Spiral demystified

Spiral acquisition schemes offer unique advantages such as flow compensation, efficient k-space sampling and robustness against motion that make this option a viable choice among other non-Cartesian sampling schemes. For this reason, the main applications of spiral imaging lie in dynamic magnetic resonance imaging such as cardiac imaging and functional brain imaging. However, these advantages are counterbalanced by practical difficulties that render spiral imaging quite challenging. Firstly, the design of gradient waveforms and its hardware requires specific attention. Secondly, the reconstruction of such data is no longer straightforward because k-space samples are no longer aligned on a Cartesian grid. Thirdly, to take advantage of parallel imaging techniques, the common generalized autocalibrating partially parallel acquisitions (GRAPPA) or sensitivity encoding (SENSE) algorithms need to be extended. Finally, and most notably, spiral images are prone to particular artifacts such as blurring due to gradient deviations and off-resonance effects caused by B₀ inhomogeneity and concomitant gradient fields. In this article, various difficulties that spiral imaging brings along, and the solutions, which have been developed and proposed in literature, will be reviewed in detail.     

High resolution diffusion weighted magnetic resonance imaging of the pancreas using reduced field of view single-shot echo-planar imaging at 3 T

Diffusion weighted magnetic resonance imaging (DWI) has been mostly acquired using single-shot echo-planar imaging (ss EPI) to minimize motion induced artifacts. The spatial resolution, however, is inherently limited in ss EPI especially for abdominal imaging, even with the advances in parallel imaging. A novel method of reduced Field of View ss EPI (rFOV ss EPI) has achieved high resolution DWI in human carotid artery, spinal cord with reduced blurring and higher spatial resolution than conventional ss EPI, but it has not been used to pancreas imaging. In the work, comparisons between the full FOV ss-DW EPI and rFOV ss-DW EPI in image qualities and ADC values of pancreatic tumors and normal pancreatic tissues were performed to demonstrate the feasibility of pancreatic high resolution rFOV DWI. There were no significant differences in the mean ADC values between full FOV DWI and rFOV DWI for the 17 subjects using b = 600 s/mm² (P = 0.962). However, subjective scores of image quality was significantly higher at rFOV ss DWI (P = 0.008 and 0.000 for b-value = 0 s/mm² and 600 s/mm² respectively). The spatial resolution of DWI for pancreas was increased by a factor of over 2.0 (from almost 3.0 mm/pixel to 1.25 mm/pixel) using rFOV ss EPI technique. Reduced FOV ss EPI can provide good DW images and is promising to benefit applications for pancreatic diseases.     

Reduced field-of-view DTI segmentation of cervical spine tissue

The number of diffusion tensor imaging (DTI) studies regarding the human spine has considerably increased and it is challenging because of the spine’s small size and artifacts associated with the most commonly used clinical imaging method. A novel segmentation method based on the reduced field-of-view (rFOV) DTI dataset is presented in cervical spinal canal cerebrospinal fluid, spinal cord grey matter and white matter classification in both healthy volunteers and patients with neuromyelitis optica (NMO) and multiple sclerosis (MS). Due to each channel based on high resolution rFOV DTI images providing complementary information on spinal tissue segmentation, we want to choose a different contribution map from multiple channel images. Via principal component analysis (PCA) and a hybrid diffusion filter with a continuous switch applied on fourteen channel features, eigen maps can be obtained and used for tissue segmentation based on the Bayesian discrimination method. Relative to segmentation by a pair of expert readers, all of the automated segmentation results in the experiment fall in the good segmentation area and performed well, giving an average segmentation accuracy of about 0.852 for cervical spinal cord grey matter in terms of volume overlap. Furthermore, this has important applications in defining more accurate human spinal cord tissue maps when fusing structural data with diffusion data. rFOV DTI and the proposed automatic segmentation outperform traditional manual segmentation methods in classifying MR cervical spinal images and might be potentially helpful for detecting cervical spine diseases in NMO and MS.     

Projection-reconstruction reduced [correction of reduces] FOV imaging

Reduced field-of-view (rFOV) imaging was introduced recently as a rapid imaging technique that improves temporal resolution while maintaining spatial resolution. It is based on undersampling in k-space and utilizes the fact that the dynamics of an evolving process are often confined to a local area within the full FOV. In the work presented here the reduced FOV approach is applied to projection-reconstruction MRI and compared to the original spin-warp implementation. Results are presented that clearly demonstrate the increased robustness of the projection-reconstruction version of rFOV imaging. The technique is successfully applied to an MR-guided biopsy scenario (ex-vivo) and to cine cardiac imaging. Finally an algorithm is proposed that uses the intrinsic advantages of radial k-space sampling to evaluate the projection data to control the adjustment of position and size of the reduced FOV window.     

Improved depiction of small anatomic structures in MR images using Gaussian-weighted spirals and zero-filled interpolation

Partial-volume artifacts reduce the contrast and continuity of small structures in magnetic resonance images. Zero-filled interpolation (ZFI) has been known for some time as a useful technique to reduce partial-volume artifacts and improve the appearance of small structures and edges. However, its use is limited by the fact that ZFI can exacerbate image artifacts. For example, it can exacerbate Gibbs ringing, also known as the truncation artifact, which manifests itself as spurious ringing around sharp edges. Currently, the most common technique to address this problem is post-acquisition filtering, which causes blurring in the image. Using ZFI in conjunction with a variable-density sampling method designed to reduce ringing is proposed as a possible solution to this problem. This approach is demonstrated with a Gaussian-weighted spiral and is compared to conventional spiral sampling both with and without the application of a filter used to reduce ringing. The two spiral sampling techniques are compared using simulations, phantom images, and in vivo brain images. The Gaussian-weighted spiral demonstrates reduced ringing without the loss of spatial resolution commonly associated with post-acquisition filtering. Additionally, this sampling technique is shown to work well in conjunction with ZFI to reduce partial-volume artifacts without the apparent increase in Gibbs ringing usually associated with zero-filled reconstruction. This approach will be most useful for imaging techniques such as MR angiography which are known to be sensitive to partial-volume effects, as well as when imaging anatomic regions associated with more severe Gibbs ringing.     

Reduced aliasing artifacts using shaking projection k-space sampling trajectory

Radial imaging techniques, such as projection-reconstruction （PR）, are used in magnetic resonance imaging （MRI） for dynamic imaging, angiography, and short-T2 imaging. They are less sensitive to flow and motion artifacts, and support fast imaging with short echo times. However, aliasing and streaking artifacts are two main sources which degrade radial imaging quality. For a given fixed number of k-space projections, data distributions along radial and angular directions will influence the level of aliasing and streaking artifacts. Conventional radial k-space sampling trajectory introduces an aliasing artifact at the first principal ring of point spread function （PSF）. In this paper, a shaking projection （SP） k-space sampling trajectory was proposed to reduce aliasing artifacts in MR images. SP sampling trajectory shifts the projection alternately along the k-space center, which separates k-space data in the azimuthal direction. Simulations based on conventional and SP sampling trajectories were compared with the same number projections. A significant reduction of aliasing artifacts was observed using the SP sampling trajectory. These two trajectories were also compared with different sampling frequencies. ASP trajectory has the same aliasing character when using half sampling frequency （or half data） for reconstruction. SNR comparisons with different white noise levels show that these two trajectories have the same SNR character. In conclusion, the SP trajectory can reduce the aliasing artifact without decreasing SNR and also provide a way for undersampling recon- struction. Furthermore, this method can be applied to three-dimensional （3D） hybrid or spherical radial k-space sampling for a more efficient reduction of aliasing artifacts.     

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．     

一种基于时空变换和压缩感知的磁共振螺旋采样的图像重建算法

螺旋采样磁共振快速成像在功能性成像、并行成像和动态成像等领域发挥着越来越重要的作用.螺旋采样图像重建的传统算法是用核函数将螺旋状分布的k空间数据插值到均匀网格中,再利用傅里叶变换和最小二乘法进行重建.但是基于网格化的算法对核函数过于依赖,在网格化过程中产生难以避免的误差.该文提出了基于时空变换和压缩感知的l1范数的最优化模型和重建算法.时空变换矩阵描述了空间上的磁共振图像与采集到的时域信号间的关系,使得算法直接使用采集到的数据作为保真约束项,避免了网格化过程产生的误差.此外,基于图像处理单元的并行计算被用来提高时空变换矩阵的运算速度,使得算法具有较强的应用价值.     

Susceptibility-matched envelope for the correction of EPI artifacts

Fast gradient echo sequences, such as echo planer imaging (EPI) and spiral imaging, are vulnerable to artifacts resulting from B(0) inhomogeneities. A major contribution to these artifacts is the susceptibility variation across the head, which is most severe in regions adjacent to air-tissue interfaces, such as the mouth, nasal sinuses, ears and the cortex. Susceptibility artifacts can cause geometrical distortions in the image as well as loss of signal due to T(2)* dephasing. The extent of these artifacts increases with the main field, thus compromising the signal-to-noise ratio (SNR) benefit gained in higher fields. In the current work, inhomogeneity caused by susceptibility variations at the external boundary of the human body has been corrected by surrounding the organs with a liquid without hydrogen atoms and whose susceptibility is similar to that of the imaged organ. EPI experiments were conducted on head-sized phantom, human brain, hand and legs. This method causes minimal patient inconvenience and no interference with any function of the scanner, thus yielding a simple and efficient solution for the correction of B(0) variation.     

基于同伦l0范数最小化重建的三维动态磁共振成像

高欠采倍数的动态磁共振图像重建具有重要意义,是同时实现高时间分辨率和高空间分辨率动态对比度增强成像的重要环节.本研究提出一种结合黄金角变密度螺旋采样、并行成像和基于同伦l₀范数最小化的压缩感知的图像重建的三维动态磁共振成像方法.黄金角变密度螺旋采样轨迹被用来连续获取k空间数据,具有数据采集效率高、对运动不敏感等优点.在重建算法中,将多线圈稀疏约束应用于时间总变分域,使用基于l₀范数最小化的非线性重建算法代替传统的l₁范数最小化算法,进一步提高了欠采样率.仿真实验和在体实验表明本文所提的方法在保持图像质量的同时,也可以实现较高的空间分辨率和时间分辨率,初步验证了基于同伦l₀范数最小化重建在三维动态磁共振成像上的优势和临床价值.     

A statistical iteration approach with energy minimization to sinogram noise reduction for low-dose X-ray CT

Low-dose CT imaging has been particularly used in modern medical practice for its advantage on reducing the radiation dose to patients. However, excessive quantum noise is present in low dose X-ray imaging along with the decrease of the radiation dose; thus, there are obvious streak-like artifacts in reconstructed images. The statistical iterative reconstruction approach applied to the noisy sinogram before a filtered back-projection (FBP) is a resolution to deal with the noisy problem. In this paper, the statistical property of the noise sinogram was considered to achieve a satisfactory image reconstruction and a statistical iterative method with energy minimization was proposed to address the problem of streak-like artifacts. Simulations were performed and indicated that the proposed method could suppress noise and obviously decrease streak-like artifacts in reconstructed images.     

Real-time dynamic vocal tract imaging using an accelerated spiral GRE sequence and low rank plus sparse reconstruction

PurposeTo develop a real-time dynamic vocal tract imaging method using an accelerated spiral GRE sequence and low rank plus sparse reconstruction.MethodsSpiral k-space sampling has high data acquisition efficiency and thus is suited for real-time dynamic imaging; further acceleration can be achieved by undersampling k-space and using a model-based reconstruction. Low rank plus sparse reconstruction is a promising method with fast computation and increased robustness to global signal changes and bulk motion, as the images are decomposed into low rank and sparse terms representing different dynamic components. However, the combination with spiral scanning has not been well studied. In this study an accelerated spiral GRE sequence was developed with an optimized low rank plus sparse reconstruction and compared with L1-SPIRiT and XD-GRASP methods. The off-resonance was also corrected using a Chebyshev approximation method to reduce blurring on a frame-by-frame basis.ResultsThe low rank plus sparse reconstruction method is sensitive to the weights of the low rank and sparse terms. The optimized reconstruction showed advantages over other methods with reduced aliasing and improved SNR. With the proposed method, spatial resolution of 1.3*1.3 mm² with 150 mm field-of-view (FOV) and temporal resolution of 30 frames-per-second (fps) was achieved with good image quality. Blurring was reduced using the Chebyshev approximation method.ConclusionThis work studies low rank plus sparse reconstruction using the spiral trajectory and demonstrates a new method for dynamic vocal tract imaging which can benefit studies of speech disorders.     

CSF flow artifact reduction using cardiac cycle ordered phase-encoding method

The flow effects appear as a change of phase as well as signal intensity in NMR imaging. Since the flow of blood and CSF (cerebrospinal fluid) is pulsatile due to the heart pumping, their velocities are not constant during NMR imaging. This type of velocity fluctuation such as the blood or CSF flow induces irregular flow-dependent phase shifts, which have been one of the main causes of flow artifacts in NMR imaging. In order to reduce the flow artifacts, especially the CSF flow artifacts, a new cardiac cycle ordered phase encoding method is proposed and has been studied. This proposed technique utilizes the cardiac cycle as a precursor for the phase encoding gradients similar to the ROPE (respiratory ordered phase encoding) technique which has been used for respiratory motion artifact reduction. The basic concept and its applications are discussed together with the experimental results obtained with human volunteers using the KAIS 2.0 2.0 T whole-body NMR imaging system.     

Fast fat-suppressed reduced field-of-view temperature mapping using 2DRF excitation pulses

The purpose of this study is to develop a fast and accurate temperature mapping method capable of both fat suppression and reduced field-of-view (rFOV) imaging, using a two-dimensional spatially-selective RF (2DRF) pulse. Temperature measurement errors caused by fat signals were assessed, through simulations. An 11×1140μs echo-planar 2DRF pulse was developed and incorporated into a gradient-echo sequence. Temperature measurements were obtained during focused ultrasound (FUS) heating of a fat-water phantom. Experiments both with and without the use of a 2DRF pulse were performed at 3T, and the accuracy of the resulting temperature measurements were compared over a range of TE values. Significant inconsistencies in terms of measured temperature values were observed when using a regular slice-selective RF excitation pulse. In contrast, the proposed 2DRF excitation pulse suppressed fat signals by more than 90%, allowing good temperature consistency regardless of TE settings. Temporal resolution was also improved, from 12 frames per minute (fpm) with the regular pulse to 28 frames per minute with the rFOV excitation. This technique appears promising toward the MR monitoring of temperature in moving adipose organs, during thermal therapies.     

DC artifact correction for arbitrary phase-cycling sequence

In magnetic resonance imaging (MRI), a non-zero offset in the receiver baseline signal during acquisition results in a bright spot or a line artifact in the center of the image known as a direct current (DC) artifact. Several methods have been suggested in the past for the removal or correction of DC artifacts in MR images, however, these methods cannot be applied directly when a specific phase-cycling technique is used in the imaging sequence. In this work, we proposed a new, simple technique that enables correction of DC artifacts for any arbitrary phase-cycling imaging sequences. The technique is composed of phase unification, DC offset estimation and correction, and phase restoration. The feasibility of the proposed method was demonstrated via phantom and in vivo experiments with a multiple phase-cycling balanced steady-state free precession (bSSFP) imaging sequence. Results showed successful removal of the DC artifacts in images acquired using bSSFP with phase-cycling angles of 0°, 90°, 180°, and 270°, indicating potential feasibility of the proposed method to any imaging sequence with arbitrary phase-cycling angles.     

Anisotropic total variation minimization approach in in-line phase-contrast tomography and its application to correction of ring artifacts

In-line phase-contrast computed tomography(IL-PC-CT) imaging is a new physical and biochemical imaging method.IL-PC-CT has advantages compared to absorption CT when imaging soft tissues. In practical applications, ring artifacts which will reduce the image quality are commonly encountered in IL-PC-CT, and numerous correction methods exist to either pre-process the sinogram or post-process the reconstructed image. In this study, we develop an IL-PC-CT reconstruction method based on anisotropic total variation(TV) minimization. Using this method, the ring artifacts are corrected during the reconstruction process. This method is compared with two methods: a sinogram preprocessing correction technique based on wavelet-FFT filter and a reconstruction method based on isotropic TV. The correction results show that the proposed method can reduce visible ring artifacts while preserving the liver section details for real liver section synchrotron data.     

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images

Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.     

Quantitative susceptibility mapping of prostate with separate calculations for water and fat regions for reducing shading artifacts

We propose a novel processing method for reducing shading artifacts in quantitative susceptibility mapping (QSM) for prostate imaging. In the conventional method, calculation errors in the boundary regions between water and fat cause shading artifacts that degrade the image quality for QSM. In the proposed method, water and fat regions are separated, and susceptibilities in these two regions are calculated separately and then combined. Susceptibility in the water regions is calculated by using the fat regions as a background susceptibility source to remove shading artifacts. Susceptibility in the fat regions is calculated by using the constraint that shading artifacts in the water regions are suppressed to improve accuracy. In quantitative evaluation of the method with a numerical simulation, calculation errors for the water and fat regions were reduced by 62% and 85%, respectively, compared with the conventional method. In visual evaluation using human prostate imaging, the proposed method also reduced the shading artifacts unlike the conventional method. The proposed method is expected to improve the performance of QSM in diagnosing such diseases as prostate cancer.     

ANTHEM: anatomically tailored hexagonal MRI

PURPOSE: This study aimed to investigate the use of anatomically tailored hexagonal sampling for scan-time and error reduction in MRI. MATERIALS AND METHODS: Anatomically tailored hexagonal MRI (ANTHEM), a method that combines hexagonal sampling with specific symmetry in anatomical geometry, is proposed. By using hexagonal sampling, aliasing artifacts are moved to regions where, due to the nature of the anatomy, aliasing is inconsequential. This can be used to either reduce scan time while maintaining spatial resolution or reduce residual errors in speedup techniques like UNFOLD and k-t BLAST/SENSE, which undersample k-space and unwrap fold-over artifacts during reconstruction. Computer simulations as well as phantom and volunteer studies were used to validate the theory. A simplified reconstruction algorithm for hexagonally sampled and subsampled k-space data was also used. RESULTS: A reduction in sampling density of 13.4% and 25% in each hexagonally sampled dimension was achieved for spherical and conical geometries without aliasing or reduction in spatial resolution. Optimal subsampling schemes that can be utilized by UNFOLD and k-t BLAST/SENSE were derived using hexagonal subsampling, which resulted in maximal, isotropic dispersal of the aliases. In combination with UNFOLD, ANTHEM was shown to move residual aliasing artifacts to the corners of the field of view, yielding reduced artifacts in CINE reconstructions. CONCLUSIONS: ANTHEM was successful in reducing acquisition time in conventional MRI and in reducing errors in UNFOLD imaging.     

Parallel EPI artifact correction (PEAC) for N/2 ghost suppression in neuroimaging applications

Echo Planar Imaging (EPI) is a neuroimaging tool for clinical practice and research investigation. Due to odd-even echo phase inconsistencies, however, EPI suffers from Nyquist N/2 ghost artifacts. In standard neuroimaging protocols, EPI artifacts are suppressed using phase correction techniques that require reference data collected from a reference scan. Because reference-scan based techniques are sensitive to subject motion, EPI performance is sub-optimal in neuroimaging applications. In this technical note, we present a novel EPI data processing technique which we call Parallel EPI Artifact Correction (PEAC). By introducing an implicit data constraint associated with multi-coil sensitivity in parallel imaging, PEAC converts phase correction into a constrained problem that can be resolved using an iterative algorithm. This enables “reference-less” EPI that can improve neuroimaging performance. In the presented work, PEAC is investigated using a standard functional magnetic resonance imaging (fMRI) protocol with multi-slice 2D EPI. It is demonstrated that PEAC can suppress ghost artifacts as effectively as the standard reference-scan based phase correction technique used on a clinical MRI system. We also found that PEAC can achieve dynamic phase correction when motion occurs.