Correction for direction-dependent distortions in diffusion tensor imaging using matched magnetic field maps

Simultaneous superresolution reconstruction and distortion correction for single-shot EPI DWI using deep learning

PURPOSE

Single-shot (SS) EPI is widely used for clinical DWI. This study aims to develop an end-to-end deep learning-based method with a novel loss function in an improved network structure to simultaneously increase the resolution and correct distortions for SS-EPI DWI.

THEORY AND METHODS

Point-spread-function (PSF)-encoded EPI can provide high-resolution, distortion-free DWI images. A distorted image from SS-EPI can be described as the convolution between a PSF function with a distortion-free image. The deconvolution process to recover the distortion-free image can be achieved with a convolution neural network, which also learns the mapping function between low-resolution SS-EPI and high-resolution reference PSF-EPI to achieve superresolution. To suppress the oversmoothing effect, we proposed a modified generative adversarial network structure, in which a dense net with gradient map guidance and a multilevel fusion block was used as the generator. A fractional anisotropy loss was proposed to utilize the diffusion anisotropy information among diffusion directions. In vivo brain DWI data were used to test the proposed method.

RESULTS

The results show that distortion-corrected high-resolution DWI images with restored structural details can be obtained from low-resolution SS-EPI images by taking advantage of the high-resolution anatomical images. Additionally, the proposed network can improve the quantitative accuracy of diffusion metrics compared with previously reported networks.

CONCLUSION

Using high-resolution, distortion-free EPI-DWI images as references, a deep learning-based method to simultaneously increase the perceived resolution and correct distortions for low-resolution SS-EPI was proposed. The results show that DWI image quality and diffusion metrics can be improved.

What's new and what's next in diffusion MRI preprocessing

Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropriately accounted for. This review will cover dMRI artifacts and preprocessing steps, some of which have not typically been considered in existing pipelines or reviews, or have only gained attention in recent years: brain/skull extraction, B-matrix incompatibilities w.r.t the imaging data, signal drift, Gibbs ringing, noise distribution bias, denoising, between- and within-volumes motion, eddy currents, outliers, susceptibility distortions, EPI Nyquist ghosts, gradient deviations, B1 bias fields, and spatial normalization. The focus will be on "what's new" since the notable advances prior to and brought by the Human Connectome Project (HCP), as presented in the predecessing issue on "Mapping the Connectome" in 2013. In addition to the development of novel strategies for dMRI preprocessing, exciting progress has been made in the availability of open source tools and reproducible pipelines, databases and simulation tools for the evaluation of preprocessing steps, and automated quality control frameworks, amongst others. Finally, this review will consider practical considerations and our view on "what's next" in dMRI preprocessing.

Improving distortion correction for isotropic high-resolution 3D diffusion MRI by optimizing Jacobian modulation

PURPOSE

To improve distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI when in a time-saving acquisition scenario.

THEORY AND METHODS

Data were acquired using simultaneous multi-slab (SMSlab) acquisitions, with a b = 0 image pair encoded by reversed polarity gradients (RPG) for phase encoding (PE) and diffusion weighted images encoded by a single PE direction. Eddy current-induced distortions were corrected first. During the following susceptibility distortion correction, image deformation was first corrected by the field map estimated from the b = 0 image pair. Intensity variation was subsequently corrected by Jacobian modulation. Two Jacobian modulation methods were compared. They calculated the Jacobian modulation map from the field map, or from the deformation corrected b = 0 image pair, termed as J_Field and J_RPG , respectively. A modified version of the J_RPG method, with proper smoothing, was further proposed for improved correction performance, termed as J_RPG-smooth .

RESULTS

Compared to J_Field modulation, less remaining distortions are observed when using the J_RPG and J_RPG-smooth methods, especially in areas with large B0 field inhomogeneity. The original J_RPG method causes signal-to-noise ratio (SNR) deficiency problem, which manifests as degraded SNR of the diffusion weighted images, while the J_RPG-smooth method maintains the original image SNR. Less estimation errors of diffusion metrics are observed when using the J_RPG-smooth method.

CONCLUSION

This study improves the distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI by optimizing Jacobian modulation. The optimized method outperforms the conventional J_Field method regarding intensity variation correction and accuracy of diffusion metrics estimation, and outperforms the original J_RPG method regarding SNR performance.

Distortion correction for high-resolution single-shot EPI DTI using a modified field-mapping method

PURPOSE

The widely used single-shot EPI (SS-EPI) diffusion tensor imaging (DTI) suffers from strong image distortion due to B₀ inhomogeneity, especially for high-resolution imaging. Traditional methods such as the field-mapping method and the top-up method have various deficiencies in high-resolution SS-EPI DTI distortion correction. This study aims to propose a robust distortion correction approach, which combines the advantages of traditional methods and overcomes their deficiencies, for high-resolution SS-EPI DTI.

METHODS

The proposed correction method is based on the echo planar spectroscopic imaging field-mapping followed by an intensity correction procedure. To evaluate the efficacy of distortion correction, the proposed method was compared with the conventional field-mapping method and the top-up method, using a newly developed quantitative evaluation framework. The correction results were also compared with multi-shot EPI DTI to investigate whether the proposed method can provide high-resolution SS-EPI DTI with high geometric fidelity and high time efficiency.

RESULTS

The results show that accurate field-mapping and intensity correction are critical to distortion correction in high-resolution SS-EPI DTI. The proposed method can provide more precise field maps and better correction results than the other two methods (p < 0.0001), and the corrected images show higher geometric fidelity than those from MS-EPI DTI.

CONCLUSION

An effective method is proposed to reduce image distortion in high-resolution SS-EPI DTI. It is practical to achieve high-resolution DTI with high time efficiency and high structure accuracy using this method.

Corticospinal tract diffusion properties and robotic visually guided reaching in children with hemiparetic cerebral palsy

Perinatal stroke is the leading cause of hemiparetic cerebral palsy (CP), resulting in life-long disability. In this study, we examined the relationship between robotic upper extremity motor impairment and corticospinal tract (CST) diffusion properties. Thirty-three children with unilateral perinatal ischemic stroke (17 arterial, 16 venous) and hemiparesis were recruited from a population-based research cohort. Bilateral CSTs were defined using diffusion tensor imaging (DTI) and four diffusion metrics were quantified: fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivities. Participants completed a visually guided reaching task using the KINARM robot to define 10 movement parameters including movement time and maximum speed. Twenty-six typically developing children underwent the same evaluations. Partial correlations assessed the relationship between robotic reaching and CST diffusion parameters. All diffusion properties of the lesioned CST differed from controls in the arterial group, whereas only FA was reduced in the venous group. Non-lesioned CST diffusion measures were similar between stroke groups and controls. Both stroke groups demonstrated impaired reaching performance. Multiple reaching parameters of the affected limb correlated with lesioned CST diffusion properties. Lower FA and higher MD were associated with greater movement time. Few correlations were observed between non-lesioned CST diffusion and unaffected limb function though FA was associated with reaction time (R = -0.39, p < .01). Diffusion properties of the lesioned CST are altered after perinatal stroke, the degree of which correlates with specific elements of visually guided reaching performance, suggesting specific relevance of CST structural connectivity to clinical motor function in hemiparetic children.

Effects of Orientation and Anisometry of Magnetic Resonance Imaging Acquisitions on Diffusion Tensor Imaging and Structural Connectomes

Diffusion-weighted imaging (DWI) quantifies water molecule diffusion within tissues and is becoming an increasingly used technique. However, it is very challenging as correct quantification depends on many different factors, ranging from acquisition parameters to a long pipeline of image processing. In this work, we investigated the influence of voxel geometry on diffusion analysis, comparing different acquisition orientations as well as isometric and anisometric voxels. Diffusion-weighted images of one rat brain were acquired with four different voxel geometries (one isometric and three anisometric in different directions) and three different encoding orientations (coronal, axial and sagittal). Diffusion tensor scalar measurements, tractography and the brain structural connectome were analyzed for each of the 12 acquisitions. The acquisition direction with respect to the main magnetic field orientation affected the diffusion results. When the acquisition slice-encoding direction was not aligned with the main magnetic field, there were more artifacts and a lower signal-to-noise ratio that led to less anisotropic tensors (lower fractional anisotropic values), producing poorer quality results. The use of anisometric voxels generated statistically significant differences in the values of diffusion metrics in specific regions. It also elicited differences in tract reconstruction and in different graph metric values describing the brain networks. Our results highlight the importance of taking into account the geometric aspects of acquisitions, especially when comparing diffusion data acquired using different geometries.

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural investigation of the zebra finch brain has been performed ex vivo using invasive methods such as histology. These methods are highly specific, however, they strongly interfere with performing whole-brain analyses and exclude longitudinal studies aimed at establishing causal correlations between neuroplastic events and specific behavioral performances. Therefore, the aim of the current study was to implement an in vivo Diffusion Tensor Imaging (DTI) protocol sensitive enough to detect structural sex differences in the adult zebra finch brain. Voxel-wise comparison of male and female DTI parameter maps shows clear differences in several components of the song control system (i.e. Area X surroundings, the high vocal center (HVC) and the lateral magnocellular nucleus of the anterior nidopallium (LMAN)), which corroborate previous findings and are in line with the clear behavioral difference as only males sing. Furthermore, to obtain additional insights into the 3-dimensional organization of the zebra finch brain and clarify findings obtained by the in vivo study, ex vivo DTI data of the male and female brain were acquired as well, using a recently established super-resolution reconstruction (SRR) imaging strategy. Interestingly, the SRR-DTI approach led to a marked reduction in acquisition time without interfering with the (spatial and angular) resolution and SNR which enabled to acquire a data set characterized by a 78μm isotropic resolution including 90 diffusion gradient directions within 44h of scanning time. Based on the reconstructed SRR-DTI maps, whole brain probabilistic Track Density Imaging (TDI) was performed for the purpose of super resolved track density imaging, further pushing the resolution up to 40μm isotropic. The DTI and TDI maps realized atlas-quality anatomical maps that enable a clear delineation of most components of the song control and auditory systems. In conclusion, this study paves the way for longitudinal in vivo and high-resolution ex vivo experiments aimed at disentangling neuroplastic events that characterize the critical period for vocal learning in zebra finch ontogeny.

Current Clinical Applications and Future Potential of Diffusion Tensor Imaging in Traumatic Brain Injury

In the setting of acute central nervous system (CNS) emergencies, computed tomography (CT) and conventional magnetic resonance imaging (MRI) play an important role in the identification of life-threatening intracranial injury. However, the full extent or even presence of brain damage frequently escapes detection by conventional CT and MRI. Advanced MRI techniques such as diffusion tensor imaging (DTI) are emerging as important adjuncts in the diagnosis of microstructural white matter injury in the acute and postacute brain-injured patient. Although DTI aids in detection of brain injury pathology, which has been repeatedly associated with typical adverse clinical outcomes, the evolution of acute changes and their long-term prognostic implications are less clear and the subject of much active research. A major aim of current research is to identify imaging-based biomarkers that can identify the subset of TBI patients who are at risk for adverse outcome and can therefore most benefit from ongoing care and rehabilitation as well as future therapeutic interventions.The aim of this study is to introduce the current methods used to obtain DTI in the clinical setting, describe a set of common interpretation strategies with their associated advantages and pitfalls, as well as illustrate the clinical utility of DTI through a set of specific patient scenarios. We conclude with a discussion of future potential for the management of TBI.

Choosing the polarity of the phase-encoding direction in diffusion MRI: Does it matter for group analysis?

Notorious for degrading diffusion MRI data quality are so-called susceptibility-induced off-resonance fields, which cause non-linear geometric image deformations. While acquiring additional data to correct for these distortions alleviates the adverse effects of this artifact drastically - e.g., by reversing the polarity of the phase-encoding (PE) direction - this strategy is often not an option due to scan time constraints. Especially in a clinical context, where patient comfort and safety are of paramount importance, acquisition specifications are preferred that minimize scan time, typically resulting in data obtained with only one PE direction. In this work, we investigated whether choosing a different polarity of the PE direction would affect the outcome of a specific clinical research study. To address this methodological question, fractional anisotropy (FA) estimates of FreeSurfer brain regions were obtained in civilian and combat controls, remitted posttraumatic stress disorder (PTSD) patients, and persistent PTSD patients before and after trauma-focused therapy and were compared between diffusion MRI data sets acquired with different polarities of the PE direction (posterior-to-anterior, PA and anterior-to-posterior, AP). Our results demonstrate that regional FA estimates differ on average in the order of 5% between AP and PA PE data. In addition, when comparing FA estimates between different subject groups for specific cingulum subdivisions, the conclusions for AP and PA PE data were not in agreement. These findings increase our understanding of how one of the most pronounced data artifacts in diffusion MRI can impact group analyses and should encourage users to be more cautious when interpreting and reporting study outcomes derived from data acquired along a single PE direction.

An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging

In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. The method is based on registering the individual volumes to a model free prediction of what each volume should look like, thereby enabling its use on high b-value data where the contrast is vastly different in different volumes. In addition we show that the linear EC-model commonly used is insufficient for the data used in the present paper (high spatial and angular resolution data acquired with Stejskal-Tanner gradients on a 3T Siemens Verio, a 3T Siemens Connectome Skyra or a 7T Siemens Magnetome scanner) and that a higher order model performs significantly better. The method is already in extensive practical use and is used by four major projects (the WU-UMinn HCP, the MGH HCP, the UK Biobank and the Whitehall studies) to correct for distortions and subject movement.

Artifact correction in diffusion MRI of non-human primate brains on a clinical 3T scanner

BACKGROUND

Smearing artifacts were observed and investigated in diffusion tensor imaging (DTI) studies of macaque monkeys on a clinical whole-body 3T scanner.

METHODS

Four adult macaques were utilized to evaluate DTI artifacts. DTI images were acquired with a single-shot echo-planar imaging (EPI) sequence using a parallel imaging technique.

RESULTS

The smearing artifacts observed on the diffusion-weighted images and fractional anisotropy maps were caused by the incomplete fat suppression due to the irregular macaque frontal skull geometry and anatomy. The artifact can be reduced substantially using a novel three-dimensional (3D) shimming procedure.

CONCLUSION

The smearing artifacts observed on diffusion weighted images and fractional anisotropy (FA) maps of macaque brains can be reduced substantially using a robust 3D shimming approach. The DTI protocol combined with the shimming procedure could be a robust approach to examine brain connectivity and white matter integrity of non-human primates using a conventional clinical setting.

Dynamic and inherent B0 correction for DTI using stimulated echo spiral imaging

PURPOSE

To present a novel technique for high-resolution stimulated echo diffusion tensor imaging with self-navigated interleaved spirals readout trajectories that can inherently and dynamically correct for image artifacts due to spatial and temporal variations in the static magnetic field (B0) resulting from eddy currents, tissue susceptibilities, subject/physiological motion, and hardware instabilities.

METHODS

The Hahn spin echo formed by the first two 90° radiofrequency pulses is balanced to consecutively acquire two additional images with different echo times and generate an inherent field map, while the diffusion-prepared stimulated echo signal remains unaffected. For every diffusion-encoding direction, an intrinsically registered field map is estimated dynamically and used to effectively and inherently correct for off-resonance artifacts in the reconstruction of the corresponding diffusion-weighted image.

RESULTS

After correction with the dynamically acquired field maps, local blurring artifacts are specifically removed from individual stimulated echo diffusion-weighted images and the estimated diffusion tensors have significantly improved spatial accuracy and larger fractional anisotropy.

CONCLUSION

Combined with the self-navigated interleaved spirals acquisition scheme, our new method provides an integrated high-resolution short-echo time diffusion tensor imaging solution with inherent and dynamic correction for both motion-induced phase errors and off-resonance effects.

POCS-enhanced inherent correction of motion-induced phase errors (POCS-ICE) for high-resolution multishot diffusion MRI

PURPOSE

For multishot diffusion weighted imaging (DWI), one of the challenges is to remove phase variations induced by physiological motion among different shots. In this study, a new method is proposed to iteratively solve the phase errors and DWI images simultaneously, for navigator-free acquisitions.

THEORY AND METHODS

Instead of solving phase errors and the image sequentially in the two-step parallel imaging, the proposed method, named POCS-enhanced Inherent Correction of motion-induced phase Errors (POCS-ICE), treats both the phase and DWI image as unknowns and solves them simultaneously. Multishot DWI with constant density spiral trajectory served as a specific example. Simulation and in vivo experiments were performed to evaluate the proposed method.

RESULTS

POCS-ICE shows improved image quality in terms of higher SNR and fewer artifacts than the compared method, SENSE+CG. The improvement becomes more conspicuous as the number of shots increases. The convergence behavior of POCS-ICE was also shown to be more stable.

CONCLUSION

POCS-ICE can inherently and reliably correct motion-induced phase errors in navigator-free multishot DWI, and it is easier to determine the stopping criterion without manual interventions. The improved spatial resolution and image resolvability are beneficial to study of brain microstructures and physiological features for neuroscience.

3-D residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.

Reproducibility of corticospinal diffusion tensor tractography in normal subjects and hemiparetic stroke patients

PURPOSE

The reproducibility of corticospinal diffusion tensor tractography (DTT) for a guideline is important before longitudinal monitoring of the therapy effects in stroke patients. This study aimed to establish the reproducibility of corticospinal DTT indices in healthy subjects and chronic hemiparetic stroke patients.

MATERIALS AND METHODS

Written informed consents were obtained from 10 healthy subjects (mean age 25.8 ± 6.8 years), who underwent two scans in one session plus the third scan one week later, and from 15 patients (mean age 47.5 ± 9.1 years, 6-60 months after the onset of stroke, NIHSS scores between 9 and 20) who were scanned thrice on separate days within one month. Diffusion-tensor imaging was performed at 3T with 25 diffusion directions. Corticospinal tracts were reconstructed using fiber assignment by continuous tracking without and with motion/eddy-current corrections. Intra- and inter-rater as well as intra- and inter-session variations of the DTT derived indices (fiber number, apparent diffusion coefficient (ADC), and fractional anisotropy (FA)) were assessed.

RESULTS

Intra-session and inter-session coefficients of variations (CVs) are small for FA (1.13-2.09%) and ADC (0.45-1.64%), but much larger for fiber number (8.05-22.4%). Inter-session CVs in the stroke side of patients (22.4%) are higher than those in the normal sides (18.0%) and in the normal subjects (14.7%). Motion/eddy-current correction improved inter-session reproducibility only for the fiber number of the infarcted corticospinal tract (CV reduced from 22.4% to 14.1%).

CONCLUSION

The fiber number derived from corticospinal DTT shows substantially lower precision than ADC and FA, with infarcted tracts showing lower reproducibility than the healthy tissues.

A hitchhiker's guide to diffusion tensor imaging

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Prospective and retrospective high order eddy current mitigation for diffusion weighted echo planar imaging

PURPOSE

The proposed method is aimed at reducing eddy current (EC) induced distortion in diffusion weighted echo planar imaging, without the need to perform further image coregistration between diffusion weighted and T2 images. These ECs typically have significant high order spatial components that cannot be compensated by preemphasis.

THEORY AND METHODS

High order ECs are first calibrated at the system level in a protocol independent fashion. The resulting amplitudes and time constants of high order ECs can then be used to calculate imaging protocol specific corrections. A combined prospective and retrospective approach is proposed to apply correction during data acquisition and image reconstruction.

RESULTS

Various phantom, brain, body, and whole body diffusion weighted images with and without the proposed method are acquired. Significantly reduced image distortion and misregistration are consistently seen in images with the proposed method compared with images without.

CONCLUSION

The proposed method is a powerful (e.g., effective at 48 cm field of view and 30 cm slice coverage) and flexible (e.g., compatible with other image enhancements and arbitrary scan plane) technique to correct high order ECs induced distortion and misregistration for various diffusion weighted echo planar imaging applications, without the need for further image post processing, protocol dependent prescan, or sacrifice in signal-to-noise ratio.

A comparative evaluation of quantitative neuroimaging measurements of brain status in HIV infection

Diffusion tensor imaging (DTI), magnetization transfer imaging (MT) and automated brain volumetry were used to summarize brain involvement in human immunodeficiency virus (HIV) infection. A multiparametric neuroimaging protocol was implemented at 1.5 T in 10 HIV+ and 24 controls. Various summary parameters were calculated based on DTI, MT, and automated brain volumetry. The magnitude of the difference, as well as the between-group discrimination, was determined for each measure. Bivariate correlations were computed and redundancy among imaging parameters was examined by principal factor analysis. Significant or nearly significant differences were found for most measures. Large Cohen's d effect sizes were indicated for mean diffusivity (MD), fractional anisotropy (FA), magnetization transfer ratio (MTR) and gray matter volume fraction (GM). Between-group discrimination was excellent for FA and MTR and acceptable for MD. Correlations among all imaging parameters could be explained by three factors, possibly reflecting general atrophy, neuronal loss, and alterations. This investigation supports the utility of summary measurements of brain involvement in HIV infection. The findings also support assumptions concerning the enhanced sensitivity of DTI and MT to atrophic as well as alterations in the brain. These findings are broadly generalizable to brain imaging studies of physiological and pathological processes.

Diffusion tensor imaging of cerebral white matter integrity in cognitive aging

In this article we review recent research on diffusion tensor imaging (DTI) of white matter (WM) integrity and the implications for age-related differences in cognition. Neurobiological mechanisms defined from DTI analyses suggest that a primary dimension of age-related decline in WM is a decline in the structural integrity of myelin, particularly in brain regions that myelinate later developmentally. Research integrating behavioral measures with DTI indicates that WM integrity supports the communication among cortical networks, particularly those involving executive function, perceptual speed, and memory (i.e., fluid cognition). In the absence of significant disease, age shares a substantial portion of the variance associated with the relation between WM integrity and fluid cognition. Current data are consistent with one model in which age-related decline in WM integrity contributes to a decreased efficiency of communication among networks for fluid cognitive abilities. Neurocognitive disorders for which older adults are at risk, such as depression, further modulate the relation between WM and cognition, in ways that are not as yet entirely clear. Developments in DTI technology are providing a new insight into both the neurobiological mechanisms of aging WM and the potential contribution of DTI to understanding functional measures of brain activity. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

Dynamic correction of artifacts due to susceptibility effects and time-varying eddy currents in diffusion tensor imaging

In diffusion tensor imaging (DTI), spatial and temporal variations of the static magnetic field (B(0)) caused by susceptibility effects and time-varying eddy currents result in severe distortions, blurring, and misregistration artifacts, which in turn lead to errors in DTI metrics and in fiber tractography. Various correction methods have been proposed, but typically assume that the eddy current-induced magnetic field can be modeled as a constant or a single exponential decay within the DTI readout window. Here, we show that its temporal dependence is more complex because of the interaction of multiple eddy currents with different time constants, but that it remains very consistent over time. As such, we propose a novel dynamic B(0) mapping and off-resonance correction method that measures the exact spatial, temporal, and diffusion-weighting direction dependence of the susceptibility- and eddy current-induced magnetic fields to effectively and efficiently correct for artifacts caused by both susceptibility effects and time-varying eddy currents, thereby resulting in a high spatial fidelity and accuracy.

Distortion correction of high b-valued and high angular resolution diffusion images using iterative simulated images

High b-valued diffusion-weighted images (DWI), which were designed to solve fiber-crossing problems, are susceptible to many artifacts and distortions. Since DWIs with different diffusion gradients produce dissimilar intensity contrasts, and since the distortion is nonlinear when multiple artifactual sources are intermixed, the mutual information-based affine registration may not be adequate for precise correction of distortions in DWIs, especially for images acquired with high b-values. To overcome these problems, we proposed an iterative image registration technique through which simulated DWIs are generated, driven from a diffusion tensor estimate, as targets for measured DWIs in the registration. Since simulated DWIs have similar intensity profiles to those of measured DWIs and the same geometric profiles as b(0)-images, an iterative procedure enables intensity-based nonlinear registration. As a pre-processing step, we also proposed a motion detection and sub-volume utilization for interleaved volumes. Performance evaluation with high b-valued DWIs for high angular resolution diffusion imaging and diffusion kurtosis imaging showed that the proposed method had a superior advantage over the conventional registration technique.

Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection

Quantification of normal brain maturation is a crucial step in understanding developmental abnormalities in brain anatomy and function. The aim of this study was to develop atlas-based tools for time-dependent quantitative image analysis, and to characterize the anatomical changes that occur from 2years of age to adulthood. We used large deformation diffeomorphic metric mapping to register diffusion tensor images of normal participants into the common coordinates and used a pre-segmented atlas to segment the entire brain into 176 structures. Both voxel- and atlas-based analyses reported a structure that showed distinctive changes in terms of its volume and diffusivity measures. In the white matter, fractional anisotropy (FA) linearly increased with age in logarithmic scale, while diffusivity indices, such as apparent diffusion coefficient (ADC), and axial and radial diffusivity, decreased at a different rate in several regions. The average, variability, and the time course of each measured parameter are incorporated into the atlas, which can be used for automated detection of developmental abnormalities. As a demonstration of future application studies, the brainstem anatomy of cerebral palsy patients was evaluated and the altered anatomy was delineated.

Temporal lobe white matter asymmetry and language laterality in epilepsy patients

Recent studies using diffusion tensor imaging (DTI) have advanced our knowledge of the organization of white matter subserving language function. It remains unclear, however, how DTI may be used to predict accurately a key feature of language organization: its asymmetric representation in one cerebral hemisphere. In this study of epilepsy patients with unambiguous lateralization on Wada testing (19 left and 4 right lateralized subjects; no bilateral subjects), the predictive value of DTI for classifying the dominant hemisphere for language was assessed relative to the existing standard-the intra-carotid Amytal (Wada) procedure. Our specific hypothesis is that language laterality in both unilateral left- and right-hemisphere language dominant subjects may be predicted by hemispheric asymmetry in the relative density of three white matter pathways terminating in the temporal lobe implicated in different aspects of language function: the arcuate (AF), uncinate (UF), and inferior longitudinal fasciculi (ILF). Laterality indices computed from asymmetry of high anisotropy AF pathways, but not the other pathways, classified the majority (19 of 23) of patients using the Wada results as the standard. A logistic regression model incorporating information from DTI of the AF, fMRI activity in Broca's area, and handedness was able to classify 22 of 23 (95.6%) patients correctly according to their Wada score. We conclude that evaluation of highly anisotropic components of the AF alone has significant predictive power for determining language laterality, and that this markedly asymmetric distribution in the dominant hemisphere may reflect enhanced connectivity between frontal and temporal sites to support fluent language processes. Given the small sample reported in this preliminary study, future research should assess this method on a larger group of patients, including subjects with bi-hemispheric dominance.

Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T

Compared with conventional MRI, diffusion tensor imaging (DTI) is more prone to thermal noise and motion. Optimized sampling schemes have been proposed that reduce the propagation of noise. At 3 T, however, motion may play a more dominant role than noise. Although the effects of noise at 3 T are less compared with 1.5 T because of the higher signal-to-noise ratio, motion is independent of field strength and will persist. To improve the reliability of clinical DTI at 3 T, it is important to know to what extent noise and motion contribute to the uncertainties of the DTI indices. In this study, the effects of noise- and motion-related signal uncertainties are disentangled using in vivo measurements and computer simulations. For six clinically standard available sampling schemes, the reproducibility was assessed in vivo, with and without motion correction applied. Additionally, motion and noise simulations were performed to determine the relative contributions of motion and noise to the uncertainties of the mean diffusivity (MD) and fractional anisotropy (FA). It is shown that the contributions of noise and motion are of the same order of magnitude at 3 T. Similar to the propagation of noise, the propagation of motion-related signal perturbations is also influenced by the choice of sampling scheme. Sampling schemes with only six diffusion directions demonstrated a lower reproducibility compared with schemes with 15 and 32 directions and feature a positive bias for the FA in relatively isotropic tissue. Motion correction helps improving the precision and accuracy of DTI indices.

Cerebral white matter integrity and cognitive aging: contributions from diffusion tensor imaging

The integrity of cerebral white matter is critical for efficient cognitive functioning, but little is known regarding the role of white matter integrity in age-related differences in cognition. Diffusion tensor imaging (DTI) measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner. This review considers DTI studies of aging and their implications for understanding adult age differences in cognitive performance. Decline in white matter integrity contributes to a disconnection among distributed neural systems, with a consistent effect on perceptual speed and executive functioning. The relation between white matter integrity and cognition varies across brain regions, with some evidence suggesting that age-related effects exhibit an anterior-posterior gradient. With continued improvements in spatial resolution and integration with functional brain imaging, DTI holds considerable promise, both for theories of cognitive aging and for translational application.

Patterns of fractional anisotropy changes in white matter of cerebellar peduncles distinguish spinocerebellar ataxia-1 from multiple system atrophy and other ataxia syndromes

AIM

To determine prospectively if qualitative and quantitative diffusion tensor imaging (DTI) metrics of white matter integrity are better than conventional magnetic resonance imaging (MRI) metrics for discriminating cerebellar diseases.

METHODS

Conventional MRI images from 31 consecutive patients with ataxia and 12 controls were interpreted by a neuroradiologist given only a clinical indication of ataxia. An expert ataxologist, blinded to radiological findings, determined the clinical diagnosis, as well as ataxia severity and asymmetry for each patient. For qualitative analysis, a comparison of the cerebellar white matter in ataxic vs. control patients was made by visual inspection of directionally encoded color (DEC) images. For quantitative analysis, segmentation of the cerebellar white matter in the inferior, middle, and superior cerebellar peduncles (ICP, MCP, and SCP) was attempted using three methods: a region of interest method, a deterministic DTI tractography (DDT) method, and a probabilistic DTI tractography (PDT) method. A statistical comparison of the average fractional anisotropy (FA) in these tracts was made between subject groups, and correlated to clinical diagnosis, severity, and asymmetry.

RESULTS

Of the 31 consecutive patients with ataxia, the two largest subgroups had a clinical diagnosis of multiple system atrophy (cerebellar subtype; MSA-C), and spinocerebellar ataxia-1 (SCA1). Conventional MRI features, such as degree of pontocerebellar atrophy, correlated with ataxia severity, but were neither sensitive nor specific for the ataxia subtypes. PDT was the most accurate and least variable method of the three methods used for determining FA, especially in the ICP. Average FA in all ataxic patients was significantly decreased in the MCP, SCP and ICP and this decrease correlated to disease severity. Asymmetric ataxia correlated to proportionately larger contralateral MCP, ICP and SCP FA values. MCP, ICP, and SCP FA difference values formed distinct clusters that distinguished MSA-C from SCA-1, and other ataxia syndromes.

CONCLUSIONS

Qualitative and quantitative reductions in DTI metrics of white matter integrity in the cerebellar peduncles correlated better to clinical features of patients with sporadic and hereditary ataxias than conventional structural MRI measures of pontocerebellar atrophy.

Correction of B0 susceptibility induced distortion in diffusion-weighted images using large-deformation diffeomorphic metric mapping

Geometric distortion caused by B0 inhomogeneity is one of the most important problems for diffusion-weighted images (DWI) using single-shot, echo planar imaging (SS-EPI). In this study, large-deformation, diffeomorphic metric mapping (LDDMM) algorithm has been tested for the correction of geometric distortion in diffusion tensor images (DTI). Based on data from nine normal subjects, the amount of distortion caused by B0 susceptibility in the 3-T magnet was characterized. The distortion quality was validated by manually placing landmarks in the target and DTI images before and after distortion correction. The distortion was found to be up to 15 mm in the population-averaged map and could be more than 20 mm in individual images. Both qualitative demonstration and quantitative statistical results suggest that the highly elastic geometric distortion caused by spatial inhomogeneity of the B0 field in DTI using SS-EPI can be effectively corrected by LDDMM. This postprocessing method is especially useful for correcting existent DTI data without phase maps.

Single-shot dual-z-shimmed sensitivity-encoded spiral-in/out imaging for functional MRI with reduced susceptibility artifacts

Blood oxygenation level-dependent (BOLD) functional MRI (fMRI) can be severely hampered by signal loss due to susceptibility-induced static magnetic field (B(0)) inhomogeneities near air/tissue interfaces. A single-shot spiral-in/out sequence with a z-shim gradient embedded between the two acquisitions was previously proposed to efficiently recover the signal. However, despite promising results, this technique had several limitations, which are addressed here as follows. First, by adding a second z-shim gradient before the spiral-in acquisition and optimizing both z-shim gradients slice-by-slice, a significantly more uniform signal recovery can be achieved. Second, by acquiring a B(0) map, the optimal z-shim gradients can be directly, efficiently, and accurately determined for each subject. Third, by complementing the z-shimming approach with sensitivity encoding (SENSE), the in-plane spatial resolution can be increased and, hence, susceptibility artifacts further reduced, while maintaining a high temporal resolution for fMRI applications. These advantages are demonstrated in human functional studies.

Integrated SENSE DTI with correction of susceptibility- and eddy current-induced geometric distortions

Diffusion tensor imaging (DTI) is vulnerable to geometric distortions caused by subject-dependent susceptibility effects and diffusion-weighting direction-dependent eddy currents. Although the introduction of sensitivity encoding (SENSE) has reduced the overall distortions for the same imaging matrix size, this benefit is offset by the increasing demand for higher spatial resolution. Thus, significant distortions remain or are exacerbated in high-resolution SENSE DTI acquisitions. While the susceptibility-induced distortions cause global spatial misregistration, the direction-dependent eddy current-induced distortions cause misregistration among different diffusion-weighted images, leading to errors in the derivation of the diffusion tensor in virtually all voxels, and consequently in resulting diffusion parameters as well as in fiber tracking. Here, we apply a comprehensive approach that corrects for both susceptibility- and eddy current-induced distortions to high-resolution SENSE DTI acquisitions, and demonstrate its effectiveness, efficiency, and reliability in vivo as well as its advantages over a twice-refocused spin-echo sequence. This method should find increased use in modern DTI experiments where SENSE acquisitions are commonly used.

Elevating tensor rank increases anisotropy in brain areas associated with intra-voxel orientational heterogeneity (IVOH): a generalised DTI (GDTI) study

Rank-2 tensors are unable to represent multi-modal diffusion associated with intra-voxel orientational heterogeneity (IVOH), which occurs where axons are incoherently oriented, such as where bundles intersect or diverge. Under this condition, they are oblate or spheroidally shaped, resulting in artefactually low anisotropy, potentially masking reduced axonal density, myelinisation and integrity. Higher rank tensors can represent multi-modal diffusion, and suitable metrics such as generalised anisotropy (GA) and scaled entropy (SE) have been introduced. The effect of tensor rank was studied through simulations, and analysing high angular resolution diffusion imaging (HARDI) data from two volunteers, fit with rank-2, rank-4 and rank-6 tensors. The variation of GA and SE as a function of rank was investigated through difference maps and region of interest (ROI)-based comparisons. Results were correlated with orientation distribution functions (ODF) reconstructed with q-ball, and with colour-maps of the principal and second eigenvectors. Simulations revealed that rank-4 tensors are able to represent multi-modal diffusion, and that increasing rank further has a minor effect on measurements. IVOH was detected in subcortical regions of the corona radiata, along the superior longitudinal fasciculus, in the radiations of the genu of the corpus callosum, in peritrigonal white matter and along the inferior fronto-occipital and longitudinal fascicula. In these regions, elevating tensor rank increased anisotropy. This was also true for the corpus callosum, cingulum and anterior limb of the internal capsule, where increasing tensor rank resulted in patterns that, although mono-modal, were more anisotropic. In these regions the second eigenvector was coherently oriented. As rank-4 tensors have only 15 distinct elements, they can be determined without acquiring a large number of directions. By removing artefactual underestimation of anisotropy, their use may increase the sensitivity to pathological change.

Measuring anisotropic brain diffusion in three and six directions: influence of the off-diagonal tensor elements

Diffusion tensor imaging (DTI) has been proposed for examination of cerebral white matter. However, this measurement needs sophisticated postprocessing and is susceptible to eddy current artefacts. The aim of this study was to examine whether diffusion measured in three anatomically well defined directions provides full and reliable information on diffusion anisotropy. Measurements were performed in water and gelatine phantoms and in 14 healthy volunteers. Diffusion was measured in six independent directions. For the full tensor DTI we diagonalised the diffusion tensor, for measurements with three directions we used only the diagonal elements. We then calculated the diffusion trace and the linear anisotropy index (AIl). We measured a slight anisotropy in the phantoms, which was larger in the case of the full tensor DTI (AIl = 0.022) then for the three orthogonal diffusion directions (0.008-0.019). The linear anisotropy index measured in white matter regions within the right and left hemisphere ranged between 0.33 and 0.42. AIl values were moderately correlated between right and left hemisphere regions (correlation factor: 0.35-0.64). DTI using the full tensor information is more susceptible to systematic errors resulting from eddy current effects than the measurement of diffusion in three orthogonal directions. However, in the latter method the anisotropy index is systematically underestimated in anatomical structures that do not exhibit a principal diffusion parallel to one of the diffusion directions. Therefore it is recommended to use the full tensor method together with sophisticated methods for eddy current correction.