events., Results: Forty-three patients (47.23±12.15 years; 28 men) were enrolled in this study. Seven patients had an HVR ≥50%. During the 1-year follow-up, 7 patients had experienced a recurrent stroke. HVR were significantly higher in the event+ than event- (53.17%±29.82% vs 16.9%±15.57%, p=0.0002), whereas no significant difference was detected in plaque areas, plaque burden, remodelling index, plaque length and plaque enhancement grade. The multivariable analysis revealed that a severe HVR was significantly associated with a recurrent stroke (Odds ratio=12.93, 95% confidence interval 1.57 to 106.24, p=0.017) after adjusted by hypertension and smoking., Conclusion: HVR obtained from two PLD ASL may be a useful imaging predictor of recurrent stroke., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Myocardial ischemia and reperfusion-evoked spinal reflexes involve nociceptive signals that trigger neuronal excitation through cardiac afferents, projecting into the thoracic spinal cord. Ischemic preconditioning (IPC) involves brief episodes of sublethal ischemia and reperfusion enhances the resistance of the myocardium to subsequent ischemic insults. This study investigated the effects of IPC on ischemia-reperfusion (I/R) stimulation-induced activation in the thoracic spinal cord of rats., Methods: A new remotely controlled I/R model was established. The infarct size was determined as a percentage of area at risk (IS/AAR) and arrhythmia scores were evaluated. Non-invasive in vivo fMRI was used for signal quantitative analysis of thoracic spinal spatiotemporal. The role of IPC on the excitability of substantia gelatinosa (SG) neurons was assessed by spinal patch clamp recording technique. The altered expressions of c-Fos, SP, and CGRP in T 4 segment were detected by immunohistochemical staining., Results: The novel I/R model was induced successfully and reliably utilized, and IPC treatment markedly reduced the myocardial infarct size. fMRI analysis revealed that IPC reduced the increased BOLD signals induced by prolonged ischemia-reperfusion. Patch clamp recording showed that IPC treatment reversed the enhanced excitability of SG neurons during I/R treatment. The results of immunofluorescent staining indicated that IPC mitigated the I/R-induced dramatic increase of c-Fos, and reduced the release of SP and CGRP in dorsal horns of spinal cord., Conclusions: These results suggested that IPC suppressed neuronal activation induced by I/R stimuli in rat thoracic spinal cord using spinal cord fMRI and patch clamp recording techniques., (Copyright © 2019 Elsevier B.V. All rights reserved.)

A fluorinated aza-BODIPY derivative BDPF was developed as a small molecule contrast agent, which displayed highly efficient near infrared fluorescence/photoacoustic/19F MR tri-modality tumor imaging.

Pulmonary diseases usually result in changes of the blood-gas exchange function in the early stages. Gas exchange across the respiratory membrane and gas diffusion in the alveoli can be quantified using hyperpolarized 129 Xe MR via chemical shift saturation recovery (CSSR) and diffusion-weighted imaging (DWI), respectively. Generally, CSSR and DWI data have been collected in separate breaths in humans. Unfortunately, the lung inflation level cannot be the exactly same in different breaths, which causes fluctuations in blood-gas exchange and pulmonary microstructure. Here we combine CSSR and DWI obtained with compressed sensing, to evaluate the gas diffusion and exchange function within a single breath-hold in humans. A new parameter, namely the perfusion factor of the respiratory membrane (SVR d/g ), is proposed to evaluate the gas exchange function. Hyperpolarized 129 Xe MR data are compared with pulmonary function tests and computed tomography examinations in healthy young, age-matched control, and chronic obstructive pulmonary disease human cohorts. SVR d/g decreases as the ventilation impairment and emphysema index increase. Our results indicate that the proposed method has the potential to detect the extent of lung parenchyma destruction caused by age and pulmonary diseases, and it would be useful in the early diagnosis of pulmonary diseases in clinical practice., (© 2019 John Wiley & Sons, Ltd.)

Nano contrast agents (Nano CA) are nanomaterials used to increase contrast in the medical magnetic resonance imaging (MRI). However, the related relaxation mechanism of the Nano CA is not clear yet and little significant breakthrough in relaxivity enhancement has been achieved. Herein, a new hydrophilic Gd-DOTA complex functionalized with different chain length of PEG was synthesized and incorporated into graphene quantum dots (GQD) to obtain paramagnetic graphene quantum dots (PGQD). We performed a variable-temperature and variable-field intensity NMR study in aqueous solution on the water exchange and rotational dynamics of three different chain lengths of PGQD. The optimal GQD with paramagnetic chain length shows a great improvement in performance on 1 H NMR relaxometric studies. In vitro results demonstrated that the relaxivity of the designed PGQD could be controlled by regulating the PEG length, and its relaxivity was ∼16 times higher than that of current commercial MRI contrast agents (e.g., Gd-DTPA), on a "per Gd" basis. The relaxivity of the Nano CA can be rationally tuned to obtain unmatched potentials in MR imaging, exemplified by preparation of the paramagnetic GQD with the enhanced T 1 relaxivity. The fabricated PGQDs with suitable PEG length got the best relaxivity at 1.5 T. After intravenous injection, its feeding process by solid tumor could even be monitored by clinically used 1.5 T MRI scanners. This research will also provide an excellent platform for the design and synthesis of highly effective MR contrast agents.

Purpose: Joint design of minimum duration RF pulses and slice-selective gradient shapes for MRI via time optimal control with strict physical constraints, and its application to simultaneous multislice imaging., Theory and Methods: The minimization of the pulse duration is cast as a time optimal control problem with inequality constraints describing the refocusing quality and physical constraints. It is solved with a bilevel method, where the pulse length is minimized in the upper level, and the constraints are satisfied in the lower level. To address the inherent nonconvexity of the optimization problem, the upper level is enhanced with new heuristics for finding a near global optimizer based on a second optimization problem., Results: A large set of optimized examples shows an average temporal reduction of 87.1% for double diffusion and 74% for turbo spin echo pulses compared to power independent number of slices pulses. The optimized results are validated on a 3T scanner with phantom measurements., Conclusion: The presented design method computes minimum duration RF pulse and slice-selective gradient shapes subject to physical constraints. The shorter pulse duration can be used to decrease the effective echo time in existing echo-planar imaging or echo spacing in turbo spin echo sequences., (© 2018 International Society for Magnetic Resonance in Medicine.)

Hyperpolarized 129 Xe gas MR has been a powerful tool for evaluating pulmonary structure and function due to the extremely high enhancement in spin polarization, the good solubility in the pulmonary parenchyma, and the excellent chemical sensitivity to its surrounding environment. Generally, the quantitative structural and functional information of the lung are evaluated using hyperpolarized 129 Xe by employing the techniques of chemical shift saturation recovery (CSSR) and xenon polarization transfer contrast (XTC). Hyperpolarized 129 Xe chemical exchange saturation transfer (Hyper-CEST) is another method for quantifying the exchange information of hyperpolarized 129 Xe by using the exchange of xenon signals according to its different chemical shifts, and it has been widely used in biosensor studies in vitro. However, the feasibility of using hyperpolarized 129 Xe CEST to quantify the pulmonary gas exchange function in vivo is still unclear. In this study, the technique of CEST was used to quantitatively evaluate the gas exchange in the lung globally and regionally via hyperpolarized 129 Xe MRS and MRI, respectively. A new parameter, the pulmonary apparent gas exchange time constant (T app ), was defined, and it increased from 0.63 s to 0.95 s in chronic obstructive pulmonary disease (COPD) rats (induced by cigarette smoke and lipopolysaccharide exposure) versus the controls with a significant difference (P = 0.001). Additionally, the spatial distribution maps of T app in COPD rats' pulmonary parenchyma showed a regionally obvious increase compared with healthy rats. These results indicated that hyperpolarized 129 Xe CEST MR was an effective method for globally and regionally quantifying the pulmonary gas exchange function, which would be helpful in diagnosing lung diseases that are related to gas exchange, such as COPD., (© 2018 John Wiley & Sons, Ltd.)

The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Dynamic hyperpolarized (HP) 129 Xe MRI is able to visualize the process of lung ventilation, which potentially provides unique information about lung physiology and pathophysiology. However, the longitudinal magnetization of HP 129 Xe is nonrenewable, making it difficult to achieve high image quality while maintaining high temporal-spatial resolution in the pulmonary dynamic MRI. In this paper, we propose a new accelerated dynamic HP 129 Xe MRI scheme incorporating the low-rank, sparse and gas-inflow effects (L + S + G) constraints. According to the gas-inflow effects of HP gas during the lung inspiratory process, a variable-flip-angle (VFA) strategy is designed to compensate for the rapid attenuation of the magnetization. After undersampling k-space data, an effective reconstruction algorithm considering the low-rank, sparse and gas-inflow effects constraints is developed to reconstruct dynamic MR images. In this way, the temporal and spatial resolution of dynamic MR images is improved and the artifacts are lessened. Simulation and in vivo experiments implemented on the phantom and healthy volunteers demonstrate that the proposed method is not only feasible and effective to compensate for the decay of the magnetization, but also has a significant improvement compared with the conventional reconstruction algorithms (P-values are less than 0.05). This confirms the superior performance of the proposed designs and their ability to maintain high quality and temporal-spatial resolution., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The rational design of theranostic nanoprobe to present responsive effect of therapeutic potency and enhanced diagnostic imaging in tumor milieu plays a vital role for efficient personalized cancer therapy and other biomedical applications. We aimed to afford a potential strategy to pose both T 1 - and T 2 -weighted MRI functions, and thereby realizing imaging guided drug delivery and targeted therapy., Results: Theranostic nanocomposites Mn-porphyrin&Fe 3 O 4 @SiO 2 @PAA-cRGD were fabricated and characterized, and the nanocomposites were effectively used in T 1 - and T 2 -weighted MRI and pH-responsive drug release. Fluorescent imaging also showed that the nanocomposites specifically accumulated in lung cancer cells by a receptor-mediated process, and were nontoxic to normal cells. The r 2 /r 1 ratio was 20.6 in neutral pH 7.4, which decreased to 7.7 in acidic pH 5.0, suggesting the NCs could act as an ideal T 1 /T 2 dual-mode contrast agent at acidic environments of tumor. For in vivo MRI, T 1 and T 2 relaxation was significantly accelerated to 55 and 37%, respectively, in the tumor after i.v. injection of nanocomposites., Conclusion: The synthesized nanocomposites exhibited highly sensitive MRI contrast function no matter in solution, cells or in vivo by synergistically enhancing positive and negative magnetic resonance imaging signals. The nanocomposites showed great potential for integrating imaging diagnosis and drug controlled release into one composition and providing real-time imaging with greatly enhanced diagnostic accuracy during targeted therapy.

Background: Tuberous sclerosis complex (TSC) is a rare genetic disorder with multisystem involvement. A magnetic-resonance (MRI) based classification of tubers into types A, B and C has been proposed. However, the relationship between different tuber types and their quantitative characteristics, also the non-neurological manifestations of TSC remains unknown., Aims: To quantitatively evaluate different MRI-defined tuber types and to explore their relationships with major disease manifestations in patients with tuberous sclerosis complex., Methods: We performed quantitative manual assessment of tubers visible on T1W, T2W/FLAIR images and DW/ADC maps of 20 patients with TSC. Tubers were classified into types A, B and C based on their signal intensity on MRI. General clinical information and quantitative tuber characteristics were evaluated. Between-group comparisons were made using the nonparametric Mann-Whitney U test with Bonferroni correction., Results: In total, 20 patients with 770 tubers were evaluated. Type A tubers were most numerous followed closely by Type B tubers, whereas Type C tubers were relatively rare. Tuber size was markedly different among the three tuber types: it increased from Type A to Type B to Type C. Infantile spasms, generalized-tonic clonic seizures, poor seizure control, cardiac rhabdomyomas, SEGA and developmental delay were not associated with quantitative tuber characteristics. Increased total Type B tuber load was associated with early onset epilepsy, while individually larger Type A and Type B tubers were associated with the presence angiomyolipoma (AML) and renal cysts., Conclusions: MRI-defined tuber types differ significantly in their size and number. Larger total Type B tuber load and larger individual Type A and Type B tubers were found to be most associated with early seizure onset and renal angiomyolipomas, respectively. One possible explanation for the observed differences in the clinical phenotype based on MRI-defined tuber types is not the intrinsic qualitative distinctions between different tuber types, but rather their individual size and total tuber load., (Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.)

In this study, we investigated microvascular perfusion status, changes to fat content and fatty acid composition in the bone marrow of rat femurs after total-body irradiation by quantitative permeability parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and ex vivo high-resolution magic angle spinning (HRMAS) 1 H nuclear magnetic resonance spectroscopy (NMRS). Thirty-six Sprague-Dawley rats were randomly assigned to either an irradiated or nonirradiated control group. Permeability imaging using DCE-MRI and HRMAS 1 H NMRS was performed before irradiation, as well as at days 4 and 7 postirradiation. The volume transfer constant (K trans ) values increased to 2.219 ± 0.418/min ( P < 0.01) at day 4 and to 2.760 ± 0.217/min at day 7 ( P < 0.01) postirradiation. The plasma fraction (v p ) values gradually decreased. The proportion of (n-6) polyunsaturated fatty acids (PUFA) gradually reached a peak at day 7, the proportion of (n-3) PUFA gradually decreased and the proportion of saturated fatty acids gradually increased. After irradiation, K trans at different times showed significant negative correlation with (n-3) PUFA ( r = -0.6393, P < 0.01) and significant positive correlation with (n-6) PUFA ( r = 0.6841, P < 0.05). These findings indicate that bone marrow microcirculation perfusion and vascular permeability correlated with fat content at an early time point after irradiation. A pathophysiological mechanism may exist based on fat-vascular permeability in the case of injury to bone marrow microcirculation.

This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened resting-state fMRI functional connectivity (FC) in input-deprived and reorganized digit regions in area 3b of the S1 and S2. Concurrent reductions in local field potential and spike FC validated the use of resting-state fMRI signals for probing neural intrinsic FC alterations in pathological deafferented cortex, and indicated that disrupted FC between mesoscale functionally highly related regions may contribute to the behavioral impairments., (Copyright © 2017 the authors 0270-6474/17/3711192-12$15.00/0.)

During the measurement of hyperpolarized 129 Xe magnetic resonance imaging (MRI), the diffusion-weighted imaging (DWI) technique provides valuable information for the assessment of lung morphometry at the alveolar level, whereas the chemical shift saturation recovery (CSSR) technique can evaluate the gas exchange function of the lungs. To date, the two techniques have only been performed during separate breaths. However, the request for multiple breaths increases the cost and scanning time, limiting clinical application. Moreover, acquisition during separate breath-holds will increase the measurement error, because of the inconsistent physiological status of the lungs. Here, we present a new method, referred to as diffusion-weighted chemical shift saturation recovery (DWCSSR), in order to perform both DWI and CSSR within a single breath-hold. Compared with sequential single-breath schemes (namely the 'CSSR + DWI' scheme and the 'DWI + CSSR' scheme), the DWCSSR scheme is able to significantly shorten the breath-hold time, as well as to obtain high signal-to-noise ratio (SNR) signals in both DWI and CSSR data. This scheme enables comprehensive information on lung morphometry and function to be obtained within a single breath-hold. In vivo experimental results demonstrate that DWCSSR has great potential for the evaluation and diagnosis of pulmonary diseases., (Copyright © 2017 John Wiley & Sons, Ltd.)

Objectives: To evaluate the diagnostic performance of different mathematical models and different b-value ranges of diffusion-weighted imaging (DWI) in peripheral zone prostate cancer (PZ PCa) detection., Methods: Fifty-six patients with histologically proven PZ PCa who underwent DWI-magnetic resonance imaging (MRI) using 21 b-values (0-4500 s/mm2) were included. The mean signal intensities of the regions of interest (ROIs) placed in benign PZs and cancerous tissues on DWI images were fitted using mono-exponential, bi-exponential, stretched-exponential, and kurtosis models. The b-values were divided into four ranges: 0-1000, 0-2000, 0-3200, and 0-4500 s/mm2, grouped as A, B, C, and D, respectively. ADC, , D*, f, DDC, α, Dapp, and Kapp were estimated for each group. The adjusted coefficient of determination (R2) was calculated to measure goodness-of-fit. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of the parameters., Results: All parameters except D* showed significant differences between cancerous tissues and benign PZs in each group. The area under the curve values (AUCs) of ADC were comparable in groups C and D (p = 0.980) and were significantly higher than those in groups A and B (p< 0.05 for all). The AUCs of ADC and Kapp in groups B and C were similar (p = 0.07 and p = 0.954), and were significantly higher than the other parameters (p< 0.001 for all). The AUCs of ADC in group D was slightly higher than Kapp (p = 0.002), and both were significantly higher than the other parameters (p< 0.001 for all)., Conclusions: ADC derived from conventional mono-exponential high b-value (3200 s/mm2) models is an optimal parameter for PZ PCa detection.

Chemical exchange saturation transfer (CEST) provides sensitive magnetic resonance (MR) contrast for probing dilute compounds via exchangeable protons, serving as an emerging molecular imaging methodology. CEST Z-spectrum is often acquired by sweeping radiofrequency saturation around bulk water resonance, offset by offset, to detect CEST effects at characteristic chemical shift offsets, which requires prolonged acquisition time. Herein, combining high-resolution magic angle spinning (HRMAS) with concurrent application of gradient and rf saturation to achieve fast Z-spectral acquisition, we demonstrated the feasibility of fast quantitative HRMAS CEST Z-spectroscopy. The concept was validated with phantoms, which showed excellent agreement with results obtained from conventional HRMAS MR spectroscopy (MRS). We further utilized the HRMAS Z-spectroscopy for fast ex vivo quantification of ischemic injury with rodent brain tissues after ischemic stroke. This method allows rapid and quantitative CEST characterization of biological tissues and shows potential for a host of biomedical applications.

Image enhancement techniques are able to improve the contrast and visual quality of magnetic resonance (MR) images. However, conventional methods cannot make up some deficiencies encountered by respective brain tumor MR imaging modes. In this paper, we propose an adaptive intuitionistic fuzzy sets-based scheme, called as AIFE, which takes information provided from different MR acquisitions and tries to enhance the normal and abnormal structural regions of the brain while displaying the enhanced results as a single image. The AIFE scheme firstly separates an input image into several sub images, then divides each sub image into object and background areas. After that, different novel fuzzification, hyperbolization and defuzzification operations are implemented on each object/background area, and finally an enhanced result is achieved via nonlinear fusion operators. The fuzzy implementations can be processed in parallel. Real data experiments demonstrate that the AIFE scheme is not only effectively useful to have information from images acquired with different MR sequences fused in a single image, but also has better enhancement performance when compared to conventional baseline algorithms. This indicates that the proposed AIFE scheme has potential for improving the detection and diagnosis of brain tumors.

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute labile protons and microenvironmental properties, augmenting routine relaxation-based MRI. Recent developments of quantitative CEST (qCEST) analysis such as omega plots and RF-power based ratiometric calculation have extended our ability to elucidate the underlying CEST system beyond the simplistic apparent CEST measurement. CEST MRI strongly varies with experimental factors, including the RF irradiation level and duration as well as repetition time and flip angle. In addition, the CEST MRI effect is typically small, and experimental optimization strategies have to be carefully evaluated in order to enhance the CEST imaging sensitivity. Although routine CEST MRI has been optimized largely based on maximizing the magnitude of the CEST effect, the CEST signal-to-noise (SNR) efficiency provides a more suitable optimization index, particularly when the scan time is constrained. Herein, we derive an analytical solution of the CEST effect that takes into account key experimental parameters including repetition time, imaging flip angle and RF irradiation level, and solve its SNR efficiency. The solution expedites CEST imaging sensitivity calculation, substantially faster than the Bloch-McConnell equation-based numerical simulation approach. In addition, the analytical solution-based SNR formula enables the exhaustive optimization of CEST MRI, which simultaneously predicts multiple optimal parameters such as repetition time, flip angle and RF saturation level based on the chemical shift and exchange rate. The sensitivity efficiency-based optimization approach could simplify and guide imaging of CEST agents, including glycogen, glucose, creatine, gamma-aminobutyric acid and glutamate. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Purpose: To demonstrate the feasibility of quantitative and comprehensive global evaluation of pulmonary function and microstructural changes in rats with radiation-induced lung injury (RILI) using hyperpolarized xenon MR., Methods: Dissolved xenon spectra were dynamically acquired using a modified chemical shift saturation recovery pulse sequence in five rats with RILI (bilaterally exposed by 6-MV x-ray with a dose of 14 Gy 3 mo. prior to MR experiments) and five healthy rats. The dissolved xenon signals were quantitatively analyzed, and the pulmonary physiological parameters were extracted with the model of xenon exchange., Results: The obtained pulmonary physiological parameters and the ratio of (129) Xe signal in red blood cells (RBCs) versus barrier showed a significant difference between the groups. In RILI rats versus controls, the exchange time increased from 44.5 to 112 ms, the pulmonary capillary transit time increased from 0.51 to 1.48 s, and the ratio of (129) Xe spectroscopic signal in RBCs versus barrier increased from 0.294 to 0.484., Conclusion: Hyperpolarized xenon MR is effective for quantitative and comprehensive global evaluation of pulmonary function and structural changes without the use of radiation. This may open the door for its use in the diagnosis of lung diseases that are related to gas exchange. Magn Reson Med 76:408-416, 2016. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)