Targeted-ROI imaging in electron paramagnetic resonance imaging

Electron paramagnetic resonance imaging (EPRI) is a technique that has been used for in vivo oxygen imaging of small animals. In continuous wave (CW) EPRI, the measurement can be interpreted as a sampled 4D Radon transform of the image function. The conventional filtered-backprojection (FBP) algorithm has been used widely for reconstructing images from full knowledge of the Radon transform acquired in CW EPRI. In practical applications of CW EPRI, one often is interested in information only in a region of interest (ROI) within the imaged subject. It is desirable to accurately reconstruct an ROI image only from partial knowledge of the Radon transform because acquisition of the partial data set can lead to considerable reduction of imaging time. The conventional FBP algorithm cannot, however, reconstruct accurate ROI images from partial knowledge of the Radon transform of even dimension. In this work, we describe two new algorithms, which are referred to as the backprojection filtration (BPF) and minimum-data filtered-backprojection (MDFBP) algorithms, for accurate ROI-image reconstruction from a partial Radon transform (or, truncated Radon transform) in CW EPRI. We have also performed numerical studies in the context of ROI-image reconstruction of a synthetic 2D image with density similar to that found in a small animal EPRI. This demonstrates both the inadequacy of the conventional FBP algorithm and the success of BPF and MDFBP algorithms in ROI reconstruction. The proposed ROI imaging approach promises a means to substantially reduce image acquisition time in CW EPRI.     

Adaptive fixed-point iterative shrinkage/thresholding algorithm for MR imaging reconstruction using compressed sensing

Recently compressed sensing (CS) has been applied to under-sampling MR image reconstruction for significantly reducing signal acquisition time. To guarantee the accuracy and efficiency of the CS-based MR image reconstruction, it necessitates determining several regularization and algorithm-introduced parameters properly in practical implementations. The regularization parameter is used to control the trade-off between the sparsity of MR image and the fidelity measures of k-space data, and thus has an important effect on the reconstructed image quality. The algorithm-introduced parameters determine the global convergence rate of the algorithm itself. These parameters make CS-based MR image reconstruction a more difficult scheme than traditional Fourier-based method while implemented on a clinical MR scanner. In this paper, we propose a new approach that reveals that the regularization parameter can be taken as a threshold in a fixed-point iterative shrinkage/thresholding algorithm (FPIST) and chosen by employing minimax threshold selection method. No extra parameter is introduced by FPIST. The simulation results on synthetic and real complex-valued MRI data show that the proposed method can adaptively choose the regularization parameter and effectively achieve high reconstruction quality. The proposed method should prove very useful for practical CS-based MRI applications.     

Electron paramagnetic resonance imaging using magnetic-field-gradient spinning

A novel X-band CW EPR imaging has been developed using magnetic-field-gradient (MFG) spinning to obtain spatial distributions of electron paramagnetic species. Spinning MFG EPR imaging for 65 projection spectra required just 55 s while conventional imaging took 11 min 40 s, that is, the acquisition time for the new system is one order of magnitude shorter than that for conventional EPR imaging. Spinning MFG EPR imaging allows one to measure reconstructed images in an interactive manner where resolution and condition can be changed quickly.     

Study on compressed sensing imaging based on intensity modulation in Fourier domain

In 4F system, compressed sensing is usually implemented by using phase modulation in Fourier domain. In this paper, we present a type of 4F system based on intensity modulation in Fourier domain as the measurement system for compressed sensing. The feasibility of this system is demonstrated. At the point of coherence, the two modulation methods are compared and superiority of intensity modulation in Fourier domain was verified. Simulations are presented and the conclusion we presented is validated. Finally, we analyze the results.     

Detection of electron paramagnetic resonance absorption using frequency modulation

A frequency modulation (FM) method was developed to measure electron paramagnetic resonance (EPR) absorption. The first-derivative spectrum of 1,1-diphenyl-2-picrylhydrazyl (DPPH) powder was measured with this FM method. Frequency modulation of up to 1.6 MHz (peak-to-peak) was achieved at a microwave carrier frequency of 1.1 GHz. This corresponds to a magnetic field modulation of 57microT (peak-to-peak) at 40.3 mT. By using a tunable microwave resonator and automatic control systems, we achieved a practical continuous-wave (CW) EPR spectrometer that incorporates the FM method. In the present experiments, the EPR signal intensity was proportional to the magnitude of frequency modulation. The background signal at the modulation frequency (1 kHz) for EPR detection was also proportional to the magnitude of frequency modulation. An automatic matching control (AMC) system reduced the amplitude of noise in microwave detection and improved the baseline stability. Distortion of the spectral lineshape was seen when the spectrometer settings were not appropriate, e.g., with a lack of the open-loop gain in automatic tuning control (ATC). FM is an alternative to field modulation when the side-effect of field modulation is detrimental for EPR detection. The present spectroscopic technique based on the FM scheme is useful for measuring the first derivative with respect to the microwave frequency in investigations of electron-spin-related phenomena.     

Tunable-frequency high-field electron paramagnetic resonance

A tunable-frequency methodology based on backward wave oscillator sources in high-frequency and -field EPR (HFEPR) is described. This methodology is illustrated by an application to three non-Kramers transition metal ion complexes and one Kramers ion complex. The complexes are of: Ni(II) (S=1) as found in dichlorobistriphenylphosphanenickel(II), Mn(III) (S=2) as found in mesotetrasulfonatoporphyrinatomanganese(III) chloride, Fe(II) (S=2) as found in ferrous sulfate tetrahydrate, and Co(II) (S=3/2) as found in azido(tris(3-tert-butylpyrazol-1-yl)hydroborate)cobalt(II). The above Ni(II) and Mn(III) complexes have been studied before by HFEPR using the multifrequency methodology based on Gunn oscillator sources, but not by the present method, while the Fe(II) and Co(II) complexes presented here have not been studied by any form of HFEPR. Highly accurate spin Hamiltonian parameters can be obtained by the experimental methodology described here, in combination with automated fitting procedures. This method is particularly successful in determining g-matrix parameters, which are very difficult to extract for high-spin systems from single frequency (or a very limited set of multi-frequency) HFEPR spectra, but is also able to deliver equally accurate values of the zero-field splitting tensor. The experimental methods involve either conventional magnetic field modulation or an optical modulation of the sub-THz wave beam. The relative merits of these and other experimental methods are discussed.     

High fidelity single qubit operations using pulsed electron paramagnetic resonance

Systematic errors in spin rotation operations using simple rf pulses place severe limitations on the usefulness of the pulsed magnetic resonance methods in quantum computing applications. In particular, the fidelity of quantum logic operations performed on electron spin qubits falls well below the threshold for the application of quantum algorithms. Using three independent techniques, we demonstrate the use of composite pulses to improve this fidelity by several orders of magnitude. The observed high-fidelity operations are limited by pulse phase errors, but nevertheless fall within the limits required for the application of quantum error correction.     

Integration of digital signal processing technologies with pulsed electron paramagnetic resonance imaging

The integration of modern data acquisition and digital signal processing (DSP) technologies with Fourier transform electron paramagnetic resonance (FT-EPR) imaging at radiofrequencies (RF) is described. The FT-EPR system operates at a Larmor frequency (L(f)) of 300MHz to facilitate in vivo studies. This relatively low frequency L(f), in conjunction with our approximately 10MHz signal bandwidth, enables the use of direct free induction decay time-locked subsampling (TLSS). This particular technique provides advantages by eliminating the traditional analog intermediate frequency downconversion stage along with the corresponding noise sources. TLSS also results in manageable sample rates that facilitate the design of DSP-based data acquisition and image processing platforms. More specifically, we utilize a high-speed field programmable gate array (FPGA) and a DSP processor to perform advanced real-time signal and image processing. The migration to a DSP-based configuration offers the benefits of improved EPR system performance, as well as increased adaptability to various EPR system configurations (i.e., software configurable systems instead of hardware reconfigurations). The required modifications to the FT-EPR system design are described, with focus on the addition of DSP technologies including the application-specific hardware, software, and firmware developed for the FPGA and DSP processor. The first results of using real-time DSP technologies in conjunction with direct detection bandpass sampling to implement EPR imaging at RF frequencies are presented.     

Evaluation of sub-microsecond recovery resonators for in vivo electron paramagnetic resonance imaging

Time-domain (TD) electron paramagnetic resonance (EPR) imaging at 300MHz for in vivo applications requires resonators with recovery times less than 1 micros after pulsed excitation to reliably capture the rapidly decaying free induction decay (FID). In this study, we tested the suitability of the Litz foil coil resonator (LCR), commonly used in MRI, for in vivo EPR/EPRI applications in the TD mode and compared with parallel coil resonator (PCR). In TD mode, the sensitivity of LCR was lower than that of the PCR. However, in continuous wave (CW) mode, the LCR showed better sensitivity. The RF homogeneity was similar in both the resonators. The axis of the RF magnetic field is transverse to the cylindrical axis of the LCR, making the resonator and the magnet co-axial. Therefore, the loading of animals, and placing of the anesthesia nose cone and temperature monitors was more convenient in the LCR compared to the PCR whose axis is perpendicular to the magnet axis.     

Systematic approach to cutoff frequency selection in continuous-wave electron paramagnetic resonance imaging

This article describes a systematic method for determining the cutoff frequency of the low-pass window function that is used for deconvolution in two-dimensional continuous-wave electron paramagnetic resonance (EPR) imaging. An evaluation function for the criterion used to select the cutoff frequency is proposed, and is the product of the effective width of the point spread function for a localized point signal and the noise amplitude of a resultant EPR image. The present method was applied to EPR imaging for a phantom, and the result of cutoff frequency selection was compared with that based on a previously reported method for the same projection data set. The evaluation function has a global minimum point that gives the appropriate cutoff frequency. Images with reasonably good resolution and noise suppression can be obtained from projections with an automatically selected cutoff frequency based on the present method.     

Nuclear polarization by electron paramagnetic resonance in paramagnetic crystals

The possibility of the polarization of nuclei in paramagnetic salts by saturation of electron paramagnetic resonance is theoretically analyzed. The proposed method assumes saturation of the forbidden transition of the typeM=±1, m=±1, ±2, for mutually perpendicular external magnetic and high-frequency fields. The analysis is carried out for the case of a large quadrupole moment of the nucleus. The degree of orientation attained is comparable in order of magnitude with Overhauser's method. This method is particularly suitable for the polarization of nuclei of transuranium elements.

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. M=± 1, m==±1, ±2 . . . .

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In conclusion the author would like to thank J. Burget, J. ajko, M. Kolá and M. ott for helping in the laborious solution of system (16).     

Low-power electron paramagnetic resonance spin-echo spectroscopy

Electron spin-echo experiments generally require microwave power levels of hundreds of watts to produce the 5–10 G of RF field to generate 90° and 180° pulses in 10 ns. A low-power (i.e., less than I W) EPR spectrometer using a loop-gap resonator can generate the full range of time-domain experiments on samples with submicrosecond recovery times; 90° pulses are generated in 40 ns, and relaxation times as short as 22 ns are measured. Appropriate time-domain experiments were performed to independently measure the spinspin relaxation time, phase memory time, and spin-lattice relaxation time; the results were compared with CW saturation. It was found that the spin-spin and spin-lattice relaxation rates do differ by about 5%. The entire CW signal of PADS is reconstructed from a pulse experiment at a single field position. Small differences in linewidths among the three lines were seen in accordance with theory.     

Three dimension double inversion recovery gray matter imaging using compressed sensing

The double inversion recovery (DIR) imaging technique has various applications such as black blood magnetic resonance imaging and gray/white matter imaging. Recent clinical studies show the promise of DIR for high resolution three dimensional (3D) gray matter imaging. One drawback in this case however is the long data acquisition time needed to obtain the fully sampled 3D spatial frequency domain (k-space) data. In this paper, we propose a method to solve this problem using the compressed sensing (CS) algorithm with contourlet transform. The contourlet transform is an effective sparsifying transform especially for images with smooth contours. Therefore, we applied this algorithm to undersampled DIR images and compared with a CS algorithm using wavelet transform by evaluating the reconstruction performance of each algorithm for undersampled k-space data. The results show that the proposed CS algorithm achieves a more accurate reconstruction in terms of the mean structural similarity index and root mean square error than the CS algorithm using wavelet transform.     

Cardiac magnetic resonance imaging using radial k-space sampling and self-calibrated partial parallel reconstruction

Radial sampling has been demonstrated to be potentially useful in cardiac magnetic resonance imaging because it is less susceptible to motion than Cartesian sampling. Nevertheless, its capability of imaging acceleration remains limited by undersampling-induced streaking artifacts. In this study, a self-calibrated reconstruction method was developed to suppress streaking artifacts for highly accelerated parallel radial acquisitions in cardiac magnetic resonance imaging. Two- (2D) and three-dimensional (3D) radial k-space data were collected from a phantom and healthy volunteers. Images reconstructed using the proposed method and the conventional regridding method were compared based on statistical analysis on a four-point scale imaging scoring. It was demonstrated that the proposed method can effectively remove undersampling streaking artifacts and significantly improve image quality (P<.05). With the use of the proposed method, image score (1–4, 1=poor, 2=good, 3=very good, 4=excellent) was improved from 2.14 to 3.34 with the use of an undersampling factor of 4 and from 1.09 to 2.5 with the use of an undersampling factor of 8. Our study demonstrates that the proposed reconstruction method is effective for highly accelerated cardiac imaging applications using parallel radial acquisitions without calibration data.     

Parallel coil resonators for time-domain radiofrequency electron paramagnetic resonance imaging of biological objects

Resonators suitable for time-domain electron paramagnetic resonance spectroscopy and imaging at a radiofrequency capable of accommodating experimental animals such as mice are described. Design considerations included B(1) field homogeneity, optimal Q, spectral bandwidth, resonator ring-down, and sensitivity. Typically, a resonator with 25-mm diameter and 25-mm length was constructed by coupling 11 single loops in parallel with a separation of 2.5 mm. To minimize the resonator ring-down time and provide the necessary spectral bandwidth for in vivo imaging experiments, the Q was reduced predominantly by overcoupling. Capacitative coupling was utilized to minimize microphonic effects. The B(1) field in the resonator was mapped both radially and axially and found to be uniform and adequate for imaging studies. Imaging studies with phantom objects containing a narrow-line spin probe as well as in vivo objects administered with the spin probe show the suitability of these resonators for valid reproduction of the spin probe distribution in three dimensions. The fabrication of such resonators is simple and can be scaled up with relative ease to accommodate larger objects as well.     

Quantitative single point imaging with compressed sensing

A novel approach with respect to single point imaging (SPI), compressed sensing, is presented here that is shown to significantly reduce the loss of accuracy of reconstructed images from under-sampled acquisition data. SPI complements compressed sensing extremely well as it allows unconstrained selection of sampling trajectories. Dynamic processes featuring short NMR signal can thus be more rapidly imaged, in our case the absorption of moisture by a cereal-based wafer material, with minimal loss of image quantification. The absolute moisture content distribution is recovered via a series of images acquired with variable phase encoding times allowing extrapolation to time zero for each image pixel and the effective removal of contrast.     

Computational ghost imaging with deep compressed sensing

Computational ghost imaging (CGI) provides an elegant framework for indirect imaging, but its application has been restricted by low imaging performance. Herein, we propose a novel approach that significantly improves the imaging performance of CGI. In this scheme, we optimize the conventional CGI data processing algorithm by using a novel compressed sensing (CS) algorithm based on a deep convolution generative adversarial network (DCGAN). CS is used to process the data output by a conventional CGI device. The processed data are trained by a DCGAN to reconstruct the image. Qualitative and quantitative results show that this method significantly improves the quality of reconstructed images by jointly training a generator and the optimization process for reconstruction via meta-learning. Moreover, the background noise can be eliminated well by this method.