Positive Contrast Imaging of SPIO Nanoparticles

It is advantageous to achieve positive contrast images instead of negative contrast images in superparamagnetic iron-oxide (SPIO) nanoparticles-based MR imaging in order to distinguish the signal surrounding SPIO nanoparticles from the dark signal due to local field inhomogeneity and the artifacts due to tissue interface and background noise, eliminate the inherent defects in the traditional MRI such as partial-volume effects and large void volume for reliable visualization, and increase contrast-to-noise ratio. Many methods generating positive signal with SPIO nanoparticles have been developed in the last decade. This paper provides an overview of current visualization methods and states their advantages and disadvantages. In practice, these techniques have been widely applied to cell labeling and disease diagnosis and monitoring. However, there is still a need for an ideal method to achieve both accuracy and sensitivity

High-efficient Bloch simulation of magnetic resonance imaging sequences based on deep learning

Objective: Bloch simulation constitutes an essential part of magnetic resonance imaging (MRI) development. However, even with the graphics processing unit (GPU) acceleration, the heavy computational load remains a major challenge, especially in large-scale, high-accuracy simulation scenarios. This work aims to develop a deep learning-based simulator to accelerate Bloch simulation. Approach: The simulator model, called Simu-Net, is based on an end-to-end convolutional neural network and is trained with synthetic data generated by traditional Bloch simulation. It uses dynamic convolution to fuse spatial and physical information with different dimensions and introduces position encoding templates to achieve position-specific labeling and overcome the receptive field limitation of the convolutional network. Main Results: Compared with mainstream GPU-based MRI simulation software, Simu-Net successfully accelerates simulations by hundreds of times in both traditional and advanced MRI pulse sequences. The accuracy and robustness of the proposed framework were verified qualitatively and quantitatively. Besides, the trained Simu-Net was applied to generate sufficient customized training samples for deep learning-based T2 mapping and comparable results to conventional methods were obtained in the human brain. Significance: As a proof-of-concept work, Simu-Net shows the potential to apply deep learning for rapidly approximating the forward physical process of MRI and may increase the efficiency of Bloch simulation for optimization of MRI pulse sequences and deep learning-based methods.Comment: 18 pages, 8 figure

High-efficient deep learning-based DTI reconstruction with flexible diffusion gradient encoding scheme

Purpose: To develop and evaluate a novel dynamic-convolution-based method called FlexDTI for high-efficient diffusion tensor reconstruction with flexible diffusion encoding gradient schemes. Methods: FlexDTI was developed to achieve high-quality DTI parametric mapping with flexible number and directions of diffusion encoding gradients. The proposed method used dynamic convolution kernels to embed diffusion gradient direction information into feature maps of the corresponding diffusion signal. Besides, our method realized the generalization of a flexible number of diffusion gradient directions by setting the maximum number of input channels of the network. The network was trained and tested using data sets from the Human Connectome Project and a local hospital. Results from FlexDTI and other advanced tensor parameter estimation methods were compared. Results: Compared to other methods, FlexDTI successfully achieves high-quality diffusion tensor-derived variables even if the number and directions of diffusion encoding gradients are variable. It increases peak signal-to-noise ratio (PSNR) by about 10 dB on Fractional Anisotropy (FA) and Mean Diffusivity (MD), compared with the state-of-the-art deep learning method with flexible diffusion encoding gradient schemes. Conclusion: FlexDTI can well learn diffusion gradient direction information to achieve generalized DTI reconstruction with flexible diffusion gradient schemes. Both flexibility and reconstruction quality can be taken into account in this network.Comment: 11 pages,6 figures,3 table

Theoretical formalism and experimental verification of line shapes of NMR intermolecular multiple-quantum coherence spectra

Although the theories and potential applications of intermolecular multiple-quantum coherences (iMQCs) have been under active investigations for over a decade, discussion of iMQC NMR signal formation was mainly confined in the time domain. In this paper, a full line-shape theory was developed to describe iMQC signals in the frequency domain. Relevant features of the line shape, such as peak height, linewidth, and phase, were investigated in detail. Predictions based on the theory agree well with experimental and simulated results. Since radiation-damping effects always couple with iMQCs in highly polarized liquid-state NMR systems, and strongly radiation-damped signals have many spectral characteristics similar to those of iMQCs, a detailed comparison was also made between them from different spectral aspects. With detailed comparison of peak height, linewidth, and phase, this work demonstrates that the iMQC and radiation-damping phenomena result from two completely different physical mechanisms despite that both present similar signal features and coexist in highly polarized liquid-state NMR systems. (c) 2005 American Institute of Physics

Mechanisms associated with the synergistic induction of resistance to tobacco black shank in tobacco by arbuscular mycorrhizal fungi and β-aminobutyric acid

Tobacco black shank (TBS), caused by Phytophthora nicotianae, is one of the most harmful diseases of tobacco. There are many studies have examined the mechanism underlying the induction of disease resistance by arbuscular mycorrhizal fungi (AMF) and β-aminobutyric acid (BABA) alone, but the synergistic effects of AMF and BABA on disease resistance have not yet been studied. This study examined the synergistic effects of BABA application and AMF inoculation on the immune response to TBS in tobacco. The results showed that spraying BABA on leaves could increase the colonization rate of AMF, the disease index of tobacco infected by P.nicotianae treated with AMF and BABA was lower than that of P.nicotianae alone. The control effect of AMF and BABA on tobacco infected by P.nicotianae was higher than that of AMF or BABA and P.nicotianae alone. Joint application of AMF and BABA significantly increased the content of N, P, and K in the leaves and roots, in the joint AMF and BABA treatment than in the sole P. nicotianae treatment. The dry weight of plants treated with AMF and BABA was 22.3% higher than that treated with P.nicotianae alone. In comparison to P. nicotianae alone, the combination treatment with AMF and BABA had increased Pn, Gs, Tr, and root activity, while P. nicotianae alone had reduced Ci, H2O2 content, and MDA levels. SOD, POD, CAT, APX, and Ph activity and expression levels were increased under the combined treatment of AMF and BABA than in P.nicotianae alone. In comparison to the treatment of P.nicotianae alone, the combined use of AMF and BABA increased the accumulation of GSH, proline, total phenols, and flavonoids. Therefore, the joint application of AMF and BABA can enhance the TBS resistance of tobacco plants to a greater degree than the application of either AMF or BABA alone. In summary, the application of defense-related amino acids, combined with inoculation with AMF, significantly promoted immune responses in tobacco. Our findings provide new insights that will aid the development and use of green disease control agents

High-resolution intermolecular zero-quantum coherence spectroscopy under inhomogeneous fields with effective solvent suppression

Intermolecular zero-quantum coherences (iZQCs) are not susceptible to magnetic field inhomogeneities significantly larger than the dipolar correlation distance and can be used to obtain 1D high-resolution spectra in an inhomogeneous field. However, with the iZQC methods proposed previously, residual conventional single-quantum coherences (SQCs) originating mainly from solvent resonance result in strong t(1) ridge noises. A modified HOMOGENIZED with an intermolecular double-quantum. filter (iDQF), named iDQF-HOMOGENIZED, is presented in this work to suppress the residual conventional SQC signals as well as solvent iZQC signals. The solvent-suppression efficiency of the iDQF-HOMOGENIZED is analyzed and a thorough comparison of the new sequence with several relevant pulse sequences is made. Dramatic resolution enhancement and solvent suppression in the measurements of a piece of grape sarcocarp suggest potential applications of the method in in vivo spectroscopy

High-resolution magnetic resonance spectroscopy in unstable fields via intermolecular zero-quantum coherences

Intermolecular zero-quantum coherences (iZQCs) have been utilized to achieve high-resolution nuclear magnetic resonance (NMR) proton spectra under inhomogeneous and/or unstable fields. In this paper, we demonstrated that despite the insensitivity of iZQCs to B-0 variations, the influence of unstable fields on the observable single-quantum coherence signals causes strong t(1) noises in the high-resolution iZQC spectra. Short-time acquisition (STA) and phase spectrum schemes were proposed for noise suppression in in vivo iZQC magnetic resonance spectroscopy (MRS) under temporal B-0 variations. The feasibility of these schemes were verified by localized spectroscopic studies under B-0 variations generated by the Z(0) coil current oscillations and by voxel position variations in the presence of field gradients, which simulate the field conditions of MRS in the presence of physiological motions. The phase scheme not only improves the signal-to-noise ratio but also further reduces the linewidth by half.NNSF of China [10774125, 10875101, 10974164]; Research Fund for the Doctoral Program of Higher Education of China [200803840019