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Stroke patients commonly face challenges during magnetic resonance imaging (MRI) examinations due to involuntary movements. This study aims to overcome these challenges by utilizing multiple overlapping-echo detachment (MOLED) quantitative technology. Through this technology, we also seek to detect microstructural changes of the normal-appearing corticospinal tract (NA-CST) in subacute-chronic stroke patients. 79 patients underwent 3.0 T MRI scans, including routine scans and MOLED technique. A deep learning network was utilized for image reconstruction, and the accuracy, reliability, and resistance to motion of the MOLED technique were validated on phantoms and volunteers. Subsequently, we assessed motor dysfunction severity, ischemic lesion volume, T 2 values of the bilateral NA-CST, and the T 2 ratio (rT 2) between the ipsilesional and contralesional NA-CST in patients. The MOLED technique showed high accuracy (P < 0.001) and excellent repeatability, with a mean coefficient of variation (CoV) of 1.11%. It provided reliable quantitative results even under head movement, with a mean difference (Mean diff) = 0.28% and a standard deviation difference (SD diff) = 1.34%. Additionally, the T 2 value of the ipsilesional NA-CST was significantly higher than contralesional side (P < 0.001), and a positive correlation was observed between rT 2 and the severity of motor dysfunction (r s = 0.575, P < 0.001). Furthermore, rT 2 successfully predicted post-stroke motor impairment, with an area under the curve (AUC) was 0.883. The MOLED technique offers significant advantages for quantitatively imaging stroke patients with involuntary movements. Additionally, T 2 mapping from MOLED can detect microstructural changes in the NA-CST, potentially aiding in monitoring stroke-induced motor impairment. [ABSTRACT FROM AUTHOR]

This project aims to investigate the diagnostic performance of multiple overlapping-echo detachment imaging (MOLED) technique-derived transverse relaxation time (T 2) maps in predicting progesterone receptor (PR) and S100 expression in meningiomas. 63 meningioma patients were enrolled from October 2021 to August 2022, who underwent a complete routine magnetic resonance imaging and T 2 MOLED, which can characterize the whole brain transverse relaxation time within 32 seconds in a single scan. After the surgical resection of meningiomas, the expression levels of PR and S100 were determined by an experienced pathologist using immunohistochemistry techniques. Histogram analysis was performed in tumor parenchyma based on the parametric maps. Independent t test and Mann-Whitney U test were applied for the comparison of histogram parameters between different groups, with a significance level of P <.05. Logistic regression and receiver operating characteristic (ROC) analysis with 95% confidence interval were conducted for the diagnostic efficiency evaluation. PR-positive group had significantly elevated T 2 histogram parameters (P =.001-.049) compared to the PR-negative group. The multivariate logistic regression model with T 2 showed the highest area under the ROC curve (AUC) for predicting PR expression (AUC = 0.818). Additionally, the multivariate model also had the best diagnostic performance for predicting meningioma S100 expression (AUC = 0.768). The MOLED technique-derived T 2 maps can distinguish PR and S100 status in meningiomas preoperatively. [ABSTRACT FROM AUTHOR]

Abstract: Chemical exchange saturation transfer (CEST) provides a new type of image contrast in MRI. Due to the intrinsically low CEST effect, new and improved experimental techniques are required to achieve reliable and quantitative CEST images. In the present work, we proposed a novel and more sensitive CEST acquisition approach, based on the intermolecular double-quantum coherence with a module of multiple refocusing pulses (iDQC-MRP). Experiments were performed on creatine and egg white phantoms using a Varian 7T animal MRI scanner. The iDQC-MRP CEST technique showed a substantial enhancement in CEST and nuclear Overhauser enhancement (NOE) signal intensities, compared to the standard single-quantum coherence approach. In addition, the iDQC-MRP approach increased the signal-to-noise ratio of acquired saturation images, compared to the conventional iDQC approach. The new iDQC-MRP CEST sequence provides a promising way for exploiting in vivo CEST and NOE imaging applications. [Copyright &y& Elsevier]

Abstract: In the COSY Revamped with Asymmetric Z-gradient Echo Detection (CRAZED) experiments, magnetization is modulated by the distant dipolar field (DDF) generated by coherence selection gradient (CSG) commonly in sinusoidal wave-form and results in detectable intermolecular multiple-quantum coherence (iMQC) signal. IMQCs have some attractive features, but their intrinsic weak signal intensity prevents their widespread applications. In this paper, a new phase cycling scheme was applied to obtain intermolecular double-quantum coherence (iDQC) signal. It is found that DDF can arise from nonspherical sample geometry or background inhomogeneous field in the absence of CSGs, which is more efficient than that created from CSGs. The experimental results show that the resulting DDF can refocus the ±iDQC signals simultaneously and thus enhance the signal intensity to about two folds of that from the conventional CRAZED sequence. Theoretical prediction and experiments give coincident results. [Copyright &y& Elsevier]

Abstract: Inhomogeneity in static field B 0 and/or RF field B 1 is inevitable under some circumstances. In this work, a method based on intermolecular double-quantum coherences is employed for high-resolution 1D MR spectroscopy via 2D acquisition under such a condition. High-resolution information on chemical shifts, multiplet patterns, J coupling constants and relative peak areas can be retained in the resulting 1D projected spectra, as shown with results from a narrow-bore NMR spectrometer and a whole-body clinical scanner. [Copyright &y& Elsevier]

Recently, magnetic resonance imaging (MRI) reconstruction based on deep learning has become popular. Nevertheless, reconstruction of highly undersampled MR images is still challenging due to severe aliasing effects. In this study we built a deep fusion connection network (DFCN) to efficiently utilize the correlation information between adjacent slices. The proposed method was evaluated with online public IXI dataset and Calgary-Campinas-359 dataset. The results show that DFCN can generate the best reconstruction images in de-aliasing and restoring tissue structure compared with several state-of-the-art methods. The mean value of the peak signal-to-noise ratio could reach 34.16 dB, the mean value of the structural similarity is 0.9626, and the mean value of the normalized mean square error is 0.1144 on T 2 -weighted brain data of IXI dataset under 10× acceleration. Additionally, the mean value of the peak signal-to-noise ratio could reach 30.17 dB, the mean value of the structural similarity is 0.9259, and the mean value of the normalized mean square error is 0.1294 on T 1 -weighted brain data of Calgary-Campinas-359 dataset under 10× acceleration. With the correlation information between adjacent slices as prior knowledge, our method can dramatically eliminate aliasing effects and enhance the reconstruction quality of undersampled MR images. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) theory assures us that we can accurately reconstruct magnetic resonance images using fewer k-space measurements than the Nyquist sampling rate requires. In traditional CS-MRI inversion methods, the fact that the energy within the Fourier measurement domain is distributed non-uniformly is often neglected during reconstruction. As a result, more densely sampled low frequency information tends to dominate penalization schemes for reconstructing MRI at the expense of high frequency details. In this paper, we propose a new framework for CS-MRI inversion in which we decompose the observed k-space data into "subspaces" via sets of filters in a lossless way, and reconstruct the images in these various spaces individually using off-the-shelf algorithms. We then fuse the results to obtain the final reconstruction. In this way, we are able to focus reconstruction on frequency information within the entire k-space more equally, preserving both high and low frequency details. We demonstrate that the proposed framework is competitive with state-of-the-art methods in CS-MRI in terms of quantitative performance, and often improves an algorithm's results qualitatively compared with its direct application to k-space. Unlabelled Image • The MRI measurements distribute non-uniformly in k-space. • A divide-and-conquer (DAC) approach for compressed sensing MRI is proposed. • The DAC approach can fully utilize the statistical characteristics of each k-space subspace. • The DAC approach often improves an undersampled MRI algorithm's results. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) imaging is an important magnetic resonance molecular imaging technology. However, long acquisition time limits its clinical application, especially when multi-slice CEST imaging is needed. Though single-shot EPI can be used to accelerate CEST imaging, images are often distorted under inhomogeneous magnetic fields. In this work, we propose a new method called CEST-SeSPEN for ultrafast multi-slice CEST imaging based on segmented spatiotemporally encoded (SeSPEN) MRI. Experiments were performed on creatine phantom and hen egg. The results show that CEST-SeSPEN can provide good CEST contrast images. Its acquisition time is much shorter than other multi-slice CEST methods currently available. It may be used in challenging situation where high temporal resolution and robustness to field inhomogeneity are vital. [ABSTRACT FROM AUTHOR]

Purpose We employ an amplitude-modulated chirp pulse to selectively excite spins in one or more regions of interest (ROIs) to realize reduced field-of-view (rFOV) imaging based on single-shot spatiotemporally encoded (SPEN) sequence and Fourier transform reconstruction. Materials and Methods The proposed rFOV imaging method was theoretically analyzed and illustrated with numerical simulation and tested with phantom experiments and in vivo rat experiments. In addition, point spread function was applied to demonstrate the feasibility of the proposed method. To evaluate the proposed method, the rFOV results were compared with those obtained using the EPI method with orthogonal RF excitation. Results The simulation and experimental results show that the proposed method can image one or two separated ROIs along the SPEN dimension in a single shot with higher spatial resolution, less sensitive to field inhomogeneity, and practically no aliasing artifacts. In addition, the proposed method may produce rFOV images with comparable signal-to-noise ratio to the rFOV EPI images. Conclusion The proposed method is promising for the applications under severe susceptibility heterogeneities and for imaging separate ROIs simultaneously. [ABSTRACT FROM AUTHOR]