卷 48, 编号 8 (2017)

In magnetic resonance imaging, the gradient recalled echo sequence preserves information about spatial heterogeneities of magnetic field within a voxel, providing additional opportunity for classification of biological tissues. All the information, composed of physically meaningful parameters, like proton density, spin–spin relaxation time T₂, gradients of magnetic field and spin–spin relaxation, effective relaxation time \(T_{2}^{*}\), and many others, is encoded in the shape of a relaxation curve, which is more complicated than a pure monoexponent, traditionally observed in spin echo sequences. The previous work [A. Protopopov, Appl. Magn. Reason. 48, 255-274 (2017)], introduced the theory and basic algorithms for separation of those parameters. The present work further expands this theory to the case of spin–spin relaxation gradients, improves reliability of the algorithms, introduces physical explanation of the phenomenon previously known as “multiexponentiality”, and presents new validation of the algorithms on volunteers. The entire approach may be named the structural analysis of relaxation curves.

The paper describes the design of broadband excitation pulses in high resolution nuclear magnetic resonance (NMR) by method of double sweep. We first show the design of a pulse sequence that produces broadband excitation to the equator of Bloch sphere with phase linearly dispersed as frequency. We show how this linear dispersion can then be refocused by nesting free evolution between two adiabatic inversions (sweeps). We then show how this construction can be generalized to exciting arbitrary large bandwidths without increasing the peak rf-amplitude and by incorporating more adiabatic sweeps. Finally, we show how the basic design can then be modified to give a broadband x rotation over arbitrary large bandwidth and with limited rf-amplitude. Experimental excitation profiles for the residual HDO signal in a sample of \(99.5\%\) D\(_2\)0 are displayed as a function of resonance offset. Application of the excitation is shown for \(^{13}\)C excitation in a labelled sample of alanine.

New trinuclear gadolinium(III) complex having 2-bromoisovaleric acid pendant arm is reported. The longitudinal relaxivity (r_1p) of the complex is 23.17 mM⁻¹ s⁻¹ which correspond to a “per Gd” relaxivity of 7.72 mM⁻¹ s⁻¹. The transverse relaxivity (r_2p) of the complex is 24.79 mM⁻¹ s⁻¹ which correspond to a “per Gd” value of 8.26. The complex exhibit r_1p and r_2p values of 29.19 and 35.20, respectively, in the presence of HSA. The complex also shows pH dependant relaxivity which is an added advantage of the complex for utilization in cancer cell magnetic resonance imaging. The higher relaxivity values in water and HSA indicates a compact solution structure for the complexes and a restricted internal motion about the amide spacer.

The reorientation of the guest 4-methoxy-TEMPO (spin probe) in the disordered fraction of semicrystalline poly(dimethylsiloxane) (PDMS) is investigated by high-field electron paramagnetic resonance (HF-EPR) at 190 and 285 GHz. Accurate numerical simulations of the HF-EPR lineshapes evidence that the reorientation times of the spin probes are distributed between the melting temperature \(T_{\rm m}\) and \(T_{\rm m}\)—30 K. The distribution exhibits, in addition to a broad component, a narrow component with low mobility up to the PDMS melting point. It is shown that the temperature dependence of the reorientation time of the spin probes with low mobility is the same of the spin probes in glassy PDMS. The result suggests that the low-mobility fraction is localized in the so-called rigid amorphous fraction.

Magnetic resonance imaging (MRI) is widely adopted for clinical diagnosis due to its non-invasively detection. However, acquisition of full k-space data limits its imaging speed. Compressed sensing (CS) provides a new technique to significantly reduce the measurements with high-quality MR image reconstruction. The sparsity of the MR images is one of the crucial bases of CS-MRI. In this paper, we present to use sparsity averaging prior for CS-MRI reconstruction in the basis of that MR images have average sparsity over multiple wavelet frames. The problem is solved using a Fast Iterative Shrinkage Thresholding Algorithm (FISTA), each iteration of which includes a shrinkage step. The performance of the proposed method is evaluated for several types of MR images. The experiment results illustrate that our approach exhibits a better performance than those methods that using redundant frame or a single orthonormal basis to promote sparsity.