Description: Publication date: January 2015 Source: Magnetic Resonance Imaging, Volume 33, Issue 1 Author(s): Xiaoxu Wang , Ting Chen , Shaoting Zhang , Joël Schaerer , Zhen Qian , Suejung Huh , Dimitris Metaxas , Leon Axel Tagged magnetic resonance imaging (TMRI) provides a direct and noninvasive way to visualize the in-wall deformation of the myocardium. Due to the through-plane motion, the tracking of 3D trajectories of the material points and the computation of 3D strain field call for the necessity of building 3D cardiac deformable models. The intersections of three stacks of orthogonal tagging planes are material points in the myocardium. With these intersections as control points, 3D motion can be reconstructed with a novel meshless deformable model (MDM). Volumetric MDMs describe an object as point cloud inside the object boundary and the coordinate of each point can be written in parametric functions. A generic heart mesh is registered on the TMRI with polar decomposition. A 3D MDM is generated and deformed with MR image tagging lines. Volumetric MDMs are deformed by calculating the dynamics function and minimizing the local Laplacian coordinates. The similarity transformation of each point is computed by assuming its neighboring points are making the same transformation. The deformation is computed iteratively until the control points match the target positions in the consecutive image frame. The 3D strain field is computed from the 3D displacement field with moving least squares. We demonstrate that MDMs outperformed the finite element method and the spline method with a numerical phantom. Meshless deformable models can track the trajectory of any material point in the myocardium and compute the 3D strain field of any particular area. The experimental results on in vivo healthy and patient heart MRI show that the MDM can fully recover the myocardium motion in three dimensions.

Description: Publication date: Available online 5 December 2014 Source: Magnetic Resonance Imaging Author(s): Malte Hoffmann , T. Adrian Carpenter , Guy B. Williams , Stephen J. Sawiak Functional magnetic resonance imaging (fMRI) can be seriously impaired by patient motion. The purpose of this study was to characterise the typical motion in a clinical population of patients in disorders of consciousness and compare the performance of retrospective correction with rigid-body realignment as implemented in widely used software packages. 63 subjects were scanned with an fMRI visual checkerboard paradigm using a 3 T scanner. Time series were corrected for motion and the resulting transformations were used to calculate a motion score. SPM, FSL, AFNI and AIR were evaluated by comparing the motion obtained by re-running the tool on the corrected data. A publicly available sample fMRI dataset was modified with the motion detected in each patient with each tool. The performance of each tool was measured by comparing the number of supra-threshold voxels after standard fMRI analysis, both in the sample dataset and in simulated fMRI data. We assessed the effect of user-changeable parameters on motion correction in SPM. We found the equivalent motion in the patient population to be 1.4 mm on average. There was no significant difference in performance between SPM, FSL and AFNI. AIR was considerably worse, and took more time to run. We found that in SPM the quality factor and interpolation method have no effect on the cluster size, while higher separation and smoothing reduce it. We showed that the main packages SPM, FSL and AFNI are equally suitable for retrospective motion correction of fMRI time series. We show that typically only 80% of activated voxels are recovered by retrospective motion correction.

Description: Publication date: Available online 6 December 2014 Source: Magnetic Resonance Imaging Author(s): Yu-Chung N. Cheng , Ching-Yi Hsieh , Ronald Tackett , Paul Kokeny , Rajesh Kumar Regmi , Gavin Lawes Purpose The purpose of this work is to develop a method for accurately quantifying effective magnetic moments of spherical-like small objects from magnetic resonance imaging (MRI). A standard 3D gradient echo sequence with only one echo time is intended for our approach to measure the effective magnetic moment of a given object of interest. Methods Our method sums over complex MR signals around the object and equates those sums to equations derived from the magnetostatic theory. With those equations, our method is able to determine the center of the object with subpixel precision. By rewriting those equations, the effective magnetic moment of the object becomes the only unknown to be solved. Each quantified effective magnetic moment has an uncertainty that is derived from the error propagation method. If the volume of the object can be measured from spin echo images, the susceptibility difference between the object and its surrounding can be further quantified from the effective magnetic moment. Numerical simulations, a variety of glass beads in phantom studies with different MR imaging parameters from a 1.5 T machine, and measurements from a SQUID (superconducting quantum interference device) based magnetometer have been conducted to test the robustness of our method. Results Quantified effective magnetic moments and susceptibility differences from different imaging parameters and methods all agree with each other within two standard deviations of estimated uncertainties. Conclusion An MRI method is developed to accurately quantify the effective magnetic moment of a given small object of interest. Most results are accurate within 10% of true values and roughly half of the total results are accurate within 5% of true values using very reasonable imaging parameters. Our method is minimally affected by the partial volume, dephasing, and phase aliasing effects. Our next goal is to apply this method to in vivo studies.

Description: Publication date: Available online 5 December 2014 Source: Magnetic Resonance Imaging Author(s): Matteo Figini , Ileana Zucca , Domenico Aquino , Paolo Pennacchio , Simone Nava , Alessandro Di Marzio , Maria Giulia Preti , Guseppe Baselli , Roberto Spreafico , Carolina Frassoni Diffusion Tensor Imaging (DTI) is a Magnetic Resonance modality that permits to characterize the orientation and integrity of the white matter (WM). DTI-based tractography techniques, allowing the virtual reconstruction of WM tract pathways, have found wide application in preclinical neurological research. Recently, anatomically detailed rat brain atlases including DTI data were constructed from ex vivo DTI images, but tractographic atlases of normal rats in vivo are still lacking. We propose here a probabilistic tractographic atlas of the main WM tracts in the healthy rat brain based on in vivo DTI acquisition. Our study was carried out on 10 adult female Sprague–Dawley rats using a 7 T preclinical scanner. The MRI protocol permitted a reliable reconstruction of the main rat brain bundles: corpus callosum, cingulum, external capsule, internal capsule, anterior commissure, optic tract. The reconstructed fibers were compared with histological data, proving the viability of in vivo DTI tractography in the rat brain with the proposed acquisition and processing protocol. All the data were registered to a rat brain template in the coordinate system of the commonly used atlas by Paxinos and Watson; then the individual tracts were binarized and averaged, obtaining a probabilistic atlas in Paxinos-Watson space of the main rat brain white matter bundles. With respect to the recent high-resolution MRI atlases, the resulting tractographic atlas, available online, provides complementary information about the average anatomical position of the considered WM tracts and their variability between normal animals. Furthermore, reference values for the main DTI-derived parameters, Mean Diffusivity and Fractional Anisotropy, were provided. Both these results can be used as references in preclinical studies on pathological rat models involving potential alterations of WM.

Description: Publication date: Available online 5 December 2014 Source: Magnetic Resonance Imaging Author(s): Khader M. Hasan , John A. Lincoln , Flavia M. Nelson , Jerry S. Wolinsky , Ponnada A. Narayana In this retrospective study we tested the hypothesis that the net effect of impaired electrical conduction and therefore increased heat dissipation in multiple sclerosis (MS) results in elevated lateral ventricular (LV) cerebrospinal fluid (CSF) diffusivity as a measure of brain temperature estimated in vivo using diffusion tensor imaging (DTI). We used validated DTI-based segmentation methods to obtain normalized LV-CSF volume and its corresponding CSF diffusivity in 108 MS patients and 103 healthy controls in the age range of 21-63 years. The LV CSF diffusivity was ~ 2% higher in MS compared to controls that corresponds to a temperature rise of ~ 1 °C that could not be explained by changes in the CSF viscosity due to altered CSF protein content in MS. The LV diffusivity decreased with age in healthy controls (r = -0.29; p = 0.003), but not in MS (r = 0.15; p = 0.11), possibly related to MS pathology. Age-adjusted LV diffusivity increased with lesion load (r = 0.518; p = 1x10 - 8 ). Our data suggest that the total brain lesion load is the primary contributor to the increase in LV CSF diffusivity in MS. These findings suggest that LV diffusivity is a potential in vivo biomarker of the mismatch between heat generation and dissipation in MS. We also discuss limitations and possible confounders.

Description: Publication date: Available online 12 December 2014 Source: Magnetic Resonance Imaging Author(s): Urša Mikac , Ana Sepe , Igor Serša Magnetic resonance microscopy (MRM) was used to study water distribution and mobility in common bean ( Phaseolus vulgaris ) seed during soaking at room temperature (20°C) and during the cooking of presoaked and dry bean seed in near-boiling water (98°C). Two complementary MRI methods were used to determine the total water uptake into the seed: the T 2 -weighted 3D RARE method, which yielded an increased signal from regions of highly mobile (bulk) water and a suppressed signal from regions of poorly mobile (bound) water; and the 3D SPI method, which yielded an increased signal from regions of water restricted in motion and a suppressed signal from the bulk water regions owing to the short repetition time of the method. Based on these results, it can be concluded that during soaking water enters the bean through the micropyle, migrating below the seed coat. The raphe and hypocotyl are hydrated first, while the cotyledon tissue is hydrated next. It was also observed that the imbibition rate increases with an increasing soaking temperature.

Description: Publication date: December 2014 Source: Magnetic Resonance Imaging, Volume 32, Issue 10 Author(s): Jiang Zhang , Zhen Yuan , Jin Huang , Qin Yang , Huafu Chen Motor imagery is an experimental paradigm implemented in cognitive neuroscience and cognitive psychology. To investigate the asymmetry of the strength of cortical functional activity due to different single-hand motor imageries, functional magnetic resonance imaging (fMRI) data from right handed normal subjects were recorded and analyzed during both left-hand and right-hand motor imagery processes. Then the average power of blood oxygenation level-dependent (BOLD) signals in temporal domain was calculated using the developed tool that combines Welch power spectrum and the integral of power spectrum approach of BOLD signal changes during motor imagery. Power change analysis results indicated that cortical activity exhibited a stronger power in the precentral gyrus and medial frontal gyrus with left-hand motor imagery tasks compared with that from right-hand motor imagery tasks. These observations suggest that right handed normal subjects mobilize more cortical nerve cells for left-hand motor imagery. Our findings also suggest that the approach based on power differences of BOLD signals is a suitable quantitative analysis tool for quantification of asymmetry of brain activity intensity during motor imagery tasks.

Description: Publication date: December 2014 Source: Magnetic Resonance Imaging, Volume 32, Issue 10 Author(s): Caroline Mesmann , Monica Sigovan , Lise-Prune Berner , Adva Abergel , François Tronc , Y. Berthezène , P. Douek , Loic Boussel Purpose To compare diffusion weighted imaging with background suppression (DWIBS) sequence with classic spectral diffusion sequence (DWI) with and without respiratory gating in mediastinal lymph node analysis at 3 T. Materials and methods 26 patients scheduled for mediastinoscopic lymph node analysis, prospectively undergone a thoracic 3 T MRI with DWIBS (FatSat = STIR; TR/TE = 6674.1/44.7 ms; IR = 260 ms) and DWI sequences (FatSat = SPIR; TR/TE = 1291/59.6 ms) (b = 0-400-800 s/mm2) with and without (free breathing) respiratory gating. Images at b = 800 were analyzed by two radiologists. They performed qualitative analysis of fat-sat homogeneity and motion artifacts, rated from 0 to 4, and quantitative evaluation by studying signal to background (STB) of lymph nodes. Results Quality of fat suppression was significantly higher for DWIBS than for DWI both for free-breathing (score 3.48 ± 0.65 vs. 1.76 ± 0.96, p 〈 0.0001) and respiratory-gated scans (3.17 ± 0.77 vs. 1.72 ± 0.73, p = 0.0001). Similarly, artifacts were reduced with DWIBS (3.16 ± 0.47 vs. 1.76 ± 0.59, p 〈 0.0001; 3.0 ± 0.73 vs. 2.04 ± 0.53, p = 0.0001). Quantitative analysis showed higher STB with DWIBS (3.26 ± 1.83 vs. 0.98 ± 0.44, p 〈 0.0001; 3.56 ±, 2.09 vs. 0.92 ± 0.59, p 〈 0.0001). Gating did not improve image quality and STB on DWIBS (p > 0.05). Conclusion In thoracic MRI, ungated DWIBS sequence improves fat-sat homogeneity, reduces motion artifacts and increases STB of lymph nodes. Respiratory gating does not improve DWIBS image quality.

Description: Publication date: Available online 12 November 2014 Source: Magnetic Resonance Imaging Author(s): Jing Jiang , Paul Kokeny , Wang Ying , Chris Magnano , Robert Zivadinov , E. Mark Haacke Quantifying flow from phase-contrast MRI (PC-MRI) data requires that the vessels of interest be segmented. This estimate of the vessel area will dictate the type and magnitude of the error sources that affect the flow measurement. These sources of errors are well understood and mathematical expressions have been derived for them in previous work. However, these expressions contain many parameters that render them difficult to use for making practical error estimates. In this work, some realistic assumptions were made that allow for the simplification of such expressions in order to make them more useful. These simplified expressions were then used to numerically simulate the effect of segmentation accuracy and provide some criteria that if met, would keep errors in flow quantification below 10% or 5%. Four different segmentation methods were used on simulated and phantom MRA data to verify the theoretical results. Numerical simulations showed that including partial volumed edge pixels in vessel segmentation provides less error than missing them. This was verified with MRA simulations, as the best performing segmentation method generally included such pixels. Further, it was found that to obtain a flow error of less than 10% (5%), the vessel should be at least 4 (5) pixels in diameter, have an SNR of at least 10:1 and a peak velocity to saturation cut-off velocity ratio of at least 5:3.

Description: Publication date: Available online 7 November 2014 Source: Magnetic Resonance Imaging Author(s): Andrew B. Gill , Gayathri Anandappa , Andrew J. Patterson , Andrew N. Priest , Martin J. Graves , Tobias Janowitz , Duncan I. Jodrell , Tim Eisen , David J. Lomas This study introduces the use of ‘error-category mapping’ in the interpretation of pharmacokinetic (PK) model parameter results derived from dynamic contrast-enhanced (DCE-) MRI data. Eleven patients with metastatic renal cell carcinoma were enrolled in a multiparametric study of the treatment effects of bevacizumab. For the purposes of the present analysis, DCE-MRI data from two identical pre-treatment examinations were analysed by application of the extended Tofts model (eTM), using in turn a model arterial input function (AIF), an individually-measured AIF and a sample-average AIF. PK model parameter maps were calculated. Errors in the signal-to-gadolinium concentration ([Gd]) conversion process and the model-fitting process itself were assigned to category codes on a voxel-by-voxel basis, thereby forming a colour-coded ‘error-category map’ for each imaged slice. These maps were found to be repeatable between patient visits and showed that the eTM converged adequately in the majority of voxels in all the tumours studied. However, the maps also clearly indicated sub-regions of low Gd uptake and of non-convergence of the model in nearly all tumours. The non-physical condition v e ≥ 1 was the most frequently indicated error category and appeared sensitive to the form of AIF used. This simple method for visualisation of errors in DCE-MRI could be used as a routine quality-control technique and also has the potential to reveal otherwise hidden patterns of failure in PK model applications.