Multichannel Phased-array Coils Research Articles

Magnetic Resonance Imaging in Traumatic Brachial Plexus Injuries: A 6-Year Experience.

Background and Purpose: There is limited information in the literature on epidemiology of high-energy brachial plexus injuries evaluated with MR neurography (MRN). The aim of the present study is to describe the demographic characteristics of brachial plexus injuries secondary to motorcycle accident patients in the city of Fortaleza-Ceara, Brazil, and analyze the association of those data with the features of the brachial plexus lesions observed on MRN findings. Materials and Methods: A review of sixty medical charts and MRN findings of victims of motor vehicle accidents (MVA) in northeast, from November 2011 to November 2017. Demographic and imaging data collected included age, sex, laterality and level of the lesion and time interval between trauma and MRN examination. The MRN examinations were carried out on a GE 1.5T MR unit (Signa HDxT- General Electric, Milwaukee, USA) or on a Phillips 3T MR unit (Philips Achieva X-series - Philips Medical Systems, Best, The Netherlands). Dedicated multichannel phased-array coils. Results: The longest time interval from trauma to imaging was 330 days and between trauma and surgery was 692 days. Preganglionic lesions (avulsion) predominated, consisting of 52 patients (86.6%) reflecting the high energy trauma with upper limb traction from the neck. The lesions were most prevalent at the C6-C8 levels. Pseudomeningocele was identified in 62.9% of the preganglionic lesions and in only 1.6% of the postganglionic lesions. Regional muscle denervation changes were seen in all pre-ganglionic injuries and most of post-ganglionic injuries. Conclusions: MRN of the brachial plexus provides important insights into the distribution of neuromuscular lesions in high energy MVA trauma and these findings enrich the literature for researchers and clinicians focused on managing such patients and/or defining prognostic strategies.

Pypreclin: An automatic pipeline for macaque functional MRI preprocessing

Non-human primate functional MRI (fMRI) is a growing field in neuroscience. However, there is no standardized method for monkey fMRI data analysis, specifically for data preprocessing. The preprocessing of monkey fMRI data is challenged by several technical and experimental specificities of the monkey research such as artifacts related to body movements or to intracranial leads. Here we propose to address these challenges by developing a new versatile pipeline for macaque fMRI preprocessing. We developed a Python module, Pypreclin, to process raw images using state of the art algorithms embedded in a fully automatic pipeline. To evaluate its robustness, we applied Pypreclin to fMRI data acquired at 3T in both awake and anesthetized macaques, with or without iron oxide contrast agent, using single loop or multichannel phased-array coils, combined or not with intracranial implanted electrodes. We performed both resting-state and auditory evoked fMRI and compared the results of Pypreclin to a previously employed preprocessing pipeline. Pypreclin successfully achieved the registration of the fMRI data to the macaque brain template in all the experimental conditions. Moreover, Pypreclin enables more accurate locations of auditory evoked activations in relation to the gray matter at corrected level in the awake fMRI condition. Finally, using the Primate neuroimaging Data-Exchange open access platform, we could further validate Pypreclin for monkey fMRI images that were acquired at ultra-high fields, from other institutions and using different protocols. Pypreclin is a validated preprocessing tool that adapts to diverse experimental and technical situations of monkey fMRI. Pypreclin code is available on open source data sharing platform.

Radial magnetic resonance imaging (MRI) using a rotating radiofrequency (RF) coil at 9.4 T

The rotating radiofrequency coil (RRFC) has been developed recently as an alternative approach to multi-channel phased-array coils. The single-element RRFC avoids inter-channel coupling and allows a larger coil element with better B1 field penetration when compared with an array counterpart. However, dedicated image reconstruction algorithms require accurate estimation of temporally varying coil sensitivities to remove artefacts caused by coil rotation. Various methods have been developed to estimate unknown sensitivity profiles from a few experimentally measured sensitivity maps, but these methods become problematic when the RRFC is used as a transceiver coil. In this work, a novel and practical radial encoding method is introduced for the RRFC to facilitate image reconstruction without the measurement or estimation of rotation-dependent sensitivity profiles. Theoretical analyses suggest that the rotation-dependent sensitivities of the RRFC can be used to create a uniform profile with careful choice of sampling positions and imaging parameters. To test this new imaging method, dedicated electronics were designed and built to control the RRFC speed and hence positions in synchrony with imaging parameters. High-quality phantom and animal images acquired on a 9.4 T pre-clinical scanner demonstrate the feasibility and potential of this new RRFC method.

Influence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging.

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.

High-resolution macaque MRI at 3T using implanted multichannel array coils.

High-resolution macaque MRI at 3T using implanted multichannel array coils.

Reconstructing very short TE phase rotation spectral data collected with multichannel phased-array coils at 3 T

Phased-array volume coils were used in conjunction with the phase rotation STEAM (PR-STEAM) spectroscopy technique to acquire very short TE data from the anterior cingulate gyrus at 3 T. A method for combining PR-STEAM data from multiple subcoils is presented. The data were acquired from seven healthy participants using PR-STEAM (repetition time/mixing time/echo time=3500/10/6.5 ms, 6 cm 3, NEX=128, spectral width=2000 Hz, 2048 complex points, Δ φ 1=135°, Δ φ 2=22.5°, Δ φ 3=112.5° and Δ φ ADC=0°). In addition to the primary metabolites, LCModel fit results suggest that glutathione and glutamate can also be identified with Cramér–Rao lower bounds of 10% or less.

3 T magnetic resonance imaging of the musculoskeletal system

The increasing distribution of high-field (3 T) magnetic resonance (MR) systems for clinical use has been accompanied by the need to fully understand the advantages and disadvantages that the increase in signal quality confers. Continuous development of the coils is required to fully express the potential of these systems, especially given the synergy between parallel imaging and the recent multichannel phased-array coils, which are able to improve image quality, spatial resolution and diagnostic accuracy in musculoskeletal imaging. The increase in signal offered by the high field makes possible improved visualisation of bone, cartilage, tendons and ligaments. This advantage, together with increased spatial resolution, is particularly useful when studying joints or some of their components, the evaluation of which has produced suboptimal results in non arthrographic examinations such as the glenoid labrum of the shoulder and the articular cartilage of the knee. Thanks to the greater signal-to-noise ratio and improved spatial resolution, MR imaging at 3 T is able to notably increase diagnostic performance in the musculoskeletal setting, with a consequent improvement in patient treatment and management.

Improvement of brain segmentation accuracy by optimizing non-uniformity correction using N3

Smoothly varying and multiplicative intensity variations within MR images that are artifactual, can reduce the accuracy of automated brain segmentation. Fortunately, these can be corrected. Among existing correction approaches, the nonparametric non-uniformity intensity normalization method N3 (Sled, J.G., Zijdenbos, A.P., Evans, A.C., 1998. Nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans. Med. Imag. 17, 87–97.) is one of the most frequently used. However, at least one recent study (Boyes, R.G., Gunter, J.L., Frost, C., Janke, A.L., Yeatman, T., Hill, D.L.G., Bernstein, M.A., Thompson, P.M., Weiner, M.W., Schuff, N., Alexander, G.E., Killiany, R.J., DeCarli, C., Jack, C.R., Fox, N.C., 2008. Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils. NeuroImage 39, 1752–1762.) suggests that its performance on 3 T scanners with multichannel phased-array receiver coils can be improved by optimizing a parameter that controls the smoothness of the estimated bias field. The present study not only confirms this finding, but additionally demonstrates the benefit of reducing the relevant parameter values to 30–50 mm (default value is 200 mm), on white matter surface estimation as well as the measurement of cortical and subcortical structures using FreeSurfer (Martinos Imaging Centre, Boston, MA). This finding can help enhance precision in studies where estimation of cerebral cortex thickness is critical for making inferences.

Cutting edge of inner ear MRI

Conclusion: Recent advances in clinical MR imagers, such as the 3-Tesla, multi-channel phased-array coil and novel pulse sequences, allow the evaluation of subtle alterations in the inner ear fluid environments and breakdown of the blood–labyrinthine barrier. Intratympanic injection of Gd-DTPA allows the imaging detection of endolymphatic hydrops in patients. Objectives: To describe the current status of inner ear MRI and future directions for imaging. Materials and methods: Based on our experiences and literature research, a brief review of the history and recent developments of inner ear MRI is presented. Results: The 3D-FLAIR technique can detect abnormalities that could not be visualized previously in many inner ear diseases, such as sudden deafness, otosclerosis, lupus erythematosus, mumps, and Ramsay-Hunt syndrome. Imaging techniques, indications, and findings for the visualization of endolymphatic hydrops after intratympanic injection of Gd-DTPA are also discussed. This procedure enabled the visualization of endolymphatic hydrops in vivo. Newly developed 3D-real IR techniques and utilities of 32 channel coil are also presented.

Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils

Measures of structural brain change based on longitudinal MR imaging are increasingly important but can be degraded by intensity non-uniformity. This non-uniformity can be more pronounced at higher field strengths, or when using multichannel receiver coils. We assessed the ability of the non-parametric non-uniform intensity normalization (N3) technique to correct non-uniformity in 72 volumetric brain MR scans from the preparatory phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Normal elderly subjects ( n = 18) were scanned on different 3-T scanners with a multichannel phased array receiver coil at baseline, using magnetization prepared rapid gradient echo (MP-RAGE) and spoiled gradient echo (SPGR) pulse sequences, and again 2 weeks later. When applying N3, we used five brain masks of varying accuracy and four spline smoothing distances ( d = 50, 100, 150 and 200 mm) to ascertain which combination of parameters optimally reduces the non-uniformity. We used the normalized white matter intensity variance (standard deviation/mean) to ascertain quantitatively the correction for a single scan; we used the variance of the normalized difference image to assess quantitatively the consistency of the correction over time from registered scan pairs. Our results showed statistically significant ( p < 0.01) improvement in uniformity for individual scans and reduction in the normalized difference image variance when using masks that identified distinct brain tissue classes, and when using smaller spline smoothing distances (e.g., 50–100 mm) for both MP-RAGE and SPGR pulse sequences. These optimized settings may assist future large-scale studies where 3-T scanners and phased array receiver coils are used, such as ADNI, so that intensity non-uniformity does not influence the power of MR imaging to detect disease progression and the factors that influence it.

Synthetic T1-weighted brain image generation with incorporated coil intensity correction using DESPOT1

The increased use of phased-array and surface coils in magnetic resonance imaging, the push toward increased field strength and the need for standardized imaging across multiple sites during clinical trials have resulted in the need for methods that can ensure consistency of intensity both within the image and across multiple subjects/sites. Here, we describe a means of addressing these concerns through an extension of the rapid T(1) mapping technique - driven equilibrium single-pulse observation of T(1). The effectiveness of the proposed approach was evaluated using human brain T(1) maps acquired at 1.5 T with a multichannel phased-array coil. Corrected "synthetic" T(1)-weighted images were reconstructed by substituting the T(1) values back into the governing signal intensity equation while assuming a constant value for the equilibrium magnetization. To demonstrate signal normalization across a longitudinal study, we calculated synthetic T(1)-weighted images from data acquired from the same healthy subject at four different time points. Signal intensity profiles between the acquired and synthetic images were compared to determine the improvements with our proposed approach. Following correction, the images demonstrate obvious qualitative improvement with increased signal uniformity across the image. Near-perfect signal normalization was also observed across the longitudinal study, allowing direct comparison between the images. In addition, we observe an increase in contrast-to-noise ratio (compared with regular T(1)-weighted images) for synthetic images created, assuming uniform proton density throughout the volume. The proposed approach permits rapid correction for signal intensity inhomogeneity without significantly lengthening exam time or reducing image signal-to-noise ratio. This technique also provides a robust method for signal normalization, which is useful in multicenter longitudinal MR studies of disease progression, and allows the user to reconstruct T(1)-weighted images with arbitrary T(1) weighting.