Fast flair imaging of the brain using the fast spin-echo and gradient spin-echo technique

The purpose of this study was to compare the gradient spin-echo (GRASE) to the fast spin-echo (FSE) implementation of fast fluid-attenuated inversion recovery (FLAIR) sequences for brain imaging. Thirty patients with high signal intensity lesions on T₂-weighted images were examined on a 1.5 T MR system. Scan time-minimized thin-section FLAIR-FSE and FLAIR-GRASE sequences were obtained and compared side by side. Image assessment criteria were lesion conspicuity, contrast between different types of normal tissue, image quality, and artifacts. In addition, contrast ratios and contrast-to-noise ratios were determined. Compared to FSE, the GRASE technique allowed a 17% reduction in scan time but conspicuity of small lesions in particular was significantly lower on FLAIR-GRASE images because of higher image noise and increased artifacts. Gray-white differentiation was slightly worse on FLAIR-GRASE. Physiological ferritin deposition appeared slightly darker on FLAIR-GRASE images and susceptibility artifacts were stronger. Fatty tissue was less bright with FLAIR-GRASE. With current standard hardware equipment, the GRASE technique is not an adequate alternative to FSE for the implementation of fast FLAIR sequences in routine clinical MR brain imaging.     

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.     

An energy minimization method for MS lesion segmentation from T1-w and FLAIR images

In this paper, we extend the multiplicative intrinsic component optimization (MICO) algorithm to multichannel MR image segmentation, with focus on segmentation of multiple sclerosis (MS) lesions. The MICO algorithm was originally proposed by Li et al. in Ref. [1] for normal brain tissue segmentation and intensity inhomogeneity correction of a single channel MR image, which exhibits desirable advantages over other methods for MR image segmentation and intensity inhomogeneity correction in terms of segmentation accuracy and robustness. In this paper, we extend the MICO algorithm to multi-channel MR image segmentation and enable the segmentation of MS lesions. We assign different weights for different channels to control the impact of each channel. The weighted channels allow the enhancement of the impact of the FLAIR image on the segmentation of MS lesions by assigning a larger weight to the FLAIR image channel than the other channels. With the inherent mechanism of estimation of the bias field, our method is able to deal with the intensity inhomogeneity in the input multi-channel MR images. In the application of our method, we only use T1-w and FLAIR images as the input two channel MR images. Experimental results show promising result of our method.     

Fast spoiled gradient-recalled MR imaging of thoracic aortic dissection: Preliminary clinical experience at 1.5 T

The purpose of this study was to evaluate fast spoiled gradient-recalled (FSPGR) magnetic resonance (MR) imaging in the diagnosis of thoracic aortic dissection (TAD). Twenty-eight patients with suspected TAD underwent MR imaging with FSPGR and either cine or cardiac-gated spin-echo MR techniques. The average scanning time for the FSPGR images was approximately 1 min. Three readers interpreted the FSPGR images for the presence or absence of TAD. An ROC analysis was done. At a specificity of 90%, the sensitivity ranged from 52% to 90% for the three readers. Pulsatility artifacts and mural thrombus were causes of false-positive and false-negative readings. The areas under the ROC curves (A_z) ranged from 0.85 to 0.97 for the three readers. There was a statistically significant difference in the A_z values for two of the experienced readers (p = .02). The correct type of dissection was determined in only 65% of the true-positive diagnoses. FSPGR has a very limited role in screening and for rapid evaluation of the unstable patient. The results are reader dependent and susceptible to pulsatility artifacts. Determination of the type of dissection is limited. With a suspected thoracic aortic dissection, therefore, additional imaging sequences should be obtained to maximize accuracy.     

Magnetization transfer contrast (MTC) and long repetition time spin-echo MR imaging in multiple sclerosis

Purpose: To study whether application of magnetization transfer contrast (MTC) improves visibility and detection of multiple sclerosis (MS) lesions on long repetition time (TR) conventional spin-echo (CSE) or fast spin-echo (FSE) magnetic resonance (MR) imaging.Material and methods: In 20 patients and 5 controls, MR images were obtained using long repetition time CSE and FSE sequences with and without MTC. Signal-to-noise ratios of normal appearing white matter (NAWM) and selected lesions, and contrast-to-noise ratios between lesions and NAWM, were calculated. Lesions were counted and total lesion volume was measured in a blinded fashion for each sequence.Results: In controls, MT effect in white matter (16.3% vs. 12.2%) was higher for CSE than for FSE (p < 0.01). Application of MTC to either CSE or FSE resulted in a significantly lower decrease in signal intensity of NAWM in patients compared to white matter in controls (p < 0.01). Furthermore, in patients signal intensity of lesions was less decreased than signal intensity of NAWM (p < 0.01). Compared to sequences without MTC, contrast-to-noise ratios were significantly higher on both CSE (10.9%) and FSE (6.3%) when MTC was applied (p < 0.01). Despite better visibility, the number of lesions detected on either sequences did not increase when MTC was applied. For CSE with MTC, we found an almost equal number of lesions and for FSE with MTC, we found even less lesions (p < 0.01). Total lesion volume did not change significantly when MTC was applied.Conclusion: Although contrast between lesions and NAWM improved when magnetization transfer contrast was applied, this did not increase detection of MS lesions on either CSE or FSE MR imaging.     

Usefulness of slice encoding for metal artifact correction (SEMAC) for reducing metallic artifacts in 3-T MRI

Purpose

The purpose of the study was to assess the usefulness of slice encoding for metal artifact correction (SEMAC) in 3.0-T magnetic resonance (MR) in minimizing metallic artifacts in patients with spinal prostheses.

Materials and Methods

Institutional review board approval and informed consent were obtained for this study. Twenty-seven spine MR scans were performed with metal artifact reduction SEMAC between May 2011 and July 2012 in patients with metallic devices. The MR scans were performed on a 3-T MR system (Achieva; Philips Healthcare, Best, the Netherlands) including SEMAC-corrected T2-weighted axial/sagittal images and two-dimensional fast spin echo (FSE) axial/sagittal images. The SEMAC-corrected images were compared to conventional T2-weighted FSE images. Two musculoskeletal radiologists qualitatively analyzed the images in terms of visualization of the pedicle, vertebral body, dural sac, intervertebral disc, intervertebral neural foramina, screws and metallic artifacts. The paired images were rated using a 5-point scale. P values less than .05 were considered to indicate statistically significant differences.

Results

The SEMAC-corrected MR images significantly reduced the metal-related artifacts. The T2-weighted images with SEMAC sequences enabled significantly improved periprosthetic visualizations of the pedicle, vertebral body, dural sac and neural foramina, with the exception of the intervertebral disc (P < .05). In addition, there was significant improvement in prosthesis visualization (P < .05).

Conclusion

MR images with SEMAC can reduce metal-related artifacts, providing improved delineation of the prosthesis and periprosthetic region. However, for the evaluation of the intervertebral disc, the SEMAC-corrected MR images showed no significant benefits.     

Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI

Undersampling k-space is an effective way to decrease acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of magnetic resonance images, which often contain important information for clinical diagnosis. Moreover, k-space data is often contaminated by the noise signals of unknown intensity. To better preserve the edge features while suppressing the aliasing artifacts and noises, we present a new wavelet-based algorithm for undersampled MRI reconstruction. The algorithm solves the image reconstruction as a standard optimization problem including a ?₂ data fidelity term and ?₁ sparsity regularization term. Rather than manually setting the regularization parameter for the ?₁ term, which is directly related to the threshold, an automatic estimated threshold adaptive to noise intensity is introduced in our proposed algorithm. In addition, a prior matrix based on edge correlation in wavelet domain is incorporated into the regularization term. Compared with nonlinear conjugate gradient descent algorithm, iterative shrinkage/thresholding algorithm, fast iterative soft-thresholding algorithm and the iterative thresholding algorithm using exponentially decreasing threshold, the proposed algorithm yields reconstructions with better edge recovery and noise suppression.     

In vivo NMR imaging and T1 measurements of water protons in the human brain

Nuclear magnetic resonance (NMR) proton density images of the human brain have been made by the FONAR method. Spin-lattice relaxation times, T₁, of water hydrogen protons have been determined at random positions within frontal and temporal regions of the human brain. The primary purpose of this ongoing research is to accumulate a large data base of normal T₁ values for water protons in normal human brain tissue. Our experience to data includes 31 measurements on 18 volunteer subjects, and the mean value ± standard deviation is 215 ± 42 msec. In addition, two metastatic lesions of the brain were studied and found to have T₁ values longer than those for normal brain tissue.     

MR findings of focal eosinophilic liver disease using gadoxetic acid

Purpose

The purpose of this study was to describe magnetic resonance (MR) findings of focal eosinophilic liver disease using gadoxetic acid (Gd-EOB-DTPA).

Materials and Methods

Nineteen patients (M:F=14:5; age range, 26–66 years; mean age, 50 years) with 35 focal eosinophilic liver lesions were included after reviewing the medical records of 482 patients who underwent Gd-EOB-DTPA-enhanced MR imaging (MRI) on a 3.0-T unit between April 2008 and June 2009. The diagnosis of focal eosinophilic liver disease was established by means of percutaneous liver biopsy or surgery and consistent clinical findings. Two radiologists retrospectively reviewed MR images with consensus. Margin, shape and distribution of the lesions were analyzed. We also evaluated signal intensity of focal hepatic lesions on T₁- and T₂-weighted images and patterns of enhancement in dynamic contrast study.

Results

The mean diameter of the lesions was 1.7 cm (range, 0.7–6.1 cm). Most of the focal eosinophilic liver lesions [n=31/35 (88.6%)] had poorly defined margins. They were usually isointense or slightly hypointense [n=34/35 (97.2%)] on T₁-weighted images and hyperintense [n=32/35 (91.4%)] on T₂-weighted images. Dynamic study showed enhancement (rim or homogeneous) on the arterial phase [n=21/35 (60%)] and hypointensity on the late venous phase [n=31/35 (88.6%)]. All the lesions were hypointense on the hepatobiliary phase images.

Conclusion

Focal eosinophilic liver lesions tend to be hyperintense on the arterial phase and hypointense on the late venous phase during dynamic study of Gd-EOB-DTPA-enhanced MRI. Although these findings mimic other focal hepatic lesions, poorly defined margins of the lesions and peripheral eosinophilia might help distinguish focal eosinophilic liver disease from other hepatic lesions.     

Metastatic Gastric Leiomyoblastoma: A Case Report

Gastric leiomyoblastoma is a rare entity. In this report, we describe the magnetic resonance (MR) appearance of a recurrent gastric leiomyoblastoma 14 years after initial presentation. This tumor was heterogeneous and moderately low signal intensity on T₁-weighted images and heterogeneous and moderately high signal intensity on T₂-weighted images. The tumor also contained foci of low signal intensity on the post gadolinium images, consistent with areas of necrosis. The mass enhanced mildly and increased in enhancement on the delayed images, consistent with a hypovascular mass. Multiple liver metastases were noted. Magnetic resonance findings were confirmed with surgical specimens.     

Feasibility of fat-saturated T2-weighted magnetic resonance imaging with slice encoding for metal artifact correction (SEMAC) at 3T

Background and Purpose

Fluid-sensitive MR imaging in postoperative evaluation is important, however, metallic artifacts is inevitable. The purpose is to investigate the feasibility of fat-saturated slice encoding for metal artifact correction (SEMAC)-corrected T2-weighted magnetic resonance (MR) at 3T in patients with spinal prostheses.

Methods

Following institutional review board approval, 27 SEMAC-encoded spinal MRs between September 2012 and October 2013 in patients with spinal metallic prostheses were analyzed. The MR images were scanned on a 3T MR system including SEMAC-corrected and uncorrected fast spin echo (FSE) T2-weighted MR images with fat-saturation. Two musculoskeletal radiologists compared the image sets and qualitatively analyzed the images using a five-point scale in terms of artifact reduction around the prosthesis, visualization of the prosthesis and pedicle, and intervertebral neural foramina. Quantitative assessments were performed by calculating the ratio of signal intensity from the fixated vertebra and that from upper level vertebra. For statistical analyses, paired t-test was used.

Results

Fat-saturated SEMAC-corrected T2-weighted MR images enabled significantly improved metallic artifact reduction (P < 0.05). Quantitative evaluation of the signal intensity ratio of screw-fixated vertebra and upper level vertebra showed a significantly lower ratio on fat-saturated SEMAC images (P < 0.05), however, the high signal intensity of signal pile-up could be not completely corrected.

Conclusion

SEMAC correction in fat-suppressed T2-weighted MR images can overcome the signal loss of metallic artifacts and provide improved delineation of the pedicle screw and peri-prosthetic region. Signal pile-up, however, could not be corrected completely, therefore readers should be cautious in the evaluation of marrow around the prosthesis.     

Diffusion-weighted MR imaging for assessing synovitis of wrist and hand in patients with rheumatoid arthritis: A feasibility study

The purpose of this study was to investigate the feasibility of diffusion-weighted imaging (DWI) in detecting synovitis of wrist and hand in patients with rheumatoid arthritis (RA) and evaluate its sensitivity, specificity and accuracy as compared to T₂-weighted imaging (T2WI) with short tau inversion recovery (STIR) with the reference standard contrast-enhanced magnetic resonance imaging (CE-MRI). Twenty-five patients with RA underwent MR examinations including DWI, T2WI with STIR and CE-MRI. MR images were reviewed for the presence and location of synovitis of wrist and hand. The sensitivity, specificity and accuracy of DWI and T2WI with STIR were calculated respectively and then compared. All patients included in this study completed MR examinations and yielded diagnostic image quality of DWI. For individual joint, there was good to excellent inter-observer agreement (k = 0.62–0.83) using DWI images, T2WI with STIR images and CE-MR images, respectively. There was a significance between DWI and T2WI with STIR in analyzing proximal interphalangeal joints II–V, respectively (P < 0.05). The k-values for the detection of synovitis indicated excellent overall inter-observer agreements using DWI images (k = 0.86), T2WI with STIR images (k = 0.85) and CE-MR images (k = 0.91), respectively. Overall, DWI demonstrated a sensitivity, specificity and accuracy of 75.6%, 89.3% and 84.6%, respectively, for detection of synovitis, while 43.0%, 95.7% and 77.6% for T2WI with STIR, respectively. DWI showed positive lesions much better and more than T2WI with STIR. Our results indicate that DWI presents a novel non-invasive approach to contrast-free imaging of synovitis. It may play a role as an addition to standard protocols.     

Exploiting rank deficiency and transform domain sparsity for MR image reconstruction

The reconstruction of magnetic resonance (MR) images from the partial samples of their k-space data using compressed sensing (CS)-based methods has generated a lot of interest in recent years. To reconstruct the MR images, these techniques exploit the sparsity of the image in a transform domain (wavelets, total variation, etc.). In a recent work, it has been shown that it is also possible to reconstruct MR images by exploiting their rank deficiency. In this work, it will be shown that, instead of exploiting the sparsity of the image or rank deficiency alone, better reconstruction results can be achieved by combining transform domain sparsity with rank deficiency.To reconstruct an MR image using its transform domain sparsity and its rank deficiency, this work proposes a combined l₁-norm (of the transform coefficients) and nuclear norm (of the MR image matrix) minimization problem. Since such an optimization problem has not been encountered before, this work proposes and derives a first-order algorithm to solve it.The reconstruction results show that the proposed approach yields significant improvements, in terms of both visual quality as well as the signal to noise ratio, over previous works that reconstruct MR images either by exploiting rank deficiency or by the standard CS-based technique popularly known as the ‘Sparse MRI.’     

MR spectroscopic imaging of glutathione in the white and gray matter at 7 T with an application to multiple sclerosis

Detection of glutathione (GSH) is technically challenging at clinical field strengths of 1.5 or 3 T due to its low concentration in the human brain coupled with the fact that conventional single-echo acquisitions, typically used for magnetic resonance (MR) spectroscopy acquisitions, cannot be used to resolve GSH given its overlap with other resonances. In this study, an MR spectral editing scheme was used to generate an unobstructed detection of GSH at 7 T. This technique was used to obtain normative white (WM) and gray matter (GM) GSH concentrations over a two-dimensional region. Results indicated that GSH was significantly higher (P<.001) in GM relative to WM in normal subjects. This finding is consistent with previous radionuclide experiments and histochemical staining and validates this 7 T MR spectroscopy technique. To our knowledge, this is the first study to report normative differences in WM and GM glutathione concentrations in the human brain. Glutathione is a biomarker for oxidative status and this non-invasive in vivo measurement of GSH was used to explore its sensitivity to oxidative state in multiple sclerosis (MS) patients. There was a significant reduction (P<.001) of GSH between the GM in MS patients and normal controls. No statistically significant GSH differences were found between the WM in controls and MS patients. Reduced GSH was also observed in a MS WM lesion. This preliminary investigation demonstrates the potential of this marker to probe oxidative state in MS.     

Labeling of macrophages using bacterial magnetosomes and their characterization by magnetic resonance imaging

This work investigated macrophages labeled with magnetosomes for the possible detection of inflammations by MR molecular imaging. Pure magnetosomes and macrophages containing magnetosomes were analyzed using a clinical 1.5 T MR-scanner. Relaxivities of magnetosomes and relaxation rates of cells containing magnetosomes were determined. Peritonitis was induced in two mice. T₁, T₂ and T₂* weighted images were acquired following injection of the probes. Pure magnetosomes and labeled cells showed slight effects on T₁, but strong effects on T₂ and T₂* images. Labeled macrophages were located with magnetic resonance imaging (MRI) in the colon area, thus demonstrating the feasibility of the proposed approach.     

Magnetic resonance image enhancement using stochastic resonance in Fourier domain

Objective

In general, low-field MRI scanners such as the 0.5- and 1-T ones produce images that are poor in quality. The motivation of this study was to lessen the noise and enhance the signal such that the image quality is improved. Here, we propose a new approach using stochastic resonance (SR)-based transform in Fourier space for the enhancement of magnetic resonance images of brain lesions, by utilizing an optimized level of Gaussian fluctuation that maximizes signal-to-noise ratio (SNR).

Materials and Methods

We acquired the T1-weighted MR image of the brain in DICOM format. We processed the original MR image using the proposed SR procedure. We then tested our approach on about 60 patients of different age groups with different lesions, such as arteriovenous malformation, benign lesion and malignant tumor, and illustrated the image enhancement by using just-noticeable difference visually as well as by utilizing the relative enhancement factor quantitatively.

Results

Our method can restore the original image from noisy image and optimally enhance the edges or boundaries of the tissues, clarify indistinct structural brain lesions without producing ringing artifacts, as well as delineate the edematous area, active tumor zone, lesion heterogeneity or morphology, and vascular abnormality. The proposed technique improves the enhancement factor better than the conventional techniques like the Wiener- and wavelet-based procedures.

Conclusions

The proposed method can readily enhance the image fusing a unique constructive interaction of noise and signal, and enables improved diagnosis over conventional methods. The approach well illustrates the novel potential of using a small amount of Gaussian noise to improve the image quality.     

Quantitative T2 Imaging of Plant Tissues By Means Of Multi-Echo MRI Microscopy

A method for quantitative T₂ imaging is presented which covers the large range of T₂ values in plants (5 to 2000 ms) simultaneously. The transverse relaxation is characterized by phase-sensitive measurement of many echo images in a multi-echo magnetic resonance imaging sequence. Up to 1000 signal-containing echo images can be measured with an inter-echo time of 2.5 ms at 0.47 T. Separate images of water density and of T₂ are obtained. Results on test samples, on the cherry tomato and on the stem of giant hogweed are presented. The effects of field strength, spatial resolution and echo time on the observed T₂ values is discussed. The combination of a relatively low magnetic field strength, short echo time and medium pixel resolution results in excellent T₂ contrast and in images hardly affected by susceptibility artifacts. The characterization of transverse relaxation by multi-echo image acquisition opens a new route for studies of water balance in plants.     

A multi-scale residual network for accelerated radial MR parameter mapping

A deep learning MR parameter mapping framework which combines accelerated radial data acquisition with a multi-scale residual network (MS-ResNet) for image reconstruction is proposed. The proposed supervised learning strategy uses input image patches from multi-contrast images with radial undersampling artifacts and target image patches from artifact-free multi-contrast images. Subspace filtering is used during pre-processing to denoise input patches. For each anatomy and relaxation parameter, an individual network is trained. in vivo T₁ mapping results are obtained on brain and abdomen datasets and in vivo T₂ mapping results are obtained on brain and knee datasets. Quantitative results for the T₂ mapping of the knee show that MS-ResNet trained using either fully sampled or undersampled data outperforms conventional model-based compressed sensing methods. This is significant because obtaining fully sampled training data is not possible in many applications. in vivo brain and abdomen results for T₁ mapping and in vivo brain results for T₂ mapping demonstrate that MS-ResNet yields contrast-weighted images and parameter maps that are comparable to those achieved by model-based iterative methods while offering two orders of magnitude reduction in reconstruction times. The proposed approach enables recovery of high-quality contrast-weighted images and parameter maps from highly accelerated radial data acquisitions. The rapid image reconstructions enabled by the proposed approach makes it a good candidate for routine clinical use.     

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.     

The effects of changing water content,relaxation times,and tissue contrast on tissue segmentation and measures of cortical anatomy in MR images

Water content is the dominant chemical compound in the brain and it is the primary determinant of tissue contrast in magnetic resonance (MR) images. Water content varies greatly between individuals, and it changes dramatically over time from birth through senescence of the human life span. We hypothesize that the effects that individual- and age-related variations in water content have on contrast of the brain in MR images also have important, systematic effects on in vivo, MRI-based measures of regional brain volumes. We also hypothesize that changes in water content and tissue contrast across time may account for age-related changes in regional volumes, and that differences in water content or tissue contrast across differing neuropsychiatric diagnoses may account for differences in regional volumes across diagnostic groups.