Correction of concomitant gradient artifacts in experimental microtesla MRI

Magnetic resonance imaging (MRI) suffers from artifacts caused by concomitant gradients when the product of the magnetic field gradient and the dimension of the sample becomes comparable to the static magnetic field. To investigate and correct for these artifacts at very low magnetic fields, we have acquired MR images of a 165-mm phantom in a 66-microT field using gradients up to 350 microT/m. We prepolarize the protons in a field of about 100 mT, apply a spin-echo pulse sequence, and detect the precessing spins using a superconducting gradiometer coupled to a superconducting quantum interference device (SQUID). Distortion and blurring are readily apparent at the edges of the images; by comparing the experimental images to computer simulations, we show that concomitant gradients cause these artifacts. We develop a non-perturbative, post-acquisition phase correction algorithm that eliminates the effects of concomitant gradients in both the simulated and the experimental images. This algorithm assumes that the switching time of the phase-encoding gradient is long compared to the spin precession period. In a second technique, we demonstrate that raising the precession field during phase encoding can also eliminate blurring caused by concomitant phase-encoding gradients; this technique enables one to correct concomitant gradient artifacts even when the detector has a restricted bandwidth that sets an upper limit on the precession frequency. In particular, the combination of phase correction and precession field cycling should allow one to add MRI capabilities to existing 300-channel SQUID systems used to detect neuronal currents in the brain because frequency encoding could be performed within the 1-2 kHz bandwidth of the readout system.     

Parallel MRI at microtesla fields

Parallel imaging techniques have been widely used in high-field magnetic resonance imaging (MRI). Multiple receiver coils have been shown to improve image quality and allow accelerated image acquisition. Magnetic resonance imaging at ultra-low fields (ULF MRI) is a new imaging approach that uses SQUID (superconducting quantum interference device) sensors to measure the spatially encoded precession of pre-polarized nuclear spin populations at microtesla-range measurement fields. In this work, parallel imaging at microtesla fields is systematically studied for the first time. A seven-channel SQUID system, designed for both ULF MRI and magnetoencephalography (MEG), is used to acquire 3D images of a human hand, as well as 2D images of a large water phantom. The imaging is performed at 46 mu T measurement field with pre-polarization at 40 mT. It is shown how the use of seven channels increases imaging field of view and improves signal-to-noise ratio for the hand images. A simple procedure for approximate correction of concomitant gradient artifacts is described. Noise propagation is analyzed experimentally, and the main source of correlated noise is identified. Accelerated imaging based on one-dimensional undersampling and 1D SENSE (sensitivity encoding) image reconstruction is studied in the case of the 2D phantom. Actual threefold imaging acceleration in comparison to single-average fully encoded Fourier imaging is demonstrated. These results show that parallel imaging methods are efficient in ULF MRI, and that imaging performance of SQUID-based instruments improves substantially as the number of channels is increased.     

Distortion-free magnetic resonance imaging in the zero-field limit

MRI is a powerful technique for clinical diagnosis and materials characterization. Images are acquired in a homogeneous static magnetic field much higher than the fields generated across the field of view by the spatially encoding field gradients. Without such a high field, the concomitant components of the field gradient dictated by Maxwell’s equations lead to severe distortions that make imaging impossible with conventional MRI encoding. In this paper, we present a distortion-free image of a phantom acquired with a fundamentally different methodology in which the applied static field approaches zero. Our technique involves encoding with pulses of uniform and gradient field, and acquiring the magnetic field signals with a SQUID. The method can be extended to weak ambient fields, potentially enabling imaging in the Earth’s field without cancellation coils or shielding. Other potential applications include quantum information processing and fundamental studies of long-range ferromagnetic interactions.     

On concomitant gradients in low-field MRI

Growing interest in magnetic resonance imaging (MRI) at ultra-low magnetic fields (ULF, approximately muT fields) has been motivated by several advantages over its counterparts at higher magnetic fields. These include narrow line widths, the possibility of novel imaging schemes, reduced imaging artifacts from susceptibility variations within a sample, and reduced system cost and complexity. In addition, ULF NMR/MRI with superconducting quantum interference devices is compatible with simultaneous measurements of biomagnetic signals, a capability conventional systems cannot offer. Acquisition of MRI at ULF must, however, account for concomitant gradients that would otherwise result in severe image distortions. In this paper, we introduce the general theoretical framework that describes concomitant gradients, explain why such gradients are more problematic at low field, and present possible approaches to correct for these unavoidable gradients in the context of a non-slice-selective MRI protocol.     

一种永磁磁共振中磁体涡流场的测量方法

磁共振成像（Magntic Resonance Imaging,MRI）技术是一种先进的医疗影像技术.在MRI系统中,通过梯度线圈电流快速切换方向,对待测区域施加梯度磁场,产生的梯度磁场会在其周围的金属体内激发出变化的涡旋电场,进而导致金属体内闭合的回路中产生对原来的梯度电流起抑制作用的感生电流,也就是我们所说的涡流.本文介绍了一种测量磁体涡流场的方法,结合电磁感应定律,设计了一种磁体涡流场测量装置,通过硬件采集以及软件处理的方法,将理想梯度场与实际磁场进行相减并将波形实时呈现,实验结果表明该方法可实现对磁体涡流场的测量.     

Theory of MRI in the presence of zero to low magnetic fields and tensor imaging field gradients

Today, all commonly practiced magnetic resonance imaging (MRI) reconstruction methods assume that the magnetic field created by the gradient coils is everywhere truncated by a dominant static uniform magnetic field. However, with the advent of SQUID detected MRI at microtesla fields, the opposite limit attracts attention, i.e., image formation in the unperturbed tensor field of the gradient coils. Here, we show by numerical simulations that, in principle, it is possible to reconstruct the image of an object in the absence of a uniform static field, working with the same gradient field setup as used in conventional MRI. Our calculations show that this approach could increase the image resolution limit attainable at low fields with a minimal incorporation of additional hardware and pulse sequences.     

Fast 3D spatial EPR imaging using spiral magnetic field gradient

Electron paramagnetic resonance imaging (EPRI) provides direct detection and mapping of free radicals. The continuous wave (CW) EPRI technique, in particular, has been widely used in a variety of applications in the fields of biology and medicine due to its high sensitivity and applicability to a wide range of free radicals and paramagnetic species. However, the technique requires long image acquisition periods, and this limits its use for many in vivo applications where relatively rapid changes occur in the magnitude and distribution of spins. Therefore, there has been a great need to develop fast EPRI techniques. We report the development of a fast 3D CW EPRI technique using spiral magnetic field gradient. By spiraling the magnetic field gradient and stepping the main magnetic field, this approach acquires a 3D image in one sweep of the main magnetic field, enabling significant reduction of the imaging time. A direct one-stage 3D image reconstruction algorithm, modified for reconstruction of the EPR images from the projections acquired with the spiral magnetic field gradient, was used. We demonstrated using a home-built L-band EPR system that the spiral magnetic field gradient technique enabled a 4-7-fold accelerated acquisition of projections. This technique has great potential for in vivo studies of free radicals and their metabolism.     

基于稀疏重建的磁共振图像尖峰噪声消除方法

磁共振图像K空间中的尖峰噪声会严重影响图像质量.该文在磁共振图像压缩感知的共轭梯度重建法的基础上,提出一种新的利用磁共振图像稀疏性进行尖峰噪声修复的方法.传统的共轭梯度重建是通过小波域迭代进行的,对于K空间的尖峰噪声的消除不是最适合.首先提出压缩感知的K空间重建算法,该算法与小波域重建等效.在此基础上,提出可以较好地修复尖峰噪声的K空间部分重建算法.即在迭代过程中,以图像的稀疏性作为约束条件,仅修改尖峰噪声所遮盖区域的数据,其他位置的数据保持不变.该算法与传统的插值算法及共轭梯度算法相比,能够更好地修复K空间尖峰噪声点,减少图像伪影,同时降低了对尖峰噪声定位准确性的要求.     

A novel acquisition-reconstruction algorithm for surface magnetic resonance imaging

In U-shaped, hand-size magnetic resonance surface scanners, imaging is performed along only one spatial direction, with the application of just one gradient (one-dimensional imaging). Lateral spatial resolution can be obtained by magnet displacement, but, in this case, resolution is very poor (on the order of some millimeters) and cannot be useful for high-resolution imaging applications. In this article, an innovative technique for acquisition and reconstruction of images produced by U-shaped, hand-size MRI surface scanners is presented. The proposed method is based on the acquisition of overlapping strips and an analytical reconstruction technique; it is capable of arbitrarily improving spatial lateral resolution without either using a second magnetic field gradient or making any assumptions about the imaged sample extension. Numerical simulations on synthetic images are reported demonstrating the method functionalities. The presented method also makes it possible to use U-shaped, hand-size MRI surface scanners for high-resolution biomedical applications, such as the imaging of skin lesions.     

Use of a Phase Reference for Field Mapping with Amplitude Images at Low Field

We present a method to obtain MRI amplitude images that can picture the magnetic field due to arbitrary shaped magnetized objects. The method employees the gradient recalled echo sequence and two sets of data obtained in separate experiments, one of which provides a phase reference image making it possible to eliminate the effect of theB₀field inhomogeneities. The final magnitude images have a good signal-to-noise even at low fields, and provide qualitative as well as quantitative information about the magnetic field produced by the ferromagnetic object. As an example the method is applied to study the field produced by a small metal piece in a 500-G scanner, and the experimental results are compared with numerical simulations.     

An NMR technique for measurement of magnetic field gradient waveforms

Almost all NMR imaging and localized spectroscopic methods fundamentally rely on the use of magnetic field gradients. It follows that precise information on gradient waveform shape and rise-times is often most useful in experimental MRI. We present a very simple and robust method for measuring the time evolution of a magnetic field gradient. The method is based on the analysis of the NMR signal in the time domain, and requires no specialized field measurement probes for its implementation. The technique makes use of the principal that for small flip angles the excitation profile is a good approximation to the Fourier transform of the radio frequency pulse shape. Creation of the NMR signal can be considered as an inverse Fourier transform and thus variation of the gradient strength during the excitation pulse influences the shape of the NMR signal. Although originally designed for measurement of the rise time only, we have now extended the technique to measure the exact time course of the gradient. The theory is confirmed by experimental results for gradient waveform field measurements in a high-field vertical bore system.     

Gaussian mixture model-based gradient field reconstruction for infrared image detail enhancement and denoising

Infrared images are characterized by low signal-to-noise ratio and low contrast. Therefore, the edge details are easily immerged in the background and noise, making it much difficult to achieve infrared image edge detail enhancement and denoising. This article proposes a novel method of Gaussian mixture model-based gradient field reconstruction, which enhances image edge details while suppressing noise. First, by analyzing the gradient histogram of noisy infrared image, Gaussian mixture model is adopted to simulate the distribution of the gradient histogram, and divides the image information into three parts corresponding to faint details, noise and the edges of clear targets, respectively. Then, the piecewise function is constructed based on the characteristics of the image to increase gradients of faint details and suppress gradients of noise. Finally, anisotropic diffusion constraint is added while visualizing enhanced image from the transformed gradient field to further suppress noise. The experimental results show that the method possesses unique advantage of effectively enhancing infrared image edge details and suppressing noise as well, compared with the existing methods. In addition, it can be used to effectively enhance other types of images such as the visible and medical images.     

A distributed equivalent magnetic current based FDTD method for the calculation of E-fields induced by gradient coils

This paper evaluates a new, low-frequency finite-difference time-domain method applied to the problem of induced E-fields/eddy currents in the human body resulting from the pulsed magnetic field gradients in MRI. In this algorithm, a distributed equivalent magnetic current is proposed as the electromagnetic source and is obtained by quasistatic calculation of the empty coil's vector potential or measurements therein. This technique circumvents the discretization of complicated gradient coil geometries into a mesh of Yee cells, and thereby enables any type of gradient coil modelling or other complex low frequency sources. The proposed method has been verified against an example with an analytical solution. Results are presented showing the spatial distribution of gradient-induced electric fields in a multi-layered spherical phantom model and a complete body model.     

Single point measurements of magnetic field gradient waveform

Pulsed magnetic field gradients are fundamental to spatial encoding and diffusion weighting in magnetic resonance. The ideal pulsed magnetic field gradient should have negligible rise and fall times, however, there are physical limits to how fast the magnetic field gradient may change with time. Finite gradient switching times, and transient, secondary, induced magnetic field gradients (eddy currents) alter the ideal gradient waveform and may introduce a variety of undesirable image artifacts. We have developed a new method to measure the complete magnetic field gradient waveform. The measurement employs a heavily doped test sample with short MR relaxation times (T(1), T(2), and T(2)(*)<100 micros) and a series of closely spaced broadband radiofrequency excitations, combined with single point data acquisition. This technique, a measure of evolving signal phase, directly determines the magnetic field gradient waveform experienced by the test sample. The measurement is sensitive to low level transient magnetic fields produced by eddy currents and other short and long time constant non-ideal gradient waveform behaviors. Data analysis is particularly facile permitting a very ready experimental check of gradient performance.     

Transfer learning in deep neural network based under-sampled MR image reconstruction

In Magnetic Resonance Imaging (MRI), the success of deep learning-based under-sampled MR image reconstruction depends on: (i) size of the training dataset, (ii) generalization capabilities of the trained neural network. Whenever there is a mismatch between the training and testing data, there is a need to retrain the neural network from scratch with thousands of MR images obtained using the same protocol. This may not be possible in MRI as it is costly and time consuming to acquire data. In this research, a transfer learning approach i.e. end-to-end fine tuning is proposed for U-Net to address the data scarcity and generalization problems of deep learning-based MR image reconstruction. First the generalization capabilities of a pre-trained U-Net (initially trained on the human brain images of 1.5 T scanner) are assessed for: (a) MR images acquired from MRI scanners of different magnetic field strengths, (b) MR images of different anatomies and (c) MR images under-sampled by different acceleration factors. Later, end-to-end fine tuning of the pre-trained U-Net is proposed for the reconstruction of the above-mentioned MR images (i.e. (a), (b) and (c)). The results show successful reconstructions obtained from the proposed method as reflected by the Structural SIMilarity index, Root Mean Square Error, Peak Signal-to-Noise Ratio and central line profile of the reconstructed images.     

Radiofrequency magnetic field gradient echoes have reduced sensitivity to susceptibility gradients

The amplitudes of gradient-echoes produced using static field gradients are sensitive to diffusion of tissue water during the echo evolution time. Gradient-echoes have been used to produce MR images in which image intensity is proportional to the self-diffusion coefficient of water. However, such measurements are subject to error due to the presence of background magnetic field gradients caused by variations in local magnetic susceptibility. These local gradients add to the applied gradients. The use of radiofrequency (RF) gradients to produce gradient-echoes may avoid this problem. The RF magnetic field is orthogonal to the offset field produced by local magnetic susceptibility gradients. Thus, the effect of the local gradients on RF gradient-echo amplitude is small if the RF field is strong enough to minimize resonance offset effects. The effects of susceptibility gradients can be further reduced by storing magnetization longitudinally during the echo evolution period. A water phantom was used to evaluate the effects of background gradients on the amplitudes of RF gradient-echoes. A surface coil was used to produce an RF gradient of between 1.3 and 1.6 gauss/cm. Gradient-echoes were detected with and without a 0.16 gauss/cm static magnetic field gradient applied along the same direction as the RF gradient. The background static field gradient had no significant effect on the decay of RF gradient-echo amplitude as a function of echo evolution time. In contrast, the effect of the background gradient on echoes produced using a 1.6 gauss/cm static field gradient is calculated to be significant. This analysis suggests that RF gradient-echoes can produce MR images in which signal intensity is a function of the self-diffusion coefficient of water, but is not significantly affected by background gradients.     

Phase correction-based singularity function analysis for partial k-space reconstruction

Partial k-space acquisition is a conventional method in magnetic resonance imaging (MRI) for reducing imaging time while maintaining image quality. In this field, image reconstruction from partial k-space is a key issue. This paper proposes an approach fundamentally different from traditional techniques for reconstructing magnetic resonance (MR) images from partial k-space. It uses a so-called singularity function analysis (SFA) model based on phase correction. With such a reconstruction approach, some nonacquired negative spatial frequencies are first recovered by means of phase correction and Hermitian symmetry property, and then the other nonacquired negative and/or positive spatial frequencies are estimated using the mathematical SFA model. The method is particularly suitable for asymmetrical partial k-space acquisition owing to its ability of overcoming reconstruction limitations due to k-space truncations. The performance of this approach is evaluated using both simulated and real MR brain images, and compared with existing techniques. The results demonstrate that the proposed SFA based on phase correction achieves higher image quality than the initial SFA or the projection-onto-convex sets (POCS) method.     

Exploiting the wavelet structure in compressed sensing MRI

Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms.     

磁共振成像的安全性

对磁共振成像(MRI)的安全性进行了综述,主要涉及五个方面:静磁场、梯度场、射频场、噪声和造影剂.在没有铁磁性外源性物质的条件下,静磁场对人体没有明显的损害,有较高的安全系数.随时间变化的梯度场(dB/dt)可在受试者体内诱导出电场而兴奋神经或肌肉.当梯度上升时间只有数毫秒时,外周神经兴奋是梯度场安全的上限指标.在MRI测定过程中,射频场发射的功率在患者组织内转化成热能,使组织温度升高.MRI运行过程中可产生各种噪声,可能使某些患者的听力受到损伤,使用耳塞仍是削弱噪声最简单和最经济的方法.目前使用的造影剂主要为含钆的化合物,副作用发生率在2%~4%.