Comparison of magnetic resonance imaging of inhaled SF6 with respiratory gas analysis

Magnetic resonance imaging of inhaled fluorinated inert gases ((19)F-MRI) such as sulfur hexafluoride (SF(6)) allows for analysis of ventilated air spaces. In this study, the possibility of using this technique to image lung function was assessed. For this, (19)F-MRI of inhaled SF(6) was compared with respiratory gas analysis, which is a global but reliable measure of alveolar gas fraction. Five anesthetized pigs underwent multiple-breath wash-in procedures with a gas mixture of 70% SF(6) and 30% oxygen. Two-dimensional (19)F-MRI and end-expiratory gas fraction analysis were performed after 4 to 24 inhaled breaths. Signal intensity of (19)F-MRI and end-expiratory SF(6) fraction were evaluated with respect to linear correlation and reproducibility. Time constants were estimated by both MRI and respiratory gas analysis data and compared for agreement. A good linear correlation between signal intensity and end-expiratory gas fraction was found (correlation coefficient 0.99+/-0.01). The data were reproducible (standard error of signal intensity 8% vs. that of gas fraction 5%) and the comparison of time constants yielded a sufficient agreement. According to the good linear correlation and the acceptable reproducibility, we suggest the (19)F-MRI to be a valuable tool for quantification of intrapulmonary SF(6) and hence lung function.     

Pelvic phased array coil: image quality assessment for spin-echo MR imaging.

The NMR phased array coil (PA) provides improved signal-to-noise ratio (SNR) over that available with the body coil. We evaluated image quality obtained with a pelvic PA compared to that obtained with the body coil for spin-echo imaging. Thirty-three women undergoing clinical pelvic MRI were imaged with the body coil followed by imaging with the PA with the same field-of-view (FOV) in 11 patients, and with a small FOV in 23 patients. Image quality was assessed independently by two radiologists. In individual cases there was significant improvement in image quality with the PA, however the expected marked improvement in image quality was not consistently found. Two factors which may limit image quality are increased motion artifact and nonuniformity of signal with distance from the coils. Significant improvements in image quality may occur with improved techniques to decrease motion artifact.     

Regularization of bending and crossing white matter fibers in MRI Q-ball fields

In diffusion magnetic resonance imaging with high-angular-resolution diffusion imaging, a set of techniques has become available that allows better acquisition and representation of multidirectional diffusion profiles, e.g., in voxels with crossing, branching and kissing fibers. The poor spatial resolution and low signal-to-noise ratio of the data, particularly when acquired under clinical conditions, prevent tractography algorithms from reliably reconstructing complex white matter structures. With cone-beam regularization, an intervoxel smoothing approach has been described, which, in this article, is refined and adapted to fibers with subvoxel bending. By introducing the concept of asymmetric orientation distribution functions (aODFs), we are able to sharpen diffusion profiles of bending fibers and estimate subvoxel curvature. We also propose a deterministic fiber-tracking algorithm that exploits the enhanced resolution of aODFs. The approach is evaluated quantitatively and compared with state-of-the-art noise-suppression techniques in a study with a biological diffusion phantom. Moreover, we present results from an in vivo study in which we demonstrate the method's ability to optimize tractography of bending fiber pathways of optic radiation.     

Comparative study of fast MR imaging: quantitative analysis on image quality and efficiency among various time frames and contrast behaviors

The purpose of this study is to quantitatively compare the image quality and efficiency provided by widely available fast MR imaging pulse sequences. A composite phantom with various T1 and T2 values and subjected to periodic motion was imaged at 1.5 T. The fast MRI sequences evaluated included fast spin-echo (FSE), single shot fast spin-echo (SSFSE), echo-planar imaging (EPI), multi-slice gradient recalled (MPGR), fast MPGR (FMPGR), and fast multi-slice spoiled gradient echo (FMPSPGR). T1-weighted (T1WI), T2-weighted (T2WI), proton-density-weighted (PDWI), and T2*-weighted (T2*WI) images were evaluated in breath-hold and non-breath-hold time frames. Analysis included measurement of image signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), nonuniformity, ghosting ratio, SNR per unit time and CNR per unit time. Among fast T2WI sequences, FSE with breath-hold time frame resulted in the highest image quality and in superior SNR and CNR efficiency by a factor of 5 or 6 as compared with conventional spin echo sequence. Among fast T1WI sequences, FMPGR and FMPSPGR both with non-breath-hold time frame produced the highest image quality and SNR and CNR efficiency by a factor of greater than 5 as compared with conventional spin echo. Among fast PDWI and T2*WI sequences, FSE produced the highest SNR and CNR, and was maximally efficient with a factors of greater than 6 as compared with conventional spin echo.     

Design of an interventional magnetic resonance imaging coil for cerebral surgery

In clinical magnetic resonance imaging(MRI),the design of the radiofrequency(RF) coil is very important.For certain applications,the appropriate coil can produce an improved image quality.However,it is difficult to achieve a uniform B1 field and a high signal-to-noise ratio(SNR) simultaneously.In this article,we design an interventional transmitter-and-receiver RF coil for cerebral surgery.This coil adopts a disassembly structure that can be assembled and disassembled repeatedly on the cerebral surgery gantry to reduce the amount of interference from the MRI during surgery.The simulation results and the imaging experiments demonstrate that this coil can produce a uniform RF field,a high SNR,and a large imaging range to meet the requirements of the cerebral surgery.     

Fast frequency selective MR imaging

With the proposed fast frequency selective MR imaging (FFSMRI) method, we focused on the elimination of all off-resonance components from the image of the observed object. To maintain imaging speed and simultaneously achieve good frequency selectivity, MRI was divided into two steps: signal acquisition and postprocessing. After the preliminary phase in which we determine imaging parameters, MRI takes place; the signal from the same object is successively acquired M times. As a result, we obtain M partial signals in k-space, from which we calculate the image of the observed object in postprocessing phase, after signal acquisition has been completed. With proper selection of parameters, it is possible to exclude from the image a majority of off-resonance components present in the observed object. However, we can decide to keep only a chosen off-resonance component in the image and eliminate all other components, including the on-resonance component and thus producing a different image from the same acquisition. The experiments with Fe(OH)(3) and oil showed that signal-to-noise ratio (SNR) can be improved by about a factor of four. The proposed FFSMRI method is suitable for frequency selective MR imaging and quantitative measurements in dynamic MRI where exclusion of off-resonance components can improve the reliability of measurement.     

A modified fuzzy clustering algorithm for operator independent brain tissue classification of dual echo MR images.

Methods for brain tissue classification or segmentation of structural magnetic resonance imaging (MRI) data should ideally be independent of human operators for reasons of reliability and tractability. An algorithm is described for fully automated segmentation of dual echo, fast spin-echo MRI data. The method is used to assign fuzzy-membership values for each of four tissue classes (gray matter, white matter, cerebrospinal fluid and dura) to each voxel based on partition of a two dimensional feature space. Fuzzy clustering is modified for this application in two ways. First, a two component normal mixture model is initially fitted to the thresholded feature space to identify exemplary gray and white matter voxels. These exemplary data protect subsequently estimated cluster means against the tendency of unmodified fuzzy clustering to equalize the number of voxels in each class. Second, fuzzy clustering is implemented in a moving window scheme that accommodates reduced image contrast at the axial extremes of the transmitting/receiving coil. MRI data acquired from 5 normal volunteers were used to identify stable values for three arbitrary parameters of the algorithm: feature space threshold, relative weight of exemplary gray and white matter voxels, and moving window size. The modified algorithm incorporating these parameter values was then used to classify data from simulated images of the brain, validating the use of fuzzy-membership values as estimates of partial volume. Gray:white matter ratios were estimated from 20 twenty normal volunteers (mean age 32.8 years). Processing time for each three-dimensional image was approximately 30 min on a 170 MHz workstation. Mean cerebral gray and white matter volumes estimated from these automatically segmented images were very similar to comparable results previously obtained by operator dependent methods, but without their inherent unreliability.     

超极化气体肺部磁共振成像

磁共振成像(MRI)技术具有非侵入、无放射性的特点,在临床疾病诊断中具有独特的优势,但是肺部空腔的特殊结构使传统质子MRI无法对其直接成像.自旋交换光抽运(SEOP)方法可以使惰性气体原子的极化度增强4个量级以上,从而使肺部的气体MRI成为可能.该文介绍了超极化惰性气体肺部MRI的最新研究进展,包括超极化气体磁共振相关参数的测量方法、肺部通气结构成像、肺部气体交换功能成像,同时比较了常用于肺部MRI气体的优点和缺点.     

旋转不变的非局域均值算法在磁共振图像去噪中的应用

磁共振成像（MRI）实验时常采用多次扫描累加平均提高图像信噪比（SNR）,但当扫描过程中运动引起图像变形时,简单地累加平均就无法奏效.为此,本研究组曾提出一种匹配加权平均方法（MWA）提高图像的信噪比.在此基础上,该文提出一种旋转不变的非局域均值算法（RINLM）,即选取圆形邻域区域并将其划分为一系列以中心像素为圆心的等面积圆环,再计算模式的相似性.RINLM算法可以更好地利用图像中旋转的冗余信息、找到更多的相似结构,提高算法的去噪性能.我们把该方法应用于低信噪比图像序列的平均和去噪中,可以更好地处理旋转的局部运动.与非局域均值算法（NLM）相比,RINLM算法可以进一步提高图像的信噪比;与MWA方法相比,其与RINLM算法的结合可以进一步提高磁共振图像序列信噪比,更好的保持图像边缘信息.     

Correcting slice selectivity in hard pulse sequences

Many MRI sequences use non-selective hard pulse excitation in the presence of imaging gradients. In this work, we investigate to which extent the sinc-shaped frequency excitation profiles of the pulse can be used for imaging without the generation of artefacts. A correction algorithm is proposed that eliminates the influence of the excitation profile. Phantom as well as in vivo measurements prove that enhanced image quality can be obtained as long as the first minimum of the excitation profile lies outside the imaged object.     

Automatic 3D tracking of cardiac material markers using slice-following and harmonic-phase MRI

A method to track a grid of cardiac material points in three dimensions using slice-following (SF) tagged magnetic resonance imaging (MRI) and harmonic-phase MRI is presented. A three-dimensional grid of material points on the lines of intersections of short-axis (SA) and long-axis (LA) planes is automatically tracked by combining two-dimensional pathlines that are computed on both SA and LA image planes. This process yields the true three-dimensional motion of points originating on the image plane intersections. Experimental data from normal volunteers, each obtained in four short breath-holds using the SF harmonic phase MRI pulse sequence, is presented. A validation of two-dimensional in-plane tracks using this pulse sequence on a moving phantom is also presented.     

Design and Demonstration of Four-Channel Received Coil Arrays for Vertical-Field MRI

The layout of radio-frequency received coils is related to signal-to-noise ratio (SNR) in magnetic resonance imaging (MRI). In this paper, different structures of four-channel received coil arrays for vertical-field MRI are constructed and optimized by establishing the relationship between coil geometry and SNR to achieve a high SNR and a uniform SNR distribution in the region of interest (ROI). Then, the SNR distributions of three optimized configurations, including rectangular loops, non-definite shape surface coils, and solenoid loops as the main unit, are simulated and compared. The four-channel coil of solenoid loops as the main unit has been found to have the best performance with the highest mean SNR in the ROI when imaging without acceleration. In addition, g-factor and 2D SENSE SNR in yoz-plane are simply analyzed, which show a sharp decrease in SNR for all the coils. Finally, all the coils are manufactured and operated at a 0.5 T permanent magnet MRI system with phantom and joint imaging experiments. Using pixel-by-pixel manner to evaluate SNR map, the experimental results are consistent with the simulation results, while parallel imaging experiment results show that the major consideration in low field MRI is the improvement of SNR value and uniformity rather than that of the imaging speed. As different constructions of four-channel received coils are investigated, we have found the most effective configuration with high and uniform SNR for vertical-field MRI.     

In vivo SNR in DENSE MRI; temporal and regional effects of field strength, receiver coil sensitivity and flip angle strategies

Aim

The influences on the signal-to-noise ratio (SNR) of Displacement ENcoding with Stimulated Echoes (DENSE) MRI of field strength, receiver coil sensitivity and choice of flip angle strategy have been previously investigated individually. In this study, all of these parameters have been investigated in the same setting, and a mutual comparison of their impact on SNR is presented.

Materials and methods

Ten healthy volunteers were imaged in a 1.5 T and a 3 T MRI system, using standard five- or six-channel cardiac coils as well as 32-channel coils, with four different excitation patterns. Variation of spatial coil sensitivity was assessed by regional SNR analysis.

Results

SNR ranging from 2.8 to 30.5 was found depending on the combination of excitation patterns, coil sensitivity and field strength. The SNR at 3 T was 53±26% higher than at 1.5 T (P<.001), whereas spatial differences of 59±26% were found in the ventricle (P<.001). Thirty-two-channel coils provided 52±29% higher SNR compared to standard five- or six-channel coils (P<.001). A fixed flip angle strategy provided an excess of 50% higher SNR in half of the imaged cardiac cycle compared to a sweeping flip angle strategy, and a single-phase acquisition provided a sixfold increase of SNR compared to a cine acquisition.

Conclusion

The effect of field strength and receiver coil sensitivity influences the SNR with the same order of magnitude, whereas flip angle strategy can have a larger effect on SNR. Thus, careful choice of imaging hardware in combination with adaptation of the acquisition protocol is crucial in order to realize sufficient SNR in DENSE MRI.     

Muscle and fat quantification in MRI gradient echo images using a partial volume detection method. Application to the characterization of pig belly tissue

Complete dissection is the current reference method to quantify muscle and fat tissue on pig carcasses. Magnetic resonance imaging (MRI) is an appropriate nondestructive alternative method that can provide reliable and quantitative information on pig carcass composition without losing the spatial information. We have developed a method to quantify the amount of fat tissue and muscle in gradient echo MR images. This method is based on the method proposed by Shattuck et al. [12]. It provides segmentation of pure tissue and partial volume voxels, which allows separation of muscle and fat tissue including the fine insertions of intermuscular fat. Partial volume voxel signal is expected to be proportional to the signals of pure tissue constituting them or at least to vary monotonously with the proportion of each tissue. However, it is not always the case with gradient echo sequence due to the chemical shift effect. We studied this effect on a fat tissue/muscle interface model with variable proportion of water in the fat tissue and variable TE. We found that at TE=8 ms, for a 0.2-T MRI system, the requirement of Shattuck's method were filled thanks to the presence of water in fat tissue. Moreover, we extended the segmentation method with a simple correction scheme to compute more accurately the proportions of each tissue in partial volume voxels. We used this method to evaluate the fat tissue and muscle on 24 pig bellies using a gradient echo sequence (TR 700 ms, TE 8 ms, slice thickness 8 mm, number of averages 8, flip angle 90 degrees , FOV 512 mm, matrix 512*512, Rect. FOV 4/8, 19 slices, space between slices 2 mm). The image analysis results were compared with dissection results giving a prediction error of the muscle content (mean=2.7 kg) of 88.9 g and of the fat content (mean=2.7 kg) of 115.8 g without correction of the chemical shift effect in the computation of partial volume fat content. The correction scheme improved these results to, respectively, 81.5 and 107.1 g.     

Adaptive data acquisition in MRI

We propose an adaptive data acquisition technique that depends on the object to be imaged in magnetic resonance (MR) imaging. In this paper, we employed a matching pursuit (MP) algorithm to achieve the adaptive data acquisition. Since the matching pursuit is a greedy algorithm to find RF and gradient waveforms which are the best match for an object-signal, the signal can be decomposed with a few iterations and thereby lead reduction of imaging time in MR. To adopt the matching pursuit algorithm to the adaptive data acquisition in MRI, we have designed a dictionary which contains a windowed Fourier basis set. Because the basis set is localized spatially, the image signal could be divided into segmented signals so that matching pursuit with the segmented signals could lead to effective and object-dependent data acquisition. To verify the proposed technique, computer simulations and experiments are performed with a 1.0 T whole body MRI system.     

Linear-fitting-based similarity coefficient map for tissue dissimilarity analysis in T_2~*-w magnetic resonance imaging

Similarity coefficient mapping(SCM) aims to improve the morphological evaluation of T*2weighted magnetic resonance imaging(T*2-w MRI). However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM? The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T*2-w MRI. Generated maps were investigated from signal-to-noise ratio(SNR) and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.     

A statistical fMRI model for differential T2* contrast incorporating T1 and T2* of gray matter

Relaxation parameter estimation and brain activation detection are two main areas of study in magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI). Relaxation parameters can be used to distinguish voxels containing different types of tissue whereas activation determines voxels that are associated with neuronal activity. In fMRI, the standard practice has been to discard the first scans to avoid magnetic saturation effects. However, these first images have important information on the MR relaxivities for the type of tissue contained in voxels, which could provide pathological tissue discrimination. It is also well-known that the voxels located in gray matter (GM) contain neurons that are to be active while the subject is performing a task. As such, GM MR relaxivities can be incorporated into a statistical model in order to better detect brain activation. Moreover, although the MR magnetization physically depends on tissue and imaging parameters in a nonlinear fashion, a linear model is what is conventionally used in fMRI activation studies. In this study, we develop a statistical fMRI model for Differential T₂^? ConTrast Incorporating T₁ and T₂^? of GM, so-called DeTeCT-ING Model, that considers the physical magnetization equation to model MR magnetization; uses complex-valued time courses to estimate T₁ and T₂^? for each voxel; then incorporates gray matter MR relaxivities into the statistical model in order to better detect brain activation, all from a single pulse sequence by utilizing the first scans.     

The challenges in creating reference maps for verification of ultrasound images

In the development of new medical imaging techniques, references to which the images can be compared are necessary if one wants to assess how precise the images are. This is especially interesting in diagnostic ultrasound where a number of artefacts influence the image. The reference can either be derived from a phantom with precisely known properties and geometry, from the specifications of a computer phantom (simulated images) or from evaluation of biological tissue. The third approach can be conducted with other medical imaging modalities (CT, MRI, etc.) or "destructive testing" involving histology. In this paper, aspects of the latter method is considered in detail. Formalin fixed tissue is moulded into an agar block containing at set of fiducial markers. The block is scanned with ultrasound. Both tissue and fiducial markers are imaged. The block is afterwards sliced at the location of the fiducial markers. The slices are then photographed and analyzed histologically. From this data, reference maps with similar geometry as the ultrasound images can be created. Ideally, for each pixel in the ultrasound image, these reference maps indicate tissue type, such as collagen poor tissue, collagen rich tissue, etc. Many of the sources of error as well as the challenges with such a method are discussed.