Dual-echo MR Images Research Articles

Resolution enhancement, noise suppression, and joint T2* decay estimation in dual-echo sodium-23 MR imaging using anatomically guided reconstruction.

Sodium MRI is challenging because of the low tissue concentration of the 23 Na nucleus and its extremely fast biexponential transverse relaxation rate. In this article, we present an iterative reconstruction framework using dual-echo 23 Na data and exploiting anatomical prior information (AGR) from high-resolution, low-noise, 1 H MR images. This framework enables the estimation and modeling of the spatially varying signal decay due to transverse relaxation during readout (AGRdm), which leads to images of better resolution and reduced noise resulting in improved quantification of the reconstructed 23 Na images. The proposed framework was evaluated using reconstructions of 30 noise realizations of realistic simulations of dual echo twisted projection imaging (TPI) 23 Na data. Moreover, three dual echo 23 Na TPI brain datasets of healthy controls acquired on a 3T Siemens Prisma system were reconstructed using conventional reconstruction, AGR and AGRdm. Our simulations show that compared to conventional reconstructions, AGR and AGRdm show improved bias-noise characteristics in several regions of the brain. Moreover, AGR and AGRdm images show more anatomical detail and less noise in the reconstructions of the experimental data sets. Compared to AGR and the conventional reconstruction, AGRdm shows higher contrast in the sodium concentration ratio between gray and white matter and between gray matter and the brain stem. AGR and AGRdm generate 23 Na images with high resolution, high levels of anatomical detail, and low levels of noise, potentially enabling high-quality 23 Na MR imaging at 3T.

Optimization of DSC MRI Echo Times for CBV Measurements Using Error Analysis in a Pilot Study of High-Grade Gliomas.

The optimal TE must be calculated to minimize the variance in CBV measurements made with DSC MR imaging. Simulations can be used to determine the influence of the TE on CBV, but they may not adequately recapitulate the in vivo heterogeneity of precontrast T2*, contrast agent kinetics, and the biophysical basis of contrast agent-induced T2* changes. The purpose of this study was to combine quantitative multiecho DSC MRI T2* time curves with error analysis in order to compute the optimal TE for a traditional single-echo acquisition. Eleven subjects with high-grade gliomas were scanned at 3T with a dual-echo DSC MR imaging sequence to quantify contrast agent-induced T2* changes in this retrospective study. Optimized TEs were calculated with propagation of error analysis for high-grade glial tumors, normal-appearing white matter, and arterial input function estimation. The optimal TE is a weighted average of the T2* values that occur as a contrast agent bolus transverses a voxel. The mean optimal TEs were 30.0 ± 7.4 ms for high-grade glial tumors, 36.3 ± 4.6 ms for normal-appearing white matter, and 11.8 ± 1.4 ms for arterial input function estimation (repeated-measures ANOVA, P < .001). Greater heterogeneity was observed in the optimal TE values for high-grade gliomas, and mean values of all 3 ROIs were statistically significant. The optimal TE for the arterial input function estimation is much shorter; this finding implies that quantitative DSC MR imaging acquisitions would benefit from multiecho acquisitions. In the case of a single-echo acquisition, the optimal TE prescribed should be 30-35 ms (without a preload) and 20-30 ms (with a standard full-dose preload).

Using MRI to non-invasively and accurately quantify preoperative hepatic steatosis

BackgroundThe obesity epidemic has significantly increased the incidence and severity of hepatic steatosis in liver surgery patients and liver donors, potentially impacting postoperative liver regeneration and function. Development of a non-invasive means to quantify hepatic steatosis would facilitate selection of candidates for liver resection and transplant donation. MethodsAn IRB-approved protocol prospectively enrolled 28 patients with liver tumors requiring hepatic resection. In all patients, fast dual-echo gradient-echo MR images were acquired using 2-Point Dixon technique in 2D and 3D. The degree of steatosis was quantified by percent fat fraction (%FF) from in- and out-of-phase, and water-only and fat-only images. The technique-specific %FFs were compared to intraoperative and histopathological findings. ResultsFor patients with >30% steatosis by histology, the mean %FF was 22% (SD ± 5.2%) compared to a mean %FF of 5.0% (SD ± 2.1%, p = 0.0001) in patients with <30% steatosis. Using scaled values for the MR-calculated %FF, all patients with >30% pathologic steatosis could be identified preoperatively. ConclusionsQuantitative MRI identified patients with clinically-relevant steatosis with 100% accuracy. These findings could have significant impact on the management of liver resection patients and transplant donors.

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context

The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS.

CT and MR features of xanthogranulomatous cholecystitis: An analysis of consecutive 49 cases

ObjectiveTo study the CT and MR features of xanthogranulomatous cholecystitis (XGC). Materials and methods49 patients had pathologically confirmed XGC. All patients underwent contrast enhanced CT, and 10 patients had additional plain MRI. The CT and MRI results were retrospectively analyzed. ResultsOn CT, all patients had thickening of gallbladder wall, with 87.8% cases showed diffuse thickening. 85.7% cases had intramural hypo-attenuated nodules in the thickened wall. Continuous mucosal line and luminal surface enhancement were noted in 79.6% and 85.7% cases, respectively. Gallbladder stones were seen in 69.4% patients. The coexistence of the above 5 CT features was seen in 40% cases, and 80% cases had the coexistence of ≥4 features. Diffused gallbladder wall thickening in XGC is more likely to have disrupted mucosal line, and XGC with disrupted mucosal line is more likely to be associated with liver infiltration. In 60% patients the inflammatory process extended beyond gallbladder, with the interface between gallbladder and liver and/or the surrounding fat blurred. 40% cases had an early enhancement of liver parenchyma. Infiltration to other surrounding tissues included bowel (n=3), stomach (n=2), and abdominal wall (n=1). On MR images, 7 of 9 intramural nodules in 7 subjects with T1-weighted dual echo MR images showed higher signal intensity on in-phase images than out-of-phase images. ConclusionCoexisting of diffuse gallbladder wall thickening, hypo-attenuated intramural nodules, continuous mucosal line, luminal surface enhancement, and gallbladder stone highly suggest XGC. XGC frequently infiltrate liver and surrounding fat. Chemical-shift MRI helps classifying intramural nodules in the gallbladder wall.

Liver Fat Quantification by Dual-echo MR Imaging Outperforms Traditional Histopathological Analysis

The aim of this study was to evaluate the accuracy of dual-echo (DE) magnetic resonance imaging (MRI) with and without fat and water separation for the quantification of liver fat content (LFC) in vitro and in patients undergoing liver surgery, with comparison to histopathologic analysis. MRI was performed on a 1.5-T scanner using a three-dimensional DE MRI sequence with automated reconstruction of in-phase (IP) and out-of-phase (OP) and fat-signal-only and water-signal-only images. LFC was estimated by fat fractions from IP and OP images (MRI(IP/OP)) and from Dixon-based fat-only and water-only images (MRI(DIxON)). Seven phantoms containing a titrated mixture of liver and fat from 0% to 50% were examined. Forty-three biopsies in 22 patients undergoing liver surgery were prospectively evaluated by a pathologist by traditional determination of the cell-count fraction and by a computer-based algorithm, the latter serving as the reference standard. In vitro, both MRI(IP/OP) and MRI(DIxON) were significantly correlated with titrated LFC (r = 0.993, P < .001), with a smaller measurement bias for MRI(IP/OP) (+2.6%) than for MRI(DIxON) (+4.5%). In vivo, both MRI(IP/OP) and MRI(DIxON) from DE MRI were correlated significantly better with computer-based histologic results (P < .001) and showed significantly smaller measurement bias (4.8% vs 21.1%) compared to histologic cell-count fraction (P < .001). Measurement bias was significantly smaller for MRI(IP/OP) than for MRI(DIxON) (P < .001). DE MRI allows the accurate quantification of LFC in a surgical population, outperforming traditional histopathologic analysis. DE MRI without fat and water separation shows the highest accuracy and smallest measurement bias for the quantification of LFC.

Functional and Structural Connectivity of the Motor Network in Pediatric and Adult-Onset Relapsing-Remitting Multiple Sclerosis

To elucidate the factors associated with the preservation of function in relapsing-remitting (RR) multiple sclerosis (MS) by investigating effective connectivity changes of the sensorimotor network in pediatric RR MS patients in comparison with adult patients with either clinically isolated syndromes (CIS) suggestive of MS or RR MS and in adult healthy control subjects by using functional magnetic resonance imaging (MR) imaging and a dynamic causal model approach and to assess the correlation between effective connectivity changes and structural damage to the corpus callosum and the corticospinal tracts (CSTs). The study was conducted with institutional review board approval. Written informed consent was obtained from each participant. Dual-echo, diffusion-tensor, and functional MR images were acquired from 17 pediatric RR MS patients, 16 adult patients with CIS, 14 adult RR MS patients, and 10 age-matched pediatric healthy control subjects during a simple motor task. Whole-brain, corpus callosum, and CST T2 lesion loads, as well as corpus callosum and CST diffusivity measures were determined. Functional MR imaging data were analyzed by using statistical parametric mapping. Coefficients of effective connectivity of the sensorimotor network were similar in control subjects and pediatric MS patients. In adult patients with CIS and even more evidently in those with RR MS, an increase of intra- and interhemispheric strengths of coefficients of effective connectivity was found (P = .05-.008). The increases in such coefficients were correlated with corpus callosum and CST damage, in terms of T2 lesion load and diffusion-tensor MR imaging quantities (r = -0.34 to 0.40). The preservation of brain adaptive properties might explain the favorable medium-term clinical outcome of pediatric MS patients. The progressive recruitment of cortical networks over time in patients with the adult RR forms of the disease might result in a loss of their plastic reservoir, thus possibly contributing to subsequent disease evolution.

Subminute Fat-Water-Separated Dual-Echo Automated Spine Survey Iterative Scan Technique

We developed and tested an automated sub-minute 3D dual-echo MR imaging technique producing fat-water color-encoded labeled images of the entire spine. Twenty-one subjects were scanned with the 2-point Dixon technique utilizing 2 contiguous 21-22 second breath-hold sagittal acquisitions. Fourteen alternating subject scan sessions were achieved in 58 minutes. In all cases, fat-water separation was homogenous over the 70 cm FOV; in 2 lower stations fat/water assignments were reversed. Rapid automated fat-water decomposition spine screening is a promising technique.

Axial Signs and Magnetic Resonance Imaging Correlates in Parkinson's Disease

Age-related brain changes may contribute to axial features in Parkinson's disease (PD). To determine if ventricular volume and white matter high signal changes (WMC) are related to motor signs in PD and controls independent of age. Patients were rated with the Unified Parkinson's Disease Rating Scale (subscore A: tremor, rigidity, bradykinesia, and facial expression; subscore B: speech and axial impairment). Steps and time taken to walk 9.144 meters were measured. Total ventricular volume (TVV) and intracranial volume (ICV) were measured on T1-weighted MRI using manual tracing software. WMC were rated on axial T2-weighted, dual-echo or FLAIR MR images using a visual scale. TVV (cm3) (PD: 36.48 +/- 15.93; controls: 32.16 +/- 14.20, p = 0.21) and WMC did not differ between groups (PD: 3.7 +/- 4.2; controls: 3.2 +/- 3.1, p = 0.55). Age correlated positively with ICV-corrected TVV and WMC in PD (cTVV: r = 0.48, p = 0.003; WMC: r = 0.42, p = 0.01) and controls (cTVV: r = 0.31, p = 0.04; WMC: r = 0.44, p = 0.003). Subscore B (r = 0.42, p = 0.01) but not subscore A (r = 0.25, p = 0.14) correlated with cTVV in PD. Steps and walking time correlated with cTVV and WMC in PD; cadence correlated with cTVV and steps with WMC in controls. Age-adjustment eliminated correlations. Subscore B, but not subscore A correlated positively with ventricular volume in PD, though this association was accounted for by age. Age-related brain change super-imposed on PD may contribute to axial features.

An fMRI study of the motor system in patients with neuropsychiatric systemic lupus erythematosus

Functional cortical changes have been demonstrated in patients with several neurological conditions, including stroke, tumors and MS. The correlation found between the extent of fMRI activations and the extent and severity of brain structural damage suggests an adaptive role of these functional changes. In this study, we assess, using fMRI, the brain pattern of movement-associated cortical activations in neuropsychiatric systemic lupus erythematosus (NPSLE) patients and investigate whether the extent of cortical reorganization is associated with the extent of brain pathology, measured on dual-echo and diffusion tensor (DT) MR images. From 14 right-handed NPSLE patients and 14 matched controls, we obtained: (a) fMRI during the performance of repetitive flexion–extension of the last four fingers of the right hand; (b) dual-echo and (c) pulsed-gradient spin-echo echo-planar sequence to calculate DT MRI maps of the normal-appearing white (NAWM) and gray (NAGM) matter. Brain T2-visible abnormalities were detected in 11 NPSLE patients. Compared with controls, NPSLE patients had significantly higher NAWM fractional anisotropy histogram peak height ( P = 0.005), and more significant activations of the contralateral primary sensorimotor cortex, putamen and dentate nucleus. They also had more significant activations of several regions located in the frontal and parietal lobes as well as of MT/V5 and the middle occipital gyrus, bilaterally. Strong correlations (r values ranging from 0.79 to 0.87) were found between relative activations of sensorimotor areas and the extent and severity of brain damage. Movement-associated functional cortical changes do occur in patients with NPSLE and might contribute to the maintenance of their normal functional capacities.

Analysis of dual-echo MR images in first-episode psychosis: The SMaRT method

Analysis of dual-echo MR images in first-episode psychosis: The SMaRT method

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.

Utility of Dual Echo T2-Weighted Turbo Spin Echo MR Imaging for Differentiation of Solid, Malignant HepaticLesions from Nonsolid, Benign Hepatic Lesions

Purpose : To evaluate the additive value of multiphasic contrast-enhanced dynamic MR imaging as a supple-mentto dual-echo T2-weighted TSE MR imaging for the differentiation of solid, malignant hepatic lesions from nonsolid,benign hepatic lesions. Materials and Methods : Two radiologists retrospectively reviewed dual-echo T2-weightedTSE MR images and gadolinium-enhanced MR images in 51 patients with hepatic lesions (28 malignant, 69 benign). Forthe dif-ferentiation of malignant from benign lesions, as seen on dual-echo T2-weighted TSE MR images, weevaluated sensitivity, specificity, and accuracy, and compared with the results with those for dual echoT2-weighted MR images plus multiphasic contrast-enhanced dynamic MR images. In addition, Az values for dual echoT2-weighted MR images were compared with those for dual echo T2-weighted MR images plus multiphasiccon-trast-enhanced dynamic MR images. Results : For the differentiation of malignant from benign hepatic lesions,as seen on dual-echo T2-weighted TSE images, sensitivity, specificity, and accuracy were 80.0 %, 97.5 %, and 93.9%, respectively, for lesions less than 3 cm in diameter, and 92.3 %, 95.0 %, and 93.5 %, respectively, for thosethat were 3 cm or larger. The results for dual-echo T2-weighted MR imaging plus multiphasic contrast-enhanceddynamic MR imaging were 86.7%, 100.0%, and 97.3%, respectively, for lesions less than 3 cm, and 92.3%, 100.0 %,and 95.7 %, re-spectively for those that were 3 cm or larger. There were no significant differences insensitivity, specificity, or accuracy between the results obtained using dual-echo T2-weighted MR imaging andthose obtained with d-ual- echo T2-weighted MR imaging plus multiphasic contrast-enhanced dynamic MR imaging. Norwere there statistically significant differences in Az values between the two groups. Conclusions : For thedifferentiation of solid, malignant hepatic lesions from nonsolid, benign hepatic lesions, there is no differencein accuracy between dual-echo T2-weighted TSE MR imaging and the additional use of multiphasic contrast-enhancedMR imaging. Dual-echo T2-weighted TSE MR imaging may, therefore, be use-ful for the differentiation of solid,malignant hepatic lesions from nonsolid, benign hepatic lesions without the use of multiphasic contrast-enhancedMR imaging.

A dual approach for minimizing false lesion classifications on magnetic resonance images.

Segmentation methods based on dual-echo MR images are generally prone to significant false lesion classifications. We have minimized these false classifications by (1) improving the lesion-to-tissue contrast on MR images by developing a fast spin-echo sequence that incorporates both cerebrospinal fluid signal attenuation and magnetization transfer contrast and (2) including information from MR flow images. Studies on patients with multiple sclerosis indicate that this dual approach to tissue segmentation reduces the volume of false lesion classifications by an average of 87%.

Some aspects of Dempster-Shafer evidence theory for classification of multi-modality medical images taking partial volume effect into account

This paper points out some key features of Dempster-Shafer evidence theory for data fusion in medical imaging. Examples are provided to show its ability to take into account a large variety of situations, which actually often occur and are not always well managed by classical approaches nor by previous applications of Dempster-Shafer theory in medical imaging. The modelization of both uncertainty and imprecision, the introduction of possible partial or global ignorance, the computation of conflict between images, the possible introduction of a priori information are all powerful aspects of this theory, which deserve to be more exploited in medical image processing. They may be of great influence on the final decision. They are illustrated on a simple example for classifying brain tissues in pathological dual echo MR images. In particular, partial volume effect can be properly managed by this approach.

Automatic detection of intradural spaces in MR images.

An algorithm is presented for the automatic detection of intradural spaces in MR images of the human head. The primary motivation behind the present work has been to serve as a preprocessing step in automatic segmentation of brain tissue and CSF. A second objective was to use the algorithm in a fully automatic PET-MR registration algorithm. The method is primarily designed for, and requires, dual echo (T1- and T2-weighted) MR images with transaxial orientations. The algorithm consists of three main stages. First, the head contour is detected using a series of low-level image-processing techniques. In the second stage, the pixels inside the head contour are clustered into a number of classes using the K-means algorithm. Finally, the extradural connected components are eliminated based on a number of heuristics. Test results are presented for 10 MR image sets consisting of 197 slices. As a quantitative measure of accuracy, manual segmentations were performed by radiologists on a number of slices and compared with the results obtained automatically. Visual inspection and quantitative validation of the results indicate that the algorithm accurately detects the intradural spaces in MR images. This is an important step in fully automatic segmentation and registration of MR images.

Dual-echo MRI segmentation using vector decomposition and probability techniques: a two-tissue model.

We combined a vector decomposition technique with Gaussian probability thresholding in feature space to segment normal brain tissues, tumors, or other abnormalities on dual-echo MR images. The vector decomposition technique assigns to each voxel a fractional volume for each of two tissues. A probability threshold, based on an assumed Gaussian probability density function describing random noise, isolates a region in feature space for fractional volume calculation that minimizes contamination from other tissues. The calculated fractional volumes are unbiased estimates of the true fractional volumes. The contrast-to-noise ratio (CNR) between tissues on the segmented images is the same as the Euclidean norm of CNRs in the original images. The method is capable of segmenting more than two tissues from a set of dual-echo images by sequentially analyzing different pairs of tissues. The model is analyzed mathematically and in experiments with a phantom. Two clinical examples are presented.