The stimulated‐echo acquisition mode‐Burst sequence is a single‐shot, multi‐slice imaging technique that does not involve rapid gradient switching. A Burst excitation pulse train is followed by a 90° ...hard pulse and, after a mixing time, by a 90° slice‐selective pulse. A read gradient refocuses a set of stimulated echoes, which can be phase encoded to form an image. By repeating the selective pulse N times, each time with the carrier frequency offset differently, it is possible to sample N slices in a single‐shot. A comparison is made of the sequence with other three‐dimensional single‐shot methods. Experiments implementing the technique on a 3 T whole‐body imaging system and a 2 T, 31‐cm bore animal imager are described. Both phantom and brain images are presented. The principal advantages of the new sequence are its speed, the absence of rapid gradient switching and corresponding freedom from artifacts, its insensitivity to static magnetic field inhomogeneities, and its low acoustic noise. The main disadvantages are the low signal‐to‐noise ratio of the images produced and the concomitant limitation in resolution.
The effect of coherent rotational motion on images acquired with the ultrafast single-shot spin-echo Burst sequence has been analyzed. Previous experience has demonstrated that sample rotation during ...Burst experiments has the potential to cause severe image artifacts. In this paper we show that no distortions are visible when the readout gradient is parallel to the rotation axis, but that there is a very distinctive behavior for the case of the rotation axis orthogonal to the imaging plane. The mathematical expression that describes the resulting signal is presented and is used as a basis for a method of correcting the k-space data. The conditions under which undistorted images may be recovered are discussed. It is shown that there is an asymmetry, dependent on the rotation direction, in both the manifestation of the artifact and the range of angular velocities over which one can correct the images. Data from an agar gel phantom rotating at a known rate are used to show how the theory is successful at reconstructing images, with no free parameters. The range of angular velocities over which correction is possible depends on the timing parameters of the pulse sequence, but for these data was −0.016 < ω ≲ 0.1 revolutions/s. Volunteer experiments have confirmed that the theory is applicable to patient motion and can correct motional distortion even when the exact rate is not known a priori. By optimizing the reconstruction to restore a known sample geometry/aspect ratio, an estimate of the rotation angular frequency is obtained with a precision of ±10%.
Background: In a previous study, we described the latest developments of spinal cord imaging, including 1HMR spectroscopy, on a 1.5T scanner, and its application to multiple sclerosis (MS) patients ...at the onset of an acute spinal cord relapse. Objective: We have now carried out a longitudinal study on the same patient cohort to assess the mechanisms of repair which contribute to clinical recovery. We focused on two spinal cord measures: the cervical cord cross-sectional area, which reflects axonal loss, and N-acetyl-aspartate (NAA) concentration, which is marker of axonal mitochondrial metabolism and axonal count. Methods: Fourteen patients with an acute cervical cord relapse and 13 controls were studied clinically at baseline and at one, three and six months. At each time point, the cross-sectional cord area and NAA concentration were obtained from the same cervical region. Mixed-effect linear regression models were performed to investigate the temporal evolution of these measures and the association between them and clinical recovery. Ordinal logistic regression analyses identified predictors of recovery. Results: Patients showed a significant linear decline in spinal cord area during follow-up, whilst patients who recovered showed non-linear changes in NAA, which increased significantly between one and six months. A greater increase of NAA after one month was associated with a greater rate of recovery and a steeper decline in cord area. Disease duration at baseline predicted clinical recovery. Conclusions: The increase in NAA after one month indicates enhanced mitochondrial activity, presumably in an effort to maintain axonal conduction. This appears to be more evident in patients who had a greater rate of recovery, and to be related to progressive axonal loss. Repair mechanisms appear to be less efficient in patients with longer disease duration. These insights into the mechanisms of spinal cord repair highlight the need to explore therapies that enhance recovery by targeting mitochondria.
MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. ...However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.
Here we present the application of neurite orientation dispersion and density imaging (NODDI) to the healthy spinal cord in vivo. NODDI provides maps such as the intra-neurite tissue volume fraction ...(vin), the orientation dispersion index (ODI) and the isotropic volume fraction (viso), and here we investigate their potential for spinal cord imaging. We scanned five healthy volunteers, four of whom twice, on a 3T MRI system with a ZOOM-EPI sequence. In accordance to the published NODDI protocol, multiple b-shells were acquired at cervical level and both NODDI and diffusion tensor imaging (DTI) metrics were obtained and analysed to: i) characterise differences in grey and white matter (GM/WM); ii) assess the scan-rescan reproducibility of NODDI; iii) investigate the relationship between NODDI and DTI; and iv) compare the quality of fit of NODDI and DTI. Our results demonstrated that: i) anatomical features can be identified in NODDI maps, such as clear contrast between GM and WM in ODI; ii) the variabilities of vin and ODI are comparable to that of DTI and are driven by biological differences between subjects for ODI, have similar contribution from measurement errors and biological variation for vin, whereas viso shows higher variability, driven by measurement errors; iii) NODDI identifies potential sources contributing to DTI indices, as in the brain; and iv) NODDI outperforms DTI in terms of quality of fit. In conclusion, this work shows that NODDI is a useful model for in vivo diffusion MRI of the spinal cord, providing metrics closely related to tissue microstructure, in line with findings in the brain.
The authors conclude that it is possible to study optic nerves with DW imaging They also conclude that in optic neuritis, the correlation of mean ADC with the clinical and electrophysiological ...parameters suggests that the ADC is giving a surrogate measure of axonal disruption in the chronic, postinflammatory optic nerve lesion.--Valérie Biousse
An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several ...semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.
•First grey matter spinal cord segmentation challenge.•Six institutions participated in the challenge and compared their methods.•Public available dataset from multiple vendors and sites.•The challenge web site remains open to new submissions.
Some microstructure parameters, such as permeability, remain elusive because mathematical models that express their relationship to the MR signal accurately are intractable. Here, we propose to use ...computational models learned from simulations to estimate these parameters. We demonstrate the approach in an example which estimates water residence time in brain white matter. The residence time τi of water inside axons is a potentially important biomarker for white matter pathologies of the human central nervous system, as myelin damage is hypothesised to affect axonal permeability, and thus τi. We construct a computational model using Monte Carlo simulations and machine learning (specifically here a random forest regressor) in order to learn a mapping between features derived from diffusion weighted MR signals and ground truth microstructure parameters, including τi. We test our numerical model using simulated and in vivo human brain data. Simulation results show that estimated parameters have strong correlations with the ground truth parameters (R2={0.88,0.95,0.82,0.99}) for volume fraction, residence time, axon radius and diffusivity respectively), and provide a marked improvement over the most widely used Kärger model (R2={0.75,0.60,0.11,0.99}). The trained model also estimates sensible microstructure parameters from in vivo human brain data acquired from healthy controls, matching values found in literature, and provides better reproducibility than the Kärger model on both the voxel and ROI level. Finally, we acquire data from two Multiple Sclerosis (MS) patients and compare to the values in healthy subjects. We find that in the splenium of corpus callosum (CC-S) the estimate of the residence time is 0.57±0.05s for the healthy subjects, while in the MS patient with a lesion in CC-S it is 0.33±0.12s in the normal appearing white matter (NAWM) and 0.19±0.11s in the lesion. In the corticospinal tracts (CST) the estimate of the residence time is 0.52±0.09s for the healthy subjects, while in the MS patient with a lesion in CST it is 0.56±0.05s in the NAWM and 0.13±0.09s in the lesion. These results agree with our expectations that the residence time in lesions would be lower than in NAWM because the loss of myelin should increase permeability. Overall, we find parameter estimates in the two MS patients consistent with expectations from the pathology of MS lesions demonstrating the clinical potential of this new technique.
•Some tissue parameters remain elusive because mathematical models are intractable.•We propose to use machine learning to estimate these parameters, here permeability.•Simulation results show an excellent agreement between estimations and ground truth.•New technique performs better than the standard Karger Model.•In-vivo results consistent with pathology of MS lesions showing clinical potential.
Multi-parametric quantitative MRI (qMRI) of the spinal cord is a promising non-invasive tool to probe early microstructural damage in neurological disorders. It is usually performed in vivo by ...combining acquisitions with multiple signal readouts, which exhibit different thermal noise levels, geometrical distortions and susceptibility to physiological noise. This ultimately hinders joint multi-contrast modelling and makes the geometric correspondence of parametric maps challenging. We propose an approach to overcome these limitations, by implementing state-of-the-art microstructural MRI of the spinal cord with a unified signal readout in vivo (i.e. with matched spatial encoding parameters across a range of imaging contrasts). We base our acquisition on single-shot echo planar imaging with reduced field-of-view, and obtain data from two different vendors (vendor 1: Philips Achieva; vendor 2: Siemens Prisma). Importantly, the unified acquisition allows us to compare signal and noise across contrasts, thus enabling overall quality enhancement via multi-contrast image denoising methods. As a proof-of-concept, here we provide a demonstration with one such method, known as Marchenko-Pastur (MP) Principal Component Analysis (PCA) denoising. MP-PCA is a singular value (SV) decomposition truncation approach that relies on redundant acquisitions, i.e. such that the number of measurements is large compared to the number of components that are maintained in the truncated SV decomposition. Here we used in vivo and synthetic data to test whether a unified readout enables more efficient MP-PCA denoising of less redundant acquisitions, since these can be denoised jointly with more redundant ones. We demonstrate that a unified readout provides robust multi-parametric maps, including diffusion and kurtosis tensors from diffusion MRI, myelin metrics from two-pool magnetisation transfer, and T1 and T2 from relaxometry. Moreover, we show that MP-PCA improves the quality of our multi-contrast acquisitions, since it reduces the coefficient of variation (i.e. variability) by up to 17% for mean kurtosis, 8% for bound pool fraction (myelin-sensitive), and 13% for T1, while enabling more efficient denoising of modalities limited in redundancy (e.g. relaxometry). In conclusion, multi-parametric spinal cord qMRI with unified readout is feasible and provides robust microstructural metrics with matched resolution and distortions, whose quality benefits from multi-contrast denoising methods such as MP-PCA.
•We present a multi-parametric MRI protocol for in vivo spinal cord microstructural imaging based on a unified signal readout.•The protocol enables the evaluation of diffusion, relaxation and myelin metrics with matched resolution and distortions.•The unified readout enables multi-contrast analyses, which are demonstrated by multi-contrast MP-PCA denoising.•Simulations and multi-vendor in vivo data show that MP-PCA is a useful pre-processing step for spinal cord imaging pipelines.•The performance of MP-PCA greatly benefits from the increased number of measurements enabled by the unified readout.
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