An investigation of motion correction algorithms for pediatric spinal cord DTI in healthy subjects and patients with spinal cord injury

Patient and physiological motion can cause artifacts in DTI of the spinal cord which can impact image quality and diffusion indices. The purpose of this investigation was to determine a reliable motion correction method for pediatric spinal cord DTI and show effects of motion correction on DTI parameters in healthy subjects and patients with spinal cord injury. Ten healthy subjects and ten subjects with spinal cord injury were scanned using a 3 T scanner. Images were acquired with an inner field-of-view DTI sequence covering cervical spine levels C1 to C7. Images were corrected for motion using two types of transformation (rigid and affine) and three cost functions. Corrected images and transformations were examined qualitatively and quantitatively using in-house developed code. Fractional anisotropy (FA) and mean diffusivity (MD) indices were calculated and tested for statistical significance pre- and post- motion correction. Images corrected using rigid methods showed improvements in image quality, while affine methods frequently showed residual distortions in corrected images. Blinded evaluation of pre and post correction images showed significant improvement in cord homogeneity and edge conspicuity in corrected images (p < 0.0001). The average FA changes were statistically significant (p < 0.0001) in the spinal cord injury group, while healthy subjects showed less FA change and were not significant. In both healthy subjects and subjects with spinal cord injury, quantitative and qualitative analysis showed the rigid scaled-least-squares registration technique to be the most reliable and effective in improving image quality.     

MR microscopy of water diffusion tensor in biological systems

Diffusion tensor imaging (DTI) of the control and mechanically injured spinal cord of a ratin vitro andin vivo are reported.In vitro experiments were done on a home-built 6.4 T magnetic resonance microscope. Results for formaline-fixed samples show significant differences in diffusion tensor components between gray matter and white matter of the control spinal cord. Moreover, it is shown that already 6–10 min after the injury DTI can detect changes in water diffusion in areas extending far beyond the region of primary tissue damage.In vivo experiments were performed using a 9.4 T Magnex magnet and Bruker Medspec imaging system. Good-quality DTI images, free from motion artifacts were obtained. Results from control samples confirm differences in water diffusion between white matter and gray matter, observedin vitro. In vivo experiments show that characteristic changes in water diffusion observedin vitro 6–10 min after injury are preserved 60–360 min after injury, without significant alteration during this time.     

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.     

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.     

Reduced field-of-view DTI segmentation of cervical spine tissue

The number of diffusion tensor imaging (DTI) studies regarding the human spine has considerably increased and it is challenging because of the spine’s small size and artifacts associated with the most commonly used clinical imaging method. A novel segmentation method based on the reduced field-of-view (rFOV) DTI dataset is presented in cervical spinal canal cerebrospinal fluid, spinal cord grey matter and white matter classification in both healthy volunteers and patients with neuromyelitis optica (NMO) and multiple sclerosis (MS). Due to each channel based on high resolution rFOV DTI images providing complementary information on spinal tissue segmentation, we want to choose a different contribution map from multiple channel images. Via principal component analysis (PCA) and a hybrid diffusion filter with a continuous switch applied on fourteen channel features, eigen maps can be obtained and used for tissue segmentation based on the Bayesian discrimination method. Relative to segmentation by a pair of expert readers, all of the automated segmentation results in the experiment fall in the good segmentation area and performed well, giving an average segmentation accuracy of about 0.852 for cervical spinal cord grey matter in terms of volume overlap. Furthermore, this has important applications in defining more accurate human spinal cord tissue maps when fusing structural data with diffusion data. rFOV DTI and the proposed automatic segmentation outperform traditional manual segmentation methods in classifying MR cervical spinal images and might be potentially helpful for detecting cervical spine diseases in NMO and MS.     

A diffusion gradient optimization framework for spinal cord diffusion tensor imaging

The uncertainty in the estimation of diffusion model parameters in diffusion tensor imaging (DTI) can be reduced by optimally selecting the diffusion gradient directions utilizing some prior structural information. This is beneficial for spinal cord DTI, where the magnetic resonance images have low signal-to-noise ratio and thus high uncertainty in diffusion model parameter estimation. Presented is a gradient optimization scheme based on D-optimality, which reduces the overall estimation uncertainty by minimizing the Rician Cramer-Rao lower bound of the variance of the model parameter estimates. The tensor-based diffusion model for DTI is simplified to a four-parameter axisymmetric DTI model where diffusion transverse to the principal eigenvector of the tensor is assumed isotropic. Through simulations and experimental validation, we demonstrate that an optimized gradient scheme based on D-optimality is able to reduce the overall uncertainty in the estimation of diffusion model parameters for the cervical spinal cord and brain stem white matter tracts.     

Comparison of mouse brain DTI maps using K-space average,image-space average,or no average approach

Diffusion tensor imaging (DTI) is achieved by collecting a series of diffusion-weighted images (DWIs). Signal averaging of multiple repetitions can be performed in the k-space (k-avg) or in the image space (m-avg) to improve the image quality. Alternatively, one can treat each acquisition as an independent image and use all of the data to reconstruct the DTI without doing any signal averaging (no-avg). To compare these three approaches, in this study, in vivo DTI data were collected from five normal mice. Noisy data with signal-to-noise ratios (SNR) that varied between five and 30 (before averaging) were then simulated. The DTI indices, including relative anisotropy (RA), trace of diffusion tensor (TR), axial diffusivity (λ║), and radial diffusivity (λ ⊥), derived from the k-avg, m-avg, and no-avg, were then compared in the corpus callosum white matter, cortex gray matter, and the ventricles. We found that k-avg and m-avg enhanced the SNR of DWI with no significant differences. However, k-avg produced lower RA in the white matter and higher RA in the gray matter, compared to the m-avg and no-avg, regardless of SNR. The latter two produced similar DTI quantifications. We concluded that k-avg is less preferred for DTI brain imaging.     

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.     

In vivo echo-planar imaging of rat spinal cord

An integrated approach to echo-planar imaging of rat spinal cord in vivo with a small field of view (FOV) is presented. This protocol is based on a multishot interleaved echo-planar imaging (EPI) sequence and includes: 1) use of an inductively coupled implantable coil for improved signal-to-noise ratio (SNR); 2) three-dimensional (3D) automatic shimming of the magnetic field over the spinal cord; and 3) post-acquisition data processing using a multireference scan for minimizing image artifacts. Some of the practical issues in implementing this protocol are discussed. This imaging protocol will be useful in characterizing the spinal cord pathology using techniques that are otherwise time-consuming, such as diffusion tensor imaging.     

Correlation between spinal cord diffusion tensor imaging and postural response latencies in persons with multiple sclerosis: A pilot study

PurposeLonger latency of postural response in multiple sclerosis (MS) may be linked to imbalance and increased likelihood of falls. It may be caused by the compromised microstructural integrity in the spinal cord, as evidenced by slowed somatosensory conduction in the spinal cord. Thus, the purpose of this study is to investigate the correlation between latency of postural responses and microstructural integrity of the cervical spinal cord, the region particularly related to the disease severity in MS, using diffusion tensor imaging (DTI) metrics.MethodsSeventeen persons with MS with mild-to-moderate disease severity were enrolled in this study. Postural response latencies of each patient were measured using electromyography of the tibialis anterior muscle (TA) and gastrocnemius muscle (GN) in response to surface perturbations. Cervical spinal cord DTI images were obtained from each patient. DTI mean, radial, axial diffusivity, and fractional anisotropy (FA) were measured between segments C4 and C6. Correlations of DTI metrics with postural response latencies, expanded disability status scale (EDSS) scores, and 25-foot walk (T25FW) were assessed using the Spearman's rank correlation coefficient at α = 0.05.ResultsLower FA was significantly correlated with longer latencies measured on right TA in response to forward postural perturbations (r = −0.51, p = .04). DTI metrics showed no significant correlations with EDSS scores (r = −0.06–0.09, p = .73–0.95) or T25FW (r = −0.1–0.14, p = .6–0.94). DTI metrics showed no significant differences between subjects with and without spinal cord lesions (p = .2–0.7).ConclusionsOur results showed a significant correlation between lower FA in the cervical spinal cord and longer latencies measured on right TA in response to forward postural perturbations in persons with MS, suggesting that impaired cervical spinal cord microstructure assessed by DTI may be associated with the delayed postural responses.     

A Monte Carlo simulation of image misalignment effects in diffusion tensor imaging

Diffusion tensor imaging (DTI) and tractography are noninvasive MRI methods, providing an insight on microscopic structural information of anisotropic tissues in vivo. The success of this technique stems on a watchful choice of imaging parameters and post-acquisition reconstruction. In the present work, we have focused on the problem of residual linear image misalignment in the DTI data and its effects on the parameters of the diffusion tensor and fiber tracking in human brain. We demonstrate substantial sensitivity of the reconstructed diffusion tensor and fiber tractography on increasing amplitude of artificially induced random image misalignment in the DTI. We show that already a submillimeter image misalignment in the DTI is an important source of error, which may potentially mask pathological presentations of the diseases and may partially explain variations in the results obtained from the DTI. Finally, we evaluated four implementations of image registrations and demonstrate their variable performance. This further supports the fact that a robust image registration must be performed to ensure reliable and reproducible diffusion tensor mapping and reconstruction of white matter (WM) fibers.     

Diffusion anisotropy in excised normal rat spinal cord measured by NMR microscopy

A conventional spin-echo NMR imaging pulse sequence was used to obtain high-resolution images of excised normal rat spinal cord at 7 and 14 T. It was observed that the large pulsed-field gradients necessary for high-resolution imaging caused a diffusion weighting that dominated the image contrast and that could be used to infer microscopic structural organization beyond that defined by the resolution of the image matrix (i.e., fiber orientation could be assigned based on diffusion anisotropy). Anisotropic diffusion coefficients were therefore measured using apparent diffusion tensor (ADT) imaging to assess more accurately fiber orientations in the spinal cord; structural anisotropy information is portrayed in the six unique images of the complete ADT. To reduce the dimensionality of the data, a trace image was generated using a separate color scale for each of the three diagonal element images of the ADT. This new image retains much of the invariance of the trace to the relative orientations of laboratory and sample axes (inherent to a greyscale trace image) but provides, by the use of color, contrast reflecting diffusion anisotropy. The colored trace image yields a pseudo-three-dimensional view of the rat spinal cord, from which it is possible to deduce fiber orientations.     

Relationships between spinal cord blood flow measured with flow-sensitive alternating inversion recovery (FAIR) and neurobehavioral outcomes in rat spinal cord injury

In the traumatically injured spinal cord, decreased perfusion is believed to contribute to secondary tissue damage beyond the primary mechanical impact, and restoration of perfusion is believed to be a promising therapeutic target. However, methods to monitor spinal cord perfusion non-invasively are limited. Perfusion magnetic resonance imaging (MRI) techniques established for the brain have not been routinely adopted to the spinal cord. The purpose of this study was to examine the relationship between spinal cord blood flow (SCBF) and injury severity in a rat thoracic spinal cord contusion injury (SCI) model using flow-sensitive alternating inversion recovery (FAIR) with two variants of the label position. SCBF as a marker of severity was compared to T₁ mapping and to spinal cord-optimized diffusion weighted imaging (DWI) with filtered parallel apparent diffusion coefficient. Thirty-eight rats underwent a T10 contusion injury with varying severities (8 sham; 10 mild; 10 moderate; 10 severe) with MRI performed at 1 day post injury at the lesion site and follow-up neurological assessments using the Basso, Beattie, Bresnahan (BBB) locomotor scoring up to 28 days post injury. Using whole-cord regions of interest at the lesion epicenter, SCBF was decreased with injury severity and had a significant correlation with BBB scores at 28 days post injury. Importantly, estimates of arterial transit times (ATT) in the injured spinal cord were not altered after injury, which suggests that FAIR protocols optimized to measure SCBF provide more value in the context of acute traumatic injury to the cord. T₁-relaxation time constants were strongly related to injury severity and had a larger extent of changes than either SCBF or DWI measures. These findings suggest that perfusion decreases in the spinal cord can be monitored non-invasively after injury, and multi-parametric MRI assessments of perfusion, diffusion, and relaxation capture unique features of the pathophysiology of preclinical injury.     

Keyhole and zero-padding approaches for reduced-encoding diffusion tensor imaging of the mouse brains

Keyhole diffusion tensor imaging (keyhole DTI) was previously proposed in cardiac imaging to reconstruct DTI maps from the reduced phase-encoding images. To evaluate the feasibility of keyhole DTI in brain imaging, keyhole and zero-padding DTI algorithms were employed on in vivo mouse brain. The reduced phase-encoding portion, also termed as the sharing rate, was varied from 50% to 90% of the full k-space. Our data showed that zero-padding DTI resulted in decreased fractional anisotropy (FA) and decreased mean apparent diffusion coefficient (mean ADC) in white matter (WM) regions. Keyhole DTI showed a better edge preservation on mean ADC maps but not on FA maps as compared to the zero-padding DTI. When increasing the sharing rate in keyhole approach, an underestimation of FA and an over- or underestimation of mean ADC were measured in WM depending on the selected reference image. The inconsistency of keyhole DTI may add a challenge for the wide use of this modality. However, with a carefully selected directive diffusion-weighted image to serve as the reference image in the keyhole approach, this study demonstrated that one may obtain DTI indices of reduced-encoding images with high consistency to those derived with full k-space DTI.     

Multiple echo diffusion tensor acquisition technique

The standard method of diffusion tensor imaging (DTI) involves one diffusion-sensitizing gradient direction per acquired signal. This paper describes an alternative method in which the entire direction set required for calculating the diffusion tensor is captured in a few scans. In this method, a series of radiofrequency (RF) pulses are applied, resulting in a train of spin echoes. A pattern of applied magnetic field gradients between the RF pulses generates a different diffusion weighting in both magnitude and direction for each echo, resulting in a dataset sufficient to determine the tensor. This significantly reduces the time required for a full DTI scan and potentially allows a tradeoff of this time for image quality. In the present work, this method is demonstrated in an anisotropic diffusion phantom (asparagus).     

Voxelwise analysis of diffusion MRI of cervical spinal cord using tract-based spatial statistics

Robust voxelwise analysis using tract-based spatial statistics (TBSS) together with permutation statistical method is standardly used in analyzing diffusion tensor imaging (DTI) of brain. A similar analytical method could be useful when studying DTI of cervical spinal cord.Based on anatomical data of sixty-four healthy volunteers, white (WM) and gray matter (GM) masks were created and subsequently registered into DTI space. Using TBSS, two skeleton types were created (single line and dilated for WM as well as GM). From anatomical data, percentage rates of overlap were calculated for all skeletons in relation to WM and GM masks.Voxelwise analysis of fractional anisotropy values depending on age and sex was conducted. Correlation of fraction anisotropy values with age of subjects was also evaluated. The two WM skeleton types showed a high overlap rate with WM masks (~94%); GM skeletons showed lower rates (56% and 42%, respectively, for single line and dilated). WM and GM areas where fraction anisotropy values differ between sexes were identified (p < .05). Furthermore, using voxelwise analysis such WM voxels were identified where fraction anisotropy values differ depending on age (p < .05) and in these voxels linear dependence of fraction anisotropy and age (r = −0.57, p < .001) was confirmed by regression analysis. This dependence was not proven when using WM anatomical masks (r = −0.21, p = .10).The analytical approach presented shown to be useful for group analysis of DTI data for cervical spinal cord.     

扩散张量成像的人脑模板构建

扩散张量脑模板包含丰富的大脑白质组织信息,在空间标准化或者脑图谱创建中具有重要价值,然而基于扩散张量模型构建的脑模板精度不高,特别是在脑部复杂的神经元微观结构区域中应用受到限制.针对这一问题,研究者们提出了基于高分辨率扩散成像构建大脑模板的方法.本文对使用扩散张量成像方法进行脑模板构建的研究进展进行了综述,首先介绍了扩散张量脑模板构建的发展进程,阐述了脑模板构建中解决的技术问题及同时存在的局限性;接着详细论述了基于扩散频谱成像及高角度分辨率扩散成像构建脑模板的不同方法间的差异,并总结了这些研究方法取得的重要进展;最后通过分析目前研究进展提出该研究问题中存在的不足以及未来的发展趋势.     

Importance of exactb-tensor calculation for quantitative diffusion tensor imaging and tracking of neuronal fiber bundles

Quantitative diffusion tensor imaging (DTI) is a novel method of magnetic resonance (MR) imaging providing information on the brain’s microstructure in vivo. DTI can be effectively measured with modern clinical MR scanners. However, imaging sequence details required for accurateb matrix calculation and for following DTI quantification are normally unknown to the user. In this work, we investigated the accuracy ofb value approximation if theb matrix is calculated without taking into account the effect of imaging gradients. It was found that an error of more than 4% in DTI estimation arises for a quite typical brain imaging protocol. The errors in mean diffusivity and fractional anisotropy index depend on diffusion tensor shape and eigenvectors orientation and exceed noise level in DTI quantification. These errors however have a strong impact on fiber tracking — up to 30% difference was found between the fiber tracks corresponding to exact and approximate calculated DTI data. Since these errors are dependent on imaging parameters and sequence implementation, accurateb matrix calculations are important for adequate comparison between data acquired on different MR scanners and also for data measured with the different imaging protocols.     

Automated assessment of the quality of diffusion tensor imaging data using color cast of color-encoded fractional anisotropy images

Diffusion tensor imaging (DTI) data often suffer from artifacts caused by motion. These artifacts are especially severe in DTI data from infants, and implementing tight quality controls is therefore imperative for DTI studies of infants. Currently, routine procedures for quality assurance of DTI data involve the slice-wise visual inspection of color-encoded, fractional anisotropy (CFA) images. Such procedures often yield inconsistent results across different data sets, across different operators who are examining those data sets, and sometimes even across time when the same operator inspects the same data set on two different occasions. We propose a more consistent, reliable, and effective method to evaluate the quality of CFA images automatically using their color cast, which is calculated on the distribution statistics of the 2D histogram in the color space as defined by the International Commission on Illumination (CIE) on lightness and a and b (LAB) for the color-opponent dimensions (also known as the CIELAB color space) of the images. Experimental results using DTI data acquired from neonates verified that this proposed method is rapid and accurate. The method thus provides a new tool for real-time quality assurance for DTI data.     

A practical approach to in vivo high-resolution diffusion tensor imaging of rhesus monkeys on a 3-T human scanner

The nonhuman primate brain study provides important supplemental means for human brain exploration since the two species share close anatomical and functional similarities. MR diffusion tensor imaging (DTI) in human brain has revealed exquisite details of brain structures especially in the brain white matter. However, most previous monkey brain DTI results lack the spatial resolution in comparison to the conventional tracing and postmortem imaging methods, especially when it is acquired in commonly available human MRI scanners of field strength of 3 T or lower. To meet the increasing demands for nonhuman primate DTI studies, we proposed an in vivo high-resolution monkey DTI acquisition protocol that is practically feasible and combined it with an improved postprocessing procedure for a 3-T human scanner. The acquisition protocol, susceptibility distortion correction method with phase reversal acquisition, and postprocessing steps were proved to be effective in our study of rhesus monkeys. Results from diffusion tensor estimations and fiber tractography at 1 x 1 x 1 mm(3) resolution were found to be comparable to previous ex vivo DTI studies with much longer acquisition times. Effects of image resolution were evaluated and it was confirmed that the partial volume effect due to the larger voxel size in low-resolution data biased the diffusion tensor estimation and produced erroneous fiber tractography. Our results suggest that in vivo high-resolution monkey brain DTI can be achieved within practical time, which allows accurate diffusion tensor estimation and fiber tractography in monkey brains, so that the complex anatomical structures within many small but important anatomic structures can be delineated.