Quantitative assessment of motion correction for high angular resolution diffusion imaging

Several methods have been proposed for motion correction of high angular resolution diffusion imaging (HARDI) data. There have been few comparisons of these methods, partly due to a lack of quantitative metrics of performance. We compare two motion correction strategies using two figures of merit: displacement introduced by the motion correction and the 95% confidence interval of the cone of uncertainty of voxels with prolate tensors. What follows is a general approach for assessing motion correction of HARDI data that may have broad application for quality assurance and optimization of postprocessing protocols. Our analysis demonstrates two important issues related to motion correction of HARDI data: (1) although neither method we tested was dramatically superior in performance, both were dramatically better than performing no motion correction, and (2) iteration of motion correction can improve the final results. Based on the results demonstrated here, iterative motion correction is strongly recommended for HARDI acquisitions.     

Spatial normalization, bulk motion correction and coregistration for functional magnetic resonance imaging of the human cervical spinal cord and brainstem

Functional magnetic resonance imaging (fMRI) of the cortex is a powerful tool for neuroscience research, and its use has been extended into the brainstem and spinal cord as well. However, there are significant technical challenges with extrapolating the developments that have been achieved in the cortex to their use in the brainstem and spinal cord. Here, we develop a normalized coordinate system for the cervical spinal cord and brainstem, demonstrating a semiautomated method for spatially normalizing and coregistering fMRI data from these regions. fMRI data from 24 experiments in eight volunteers are normalized and combined to create the first anatomical reference volume, and based on this volume, we define a standardized region-of-interest (ROI) mask, as well as a map of 52 anatomical regions, which can be applied automatically to fMRI results. The normalization is demonstrated to have an accuracy of less than 2 mm in 93% of anatomical test points. The reverse of the normalization procedure is also demonstrated for automatic alignment of the standardized ROI mask and region-label map with fMRI data in its original (unnormalized) format. A reliable method for spatially normalizing fMRI data is essential for analyses of group data and for assessing the effects of spinal cord injury or disease on an individual basis by comparing with results from healthy subjects.     

In vivo diffusion tensor imaging of thoracic and cervical rat spinal cord at 7 T

In vivo diffusion tensor imaging (DTI) of rat cervical and thoracic spinal cord was performed using a three-element phased array coil at 7 T. The magnetic field was shimmed over the spinal cord in real time using an in-house developed automatic algorithm. Echo planar imaging (EPI)-based diffusion-weighted images (DWIs) were acquired with 21 gradient encoding directions. The DWIs were tensor encoded, and diffusion tensor metrics, fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusivity (λ₀) and transverse diffusivity (λ) were determined for both white matter (WM) and gray matter (GM). The results on six normal rats indicated no significant differences in the diffusion tensor metrics between thoracic and cervical regions. However, the DTI-derived metrics in cervical spinal cord from our study are somewhat different from the published results in rats. The possible reasons for these differences are suggested.     

Phase-aligned multiple spin-echo averaging: a simple way to improve signal-to-noise ratio of in vivo mouse spinal cord diffusion tensor image

Purpose

To improve signal-noise-ratio of in vivo mouse spinal cord diffusion tensor imaging using-phase aligned multiple spin-echo technique.

Material and methods

In vivo mouse spinal cord diffusion tensor imaging maps generated by multiple spin-echo and conventional spin-echo diffusion weighting were examined to demonstrate the efficacy of multiple spin-echo diffusion sequence to improve image quality and throughput. Effects of signal averaging using complex, magnitude and phased images from multiple spin-echo diffusion weighting were also assessed. Bayesian probability theory was used to generate phased images by moving the coherent signals to the real channel to eliminate the effect of phase variation between echoes while preserving the Gaussian noise distribution. Signal averaging of phased multiple spin-echo images potentially solves both the phase incoherence problem and the bias of the elevated Rician noise distribution in magnitude image. The proposed signal averaging with Bayesian phase-aligned multiple spin-echo images approach was compared to the conventional spin-echo data acquired with doubling the scan time. The diffusion tensor imaging parameters were compared in the mouse contusion spinal cord injury. Significance level (p-value) and effect size (Cohen’s d) were reported between the control and contused spinal cord to inspect the sensitivity of each approach in detecting white matter pathology.

Results

Compared to the spin-echo image, the signal-noise-ratio increased to 1.84-fold using the phased image averaging and to 1.30-fold using magnitude image averaging in the spinal cord white matter. Multiple spin-echo phased image averaging showed improved image quality of the mouse spinal cord among the tested methods. Diffusion tensor imaging metrics obtained from multiple spin-echo phased images using three echoes and two averages closely agreed with those derived by spin-echo magnitude data with four averages (two times more in acquisition time). The phased image averaging correctly reflected pathological features in contusion spinal cord injury.

Conclusion

Our in vivo imaging results indicate that averaging the phased multiple spin-echo images yields an 84% signal-noise-ratio increase over the spin-echo images and a 41% gain over the magnitude averaged multiple spin-echo images with equal acquisition time. Current results from the animal model of spinal cord injury suggest that the phased multiple spin-echo images could be used to improve signal-noise-ratio.     

Automatic correction of in-plane bulk motion artifacts in self-navigated radial MRI

Radial MRI is typically used for scans that are sensitive to unavoidable motion. While the translational motion artifact can be easily removed from the radial trajectory data by phase correction, correction of rotational motion still remains a challenge in radial MRI. We present a novel method to refocus the image corrupted by view-to-view motion in the view-interleaved radial MRI data. In this method, the error in rotational view angles was modeled as a polynomial function of the view order and the model parameters were estimated by minimizing the self-navigator image metrics such as image entropy, gradient entropy, normalized gradient squared and mean square difference. Translational motion correction was conducted by aligning the projection profiles. Simulation studies were conducted to demonstrate the robustness of both translational and rotational motion correction methods in different noise levels. The proposed method was successfully applied to correct for motion of healthy subjects. Substantial motion correction with relative error of less than 5% was achieved by using either first- or second-order model with the image metrics. This study demonstrates the potential of the method for motion-sensitive applications.     

Fractional amplitude of low-frequency fluctuation changes in monkeys with spinal cord injury: A resting-state fMRI study

Purpose

Although functional magnetic resonance imaging (fMRI) has revealed that spinal cord injury (SCI) causes anomalous changes in task-induced brain activation, its effect during the resting state remains unclear. The aim of this study is to explore the changes of the brain resting-state function in non-human primates with unilateral SCI.

Materials and methods

Eleven adult female rhesus monkeys were subjected to resting-state fMRI: five with unilateral thoracic SCI and six healthy monkeys, to obtain the fractional amplitude of low-frequency fluctuations (fALFF) of the blood oxygenation level-dependent (BOLD) contrast signal to determine the influence of SCI on the cerebral resting-state function.

Results

The SCI-induced fALFF vary significantly in several encephalic regions, including the left cerebellum, the left thalamus, the right lateral geniculate nucleus, the right superior parietal lobule, and the posterior cingulate gyrus.

Conclusion

Analysis of the resting-state fMRI provides evidence of abnormal spontaneous brain activations in primates with SCI, which may help us understand the pathophysiologic mechanisms underlying the changes in neural plasticity in the central nervous system after SCI.     

Functional exploration of the human spinal cord during voluntary movement and somatosensory stimulation

Demonstrations of the possibility of obtaining functional information from the spinal cord in humans using functional magnetic resonance imaging (fMRI) have been growing in number and sophistication, but the technique and the results that it provides are still perceived by the scientific community with a greater degree of scepticism than fMRI investigations of brain function. Here we review the literature on spinal fMRI in humans during voluntary movements and somatosensory stimulation. Particular attention is given to study design, acquisition and statistical analysis of the images, and to the agreement between the obtained results and existing knowledge regarding spinal cord anatomy and physiology.     

Longitudinal magnetic resonance imaging of spinal cord injury in mouse: changes in signal patterns associated with the inflammatory response

Contusion-type spinal cord injury (SCI) in mice was followed longitudinally using in vivo magnetic resonance (MR) imaging along with neurobehavioral tests performed on postinjury Days 1, 7, 14 and 28. Magnetic resonance images were acquired from seven injured wild-type mice using a 9.4-T scanner and presented in sagittal and axial views to reflect the current state of the injured cord neuropathology on each day. The data were analyzed individually to gain more insights on the neuroinflammatory response unique to the mouse, to characterize the spatiotemporal evolution of the lesion and to quantify the changes in lesion volume and length with time. The MR intensity patterns on Day 1 showed acute injuries as focal in one group of three mice and as diffuse in the remaining group of four mice. The focal injuries appeared as a region of hypointensity with well-defined boundaries. These injuries first enlarged on Day 7, but then shrunk slightly by Days 14 and 28. In contrast, the diffuse injuries were initially obscure on Day 1, mainly because of loss of contrast between gray and white matters. On Day 7, lesions expanded asymptotically in both rostral and caudal directions with respect to the epicenter, and maintained its size on Days 14 and 28. Previous studies based on postmortem histological analysis have reported lesions behaving more like in the focal group. However, this new injury with diffuse characteristics may have important implications for SCI research carried out with mice. Unique experiments on genetically engineered mice with altered neuroinflammatory response should help clarify the origin of these differences in the lesion formation.     

High-resolution in vivo diffusion tensor imaging of the injured cat spinal cord using self-navigated,interleaved, variable-density spiral acquisition (SNAILS-DTI)

Diffusion tensor magnetic resonance imaging (DTI) is useful for studying the microstructural changes in the spinal cord following traumatic injury; however, image quality is generally poor due to the small size of the spinal cord, physiological motion and susceptibility artifacts. Self-navigated, interleaved, variable-density spiral diffusion tensor imaging (SNAILS-DTI) is a distinctive pulse sequence that bypasses many of the challenges associated with DTI of the spinal cord, particularly if imaging gradient hardware is of conventional quality. In the current study, we have demonstrated the feasibility of implementing SNAILS-DTI on a clinical 3.0-T MR scanner and examined the effect of navigator filter parameters on image quality and reconstruction time. Results demonstrate high-quality, high-resolution (546 μm×546 μm) in vivo DTI images of the cat spinal cord after traumatic spinal cord injury.     

Mapping of neural activity produced by thermal pain in the healthy human spinal cord and brain stem: a functional magnetic resonance imaging study

Functional magnetic resonance imaging (fMRI) has greatly advanced our current understanding of pain, although most studies to date have focused on imaging of cortical structures. In the present study, we have used fMRI at 3 T to investigate the neural activity evoked by thermal sensation and pain (42°C and 46°C) throughout the entire lower neuroaxis from the first synapse in the spinal cord rostral to the thalamus in healthy subjects. The results demonstrate that noxious thermal stimulation (46°C) produces consistent activity within various structures known to be involved in the pain matrix including the dorsal spinal cord, reticular formation, periaqueductal gray and rostral ventral medulla. However, additional areas of activity were evident that are not considered to be part of the pain matrix, including the olivary nucleus. Thermal stimulation (42°C) reported as either not painful or mildly painful produced quantitative, but not qualitative, differences in neuronal activity depending on the order of experiments. Activity was greater in the spinal cord and brain stem in earlier experiments, compared with repeated experiments after the more noxious (46°C) stimulus had been applied. This study provides significant insight into how the lower neuroaxis integrates and responds to pain in humans.     

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.     

Dependence of the fractional anisotropy in cervical spine from the number of diffusion gradients,repeated acquisition and voxel size

The aim of this study is to investigate the consequences of using different gradient schemes, number of repeated measurements and voxel size on the fractional anisotropy (FA) value in a diffusion tensor imaging (DTI) sequence on the cervical tract of the spinal cord. Twenty healthy volunteers underwent a total of 86 DTI axial acquisitions performed by using different voxel size and number of diffusion gradient directions (NDGDs). Three different diffusion gradient schemes were applied, named 6, 15 and 32 according to the NDGD. Furthermore, some acquisitions were repeated to investigate the effects of image averaging on FA value.     

Assessment of data acquisition parameters,and analysis techniques for noise reduction in spinal cord fMRI data

Purpose

The purpose of this work is to characterize the noise in spinal cord functional MRI, assess current methods aimed at reducing noise, and optimize imaging parameters.

Methods

Functional MRI data were acquired at multiple echo times and the contrast-to-noise ratio (CNR) was calculated. Independently, the repetition time was systematically varied with and without parallel imaging, to maximize BOLD sensitivity and minimize type I errors. Noise in the images was characterized by examining the frequency spectrum, and investigating whether autocorrelations exist. The efficacy of several physiological noise reduction methods in both null (no stimuli) and task (thermal pain paradigm) data was also assessed. Finally, our previous normalization methods were extended.

Results

The echo time with the highest functional CNR at 3 Tesla is at roughly 75 msec. Parallel imaging reduced the variance and the presence of autocorrelations, however the BOLD response in task data was more robust in data acquired without parallel imaging. Model-free based approaches further increased the detection of active voxels in the task data. Finally, inter-subject registration was improved.

Conclusions

Results from this study provide a rigorous characterization of the properties of the noise and assessment of data acquisition and analysis methods for spinal cord and brainstem fMRI.     

Manifestation and post hoc correction of gradient cross-term artifacts in DTI

Cross-terms between imaging and diffusion gradients, unaccounted for during tensor calculations, can lead to erroneous estimation of diffusivity and fractional anisotropy (FA) in regions of isotropic and anisotropic diffusion. Cross-term of magnitude 136.8±1.6 s/mm(2), artificially introduced in the slice-encode direction, caused an increase in FA in isotropic phantom from 0.0546±0.0001 to 0.0996±0.0001, while the change in chimpanzee brain depended on the orientation of the white matter (WM). Mean diffusivity (MD) remained unchanged in isotropic phantom, but increased by ～20% in the WM due to cross-terms. A bias was observed in the principal eigenvectors in both phantom and chimpanzee brain, resulting in significant increase in midline crossing fibers along the bias than perpendicular to it in tractography in chimpanzee brain. Post hoc correction of these artifacts was achieved by estimating the cross-term factors using calibration scans on an isotropic phantom and modifying the b-matrix before tensor calculation. Upon correction, the FA and MD values closely resembled the values obtained from sequence without cross-terms, and the bias in principal eigenvectors was eliminated. Customized sequences involving large b-values, high-resolution imaging, or long diffusion or echo times should therefore be evaluated and any residual cross-terms corrected before implementation.     

Characterization of cardiac-related noise in fMRI of the cervical spinal cord

Magnetic resonance imaging (MRI) has recently been applied to study spinal cord function in humans. However, spinal functional MRI (fMRI) encounters major technical challenges with cardiac noise being considered a major source of noise. The present study relied on echo-planar imaging of the cervical cord at short TR (TR=250 ms; TE=40 ms; flip=45 degrees), combined with plethysmographic recordings to characterize the spatiotemporal properties of cardiac-induced signal changes in spinal fMRI. Frequency-based analyses examining signal change at the cardiac frequency confirmed mean fluctuations of about 10% (relative to the mean signal) in the spinal cord and surrounding cerebrospinal fluid (CSF), with maximal responses reaching up to 66% in some voxels. A spatial independent component analysis (sICA) confirmed that cardiac noise is an important source of variance in spinal fMRI with several components showing a response coherent with the cardiac frequency spectrum. The time course of the main cardiac components approximated a sinusoidal function tightly coupled to the cardiac systole with at least one component showing a comparable temporal profile across runs and subjects. Spatially, both the frequency-domain analysis and the sICA demonstrated cardiac noise distributed irregularly along the full rostrocaudal extent of the segments scanned with peaks concentrated in the ventral part of the lateral slices in all scans and subjects, consistent with the major channels of CSF flow. These results confirm that cardiac-induced changes are a significant source of noise likely to affect the detection of spinal Blood Oxygen Level Dependent (BOLD) responses. Most importantly, the complex spatiotemporal structure of cardiac noise is unlikely to be accounted for adequately by ad hoc linear methods, especially in data acquired using long TR (i.e. aliasing the cardiac frequency). However, the reliable spatiotemporal distribution of cardiac noise across scanning runs and within subjects may provide a valid means to identify and extract cardiac noise based on sICA methods.     

Correction strategy for diffusion-weighted images corrupted with motion: application to the DTI evaluation of infants' white matter

Objective

Diffusion imaging techniques such as DTI and HARDI are difficult to implement in infants because of their sensitivity to subject motion. A short acquisition time is generally preferred, at the expense of spatial resolution and signal-to-noise ratio. Before estimating the local diffusion model, most pre-processing techniques only register diffusion-weighted volumes, without correcting for intra-slice artifacts due to motion or technical problems. Here, we propose a fully automated strategy, which takes advantage of a high orientation number and is based on spherical-harmonics decomposition of the diffusion signal.

Material and methods

The correction strategy is based on two successive steps: 1) automated detection and resampling of corrupted slices; 2) correction for eddy current distortions and realignment of misregistered volumes. It was tested on DTI data from adults and non-sedated healthy infants.

Results

The methodology was validated through simulated motions applied to an uncorrupted dataset and through comparisons with an unmoved reference. Second, we showed that the correction applied to an infant group enabled to improve DTI maps and to increase the reliability of DTI quantification in the immature cortico-spinal tract.

Conclusion

This automated strategy performed reliably on DTI datasets and can be applied to spherical single- and multiple-shell diffusion imaging.     

Measurement and characterization of the human spinal cord SEEP response using event-related spinal fMRI

Although event-related fMRI is able to reliably detect brief changes in brain activity and is now widely used throughout systems and cognitive neuroscience, there have been no previous reports of event-related spinal cord fMRI. This is likely attributable to the various technical challenges associated with spinal fMRI (e.g., imaging a suitable length of the cord, reducing image artifacts from the vertebrae and intervertebral discs, and dealing with physiological noise from spinal cord motion). However, with many of these issues now resolved, the largest remaining impediment for event-related spinal fMRI is a deprived understanding of the spinal cord fMRI signal time course. Therefore, in this study, we used a proton density-weighted HASTE sequence, with functional contrast based on signal enhancement by extravascular water protons (SEEP), and a motion-compensating GLM analysis to (i) characterize the SEEP response function in the human cervical spinal cord and (ii) demonstrate the feasibility of event-related spinal fMRI. This was achieved by applying very brief (1 s) epochs of 22°C thermal stimulation to the palm of the hand and measuring the impulse response function. Our results suggest that the spinal cord SEEP response (time to peak ≈8 s; FWHM ≈4 s; and probably lacking pre- and poststimulus undershoots) is slower than previous estimates of SEEP or BOLD responses in the brain, but faster than previously reported spinal cord BOLD responses. Finally, by detecting and mapping consistent signal-intensity changes within and across subjects, and validating these regions with a block-designed experiment, this study represents the first successful demonstration of event-related spinal fMRI.     

Functional MRI of the cervical spinal cord during noxious and innocuous thermal stimulation in the alpha-chloralose- and halothane-anesthetized rat

Patterns of neuronal activity in the spinal cord using functional magnetic resonance imaging during noxious (48 degrees C) and innocuous (40 degrees C) thermal stimulation of the rat forepaw were examined. The patterns of functional activity elicited by thermal stimuli were compared in alpha-chloralose- and halothane-anesthetized rats. Although the locations of active pixels were similar during both types of stimulation, the mean percentage signal change was higher during noxious stimulation in both anesthetic groups. Ipsilateral dorsal horn activity was evident during both noxious and innocuous stimulation in all animals. The greatest consistency of ipsilateral dorsal horn activity occurred at the C3 to C5 spinal cord segments in all groups. Consistent contralateral dorsal horn activity appeared in segments C6 to C8 in all groups. C-fos immunohistochemical staining confirmed the presence of neural activity in the spinal cords of all animals.     

Efficacy of motion artifact reduction in neonatal DW segmented EPI at 3 T using phase correction by numerical optimization and segment data swapping

Segmented echoplanar imaging (EPI) is a potentially valuable acquisition method for neonatal diffusion-weighted imaging (DWI) due to the lower acoustic noise levels as well as reduced blurring and distortion associated with it, as compared with single-shot EPI. Reduced acoustic noise may be important for the safety of neonates. However, little information regarding the efficacy of segmented EPI motion correction schemes is available for the neonatal population. We quantitatively assessed the efficacy of a postprocessing technique for motion artifact reduction involving phase correction by nonlinear optimization, alone and in combination with a novel method of utilizing a second data set (referred to as segment data swapping). These methods were applied to three-directional eight-segment echoplanar DW images obtained from 13 sedated neonates and to nine-directional DW images from 3 unsedated neonates. For comparison, the efficacy of the nonlinear optimization method was also evaluated in four adults. Motion correction efficacy was quantified using the motion artifact-to-signal ratio (ASR). The median, 70th percentile and 90th percentile ASR values obtained from neonatal three-directional DWI using nonlinear optimization alone were 2.8%, 4.6% and 9.6%, respectively. Efficacy improved (P<.005), particularly in dealing with the images most difficult to correct, when the phase correction by numerical optimization was combined with segment data swapping (median ASR=1.9%, 70th percentile ASR=2.7%, 90th percentile ASR=4.3%). Similar results were obtained for nine-directional diffusion tensor imaging. Nonlinear optimization alone applied to adult images showed significantly (P<.001) lower ASR values (median ASR=0.9%, 70th percentile ASR=2.1%, 90th percentile ASR=4.1%), demonstrating the greater challenge in DWI of neonates with segmented EPI. In conclusion, phase correction by nonlinear optimization provides effective motion correction for neonatal DW eight-segment EPI, especially when used in conjunction with segment data swapping.     

A quality control method for detecting and suppressing uncorrected residual motion in fMRI studies

Motion correction is an important step in the functional magnetic resonance imaging (fMRI) analysis pipeline. While many studies simply exclude subjects who are estimated to have moved beyond an arbitrary threshold, there exists no objective method for determining an appropriate threshold. Furthermore, any criterion based only upon motion estimation ignores the potential for proper realignment. The method proposed here uses unsupervised learning (specifically k-means clustering) on features derived from the mean square derivative (MSD) of the signal before and after realignment to identify problem data. These classifications are refined through analysis of correlation between subject activation maps and the mean activation map, as well as the relationship between tasking and motion as measured through regression of the canonical hemodynamic response functions to fit both estimated motion parameters and MSD. The MSD is further used to identify specific scans containing residual motion, data which is suppressed by adding nuisance regressors to the general linear model; this statistical suppression is performed for identified problem subjects, but has potential for use over all subjects. For problem subjects, our results show increased hemodynamic activity more consistent with group results; that is, the addition of nuisance regressors resulted in a doubling of the correlation between the activation map for the problem subjects and the activation map for all subjects. The proposed method should be useful in helping fMRI researchers make more efficient use of their data by reducing the need to exclude entire subjects from studies and thus collect new data to replace excluded subjects.