Simulating the effects of time-varying magnetic fields with a realistic simulated scanner

Transient magnetic fields induce changes in magnetic resonance (MR) images ranging from small, visually undetectable effects (caused, for instance, by neuronal currents) to more significant ones, such as those created by the gradient fields and eddy currents. Accurately simulating these effects may assist in correcting or optimising MR imaging for many applications (e.g., diffusion imaging, current density imaging, use of magnetic contrast agents, neuronal current imaging, etc.). Here we have extended an existing MR simulator (POSSUM) with a model for changing magnetic fields at a very high-resolution time-scale. This simulator captures a realistic range of scanner and physiological artifacts by modeling the scanner environment, pulse sequence details and subject properties (e.g., brain geometry and air-tissue boundaries).     

Mapping eddy current induced fields for the correction of diffusion-weighted echo planar images

Diffusion-weighted echo-planar magnetic resonance imaging is potentially of great importance as a diagnostic imaging tool; however, the technique currently suffers a number of limitations, including the image distortion caused by the eddy current induced fields when the diffusion-weighting magnetic field gradient pulses are applied. The distortions cause mis-registration between images with different diffusion-weighting, that then results in artifacts in quantitative diffusion images. A method is presented to measure the magnetic fields generated from the eddy currents for each of three orthogonal gradient pulse vectors, and then to use these to ascertain the image distortion that occurs in subsequent diffusion-weighted images with arbitrary gradient pulse vector amplitude and direction, and image plane orientation. The image distortion can then be reversed. Both temporal and spatial dependence of the residual eddy current induced fields are included in the analysis. Image distortion was substantially reduced by the correction scheme, for arbitrary slice position and angulation. This method of correction is unaffected by the changes in image contrast that occur due to diffusion weighting, and does not need any additional scanning time during the patient scan. It is particularly suitable for use with single-shot echo planar imaging.     

An optimized pulse sequence for isotropically weighted diffusion imaging.

Single-shot echo-planar imaging is becoming the most widely used technique for magnetic resonance diffusion imaging, since it enables measurement of diffusion coefficients in human brain without motion artifacts. However, its reliability is limited by geometrical distortions due to eddy currents. In this report, an isotropically weighted echo-planar pulse sequence, optimized to give the maximum signal-to-noise ratio in the computed trace image and designed to produce inherently low distortions, is presented. It is also shown how the residual translational distortion can be easily characterized and removed by postprocessing. A full characterization of the distortion artifact involves a few measurements on a phantom, in order to estimate the distortion as a function of slice orientation, which can then be used to correct any slice orientation. Results of applying the image translation correction to data collected from a patient are presented.     

MRI梯度预加重模块的分时复用设计

为获得更优的成像质量和更快的成像速度,磁共振成像（MRI）系统的梯度预加重模块需要具有更多的补偿通道和调节参数,常规预加重模块的设计方案使现场可编程门阵列（FPGA）面临巨大的资源消耗.为解决高性能梯度预加重模块的资源消耗大的问题,本文提出了一种基于分时复用技术的梯度预加重实现方案,以常规方案1/44的资源实现了11通道×4组参数的梯度预加重模块.将该模块用于0.35 T MRI系统,测试了补偿前后的涡流曲线和磁共振图像,结果表明该模块有效降低了系统的涡流,减小了磁共振图像中的涡流伪影.     

On the use of water phantom images to calibrate and correct eddy current induced artefacts in MR diffusion tensor imaging

The accurate determination of absolute measures of diffusion anisotropy in vivo using single-shot, echo-planar imaging techniques requires the acquisition of a set of high signal-to-noise ratio, diffusion-weighted images that are free from eddy current induced image distortions. Such geometric distortions can be characterized and corrected in brain imaging data using magnification (M), translation (T), and shear (S) distortion parameters derived from separate water phantom calibration experiments. Here we examine the practicalities of using separate phantom calibration data to correct high b-value diffusion tensor imaging data by investigating the stability of these distortion parameters, and hence the eddy currents, with time. It is found that M, T, and S vary only slowly with time (i.e., on the order of weeks), so that calibration scans need not be performed after every patient examination. This not only minimises the scan time required to collect the calibration data, but also the computational time needed to characterize these eddy current induced distortions. Examples of how measurements of diffusion anisotropy are improved using this post-processing scheme are also presented.     

Estimation of mutual information objective function based on Fourier shift theorem: an application to eddy current distortion correction in diffusion tensor imaging

Diffusion tensor imaging requires correction of eddy current distortion in diffusion-weighted images. An effective retrospective correction approach is to transform a diffusion-weighted image to maximize the mutual information (MI) between the transformed diffusion-weighted image and the corresponding T2-weighted image. In the literature, either linear interpolation or partial volume interpolation is applied to estimate the MI objective function. However, these interpolation methods induce artifacts to the MI objective function, thus compromising correction results. In this work, the MI objective function is estimated based on interpolation using Fourier shift theorem. This method eliminates the artifacts incurred with the aforementioned interpolation methods. The algorithm is further improved by approximating pixel values using their nearest neighbors in the up-sampled spatial domain, resulting in dramatically increased computational efficiency without compromising the correction results. The effects of varying the number of quantization levels and using Parzen window filtering to smooth the MI objective function are also investigated to obtain optimized algorithm parameters. The diffusion tensor image quality after applying the proposed distortion correction method is significantly improved visually.     

一种以超分辨率理论为基础的磁共振眼球成像方法

磁共振成像（MRI）是一种无电离辐射的非介入性的眼内肿瘤检测方法,但分辨率和运动伪影是成像过程中不易克服的困难．以往的扫描方法或是不可避免的引入运动伪影,或是需要受试者做精确的配合,增加了成像的难度,给受试者带来不舒适的体验．本文提出了一种以超分辨率理论为基础的新的磁共振眼球成像方法,使用一种特制的眼球线圈,对眼部区域扫描一系列动态的图像,使得不同方向上的采集分辨率互补．最后经过预处理、配准、超分辨率重建等操作,得到高质量的磁共振眼球图像．实验结果表明,这种方法可以在不需要受试者做额外配合工作的情况下,得到更加清晰的磁共振眼球图像．     

Double-spin-echo diffusion weighting with a modified eddy current adjustment

Magnetic field inhomogeneities like eddy current-related gradient fields cause geometric distortions in echo-planar imaging (EPI). This in particular affects diffusion-weighted imaging where these distortions vary with the direction of the diffusion weighting and hamper the accurate determination of diffusion parameters. The double-spin-echo preparation often used aims to reduce the cumulative eddy current effect by adjusting the diffusion-weighting gradient pulse durations to the time constant of the dominant eddy current contribution. However, eddy currents with a variety of time constants may be present and cause residual distortions. Here, a modification is proposed where the two bipolar gradient pairs of the preparation are adjusted independently to different time constants. At the expense of a slightly prolonged echo time, residual geometric distortions and correspondingly increased values of the diffusion anisotropy can be reduced as is demonstrated in phantoms and the human brain. Thus, it may help to improve the reliability of diffusion-weighted EPI.     

High-resolution diffusion imaging using phase-corrected segmented echo-planar imaging

Diffusion magnetic resonance imaging (MRI) was performed with a high-resolution segmented echo-planar imaging technique, which provided images with substantially less susceptibility artifacts than images obtained with single-shot echo-planar imaging (EPI). Diffusion imaging performed with any multishot pulse sequence is inherently sensitive to motion artifacts and in order to reduce motion artifacts, the presented method utilizes navigator echo phase corrections, performed after a one-dimensional Fourier transform along the frequency-encoding direction. Navigator echo phases were fitted to a straight line prior to phase correction to avoid errors from internal motion. In vivo imaging was performed using electro cardiographic (ECG) triggering. Apparent diffusion coefficient (ADC) maps were calculated on a pixel-by-pixel basis using up to seven diffusion sensitivities, ranging from b = 0 to 1129 x 10(6) s/m(2).     

Correction of eddy current-induced artefacts in diffusion tensor imaging using iterative cross-correlation.

Geometric distortions of echo-planar images produced by the strong eddy currents present in the diffusion tensor imaging experiment are a major confound to the accurate quantification of diffusion coefficients, and measures of diffusion anisotropy based upon them. Here we investigate how the method of iterative cross-correlation (ICC) of baseline and diffusion-weighted images (DWIs) originally proposed by Haselgrove and Moore (Magn. Reson. Med. 36:960-964; 1996) can be extended to correct high b-value DWIs, without the need for extrapolation of distortion parameters determined from low b-value images. Monte Carlo simulations of synthetic brain images show that the maximum value of the trace of the b-matrix, Tr(b), at which distorted DWIs can be accurately corrected by direct comparison with the undistorted baseline image is approximately 300 s mm(-2). Removal of the cerebrospinal fluid signal greatly extends this value of Tr(b) (up to approximately 2000 s mm(-2)), thereby allowing direct comparison of baseline and distorted images. The use of ICC distortion parameters determined from separate calibrations of water phantom images is also investigated, and found to be effective in correcting geometric distortions observed in the DWIs collected as part of a human volunteer diffusion tensor imaging study. This work suggests that distorted DWIs acquired at high values of b may be corrected using the ICC algorithm without collecting additional low b-value images, thus allowing simplified methods of measuring the apparent diffusion tensor D, based on collecting a small number of DWIs, to be implemented in quantitative patient examinations.     

Improved reduction of motion artifacts in diffusion imaging using navigator echoes and velocity compensation

Navigator echoes provide a means with which to remove motion artifacts from diffusion-weighted images obtained using any multishot imaging technique. However, residual motion artifact is often present in the corrected images rendering the technique unreliable. It is shown that velocity-compensated diffusion sensitization when used in tandem with a navigator echo further reduces the degree of residual motion artifacts present in the corrected images and improves the reliability and clinical utility of the technique. This is demonstrated by applying a method for quantification of motion artifact to brain images of healthy volunteers scanned using both conventional (Stejskal-Tanner) and velocity-compensated gradient sensitization. Other factors affecting the efficacy of the navigator echo technique, such as brain pulsatile motion, gradient b factor, and navigator echo signal-to-noise ratio, are also discussed.     

A comparison study of multishot vs. single-shot DWI-EPI in the neonatal brain: reduced effects of ghosting compared to adults

In the neonatal brain, it is important to use a fast imaging technique to acquire all diffusion weighted images (DWI) for apparent diffusion coefficient (ADC) calculation. Taking into account the occurrence of typical echo planar imaging (EPI) artifacts, we have investigated whether single-shot (SSh) or multishot (MSh) DWI-EPI should be preferred. In 14 neonates, 17 adult patients and 5 adult volunteers, DWIs are obtained both with SSh and MSh EPI. The occurrence of artifacts and their influence on the ADC are explored and further quantified using simulations and phantom studies. Two radiologists scored overall image quality and diagnosability of all images. Single-shot and MSh DWI-EPI scored equally well in neonates with respect to overall image quality and diagnosability. In newborns, more motion artifacts in MSh can be noticed while N/2-ghost artifacts in SSh occur less frequently than in adults. Both N/2-ghost and motion artifacts result in significant ADC abnormalities. There is a serious risk that these artifacts will be mistaken for genuine diffusion abnormalities. N/2-ghost artifacts are hardly noticed in the neonatal brain, which might be due to smaller cerebrospinal fluid (CSF) velocity than in adults. Apparent diffusion coefficient values in MSh are unreliable if motion occurs. We conclude that for ADC calculations in neonates SSh DWI-EPI is more reliable than MSh.     

Quantitative analysis of spatial distortions of diffusion techniques at 3T

Diffusion has been widely adopted in the clinical setting to study the microstructural tissue changes in conjunction with anatomic imaging and metabolic imaging to offer insights on the status of the tissue injury or lesion. However, geometric distortions caused by magnetic susceptibility effects, eddy currents and gradient imperfections greatly affect the clinical utility of the diffusion images. Several diffusion methods have been proposed in the recent years to obtain diffusion parameters with increased accuracy. In most cases, the comparisons to the clinical standard echo-planar imaging (EPI) diffusion are done visually without quantitative measurements. In this study, we present three simple, complementary quantitative methods of nonrigid image registration and shape analyses for evaluating spatial distortions on magnetic resonance images with application in comparing single-shot fast spin-echo (SSFSE) and EPI based diffusion measurements. These methods have confirmed the SSFSE based diffusion method is less distorted than the EPI based one, which is generally accepted through visual inspection.     

Finite element analysis of gradient z-coil induced eddy currents in a permanent MRI magnet

In permanent magnetic resonance imaging (MRI) systems, pulsed gradient fields induce strong eddy currents in the conducting structures of the magnet body. The gradient field for image encoding is perturbed by these eddy currents leading to MR image distortions. This paper presents a comprehensive finite element (FE) analysis of the eddy current generation in the magnet conductors. In the proposed FE model, the hysteretic characteristics of ferromagnetic materials are considered and a scalar Preisach hysteresis model is employed. The developed FE model was applied to study gradient z-coil induced eddy currents in a 0.5 T permanent MRI device. The simulation results demonstrate that the approach could be effectively used to investigate eddy current problems involving ferromagnetic materials. With the knowledge gained from this eddy current model, our next step is to design a passive magnet structure and active gradient coils to reduce the eddy current effects.     

Correction strategy for diffusion-weighted images corrupted with motion: application to the DTI evaluation of infants' white matter

Objective

Diffusion imaging techniques such as DTI and HARDI are difficult to implement in infants because of their sensitivity to subject motion. A short acquisition time is generally preferred, at the expense of spatial resolution and signal-to-noise ratio. Before estimating the local diffusion model, most pre-processing techniques only register diffusion-weighted volumes, without correcting for intra-slice artifacts due to motion or technical problems. Here, we propose a fully automated strategy, which takes advantage of a high orientation number and is based on spherical-harmonics decomposition of the diffusion signal.

Material and methods

The correction strategy is based on two successive steps: 1) automated detection and resampling of corrupted slices; 2) correction for eddy current distortions and realignment of misregistered volumes. It was tested on DTI data from adults and non-sedated healthy infants.

Results

The methodology was validated through simulated motions applied to an uncorrupted dataset and through comparisons with an unmoved reference. Second, we showed that the correction applied to an infant group enabled to improve DTI maps and to increase the reliability of DTI quantification in the immature cortico-spinal tract.

Conclusion

This automated strategy performed reliably on DTI datasets and can be applied to spherical single- and multiple-shell diffusion imaging.     

Quantitative quality assurance in a multicenter HARDI clinical trial at 3 T

A phantom-based quality assurance (QA) protocol was developed for a multicenter clinical trial including high angular resolution diffusion imaging (HARDI). A total of 27 3 T MR scanners from 2 major manufacturers, GE (Discovery and Signa scanners) and Siemens (Trio and Skyra scanners), were included in this trial. With this protocol, agar phantoms doped to mimic relaxation properties of brain tissue are scanned on a monthly basis, and quantitative procedures are used to detect spiking and to evaluate eddy current and Nyquist ghosting artifacts. In this study, simulations were used to determine alarm thresholds for minimal acceptable signal-to-noise ratio (SNR). Our results showed that spiking artifact was the most frequently observed type of artifact. Overall, Trio scanners exhibited less eddy current distortion than GE scanners, which in turn showed less distortion than Skyra scanners. This difference was mainly caused by the different sequences used on these scanners. The SNR for phantom scans was closely correlated with the SNR from volunteers. Nearly all of the phantom measurements with artifact-free images were above the alarm threshold, suggesting that the scanners are stable longitudinally. Software upgrades and hardware replacement sometimes affected SNR substantially but sometimes did not. In light of these results, it is important to monitor longitudinal SNR with phantom QA to help interpret potential effects on in vivo measurements. Our phantom QA procedure for HARDI scans was successful in tracking scanner performance and detecting unwanted artifacts.     

Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB)

Objective: Magnetic resonance imaging (MRI) acquisition is inherently sensitive to motion, and motion artifact reduction is essential for improving image quality in MRI. Methods: We developed a deep residual network with densely connected multi-resolution blocks (DRN-DCMB) model to reduce the motion artifacts in T1 weighted (T1W) spin echo images acquired on different imaging planes before and after contrast injection. The DRN-DCMB network consisted of multiple multi-resolution blocks connected with dense connections in a feedforward manner. A single residual unit was used to connect the input and output of the entire network with one shortcut connection to predict a residual image (i.e. artifact image). The model was trained with five motion-free T1W image stacks (pre-contrast axial and sagittal, and post-contrast axial, coronal, and sagittal images) with simulated motion artifacts. Results: In other 86 testing image stacks with simulated artifacts, our DRN-DCMB model outperformed other state-of-the-art deep learning models with significantly higher structural similarity index (SSIM) and improvement in signal-to-noise ratio (ISNR). The DRN-DCMB model was also applied to 121 testing image stacks appeared with various degrees of real motion artifacts. The acquired images and processed images by the DRN-DCMB model were randomly mixed, and image quality was blindly evaluated by a neuroradiologist. The DRN-DCMB model significantly improved the overall image quality, reduced the severity of the motion artifacts, and improved the image sharpness, while kept the image contrast. Conclusion: Our DRN-DCMB model provided an effective method for reducing motion artifacts and improving the overall clinical image quality of brain MRI.     

Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares

Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and by spatially and temporally varying artifacts, such as rigid-body motion and cardiac pulsation. Motion artifacts are particularly prevalent when scanning difficult patient populations, such as human infants. Although some motion during data acquisition can be corrected using image coregistration procedures, frequently individual DWIs are corrupted beyond repair by sudden, large amplitude motion either within or outside of the imaging plane. We propose a novel approach to identify and reject outlier images automatically using local binary patterns (LBP) and 2D partial least square (2D-PLS) to estimate diffusion tensors robustly. This method uses an enhanced LBP algorithm to extract texture features from a local texture feature of the image matrix from the DWI data. Because the images have been transformed to local texture matrices, we are able to extract discriminating information that identifies outliers in the data set by extending a traditional one-dimensional PLS algorithm to a two-dimension operator. The class-membership matrix in this 2D-PLS algorithm is adapted to process samples that are image matrix, and the membership matrix thus represents varying degrees of importance of local information within the images. We also derive the analytic form of the generalized inverse of the class-membership matrix. We show that this method can effectively extract local features from brain images obtained from a large sample of human infants to identify images that are outliers in their textural features, permitting their exclusion from further processing when estimating tensors using the DWIs. This technique is shown to be superior in performance when compared with visual inspection and other common methods to address motion-related artifacts in DWI data. This technique is applicable to correct motion artifact in other magnetic resonance imaging (MRI) techniques (e.g., the bootstrapping estimation) that use univariate or multivariate regression methods to fit MRI data to a pre-specified model.     

Single-shot diffusion imaging at 2.0 tesla

A single-shot echo-planar diffusion imaging sequence (IVIM-EPI: intra-voxel incoherent motion echo-planar imaging) is presented, which is immune from the motion artifacts which may seriously impair images obtained using other diffusion imaging sequences. For a static water phantom, the measured value of diffusion constant (D = 2.30 × 10⁻⁹ m² s⁻¹ at T = 298 K) shows excellent agreement with that obtained using a multipulse spin-echo technique and with literature values. Single-shot diffusion imaging can now be used reliably to make dynamic time-course studies with excellent time resolution.     

Eddy current simulation in thick cylinders of finite length induced by coils of arbitrary geometry

Eddy currents are inevitably induced when time-varying magnetic field gradients interact with the metallic structures of a magnetic resonance imaging (MRI) scanner. The secondary magnetic field produced by this induced current degrades the spatial and temporal performance of the primary field generated by the gradient coils. Although this undesired effect can be minimized by using actively and/or passively shielded gradient coils and current pre-emphasis techniques, a residual eddy current still remains in the MRI scanner structure. Accurate simulation of these eddy currents is important in the successful design of gradient coils and magnet cryostat vessels. Efficient methods for simulating eddy currents are currently restricted to cylindrical-symmetry. The approach presented in this paper divides thick conducting cylinders into thin layers (thinner than the skin depth) and expresses the current density on each as a Fourier series. The coupling between each mode of the Fourier series with every other is modeled with an inductive network method. In this way, the eddy currents induced in realistic cryostat surfaces by coils of arbitrary geometry can be simulated. The new method was validated by simulating a canonical problem and comparing the results against a commercially available software package. An accurate skin depth of 2.76 mm was calculated in 6 min with the new method. The currents induced by an actively shielded x-gradient coil were simulated assuming a finite length cylindrical cryostat consisting of three different conducting materials. Details of the temporal-spatial induced current diffusion process were simulated through all cryostat layers, which could not be efficiently simulated with any other method. With this data, all quantities that depend on the current density, such as the secondary magnetic field, are simply evaluated.