Diffusion tensor imaging and axonal tracking in the human brainstem

Outcome Prediction by Diffusion Tensor Imaging (DTI) in Patients with Traumatic Injuries of the Median Nerve

Background/Objectives: The accurate quantification of peripheral nerve axonal regeneration after injury is critically important. Current strategies are limited to detecting early reinnervation. DTI is an MRI modality permitting the assessment of fractional anisotropy, which increases with axonal regeneration. The aim of this pilot study is to evaluate DTI as a potential predictive factor of clinical outcome after median nerve section and microsurgical repair. Methods: We included 10 patients with a complete section of the median nerve, who underwent microsurgical repair up to 7 days after injury. The follow-up period was 1 year, including the current strategy with clinical visits, the Rosén-Lundborg score and electroneuromyography. Additionally, DTI MRI of the injured wrist was planned 1, 3 and 12 months post-operatively and once for the contralateral wrist. Results: The interobserver reliability of DTI measures was almost perfect (ICC 0.802). We report an early statistically significant increase in the fractional anisotropy value after median nerve repair, especially in the region located distal to the suture. Meanwhile, Rosén-Lundborg score gradually increased between the third and sixth month, and continued to increase between the sixth and twelfth month. Conclusions: DTI outcomes three months post-operation could offer greater predictability compared to current strategies. This would enable faster decision-making regarding the need for a potential re-operation in cases of inadequate early reinnervation.

Color Maps: Facilitating the Clinical Impact of Quantitative MRI

Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Diffusion tensor imaging within the healthy cervical spinal cord: Within- participants reliability and measurement error

BACKGROUND

Diffusion tensor imaging (DTI) is a promising technique for the visualization of the cervical spinal cord (CSC) in vivo. It provides information about the tissue structure of axonal white matter, and it is thought to be more sensitive than other MR imaging techniques for the evaluation of damage to tracts in the spinal cord.

AIM

The purpose of this study was to determine the within-participants reliability and error magnitude of measurements of DTI metrics in healthy human CSC.

METHODS

A total of twenty healthy controls (10 male, mean age: 33.9 ± 3.5 years, 10 females, mean age: 47.5 ± 14.4 years), with no family history of any neurological disorders or a contraindication to MRI scanning were recruited over a period of two months. Each participant was scanned twice with an MRI 3 T scanner using standard DTI sequences. Spinal Cord Toolbox (SCT) software was used for image post-processing. Data were first corrected for motion artefact, then segmented, registered to a template, and then the DTI metrics were computed. The within-participants coefficients of variation (CV%), the single and average within-participants intraclass correlation coefficients (ICC) and Bland-Altman plots for WM, VC, DC and LC fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were determined for the cervical spinal cord (between the 2nd and 5th cervical vertebrae).

RESULTS

DTI metrics showed poor to excellent within-participants reliability for both single and average ICC and moderate to high reproducibility for CV%, all variation dependent on the location of the ROI. The BA plots showed good within-participants agreement between the scan-rescan values.

CONCLUSION

Results from this reliability study demonstrate that clinical trials using the DTI technique are feasible and that DTI, in particular regions of the cord is suitable for use for the monitoring of degenerative WM changes.

Assessment of corticospinal tract remodeling based on diffusion tensor imaging in the treatment of motor dysfunction after ischemic stroke by acupuncture: A meta-analysis

BACKGROUND

To investigate the efficacy of acupuncture in improving motor dysfunction after ischemic stroke (IS) and to investigate the effect of acupuncture on corticospinal tract (CST) remodeling using diffusion tensor imaging.

METHODS

Published literature on the effect of acupuncture on CST remodeling after IS using diffusion tensor imaging in the form of randomized controlled trials (RCTs) were systematically retrieved and screened from Cochrane Library, Web of Science, PubMed, Embase, CNKI, CBM, VIP, and Wanfang databases from inception to December 2022. The methodological quality of the included studies was critically and independently evaluated by 2 reviewers using the Cochrane Risk of Bias Assessment Tool for RCTs. The correlated data were extracted using the pre-designed form, and all analyses were performed using Reviewer Manager version 5.4.

RESULTS

Eleven eligible RCTs involving 459 patients were eventually included. The combined evidence results showed that the acupuncture group significantly improved patients' National Institute of Health stroke scale, Fugl-Meyer Assessment Scale, and Barthel index compared with conventional medical treatment. The acupuncture group significantly promoted remodeling of the CST, as reflected by an increase in fractional anisotropy (FA) throughout the CST [MD = 0.04, 95% CI (0.02, 0.07), P = .001], and in addition, subgroup analysis showed that the acupuncture group significantly improved FA in the infarct area compared with conventional medical treatment at around 4 weeks [MD = 0.04, 95% CI (0.02, 0.06), P = .0002] and FA of the affected cerebral peduncle [MD = 0.03, 95% CI (0.00, 0.07), P = .02]. Also, compared with conventional medical treatment, the acupuncture group significantly increased average diffusion coefficient of the affected cerebral peduncle [MD = -0.21, 95% CI (-0.28, -0.13), P < .00001].

CONCLUSION

The results of the meta-analysis suggest that acupuncture therapy can improve the clinical manifestations of motor dysfunction in patients after IS and advance a possibly beneficial effect on CST remodeling. However, due to the number and quality of eligible studies, these findings need to be further validated in more standardized, rigorous, high-quality clinical trials.

Deep Learning Methods for Identification of White Matter Fiber Tracts: Review of State-of-the-Art and Future Prospective

Quantitative analysis of white matter fiber tracts from diffusion Magnetic Resonance Imaging (dMRI) data is of great significance in health and disease. For example, analysis of fiber tracts related to anatomically meaningful fiber bundles is highly demanded in pre-surgical and treatment planning, and the surgery outcome depends on accurate segmentation of the desired tracts. Currently, this process is mainly done through time-consuming manual identification performed by neuro-anatomical experts. However, there is a broad interest in automating the pipeline such that it is fast, accurate, and easy to apply in clinical settings and also eliminates the intra-reader variabilities. Following the advancements in medical image analysis using deep learning techniques, there has been a growing interest in using these techniques for the task of tract identification as well. Recent reports on this application show that deep learning-based tract identification approaches outperform existing state-of-the-art methods. This paper presents a review of current tract identification approaches based on deep neural networks. First, we review the recent deep learning methods for tract identification. Next, we compare them with respect to their performance, training process, and network properties. Finally, we end with a critical discussion of open challenges and possible directions for future works.

Diffusion pore imaging in the presence of extraporal water

Diffusion-weighted imaging (DWI) is a powerful, non-invasive tool which is widely used in clinical routine. Mostly, apparent diffusion coefficient maps are acquired, which cannot be related directly to cellular structure. More recently it was shown that DWI is able to reconstruct pore shapes using a specialized magnetic field gradient scheme so that cell size distributions may be obtained. So far, artificial systems have been used for experimental demonstration without extraporal signal components and relatively low gradient amplitudes. The aim of this study was to investigate the feasibility of diffusion pore imaging in the presence of extraporal fluids and to develop correction methods for the effects arising from extraporal signal contributions. Monte Carlo simulations and validation experiments on a 14.1 T NMR spectrometer equipped with a dedicated diffusion probe head were performed. Both by using a filter gradient approach suppressing extraporal signal components as well as by using post-processing methods relying on the Gaussian phase approximation, it was possible to reconstruct pore space functions in the presence of extraporal fluids with little to no deviations from the expectations. These results may be a significant step towards application of diffusion pore imaging to biological samples.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Brainstem Diffusion Tensor Tractography and Clinical Applications in Pain

The brainstem is one of the most vulnerable brain structures in many neurological conditions, such as pain, sleep problems, autonomic dysfunctions, and neurodegenerative disorders. Diffusion tensor imaging and tractography provide structural details and quantitative measures of brainstem fiber pathways. Until recently, diffusion tensor tractographic studies have mainly focused on whole-brain MRI acquisition. Due to the brainstem's spatial localization, size, and tissue characteristics, and limits of imaging techniques, brainstem diffusion MRI poses particular challenges in tractography. We provide a brief overview on recent advances in diffusion tensor tractography in revealing human pathways connecting the brainstem to the subcortical regions (e.g., basal ganglia, mesolimbic, basal forebrain), and cortical regions. Each of these pathways contains different distributions of fiber tracts from known neurotransmitter-specific nuclei in the brainstem. We compare the brainstem tractographic approaches in literature and our in-lab developed automated brainstem tractography in terms of atlas building, technical advantages, and neuroanatomical implications on neurotransmitter systems. Lastly, we summarize recent investigations of using brainstem tractography as a promising tool in association with pain.

Investigating the Anatomy and Microstructure of the Dentato-rubro-thalamic and Subthalamo-ponto-cerebellar Tracts in Parkinson's Disease

Cerebellar-thalamic connections play a central role in deep brain stimulation-based treatment of tremor syndromes. Here, we used diffusion Magnetic Resonance Imaging (MRI) tractography to delineate the main cerebellar peduncles as well as two main white matter tracts that connect the cerebellum with the thalamus, the dentato-rubro-thalamic tract (DRTT) and the subthalamo-ponto-cerebellar tract (SPCT). We first developed a reconstruction protocol in young healthy adults with high-resolution diffusion imaging data and then demonstrate feasibility of transferring this protocol to clinical studies using standard diffusion MRI data from a cohort of patients with Parkinson's disease (PD) and their matched healthy controls. The tracts obtained closely corresponded to the previously described anatomical pathways and features of the DRTT and the SPCT. Second, we investigated the microstructure of these tracts with fractional anisotropy (FA), radial diffusivity (RD), and hindrance modulated orientational anisotropy (HMOA) in patients with PD and healthy controls. By reducing dimensionality of both the microstructural metrics and the investigated cerebellar and cerebellar-thalamic tracts using principal component analyses, we found global differences between patients with PD and controls, suggestive of higher fractional anisotropy, lower radial diffusivity, and higher hindrance modulated orientational anisotropy in patients. However, separate analyses for each of the tracts did not yield any significant differences. Our findings contribute to the characterization of the distinct anatomical connections between the cerebellum and the diencephalon. Microstructural differences between patients and controls in the cerebellar pathways suggest involvement of these structures in PD, complementing previous functional and diffusion imaging studies.

An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.

Physical and digital phantoms for validating tractography and assessing artifacts

Fiber tractography is widely used to non-invasively map white-matter bundles in vivo using diffusion-weighted magnetic resonance imaging (dMRI). As it is the case for all scientific methods, proper validation is a key prerequisite for the successful application of fiber tractography, be it in the area of basic neuroscience or in a clinical setting. It is well-known that the indirect estimation of the fiber tracts from the local diffusion signal is highly ambiguous and extremely challenging. Furthermore, the validation of fiber tractography methods is hampered by the lack of a real ground truth, which is caused by the extremely complex brain microstructure that is not directly observable non-invasively and that is the basis of the huge network of long-range fiber connections in the brain that are the actual target of fiber tractography methods. As a substitute for in vivo data with a real ground truth that could be used for validation, a widely and successfully employed approach is the use of synthetic phantoms. In this work, we are providing an overview of the state-of-the-art in the area of physical and digital phantoms, answering the following guiding questions: "What are dMRI phantoms and what are they good for?", "What would the ideal phantom for validation fiber tractography look like?" and "What phantoms, phantom datasets and tools used for their creation are available to the research community?". We will further discuss the limitations and opportunities that come with the use of dMRI phantoms, and what future direction this field of research might take.

Prospective Quantitative Neuroimaging Analysis of Putative Temporal Lobe Epilepsy

Purpose: A prospective study of individual and combined quantitative imaging applications for lateralizing epileptogenicity was performed in a cohort of consecutive patients with a putative diagnosis of mesial temporal lobe epilepsy (mTLE). Methods: Quantitative metrics were applied to MRI and nuclear medicine imaging studies as part of a comprehensive presurgical investigation. The neuroimaging analytics were conducted remotely to remove bias. All quantitative lateralizing tools were trained using a separate dataset. Outcomes were determined after 2 years. Of those treated, some underwent resection, and others were implanted with a responsive neurostimulation (RNS) device. Results: Forty-eight consecutive cases underwent evaluation using nine attributes of individual or combinations of neuroimaging modalities: 1) hippocampal volume, 2) FLAIR signal, 3) PET profile, 4) multistructural analysis (MSA), 5) multimodal model analysis (MMM), 6) DTI uncertainty analysis, 7) DTI connectivity, and 9) fMRI connectivity. Of the 24 patients undergoing resection, MSA, MMM, and PET proved most effective in predicting an Engel class 1 outcome (>80% accuracy). Both hippocampal volume and FLAIR signal analysis showed 76% and 69% concordance with an Engel class 1 outcome, respectively. Conclusion: Quantitative multimodal neuroimaging in the context of a putative mTLE aids in declaring laterality. The degree to which there is disagreement among the various quantitative neuroimaging metrics will judge whether epileptogenicity can be confined sufficiently to a particular temporal lobe to warrant further study and choice of therapy. Prediction models will improve with continued exploration of combined optimal neuroimaging metrics.

Reliability of the freehand region-of-interest method in quantitative cerebral diffusion tensor imaging

Background

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique used for evaluating changes in the white matter in brain parenchyma. The reliability of quantitative DTI analysis is influenced by several factors, such as the imaging protocol, pre-processing and post-processing methods, and selected diffusion parameters. The region-of-interest (ROI) method is most widely used of the post-processing methods because it is found in commercial software. The focus of our research was to study the reliability of the freehand ROI method using various intra- and inter-observer analyses.

Methods

This study included 40 neurologically healthy participants who underwent diffusion MRI of the brain with a 3 T scanner. The measurements were performed at nine different anatomical locations using a freehand ROI method. The data extracted from the ROIs included the regional mean values, intra- and inter-observer variability and reliability. The used DTI parameters were fractional anisotropy (FA), the apparent diffusion coefficient (ADC), and axial (AD) and radial (RD) diffusivity.

Results

The average intra-class correlation coefficient (ICC) of the intra-observer was found to be 0.9 (excellent). The single ICC results were excellent (> 0.8) or adequate (> 0.69) in eight out of the nine regions in terms of FA and ADC. The most reliable results were found in the frontobasal regions. Significant differences between age groups were also found in the frontobasal regions. Specifically, the FA and AD values were significantly higher and the RD values lower in the youngest age group (18–30 years) compared to the other age groups.

Conclusions

The quantitative freehand ROI method can be considered highly reliable for the average ICC and mostly adequate for the single ICC. The freehand method is suitable for research work with a well-experienced observer. Measurements should be performed at least twice in the same region to ensure that the results are sufficiently reliable. In our study, reliability was slightly undermined by artifacts in some regions such as the cerebral peduncle and centrum semiovale. From a clinical point of view, the results are most reliable in adults under the age of 30, when age-related changes in brain white matter have not yet occurred.

The total resection rate of glioma can be improved by the application of US-MRI fusion combined with contrast-enhanced ultrasound

OBJECTIVE

This study was performed to evaluate the diagnostic performance of ultrasound-magnetic resonance imaging (MRI) fusion combined with contrast-enhanced ultrasound and to explore its role in improving the total tumor resection rate.

METHODS

Between January 2018 and December 2018, 16 patients in the observation group and 23 patients in the control group were enrolled in this study. The tumor depth and brain shift distance were analyzed, as well as the peak intensity and microvessel density of different grades of gliomas in the observation group. Finally, we compared the difference in total resection rate between the observation and control groups.

RESULTS

Using ultrasound during operations, we found a significant negative correlation between brain shift distance and tumor depth, with correlation coefficient r=-0.868(P<0.05). In glioma, the peak intensity and microvessel density increased synchronously with glioma grade(r=0.806, P<0.05). The total resection rate of lesions was significantly higher in the observation group than in the control group (P<0.05).

CONCLUSIONS

The application of ultrasound-MRI fusion combined with contrast-enhanced ultrasound can improve the total resection rate of lesions, thus playing an important role in clinical practice.

Structural and resting state functional connectivity beyond the cortex

Mapping the structural and functional connectivity of the central nervous system has become a key area within neuroimaging research. While detailed network structures across the entire brain have been probed using animal models, non-invasive neuroimaging in humans has thus far been dominated by cortical investigations. Beyond the cortex, subcortical nuclei have traditionally been less accessible due to their smaller size and greater distance from radio frequency coils. However, major neuroimaging developments now provide improved signal and the resolution required to study these structures. Here, we present an overview of the connectivity between the amygdala, brainstem, cerebellum, spinal cord and the rest of the brain. While limitations to their imaging and analyses remain, we also provide some recommendations and considerations for mapping brain connectivity beyond the cortex.

Maturation and degeneration of the human brainstem across the adult lifespan

Brainstem tissue microstructural properties change across the adult lifespan. However, studies elucidating the biological processes that govern brainstem maturation and degeneration in-vivo are lacking. In the present work, conducted on a large cohort of 140 cognitively unimpaired subjects spanning a wide age range of 21 to 94 years, we implemented a multi-parameter approach to characterize the sex- and age differences. In addition, we examined regional correlations between myelin water fraction (MWF), a direct measure of myelin content, and diffusion tensor imaging indices, and transverse and longitudinal relaxation rates to evaluate whether these metrics provide information complementary to MWF. We observed region-dependent differences in myelin content and axonal density with age and found that both exhibit an inverted U-shape association with age in several brainstem substructures. We emphasize that the microstructural differences captured by our distinct MRI metrics, along with their weak associations with MWF, strongly indicate the potential of using these outcome measures in a multi-parametric approach. Furthermore, our results support the gain-predicts-loss hypothesis of tissue maturation and degeneration in the brainstem. Indeed, our results indicate that myelination follows a temporally symmetric time course across the adult life span, while axons appear to degenerate significantly more rapidly than they mature.

WIKIBrainStem: An online atlas to manually segment the human brainstem at the mesoscopic scale from ultrahigh field MRI

The brainstem is one of the most densely packed areas of the central nervous system in terms of gray, but also white, matter structures and, therefore, is a highly functional hub. It has mainly been studied by the means of histological techniques, which requires several hundreds of slices with a loss of the 3D coherence of the whole specimen. Access to the inner structure of the brainstem is possible using Magnetic Resonance Imaging (MRI), but this method has a limited spatial resolution and contrast in vivo. Here, we scanned an ex vivo specimen using an ultra-high field (11.7T) preclinical MRI scanner providing data at a mesoscopic scale for anatomical T2-weighted (100 µm and 185 µm isotropic) and diffusion-weighted imaging (300 µm isotropic). We then proposed a hierarchical segmentation of the inner gray matter of the brainstem and defined a set of rules for each segmented anatomical class. These rules were gathered in a freely accessible web-based application, WIKIBrainStem (https://fibratlas.univ-tours.fr/brainstems/index.html), for 99 structures, from which 13 were subdivided into 29 substructures. This segmentation is, to date, the most detailed one developed from ex vivo MRI of the brainstem. This should be regarded as a tool that will be complemented by future results of alternative methods, such as Optical Coherence Tomography, Polarized Light Imaging or histology… This is a mandatory step prior to segmenting multiple specimens, which will be used to create a probabilistic automated segmentation method of ex vivo, but also in vivo, brainstem and may be used for targeting anatomical structures of interest in managing some degenerative or psychiatric disorders.

Apparent exchange rate imaging: On its applicability and the connection to the real exchange rate

PURPOSE

Water exchange between the intracellular and extracellular space can be measured using apparent exchange rate (AXR) imaging. The aim of this study was to investigate the relationship between the measured AXR and the geometry of diffusion restrictions, membrane permeability, and the real exchange rate, as well as to explore the applicability of AXR for typical human measurement settings.

METHODS

The AXR measurements and the underlying exchange rates were simulated using the Monte Carlo method with different geometries, size distributions, packing densities, and a broad range of membrane permeabilities. Furthermore, the influence of SNR and sequence parameters was analyzed.

RESULTS

The estimated AXR values correspond to the simulated values and show the expected proportionality to membrane permeability, except for fast exchange (ie, AXR > 20 - 30 s - 1 ) and small packing densities. Moreover, it was found that the duration of the filter gradient must be shorter than 2 · AX R - 1 . In cell size and permeability distributions, AXR depends on the average surface-to-volume ratio, permeability, and the packing density. Finally, AXR can be reliably determined in the presence of orientation dispersion in axon-like structures with sufficient gradient sampling (ie, 30 gradient directions).

CONCLUSION

Currently used experimental settings for in vivo human measurements are well suited for determining AXR, with the exception of single-voxel analysis, due to limited SNR. The detection of changes in membrane permeability in diseased tissue is nonetheless challenging because of the AXR dependence on further factors, such as packing density and geometry, which cannot be disentangled without further knowledge of the underlying cell structure.

Visualization of cerebellar peduncles using diffusion tensor imaging

The cerebellum communicates with the cerebral cortex via the superior, middle, and inferior cerebellar peduncles (CPs). To preserve the structure and function of the brainstem and cerebellum, which is compressed in various pathological conditions, it is important to delineate the spatial interrelationship of the CPs for presurgical planning and intraoperative guidance. Diffusion tensor tractography (DTT) is a technique capable of depicting the major fiber bundles in CPs. However, routine use of this technology for brainstem visualization remains challenging due to the anatomical smallness and complexity of the brainstem and susceptibility-induced image distortions. Here, we attempt to visualize CPs using high-resolution DTT in a commercial equipment for the application of this technique in normal clinical settings. DTT and fast imaging employing steady-state acquisition-cycled phases (FIESTA) of the whole brainstem were performed. We rendered the DTT fiber bundle using a region-of-interest-based fiber tracking method onto the structural image generated in FIESTA by automatic image coregistration. Fibers of the CPs were clearly visualized by DTT. The DTT-FIESTA overlaid image revealed the cross-sectional and three-dimensional anatomy of the pyramidal tract and the ascending sensory fibers, in addition to the CPs. This could indicate a geometrical relationship of these fibers in the brainstem. The CPs could be visualized clearly using DTT within clinically acceptable scanning times. This method of visualizing the exact pathway of fiber bundles and cranial nerves in the skull base helps in the planning of surgical approaches.

Brain morphological and connectivity changes on MRI after stem cell therapy in a rat stroke model

In animal models of stroke, behavioral assessments could be complemented by a variety of neuroimaging studies to correlate them with recovery and better understand mechanisms of improvement after stem cell therapy. We evaluated morphological and connectivity changes after treatment with human mesenchymal stem cells (hMSCs) in a rat stroke model, through quantitative measurement of T₂-weighted images and diffusion tensor imaging (DTI). Transient middle cerebral artery occlusion rats randomly received PBS (PBS-only), FBS cultured hMSCs (FBS-hMSCs), or stroke patients’ serum cultured hMSCs (SS-hMSCs). Functional improvement was assessed using a modified neurological severity score (mNSS). Quantitative analyses of T₂-weighted ischemic lesion and ventricular volume changes were performed. Brain microstructure/connectivity changes were evaluated in the ischemic recovery area by DTI-derived microstructural indices such as relative fractional anisotropy (rFA), relative axial diffusivity (rAD), and relative radial diffusivity (rRD), and relative fiber density (rFD) analyses. According to mNSS results, the SS-hMSCs group showed the most prominent functional improvement. Infarct lesion volume of the SS-hMSCs group was significantly decreased at 2 weeks when compared to the PBS-only groups, but there were no differences between the FBS-hMSCs and SS-hMSCs groups. Brain atrophy was significantly decreased in the SS-hMSCs group compared to the other groups. In DTI, rFA and rFD values were significantly higher and rRD value was significant lower in the SS-hMSCs group and these microstructure/connectivity changes were correlated with T₂-weighted morphological changes. T₂-weighted volume alterations (ischemic lesion and brain atrophy), and DTI microstructural indices and rFD changes, were well matched with the results of behavioral assessment. These quantitative MRI measurements could be potential outcome predictors of functional recovery after treatment with stem cells for stroke.

Translational application of neuroimaging in major depressive disorder: a review of psychoradiological studies

Major depressive disorder (MDD) causes great decrements in health and quality of life with increments in healthcare costs, but the causes and pathogenesis of depression remain largely unknown, which greatly prevent its early detection and effective treatment. With the advancement of neuroimaging approaches, numerous functional and structural alterations in the brain have been detected in MDD and more recently attempts have been made to apply these findings to clinical practice. In this review, we provide an updated summary of the progress in translational application of psychoradiological findings in MDD with a specified focus on potential clinical usage. The foreseeable clinical applications for different MRI modalities were introduced according to their role in disorder classification, subtyping, and prediction. While evidence of cerebral structural and functional changes associated with MDD classification and subtyping was heterogeneous and/or sparse, the ACC and hippocampus have been consistently suggested to be important biomarkers in predicting treatment selection and treatment response. These findings underlined the potential utility of brain biomarkers for clinical practice.

Diffusion Tensor Imaging Color-Coded Maps: An Alternative to Tractography

INTRODUCTION

White matter tracts can be observed using tractograms generated from diffusion tensor imaging (DTI). However, the dependence of these white matter tract images on subjective variables, including how seed points are placed and the preferred level of fractional anisotropy, introduces interobserver inconsistency and potential lack of reliability. We propose that color-coded maps (CCM) generated from DTI can be a preferred method for the visualization of important white matter tracts, circumventing bias in preoperative brain tumor resection planning.

METHODS

DTI was acquired retrospectively in 25 patients with brain tumors. Lesions included 15 tumors of glial origin, 9 metastatic tumors, 2 meningiomas, and 1 cavernous angioma. Tractograms of the pyramidal tract and/or optic radiations, based on tumor location, were created by marking seed regions of interest using known anatomical locations. We compared the degree of tract involvement and white matter alteration between CCMs and tractograms. Neurological outcomes were obtained from chart reviews.

RESULTS

The pyramidal tract was evaluated in 20/25 patients, the visual tracts were evaluated in 10/25, and both tracts were evaluated in 5/25. In 19/25 studies, the same patterns of white matter alternations were found between the CCMs and tractograms. In the 6 patients where patterns differed, 2 tractograms were not useful in determining pattern alteration; in the remaining 4/6, no practical difference was seen in comparing the studies. Two patients were lost to follow-up. Thirteen patients were neurologically improved or remained intact after intervention. In these, 10 of the 13 patients showed tumor-induced white matter tract displacement on CCM. Twelve patients had no improvement of their preoperative deficit. In 9 of these 12 patients, CCM showed white matter disruption.

CONCLUSION

CCMs provide a convenient, practical, and objective method of visualizing white matter tracts, obviating the need for potentially subjective and time-consuming tractography. CCMs are at least as reliable as tractograms in predicting neurological outcomes after neurosurgical intervention.

Diffusion Tensor Imaging and Tractography Utilized in the Resection of a Midbrain Cavernous Malformation

Background: Diffusion tensor imaging (DTI) is a magnetic resonance–based imaging technique that can provide important information about the underlying structure and integrity of the white matter in the brain. Tractography, a DTI postprocessing technique, can provide a detailed model of individual white matter fiber tracts. Knowledge of these tracts may be beneficial in the surgical planning and execution for neurosurgical patients.

Case Report: We review the basic principles behind DTI and present an illustrative case in which DTI was used to delineate the relationship of eloquent white matter tracts to a cavernous malformation in a patient undergoing resection.

Conclusion: The use of DTI during preoperative planning allows the neurosurgeon to understand if a lesion is disrupting, infiltrating, or altering the course of local white matter tracts. With the combined use of DTI and intraoperative neuronavigation, the neurosurgeon can better identify and avoid white matter tracts, not only in the local area of resection but also during approach to the lesion, thereby reducing the risk of damage to vital cortical pathways and subsequent functional impairment.

Cerebellar Blood Flow and Gene Expression in Crossed Cerebellar Diaschisis after Transient Middle Cerebral Artery Occlusion in Rats

Crossed cerebellar diaschisis (CCD) is a state of hypoperfusion and hypometabolism in the contralesional cerebellar hemisphere caused by a supratentorial lesion, but its pathophysiology is not fully understood. We evaluated chronological changes in cerebellar blood flow (CbBF) and gene expressions in the cerebellum using a rat model of transient middle cerebral artery occlusion (MCAO). CbBF was analyzed at two and seven days after MCAO using single photon emission computed tomography (SPECT). DNA microarray analysis and western blotting of the cerebellar cortex were performed and apoptotic cells in the cerebellar cortex were stained. CbBF in the contralesional hemisphere was significantly decreased and this lateral imbalance recovered over one week. Gene set enrichment analysis revealed that a gene set for “oxidative phosphorylation” was significantly upregulated while fourteen other gene sets including “apoptosis”, “hypoxia” and “reactive oxygen species” showed a tendency toward upregulation in the contralesional cerebellum. MCAO upregulated the expressions of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) in the contralesional cerebellar cortex. The number of apoptotic cells increased in the molecular layer of the contralesional cerebellum. Focal cerebral ischemia in our rat MCAO model caused CCD along with enhanced expression of genes related to oxidative stress and apoptosis.

Sensorimotor white matter projections and disease severity in primary Restless Legs Syndrome/Willis-Ekbom disease: a multimodal DTI analysis

BACKGROUND

Restless Legs Syndrome, a potentially disabling sleep disorder, also known as Willis-Ekbom disease (RLS/WED), may be caused by loss of inhibitory modulation of descending central motor pathways, structural changes in the somatosensory cortex, abnormal connectivity between motor and sensory areas, as well as by subtle abnormalities in white matter micro-organization.

OBJECTIVE

To compare diffusion-tensor imaging (DTI) metrics in areas associated with sensory or motor function, as well as sensorimotor integration, between subjects with primary mild-to-severe RLS/WED and controls.

METHODS

DTI metrics were assessed in 38 subjects with RLS/WED (14 mild to moderate, 24 severe to very severe) and 24 healthy age-matched controls with whole-brain Tract Based Spatial Statistics (TBSS), Region-of-interest (ROI) and probabilistic tractography based analyses. The ROIs corresponded to the corticospinal tract (CST) at the level of the cerebral peduncle; the superior, middle and inferior cerebellar peduncles. Subgroup analyses were made according to the severity of RLS/WED symptoms. The corticospinal tract was evaluated with probabilistic tractography. We also explored associations between significant findings and severity of symptoms with the Spearman's correlation coefficient.

RESULTS

TBSS analysis revealed decreased axial diffusivity (AD) in the left posterior thalamic radiation in RLS/WED. In subjects with severe RLS/WED, AD was reduced in the left posterior corona radiata and this reduction was negatively correlated with severity of symptoms. ROI-based analysis showed that radial diffusivity (RD) was increased in the superior cerebellar peduncles of individuals with severe RLS/WED. Tractography did not show between-group or subgroup differences.

CONCLUSIONS

Our results are consistent with subtle white matter changes, prominently in RLS/WED subjects with more severe symptoms, in areas related to sensory or motor function, as well as to sensorimotor integration, compared to controls. These findings support the hypothesis, raised by prior pathophysiological studies, of defective integration within these networks.

Individual variations of the human corticospinal tract and its hand-related motor fibers using diffusion MRI tractography

The corticospinal tract (CST) is one of the most well studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many notable traumatic conditions and diseases such as stroke, spinal cord injury (SCI) or amyotrophic lateral sclerosis (ALS). With the advent of diffusion MRI and tractography the computational representation of the human CST in a 3D model became available. However, the representation of the entire CST and, specifically, the hand motor area has remained elusive. In this paper we propose a novel method, using manually drawn ROIs based on robustly identifiable neuroanatomic structures to delineate the entire CST and isolate its hand motor representation as well as to estimate their variability and generate a database of their volume, length and biophysical parameters. Using 37 healthy human subjects we performed a qualitative and quantitative analysis of the CST and the hand-related motor fiber tracts (HMFTs). Finally, we have created variability heat maps from 37 subjects for both the aforementioned tracts, which could be utilized as a reference for future studies with clinical focus to explore neuropathology in both trauma and disease states.

Right arcuate fasciculus and superior longitudinal fasciculus abnormalities in primary insomnia

Primary insomnia (PI) is a very common phenomenon and associated with functional impairments of attention, memory and mood regulation. However, its neurobiology is poorly understood. To date, the studies about integrity of white matter (WM) tracts in PI patients have been still rare. In the present study, we used Automated Fiber Quantification (AFQ), which reliably and efficiently quantified diffusion measurements at multiple locations along the WM trajectory based on diffusion tensor imaging (DTI), to assess WM diffusion properties differences between 23 PI patients and 32 matched healthy controls in 18 tracts. The relationships between neuroimaging differences and sleep behaviors were explored, including Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index Scale (ISI). Compared with healthy control group, right arcuate fasciculus (Arc) and superior longitudinal fasciculus (SLF) showed significant higher fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) along tract length in PI patients (FWE corrected, p < 0.01). Axial diffusivity (AD) for PI patients was higher in right Arc and lower in right SLF. Correlation analyses revealed that FA of right Arc and MD of right SLF were negatively correlated with PSQI score in PI patients, and AD of right Arc and FA of right SLF were positively correlated with PSQI score. Negative correlation was observed between FA of right Arc and AD of right SLF and ISI score in PI patients. Our findings can help us to improve the understanding of the neural mechanisms of primary insomnia at abnormalities in WM microstructure.

Direct evidence of the relationship between brain metastatic adenocarcinoma and white matter fibers: A fiber dissection and diffusion tensor imaging tractography study

It is commonly known that brain metastases usually have clear boundaries in magnetic resonance imaging. However, little is known regarding the trajectory of white matter fibers around the tumors, especially using the fiber dissection technique. Here, we focused on the anatomical interaction between white matter fibers and the tumor, using the fiber dissection in a postmortem brain with metastatic tumor and compared the findings with those of diffusion tensor imaging (DTI) tractography. One postmortem human brain hemisphere with metastatic adenocarcinoma in the Broca's area was dissected using fiber dissection following the Klingler's method. In order to compare the in vitro and in vivo results, additional brains from 15 patients with metastatic adenocarcinomas, the volumes of which were comparable to that of the adenocarcinoma in the brain used for fiber dissection, were analyzed using DTI tractographic reconstruction. Morphological findings of white matter bundles running around the tumor were compared between the two techniques. In the fiber dissection technique, the superior longitudinal fascicle, arcuate fascicle, and frontal aslant tract could be dissected, and the white matter bundles were curved and retracted to avoid the tumor. In all the cases analyzed, white matter fibers or streamlines surrounding the tumor avoided the lesion. Using the fiber dissection technique, this is the first direct evidence to elucidate the anatomy of white matter fibers affected by a metastatic brain. This suggests that brain metastatic adenocarcinoma is an intra-axial neoplasm with extra-axial white matter structures.

A Combination of Particle Swarm Optimization and Minkowski Weighted K-Means Clustering: Application in Lateralization of Temporal Lobe Epilepsy

K-Means is one of the most popular clustering algorithms that partitions observations into nonoverlapping subgroups based on a predefined similarity metric. Its drawbacks include a sensitivity to noisy features and a dependency of its resulting clusters upon the initial selection of cluster centroids resulting in the algorithm converging to local optima. Minkowski weighted K-Means (MWK-Means) addresses the issue of sensitivity to noisy features, but is sensitive to the initialization of clusters, and so the algorithm may similarly converge to local optima. Particle Swarm Optimization (PSO) uses a globalized search method to solve this issue. We present a hybrid Particle Swarm Optimization (PSO) + MWK-Means clustering algorithm to address all the above problems in a single framework, while maintaining benefits of PSO and MWK Means methods. This study investigated the utility of this approach in lateralizing the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Using MEG-CSI, we analyzed preoperative resting state MEG data from 17 adults TLE patients with Engel class I outcomes to determine coherence at 54 anatomical sites and compared the results with 17 age- and gender-matched controls. Fiber-tracking was performed through the same anatomical sites using DTI data. Indices of both MEG coherence and DTI nodal degree were calculated. A PSO + MWK-Means clustering algorithm was applied to identify the side of temporal lobe epileptogenicity and distinguish between normal and TLE cases. The PSO module was aimed at identifying initial cluster centroids and assigning initial feature weights to cluster centroids and, hence, transferring to the MWK-Means module for the final optimal clustering solution. We demonstrated improvements with the use of the PSO + MWK-Means clustering algorithm compared to that of K-Means and MWK-Means independently. PSO + MWK-Means was able to successfully distinguish between normal and TLE in 97.2% and 82.3% of cases for DTI and MEG data, respectively. It also lateralized left and right TLE in 82.3% and 93.6% of cases for DTI and MEG data, respectively. The proposed optimization and clustering methodology for MEG and DTI features, as they relate to focal epileptogenicity, would enhance the identification of the TLE laterality in cases of unilateral epileptogenicity.

Diffusion tensor tractography of brainstem fibers and its application in pain

Evaluation of brainstem pathways with diffusion tensor imaging (DTI) and tractography may provide insights into pathophysiologies associated with dysfunction of key brainstem circuits. However, identification of these tracts has been elusive, with relatively few in vivo human studies to date. In this paper we proposed an automated approach for reconstructing nine brainstem fiber trajectories of pathways that might be involved in pain modulation. We first performed native-space manual tractography of these fiber tracts in a small normative cohort of participants and confirmed the anatomical precision of the results using existing anatomical literature. Second, region-of-interest pairs were manually defined at each extracted fiber's termini and nonlinearly warped to a standard anatomical brain template to create an atlas of the region-of-interest pairs. The resulting atlas was then transformed non-linearly into the native space of 17 veteran patients' brains for automated brainstem tractography. Lastly, we assessed the relationships between the integrity levels of the obtained fiber bundles and pain severity levels. Fractional anisotropy (FA) measures derived using automated tractography reflected the respective tracts' FA levels obtained via manual tractography. A significant inverse relationship between FA and pain levels was detected within the automatically derived dorsal and medial longitudinal fasciculi of the brainstem. This study demonstrates the feasibility of DTI in exploring brainstem circuitries involved in pain processing. In this context, the described automated approach is a viable alternative to the time-consuming manual tractography. The physiological and functional relevance of the measures derived from automated tractography is evidenced by their relationships with individual pain severities.

A computational model of bidirectional axonal growth in micro-tissue engineered neuronal networks (micro-TENNs)

Micro-Tissue Engineered Neural Networks (Micro-TENNs) are living three-dimensional constructs designed to replicate the neuroanatomy of white matter pathways in the brain and are being developed as implantable micro-tissue for axon tract reconstruction, or as anatomically-relevant in vitro experimental platforms. Micro-TENNs are composed of discrete neuronal aggregates connected by bundles of long-projecting axonal tracts within miniature tubular hydrogels. In order to help design and optimize micro-TENN performance, we have created a new computational model including geometric and functional properties. The model is built upon the three-dimensional diffusion equation and incorporates large-scale uni- and bi-directional growth that simulates realistic neuron morphologies. The model captures unique features of 3D axonal tract development that are not apparent in planar outgrowth and may be insightful for how white matter pathways form during brain development. The processes of axonal outgrowth, branching, turning and aggregation/bundling from each neuron are described through functions built on concentration equations and growth time distributed across the growth segments. Once developed we conducted multiple parametric studies to explore the applicability of the method and conducted preliminary validation via comparisons to experimentally grown micro-TENNs for a range of growth conditions. Using this framework, the model can be applied to study micro-TENN growth processes and functional characteristics using spiking network or compartmental network modeling. This model may be applied to improve our understanding of axonal tract development and functionality, as well as to optimize the fabrication of implantable tissue engineered brain pathways for nervous system reconstruction and/or modulation.

Evidence of corticofugal tau spreading in patients with frontotemporal dementia

Common neurodegenerative diseases feature progressive accumulation of disease-specific protein aggregates in selectively vulnerable brain regions. Increasing experimental evidence suggests that misfolded disease proteins exhibit prion-like properties, including the ability to seed corruptive templating and self-propagation along axons. Direct evidence for transneuronal spread in patients, however, remains limited. To test predictions made by the transneuronal spread hypothesis in human tissues, we asked whether tau deposition within axons of the corticospinal and corticopontine pathways can be predicted based on clinical syndromes and cortical atrophy patterns seen in frontotemporal lobar degeneration (FTLD). Sixteen patients with Pick's disease, 21 with corticobasal degeneration, and 3 with FTLD-MAPT were included, spanning a range of clinical syndromes across the frontotemporal dementia (FTD) spectrum. Cortical involvement was measured using a neurodegeneration score, a tau score, and a composite score based on semiquantitative ratings and complemented by an MRI-based cortical atrophy W-map based on antemortem imaging. Midbrain cerebral peduncle and pontine base descending fibers were divided into three subregions, representing prefrontopontine, corticospinal, and parieto-temporo-occipital fiber pathways. Tau area fraction was calculated in each subregion and related to clinical syndrome and cortical measures. Within each clinical syndrome, there were predicted relationships between cortical atrophy patterns and axonal tau deposition in midbrain cerebral peduncle and pontine base. Between syndromes, contrasting and predictable patterns of brainstem axonal tau deposition emerged, with, for example, greater tau in prefrontopontine fibers in behavioral variant FTD and in corticospinal fibers in corticobasal syndrome. Finally, semiquantitative and quantitative cortical degeneration scores predicted brainstem axonal tau deposition based on anatomical principles. Taken together, these findings provide important human evidence in support of axonal tau spreading in patients with specific forms of tau-related neurodegeneration.

Age-Dependent White Matter Characteristics of the Cerebellar Peduncles from Infancy Through Adolescence

Cerebellum-cerebrum connections are essential for many motor and cognitive functions and cerebellar disorders are prevalent in childhood. The middle (MCP), inferior (ICP), and superior cerebellar peduncles (SCP) are the major white matter pathways that permit communication between the cerebellum and the cerebrum. Knowledge about the microstructural properties of these cerebellar peduncles across childhood is limited. Here, we report on a diffusion magnetic resonance imaging tractography study to describe age-dependent characteristics of the cerebellar peduncles in a cross-sectional sample of infants, children, and adolescents from newborn to 17 years of age (N = 113). Scans were collected as part of clinical care; participants were restricted to those whose scans showed no abnormal findings and whose history and exam had no risk factors for cerebellar abnormalities. A novel automated tractography protocol was applied. Results showed that mean tract-FA increased, while mean tract-MD decreased from infancy to adolescence in all peduncles. Rapid changes were observed in both diffusion measures in the first 24 months of life, followed by gradual change at older ages. The shape of the tract profiles was similar across ages for all peduncles. These data are the first to characterize the variability of diffusion properties both across and within cerebellar white matter pathways that occur from birth through later adolescence. The data represent a rich normative data set against which white matter alterations seen in children with posterior fossa conditions can be compared. Ultimately, the data will facilitate the identification of sensitive biomarkers of cerebellar abnormalities.

Gene-Related Cerebellar Neurodegeneration in SCA3/MJD: A Case-Controlled Imaging-Genetic Study

Background: Spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) is one of the nine polyglutamine (polyQ) diseases and is caused by a CAG repeat expansion within the coding sequence of the ATXN3 gene. Few multimodal imaging analyses of the macro- and micro-structural changes have been performed.

Methods: In the present study, we recruited 31 genetically-confirmed symptomatic SCA3/MJD patients and 31 healthy subjects as controls for a multimodal neuroimaging study using structural magnetic resonance imaging (sMRI), proton magnetic resonance spectroscopy (¹H-MRS) and diffusion tensor imaging (DTI).

Results: The SCA3/MJD patients displayed a significantly reduced of gray matter volume in the cerebellum, pons, midbrain and medulla, as well as inferior frontal gyrus and insula, and left superior frontal gyrus. The total International Cooperative Ataxia Rating Scale (ICARS) score was inversely correlated with the gray matter volume in the cerebellar culmen, pons and midbrain. The numbers of CAG repeats in the expanded alleles were inversely correlated with the gray matter in the cerebellar culmen. NAA/Cr and NAA/Cho ratio in the middle cerebellar peduncles, dentate nucleus, cerebellar vermis, and thalamus in the SCA3/MJD patients were significantly reduced when compared to that in the normal controls, suggesting neurochemical alterations in cerebellum in the SCA3/MJD patients. Tract-Based Spatial Statistics (TBSS) analysis revealed significant lower volume and mean FA values of the cerebellar peduncles, which inversely correlated with the total scores of ICARS in our patients.

Conclusions: In this study, we demonstrated cerebellar degeneration in SCA3/MJD based on tissue volume, neurochemistry, and tissue microstructure. Moreover, the associations between the clinical measures, cerebellar degeneration and genetic variation support a distinct genotype-phenotype relationship in SCA3/MJD.

Clinical Uses of Diffusion Tensor Imaging Fiber Tracking Merged Neuronavigation with Lesions Adjacent to Corticospinal Tract : A Retrospective Cohort Study

OBJECTIVE

To investigate the efficiency of diffusion tensor imaging (DTI) fiber-tracking based neuronavigation and assess its usefulness in the preoperative surgical planning, prognostic prediction, intraoperative course and outcome improvement.

METHODS

Seventeen patients with cerebral masses adjacent to corticospinal tract (CST) were given standard magnetic resonance imaging and DTI examination. By incorporation of DTI data, the relation between tumor and adjacent white matter tracts was reconstructed and assessed in the neuronavigation system. Distance from tumor border to CST was measured.

RESULTS

The sub-portion of CST in closest proximity to tumor was found displaced in all patients. The chief disruptive changes were classified as follows : complete interruption, partial interruption, or simple displacement. Partial interruption was evident in seven patients (41.2%) whose lesions were close to cortex. In the other 10 patients (58.8%), delineated CSTs were intact but distorted. No complete CST interruption was identified. Overall, the mean distance from resection border to CST was 6.12 mm (range, 0-21), as opposed to 8.18 mm (range, 2-21) with simple displacement and 2.33 mm (range, 0-5) with partial interruption. The clinical outcomes were analyzed in groups stratified by intervening distances (close, <5 mm; moderated, 5-10 mm; far, >10 mm). For the primary brain tumor patients, the proportion of completely resected tumors increased progressively from close to far grouping (42.9%, 50%, and 100%, respectively). Five patients out of seven (71.4%) experienced new neurologic deficits postoperatively in the close group. At meantime, motor deterioration was found in six cases in the close group. All patients in the far and moderate groups received excellent (modified Rankin Scale [mRS] score, 0-1) or good (mRS score, 2-3) rankings, but only 57.1% of patients in the close group earned good outcome scores.

CONCLUSION

DTI fiber tracking based neuronavigation has merit in assessing the relation between lesions and adjacent white matter tracts, allowing prediction of patient outcomes based on lesion-CST distance. It has also proven beneficial in formulating surgical strategies.

The α3 and α4 nicotinic acetylcholine receptor (nAChR) subunits in the brainstem medulla of sudden infant death syndrome (SIDS)

SIDS occurs in early infancy and predominantly during a sleep period. Abnormalities in nicotine receptor binding and in the expression of the nicotinic acetylcholine receptor (nAChR) subunits α7 and β2 have been reported in the brainstem of SIDS infants. This study focuses on the α3 and α4 nAChR subunits as α3 is important for early postnatal survival while α4 is crucial for nicotine-elicited antinociception and sleep-wake cycle regulation. Tissue from the rostral medulla of infants who died with a known cause of death (eSUDI, n = 7), and from SIDS classified as SIDS I (n = 8) and SIDS II (n = 27), was immunohistochemically stained for the α3 and α4 nAChR subunits and quantified in 9 nuclei comparing amongst these groups. The association with risk factors of sex, cigarette smoke exposure, upper respiratory tract infection (URTI), prone sleeping and bedsharing was also evaluated. Results showed that only α4 changes (increase) were evident in SIDS, occurring in the hypoglossal and cuneate nuclei of SIDS II infants and the nucleus of the spinal trigeminal tract of SIDS I infants. Amongst the SIDS infants, cigarette smoke exposure was only associated with decreased α4 in cribriform fibre tracts, while sex and bedsharing were associated with increases in α3 in the dorsal motor nucleus of the vagus and solitary nucleus, respectively. Combined, these findings suggest that abnormalities in endogenous acetylcholine synthesis and regulation may underlie the altered α3 and α4 nAChR subunit expressions in the SIDS brainstem medulla since the changes were not related to cigarette smoke exposure.

Collagen networks determine viscoelastic properties of connective tissues yet do not hinder diffusion of the aqueous solvent

Collagen accounts for the major extracellular matrix (ECM) component in many tissues and provides mechanical support for cells. Magnetic Resonance (MR) Imaging, MR based diffusion measurements and MR Elastography (MRE) are considered sensitive to the microstructure of tissues including collagen networks of the ECM. However, little is known whether water diffusion interacts with viscoelastic properties of tissues. This study combines highfield MR based diffusion measurements, novel compact tabletop MRE and confocal microscopy in collagen networks of different cross-linking states (untreated collagen gels versus additional treatment with glutaraldehyde). The consistency of bulk rheology and MRE within a wide dynamic range is demonstrated in heparin gels, a viscoelastic standard for MRE. Additional crosslinking of collagen led to an 8-fold increased storage modulus, a 4-fold increased loss modulus and a significantly decreased power law exponent, describing multi-relaxational behavior, corresponding to a pronounced transition from viscous-soft to elastic-rigid properties. Collagen network changes were not detectable by MR based diffusion measurements and microscopy which are sensitive to the micrometer scale. The MRE-measured shear modulus is sensitive to collagen fiber interactions which take place on the intrafiber level such as fiber stiffness. The insensitivity of MR based diffusion measurements to collagen hydrogels of different cross-linking states alludes that congeneric collagen structures in connective tissues do not hinder extracellular diffusive water transport. Furthermore, the glutaraldehyde induced rigorous changes in viscoelastic properties indicate that intrafibrillar dissipation is the dominant mode of viscous dissipation in collagen-dominated connective tissue.

Noise reduction in diffusion MRI using non-local self-similar information in joint x-q space

Diffusion MRI affords valuable insights into white matter microstructures, but suffers from low signal-to-noise ratio (SNR), especially at high diffusion weighting (i.e., b-value). To avoid time-intensive repeated acquisition, post-processing algorithms are often used to reduce noise. Among existing methods, non-local means (NLM) has been shown to be particularly effective. However, most NLM algorithms for diffusion MRI focus on patch matching in the spatial domain (i.e., x-space) and disregard the fact that the data live in a combined 6D space covering both spatial domain and diffusion wavevector domain (i.e., q-space). This drawback leads to inaccurate patch matching in curved white matter structures and hence the inability to effectively use recurrent information for noise reduction. The goal of this paper is to overcome this limitation by extending NLM to the joint x-q space. Specifically, we define for each point in the x-q space a spherical patch from which we extract rotation-invariant features for patch matching. The ability to perform patch matching across q-samples allows patches from differentially orientated structures to be used for effective noise removal. Extensive experiments on synthetic, repeated-acquisition, and HCP data demonstrate that our method outperforms state-of-the-art methods, both qualitatively and quantitatively.

Brain morphological alteration and cognitive dysfunction in multiple system atrophy

Multiple system atrophy (MSA) is a progressive neurodegenerative disease in adults, manifesting various clinical symptoms including autonomic nerve dysfunction, Parkinson's syndrome, cerebellar ataxia, and pyramidal sign. The clinical diagnosis and classification of MSA are mainly dependent on motion and non-motion symptoms, such as autonomic nerve dysfunction. In addition, an increasing amount of clinical and pathological evidence has shown that about half of the MSA patients exhibit distinct types and levels of cognitive dysfunction. However, cognitive dysfunction has not been included in the current diagnosis criteria of MSA. In most cases, it was even used as an exclusion criterion of MSA. Based on the neuroimaging, neuropathology and neuropsychology, this review summarized the morphological changes of the brain in the patients with MSA, and discussed possible brain regions that could be associated with cognitive impairment. The article may provide a theoretical basis for incorporating cognitive dysfunction into the criteria of MSA diagnosis.

Cerebellar peduncle injury predicts motor impairments in preterm infants: A quantitative tractography study at term-equivalent age

PURPOSE

Cerebellar injury is well established as an important finding in preterm infants with cerebral palsy (CP). In this study, we investigated associations between injury to the cerebellar peduncles and motor impairments in preterm infants using quantitative tractography at term-equivalent age, which represents an early phase before the onset of motor impairments.

METHODS

We studied 64 preterm infants who were born at <33 weeks gestational age. These infants were divided into three groups: CP, Non-CP (defined as infants with periventricular leukomalacia but having normal motor function), and a Normal group. Diffusion tensor imaging was performed at term-equivalent age and motor function was assessed no earlier than a corrected age of 2 years. Using tractography, we measured fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of the superior cerebellar peduncles (SCP) and middle cerebellar peduncles (MCP), as well as the motor/sensory tracts.

RESULTS

The infants in the CP group had significantly lower FA of the SCP and sensory tract than those in the other groups. There was no significant difference in FA and ADC of the motor tract among the three groups. Severity of CP had a significant correlation with FA of the MCP, but not with the FA of other white matter tracts.

CONCLUSION

Our results suggested that the infants with CP had injuries of the ascending tracts (e.g. the SCP and sensory tract), and that additional MCP injury might increase the severity of CP. Quantitative tractography assessment at term-equivalent age may be useful for screening preterm infants for prediction of future motor impairments.

In vivo Diffusion Tensor Imaging, Diffusion Kurtosis Imaging, and Tractography of a Sciatic Nerve Injury Model in Rat at 9.4T

Peripheral nerve injuries result in severe loss of sensory and motor functions in the afflicted limb. There is a lack of standardised models to non-invasively study degeneration, regeneration, and normalisation of neuronal microstructure in peripheral nerves. This study aimed to develop a non-invasive evaluation of peripheral nerve injuries, using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and tractography on a rat model of sciatic nerve injury. 10 female Sprague Dawley rats were exposed to sciatic nerve neurotmesis and studied using a 9.4 T magnet, by performing DTI and DKI of the sciatic nerve before and 4 weeks after injury. The distal nerve stump showed a decrease in fractional anisotropy (FA), mean kurtosis (MK), axonal water fraction (AWF), and radial and axonal kurtosis (RK, AK) after injury. The proximal stump showed a significant decrease in axial diffusivity (AD) and increase of MK and AK as compared with the uninjured nerve. Both mean diffusivity (MD) and radial diffusivity (RD) increased in the distal stump after injury. Tractography visualised the sciatic nerve and the site of injury, as well as local variations of the diffusion parameters following injury. In summary, the described method detects changes both proximal and distal to the nerve injury.

Connectivity-based segmentation of the brainstem by probabilistic tractography

Diffusion magnetic resonance imaging is a non-invasive tool increasingly used for the investigation of brain connectivity in vivo. In this paper we propose a method that allows segmentation of the brainstem to four subregions (frontopontine, motor, sensory and reticular) based on connections to supratentorial structures, thereby eliminating the need for using anatomical landmarks within the brainstem for the identification of these subregions. The feasibility of connectivity-based brainstem segmentation was investigated in a group of healthy subjects (n = 20). Multifiber probabilistic tractography was performed using the FMRIB Software Library, and connections between a pontomesencephalic seed mask and four supratentorial target regions (anterior and posterior limbs of the internal capsule, sensory and medial thalamus) were used to determine connectivity maps of the brainstem. Results were compared with a neuroanatomy atlas and histological sections, confirming good anatomic correspondence. The four subregions detected by the connectivity-based segmentation showed good intersubject reproducibility. The presented method may be a potential tool to investigate brainstem connectivity in diseases that distort normal anatomy, and quantitative analyses of the diffusion-related parameters may provide additional information on the involvement of brainstem pathways in certain disease states (e.g., traumatic brain injury, demyelinating disorders, brainstem tumors). The potential clinical applicability of the method is demonstrated in two cases of severe traumatic brain injury.

Diffusion tensor imaging of the sciatic and femoral nerves in unilateral osteoarthritis of the hip and osteonecrosis of femoral head: Comparison of the affected and normal sides

Objective: The aim was to compare the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the sciatic and femoral nerves in patients with unilateral osteoarthritis of the hip (OA) and osteonecrosis of the femoral head (ONFH) using diffusion tensor imaging (DTI) and to investigate the mechanism of hip pain. Methods: Forty-four patients (22 OA and 22 ONFH) underwent DTI of the sciatic and femoral nerves at the level of the hip joint and the S1 roots to visualize the tractography and quantify the FA and ADC values. Results: The tractography of the femoral and the sciatic nerves on the affected side with OA and ONFH were similar to those on the normal side. The mean FA values of the sciatic and femoral nerves, and the S1 roots were 0.542, 0.551, and 0.316 with OA, 0.568, 0.560, and 0.318 with ONFH on the affected side, and 0.559, 0.560, and 0.315 on the normal side, respectively, and did not show significant differences. The FA values of the sciatic nerve on the affected side with OA decreased with longer pain duration. Conclusion: The FA and ADC values of the sciatic and femoral nerves in patients with unilateral OA and ONFH showed no significant differences between the affected and normal sides.

A probabilistic atlas of human brainstem pathways based on connectome imaging data

The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles for each subject, which were then used to calculate the probabilistic atlases in the MNI152 space for public release. In our experimental results, we demonstrate that our method yielded anatomically faithful reconstruction of the brainstem pathways and achieved improved performance in comparison with an existing atlas of cerebellar peduncles based on HCP data. These atlases have been publicly released on NITRIC (https://www.nitrc.org/projects/brainstem_atlas/) and can be readily used by brain imaging researchers interested in studying brainstem pathways.

Neighborhood resolved fiber orientation distributions (NRFOD) in automatic labeling of white matter fiber pathways

Accurate digital representation of major white matter bundles in the brain is an important goal in neuroscience image computing since the representations can be used for surgical planning, intra-patient longitudinal analysis and inter-subject population connectivity studies. Reconstructing desired fiber bundles generally involves manual selection of regions of interest by an expert, which is subject to user bias and fatigue, hence an automation is desirable. To that end, we first present a novel anatomical representation based on Neighborhood Resolved Fiber Orientation Distributions (NRFOD) along the fibers. The resolved fiber orientations are obtained by generalized q-sampling imaging (GQI) and a subsequent diffusion decomposition method. A fiber-to-fiber distance measure between the proposed fiber representations is then used in a density-based clustering framework to select the clusters corresponding to the major pathways of interest. In addition, neuroanatomical priors are utilized to constrain the set of candidate fibers before density-based clustering. The proposed fiber clustering approach is exemplified on automation of the reconstruction of the major fiber pathways in the brainstem: corticospinal tract (CST); medial lemniscus (ML); middle cerebellar peduncle (MCP); inferior cerebellar peduncle (ICP); superior cerebellar peduncle (SCP). Experimental results on Human Connectome Project (HCP)'s publicly available "WU-Minn 500 Subjects + MEG2 dataset" and expert evaluations demonstrate the potential of the proposed fiber clustering method in brainstem white matter structure analysis.

Diffusion tensor imaging and tractography of the sciatic and femoral nerves in healthy volunteers at 3T

Background

The aim was to clarify the normal fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the sciatic and femoral nerves at the level of the hip joint and to visualize the neural tracts with diffusion tensor imaging (DTI).

Methods

Twenty-four healthy volunteers (12 men and 12 women, age 20–29 years) underwent DTI for visualization with tractography and quantification of FA and ADC values on a 3 Tesla MRI (b value = 800 s/mm², motion probing gradient, 11 directions, time to repeat/echo time = 9000/72.6 ms, axial slice orientation, slice thickness = 3.0 mm with no inter-slice gap, field of view = 320 × 320 mm, 96 × 192 matrix, 75 slices, number of acquisitions = 4). Regions of interest in the sciatic nerve were defined at the femoral head, the S1 root, and the midpoint levels. The femoral nerve was evaluated at 3–4 cm proximal to the femoral head level.

Results

The tractography of the sciatic and femoral nerves were visualized in all participants. The mean FA values of the sciatic nerve were increased distally from the S1 root level, through the midpoint, and to the femoral head level (0.314, 0.446, 0.567, p = 0.001, respectively). The mean FA values of the femoral nerve were 0.565. The mean ADC values of the sciatic nerves were significantly lower in the S1 root level than in the midpoint and the femoral head level (1.481, 1.602, 1.591 × 10⁻³ × 10⁻³ mm²/s, p = 0.001, respectively). The ADC values of the femoral nerve were 1.439 × 10⁻³ mm²/s. FA and ADC values showed moderate to substantial inter- and intra-observer reliability without significant differences in gender or laterality.

Conclusion

Visualization and quantification of the sciatic and femoral nerves simultaneously around the hip joint were achieved in healthy young volunteers with DTI. Clinical application of DTI is expected to contribute to hip pain research.

Human Connectome-Based Tractographic Atlas of the Brainstem Connections and Surgical Approaches

BACKGROUND

The brainstem is one of the most challenging areas for the neurosurgeon because of the limited space between gray matter nuclei and white matter pathways. Diffusion tensor imaging-based tractography has been used to study the brainstem structure, but the angular and spatial resolution could be improved further with advanced diffusion magnetic resonance imaging (MRI).

OBJECTIVE

To construct a high-angular/spatial resolution, wide-population-based, comprehensive tractography atlas that presents an anatomical review of the surgical approaches to the brainstem.

METHODS

We applied advanced diffusion MRI fiber tractography to a population-based atlas constructed with data from a total of 488 subjects from the Human Connectome Project-488. Five formalin-fixed brains were studied for surgical landmarks. Luxol Fast Blue-stained histological sections were used to validate the results of tractography.

RESULTS

We acquired the tractography of the major brainstem pathways and validated them with histological analysis. The pathways included the cerebellar peduncles, corticospinal tract, corticopontine tracts, medial lemniscus, lateral lemniscus, spinothalamic tract, rubrospinal tract, central tegmental tract, medial longitudinal fasciculus, and dorsal longitudinal fasciculus. Then, the reconstructed 3-dimensional brainstem structure was sectioned at the level of classic surgical approaches, namely supracollicular, infracollicular, lateral mesencephalic, perioculomotor, peritrigeminal, anterolateral (to the medulla), and retro-olivary approaches.

CONCLUSION

The advanced diffusion MRI fiber tracking is a powerful tool to explore the brainstem neuroanatomy and to achieve a better understanding of surgical approaches.

ABBREVIATIONS

CN, cranial nerveCPT, corticopontine tractCST, corticospinal tractCTT, central tegmental tractDLF, dorsal longitudinal fasciculusHCP, Human Connectome ProjectML, medial lemniscusMLF, medial longitudinal fasciculusRST, rubrospinal tractSTT, spinothalamic tract.