In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging

Gaming expertise induces meso‑scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling

Video games are a valuable tool for studying the effects of training and neural plasticity on the brain. However, the underlying mechanisms related to plasticity-associated brain structural changes and their impact on brain dynamics are unknown. Here, we used a semi-empirical whole-brain model to study structural neural plasticity mechanisms linked to video game expertise. We hypothesized that video game expertise is associated with neural plasticity-mediated changes in structural connectivity that manifest at the meso‑scale level, resulting in a more segregated functional network topology. To test this hypothesis, we combined structural connectivity data of StarCraft II video game players (VGPs, n = 31) and non-players (NVGPs, n = 31), with generic fMRI data from the Human Connectome Project and computational models, to generate simulated fMRI recordings. Graph theory analysis on simulated data was performed during both resting-state conditions and external stimulation. VGPs' simulated functional connectivity was characterized by a meso‑scale integration, with increased local connectivity in frontal, parietal, and occipital brain regions. The same analyses at the level of structural connectivity showed no differences between VGPs and NVGPs. Regions that increased their connectivity strength in VGPs are known to be involved in cognitive processes crucial for task performance such as attention, reasoning, and inference. In-silico stimulation suggested that differences in FC between VGPs and NVGPs emerge in noisy contexts, specifically when the noisy level of stimulation is increased. This indicates that the connectomes of VGPs may facilitate the filtering of noise from stimuli. These structural alterations drive the meso‑scale functional changes observed in individuals with gaming expertise. Overall, our work sheds light on the mechanisms underlying structural neural plasticity triggered by video game experiences.

Gaming expertise induces meso-scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling Gaming expertise, neuroplasticity and functional dynamics

Video games are a valuable tool for studying the effects of training and neural plasticity on the brain. However, the underlaying mechanisms related to plasticity-induced brain structural changes and their impact in brain dynamics are unknown. Here, we used a semi-empirical whole-brain model to study structural neural plasticity mechanisms linked to video game expertise. We hypothesized that video game expertise is associated with neural plasticity-mediated changes in structural connectivity that manifest at the meso-scale level, resulting in a more segregated functional network topology. To test this hypothesis, we combined structural connectivity data of StarCraft II video game players (VGPs, n = 31) and non-players (NVGPs, n = 31), with generic fMRI data from the Human Connectome Project and computational models, with the aim of generating simulated fMRI recordings. Graph theory analysis on simulated data was performed during both resting-state conditions and external stimulation. VGPs' simulated functional connectivity was characterized by a meso-scale integration, with increased local connectivity in frontal, parietal and occipital brain regions. The same analyses at the level of structural connectivity showed no differences between VGPs and NVGPs. Regions that increased their connectivity strength in VGPs are known to be involved in cognitive processes crucial for task performance such as attention, reasoning, and inference. In-silico stimulation suggested that differences in FC between VGPs and NVGPs emerge in noisy contexts, specifically when the noisy level of stimulation is increased. This indicates that the connectomes of VGPs may facilitate the filtering of noise from stimuli. These structural alterations drive the meso-scale functional changes observed in individuals with gaming expertise. Overall, our work sheds light into the mechanisms underlying structural neural plasticity triggered by video game experiences.

The preservation of right cingulum fibers in subjective cognitive decline of preclinical phase of Alzheimer's disease

Introduction

Subjective cognitive decline (SCD) with a positive amyloid burden has been recognized as the earliest clinical symptom of the preclinical phase of Alzheimers disease (AD), providing invaluable opportunities to improve our understanding of the natural history of AD and determine strategies for early therapeutic interventions.

Methods

The microstructure of white matter in patients showing SCD in the preclinical phase of AD (SCD of pre-AD) was evaluated using diffusion images, and voxel-wise fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivities were assessed and compared among participant groups. Significant clusters in the tracts were extracted to determine their associations with alterations in the cognitive domains.

Results

We found that individuals with SCD of pre-AD may have subclinical episodic memory impairment associated with the global amyloid burden. Meanwhile, we found significantly reduced FA and λ1 in the right cingulum (cingulate and hippocampus) in AD dementia, while significantly increased FA and decreased MD as well as λ23 in the SCD of pre-AD group in comparison with the HC group.

Discussion

In conclusion, increased white matter microstructural integrity in the right cingulum (cingulate and hippocampus) may indicate compensation for short-term episodic memory in individuals with SCD of pre-AD in comparison with individuals with AD and healthy elderly individuals.

A brain for all seasons: An in vivo MRI perspective on songbirds

Seasonality in songbirds includes not only reproduction but also seasonal changes in singing behavior and its neural substrate, the song control system (SCS). Prior research mainly focused on the role of sex steroids on this seasonal SCS neuroplasticity in males. In this review, we summarize the advances made in the field of seasonal neuroplasticity by applying in vivo magnetic resonance imaging (MRI) in male and female starlings, analyzing the entire brain, monitoring birds longitudinally and determining the neuronal correlates of seasonal variations in plasma hormone levels and song behavior. The first MRI studies in songbirds used manganese enhanced MRI to visualize the SCS in a living bird and validated previously described brain volume changes related to different seasons and testosterone. MRI studies with testosterone implantation established how the consequential boost in singing was correlated to structural changes in the SCS, indicating activity-induced neuroplasticity as song proficiency increased. Next, diffusion tensor MRI explored seasonal neuroplasticity in the entire brain, focusing on networks beyond the SCS, revealing that other sensory systems and even the cerebellum, which is important for the integration of sensory perception and song behavior, experience neuroplasticity starting in the photosensitive period. Functional MRI showed that olfactory, and auditory processing was modulated by the seasons. The convergence of seasonal variations in so many sensory and sensorimotor systems resembles multisensory neuroplasticity during the critical period early in life. This sheds new light on seasonal songbirds as a model for unlocking the brain by recreating seasonally the permissive circumstances for heightened neuroplasticity.

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

Brain network analyses of diffusion tensor imaging for brain aging

The approach of graph-based diffusion tensor imaging (DTI) networks has been used to explore the complicated structural connectivity of brain aging. In this study, the changes of DTI networks of brain aging were quantitatively and qualitatively investigated by comparing the characteristics of brain network. A cohort of 60 volunteers was enrolled and equally divided into young adults (YA) and older adults (OA) groups. The network characteristics of critical nodes, path length (Lp), clustering coefficient (Cp), global efficiency (Eglobal), local efficiency (Elocal), strength (Sp), and small world attribute (σ) were employed to evaluate the DTI networks at the levels of whole brain, bilateral hemispheres and critical brain regions. The correlations between each network characteristic and age were predicted, respectively. Our findings suggested that the DTI networks produced significant changes in network configurations at the critical nodes and node edges for the YA and OA groups. The analysis of whole brains network revealed that Lp, Cp increased (p < 0.05, positive correlation), Eglobal, Elocal, Sp decreased (p < 0.05, negative correlation), and σ unchanged (p ≥ 0.05, non-correlation) between the YA and OA groups. The analyses of bilateral hemispheres and brain regions showed similar results as that of the whole-brain analysis. Therefore the proposed scheme of DTI networks could be used to evaluate the WM changes of brain aging, and the network characteristics of critical nodes exhibited valuable indications for WM degeneration.

Denoise magnitude diffusion magnetic resonance images via variance-stabilizing transformation and optimal singular-value manipulation

Although shown to have a great utility for a wide range of neuroscientific and clinical applications, diffusion-weighted magnetic resonance imaging (dMRI) faces a major challenge of low signal-to-noise ratio (SNR), especially when pushing the spatial resolution for improved delineation of brain's fine structure or increasing the diffusion weighting for increased angular contrast or both. Here, we introduce a comprehensive denoising framework for denoising magnitude dMRI. The framework synergistically combines the variance stabilizing transform (VST) with optimal singular value manipulation. The purpose of VST is to transform the Rician data to Gaussian-like data so that an asymptotically optimal singular value manipulation strategy tailored for Gaussian data can be used. The output of the framework is the estimated underlying diffusion signal for each voxel in the image domain. The usefulness of the proposed framework for denoising magnitude dMRI is demonstrated using both simulation and real-data experiments. Our results show that the proposed denoising framework can significantly improve SNR across the entire brain, leading to substantially enhanced performances for estimating diffusion tensor related indices and for resolving crossing fibers when compared to another competing method. More encouragingly, the proposed method when used to denoise a single average of 7 ​Tesla Human Connectome Project-style diffusion acquisition provided comparable performances relative to those achievable with ten averages for resolving multiple fiber populations across the brain. As such, the proposed denoising method is expected to have a great utility for high-quality, high-resolution whole-brain dMRI, desirable for many neuroscientific and clinical applications.

Diffusion Weighted and Diffusion Tensor MRI in Pediatric Neuroimaging Including Connectomics: Principles and Applications

Diffusion weighted MRI (DWI) including diffusion tensor imaging (DTI) are unique imaging techniques that render qualitative and quantitative information of the central nervous system white matter (WM) ultrastructure. It uses the Brownian movement of water molecules to probe tissue microstructure. It is a noninvasive method, with superb sensitivity to the differential mobility of water molecules within various components of the brain without the necessity to inject contrast agents. By sampling the 3 dimensional shape, direction and magnitude of the water diffusion, DWI/DTI generates unique tissue contrasts that can be used to study the axonal WM organization of the central nervous system. Its application allows to study the normal and anomalous brain development including connectivity, as well as a multitude of WM diseases. This article discusses/summarizes the principles of DWI/DTI and its applications in pediatric neuroscience research.

Abnormal Structural Brain Connectome in Individuals with Preclinical Alzheimer's Disease

Alzheimer's disease has a long preclinical phase during which amyloid pathology and neurodegeneration accumulate in the brain without producing overt cognitive deficits. It is currently unclear whether these early disease stages are associated with a progressive disruption in the communication between brain regions that subsequently leads to cognitive decline and dementia. In this study we assessed the organization of structural networks in cognitively normal (CN) individuals harboring amyloid pathology (A+N-), neurodegeneration (A-N+), or both (A+N+) from the prospective and longitudinal Swedish BioFINDER study. We combined graph theory with diffusion tensor imaging to investigate integration, segregation, and centrality measures in the brain connectome in the previous groups. At baseline, our findings revealed a disrupted network topology characterized by longer paths, lower efficiency, increased clustering and modularity in CN A-N+ and CN A+N+, but not in CN A+N-. After 2 years, CN A+N+ showed significant abnormalities in all global network measures, whereas CN A-N+ only showed abnormalities in the global efficiency. Network connectivity and organization were associated with memory in CN A+N+ individuals. Altogether, our findings suggest that amyloid pathology is not sufficient to disrupt structural network topology, whereas neurodegeneration is.

Supratentorial Cavernous Malformations Involving the Corticospinal Tract and Sensory Motor Cortex: Treatment Strategies, Surgical Considerations, and Outcomes

BACKGROUND

Cavernous malformations (CMs) are congenital malformations and may be located anywhere in the brain. We present a series of CMs located close to or inside of the motor-sensory cortex or corticospinal tract (CST) with clinical onset due to hemorrhage or mass effect. In such cases, surgery becomes an acceptable option.

OBJECTIVE

To evaluate the role of diffusion tensor imaging (DTI), functional-magnetic-resonance imaging (fMRI), intraoperative neurophysiological monitoring, neuronavigation, and brain-mapping and the clinical results of surgical treatment of CMs in this critical location.

METHODS

The study included 54 patients harboring 22 cortical and 32 deep locations. This series was distinct because in group I, where the DTI was not obtained, and in the group II, where this evaluation was performed.

RESULTS

The postoperative permanent morbidity rate was 4% in the historical group for the deeper CMs, and there was no morbidity in the second group. DTI and fMRI permitted us to estimate the distance between the CMs and both the cortical activation cluster and the pyramidal tract. These data, in addition to intraoperative mapping and monitoring, made it necessary for us to perform a partial resection in 2 cases in the second series.

CONCLUSION

CMs are congenital lesions and CST fibers can run directly on their surface. Integration of fMRI and DTI data with intraoperative functional monitoring and direct cortical and subcortical mapping are mandatory to accomplish an optimal resection, tailoring the best surgical approach to the acceptable morbidity. A subtotal resection could be considered an option for deep locations.

Reduced integrity of superior longitudinal fasciculus and arcuate fasciculus as a marker for auditory hallucinations in schizophrenia: A DTI tractography study

AIMS AND OBJECTIVES

The study aimed to assess and compare fractional anisotropy (FA) in bilateral superior longitudinal fasciculi (SLF) and arcuate fasciculi (AF) across schizophrenia with auditory hallucinations(AH), without AH, and healthy controls using diffusion tensor imaging (DTI) tractography.

METHODOLOGY

Right-handed adult (18-50 years) individuals with DSM-5 diagnosis of schizophrenia with AH (group-I; n=30) were compared to those without lifetime AH (group-II; n=32) and healthy controls (group-III; n=30). Severity of psychosis in groups-I and II was assessed using SAPS, SANS, and CGI-SCH, and psychopathology was assessed using PSYRATS. The FA was calculated for all images on DTI studio-version 3.0 using tractography technique.

RESULTS

All three groups were comparable for age, gender, education and illness-severity. Schizophrenia subjects with AH had significantly lower FA values in bilateral SLF and AF compared to those without AH and healthy controls. No difference was observed in corresponding FA values between schizophrenia without AH and healthy controls.

CONCLUSION

White matter disruptions in bilateral SLF and AF appear to be specific to schizophrenia with AH and must be explored further as potential marker of AH, pending replication in other studies.

Synthesized b0 for diffusion distortion correction (Synb0-DisCo)

Diffusion magnetic resonance images typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may affect the geometric fidelity of the reconstructed volume and cause mismatches with anatomical images. State-of-the art susceptibility correction (for example, FSL's TOPUP algorithm) typically requires data acquired twice with reverse phase encoding directions, referred to as blip-up blip-down acquisitions, in order to estimate an undistorted volume. Unfortunately, not all imaging protocols include a blip-up blip-down acquisition, and cannot take advantage of the state-of-the art susceptibility and motion correction capabilities. In this study, we aim to enable TOPUP-like processing with historical and/or limited diffusion imaging data that include only a structural image and single blip diffusion image. We utilize deep learning to synthesize an undistorted non-diffusion weighted image from the structural image, and use the non-distorted synthetic image as an anatomical target for distortion correction. We evaluate the efficacy of this approach (named Synb0-DisCo) and show that our distortion correction process results in better matching of the geometry of undistorted anatomical images, reduces variation in diffusion modeling, and is practically equivalent to having both blip-up and blip-down non-diffusion weighted images.

Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions

Diffusion MRI (dMRI) fiber tractography has become a pillar of the neuroimaging community due to its ability to noninvasively map the structural connectivity of the brain. Despite widespread use in clinical and research domains, these methods suffer from several potential drawbacks or limitations. Thus, validating the accuracy and reproducibility of techniques is critical for sound scientific conclusions and effective clinical outcomes. Towards this end, a number of international benchmark competitions, or "challenges", has been organized by the diffusion MRI community in order to investigate the reliability of the tractography process by providing a platform to compare algorithms and results in a fair manner, and evaluate common and emerging algorithms in an effort to advance the state of the field. In this paper, we summarize the lessons from a decade of challenges in tractography, and give perspective on the past, present, and future "challenges" that the field of diffusion tractography faces.

Diffusion MRI fiber tractography of the brain

The ability of fiber tractography to delineate non-invasively the white matter fiber pathways of the brain raises possibilities for clinical applications and offers enormous potential for neuroscience. In the last decade, fiber tracking has become the method of choice to investigate quantitative MRI parameters in specific bundles of white matter. For neurosurgeons, it is quickly becoming an invaluable tool for the planning of surgery, allowing for visualization and localization of important white matter pathways before and even during surgery. Fiber tracking has also claimed a central role in the field of "connectomics," a technique that builds and studies comprehensive maps of the complex network of connections within the brain, and to which significant resources have been allocated worldwide. Despite its unique abilities and exciting applications, fiber tracking is not without controversy, in particular when it comes to its interpretation. As neuroscientists are eager to study the brain's connectivity, the quantification of tractography-derived "connection strengths" between distant brain regions is becoming increasingly popular. However, this practice is often frowned upon by fiber-tracking experts. In light of this controversy, this paper provides an overview of the key concepts of tractography, the technical considerations at play, and the different types of tractography algorithm, as well as the common misconceptions and mistakes that surround them. We also highlight the ongoing challenges related to fiber tracking. While recent methodological developments have vastly increased the biological accuracy of fiber tractograms, one should be aware that, even with state-of-the-art techniques, many issues that severely bias the resulting structural "connectomes" remain unresolved.

A fiber coherence index for quality control of B-table orientation in diffusion MRI scans

PURPOSE

The diffusion MRI "b-vector" table describing the diffusion sensitization direction can be flipped and permuted in dimension due to different orientation conventions used in scanners and incorrect or improperly utilized file formats. This can lead to incorrect fiber orientation estimates and subsequent tractography failure. Here, we present an automated quality control procedure to detect when the b-table is flipped and/or permuted incorrectly.

METHODS

We define a "fiber coherence index" to describe how well fibers are connected to each other, and use it to automatically detect the correct configuration of b-vectors. We examined the performance on 3981 research subject scans (Baltimore Longitudinal Study of Aging), 1065 normal subject scans of high image quality (Human Connectome Project), and 202 patient scans (Vanderbilt University Medical Center), as well as 9 in-vivo and 9 ex-vivo animal data.

RESULTS

The coherence index resulted in a 99.9% (3979/3981) and 100% (1065/1065) success rate in normal subject scans, 98% (198/202) in patient scans, and 100% (18/18) in both in-vivo and ex-vivo animal data in detecting the correct gradient table in datasets without severe image artifacts. The four failing cases (4/202) in patient scans, and two failures in healthy subject scans (2/3981), all showed prominent motion or signal dropout artifacts.

CONCLUSIONS

The fiber coherence measure can be used as an automatic quality assurance check in any diffusion analysis pipeline. Additionally, the success of this fiber coherence measure suggests potential broader applications, including evaluating data quality, or even providing diagnostic value as a biomarker of white matter integrity.

Real-time strategy video game experience and structural connectivity - A diffusion tensor imaging study

Experienced video game players exhibit superior performance in visuospatial cognition when compared to non-players. However, very little is known about the relation between video game experience and structural brain plasticity. To address this issue, a direct comparison of the white matter brain structure in RTS (real time strategy) video game players (VGPs) and non-players (NVGPs) was performed. We hypothesized that RTS experience can enhance connectivity within and between occipital and parietal regions, as these regions are likely to be involved in the spatial and visual abilities that are trained while playing RTS games. The possible influence of long-term RTS game play experience on brain structural connections was investigated using diffusion tensor imaging (DTI) and a region of interest (ROI) approach in order to describe the experience-related plasticity of white matter. Our results revealed significantly more total white matter connections between occipital and parietal areas and within occipital areas in RTS players compared to NVGPs. Additionally, the RTS group had an altered topological organization of their structural network, expressed in local efficiency within the occipito-parietal subnetwork. Furthermore, the positive association between network metrics and time spent playing RTS games suggests a close relationship between extensive, long-term RTS game play and neuroplastic changes. These results indicate that long-term and extensive RTS game experience induces alterations along axons that link structures of the occipito-parietal loop involved in spatial and visual processing.

Three-Dimensional Reconstruction of Target Self-Calibrating System with Nonlinear Optimization Technique

In this paper, the three-dimensional (3D) reconstruction of target self-calibrating system for the guidance system of air-to-air missile is researched. The basic ideology of self-calibrating theory is studied in depth and also the advantages and disadvantages of traditional calibration method, which is based on active vision and target self-calibrating method, are listed for comparison. The mathematical model of the perspective camera is established, and on this basis, the camera parameters are figured out combining with LM optimization algorithm. The reconstruction is conducted by the method of stratified calibrating. It is proved that the theory of 3D reconstruction of target self-calibrating system in air to air missile is available according to the experimental results. It puts forward a new research approach for the guidance system of air to air missile to identify the target characteristic information in different azimuths.

Age- and sex-related effects in children with mild traumatic brain injury on diffusion magnetic resonance imaging properties: A comparison of voxelwise and tractography methods

Although there are several techniques to analyze diffusion-weighted imaging, any technique must be sufficiently sensitive to detect clinical abnormalities. This is especially critical in disorders like mild traumatic brain injury (mTBI), where pathology is likely to be subtle. mTBI represents a major public health concern, especially for youth under 15 years of age. However, the developmental period from birth to 18 years is also a time of tremendous brain changes. Therefore, it is important to establish the degree of age- and sex-related differences. Participants were children aged 8-15 years with mTBI or mild orthopedic injuries. Imaging was obtained within 10 days of injury. We performed tract-based spatial statistics (TBSS), deterministic tractography using Automated Fiber Quantification (AFQ), and probabilistic tractography using TRACULA (TRActs Constrained by UnderLying Anatomy) to evaluate whether any method provided improved sensitivity at identifying group, developmental, and/or sex-related differences. Although there were no group differences from any of the three analyses, many of the tracts, but not all, revealed increases of fractional anisotropy and decreases of axial, radial, and mean diffusivity with age. TBSS analyses resulted in age-related changes across all white matter tracts. AFQ and TRACULA revealed age-related changes within the corpus callosum, cingulum cingulate, corticospinal tract, inferior and superior longitudinal fasciculus, and uncinate fasciculus. The results are in many ways consistent across all three methods. However, results from the tractography methods provided improved sensitivity and better tract-specific results for identifying developmental and sex-related differences within the brain.

Understanding the Physiopathology Behind Axial and Radial Diffusivity Changes-What Do We Know?

The use of the diffusion tensor imaging (DTI) is rapidly growing in the neuroimaging field. Nevertheless, rigorously performed quantitative validation of DTI pathologic metrics remains very limited owing to the difficulty in co-registering quantitative histology findings with magnetic resonance imaging. The aim of this review is to summarize the existing state-of-the-art knowledge with respect to axial (λ_║) and radial (λ_┴) diffusivity as DTI markers of axonal and myelin damage, respectively. First, we provide technical background for DTI and briefly discuss the specific organization of white matter in bundles of axonal fibers running in parallel; this is the natural target for imaging based on diffusion anisotropy. Second, we discuss the four seminal studies that paved the way for considering axial (λ_║) and radial (λ_┴) diffusivity as potential in vivo surrogate markers of axonal and myelin damage, respectively. Then, we present difficulties in interpreting axial (λ_║) and radial (λ_┴) diffusivity in clinical conditions associated with inflammation, edema, and white matter fiber crossing. Finally, future directions are highlighted. In summary, DTI can reveal strategic information with respect to white matter tracts, disconnection mechanisms, and related symptoms. Axial (λ_║) and radial (λ_┴) diffusivity seem to provide quite consistent information in healthy subjects, and in pathological conditions with limited edema and inflammatory changes. DTI remains one of the most promising non-invasive diagnostic tools in medicine.

Long-term effects of radiation therapy on white matter of the corpus callosum: a diffusion tensor imaging study in children

BACKGROUND

Despite improving survival rates, children are at risk for long-term cognitive and behavioral difficulties following the diagnosis and treatment of a brain tumor. Surgery, chemotherapy and radiation therapy have all been shown to impact the developing brain, especially the white matter.

OBJECTIVE

The purpose of this study was to determine the long-term effects of radiation therapy on white matter integrity, as measured by diffusion tensor imaging, in pediatric brain tumor patients 2 years after the end of radiation treatment, while controlling for surgical interventions.

MATERIALS AND METHODS

We evaluated diffusion tensor imaging performed at two time points: a baseline 3 to 12 months after surgery and a follow-up approximately 2 years later in pediatric brain tumor patients. A region of interest analysis was performed within three regions of the corpus callosum. Diffusion tensor metrics were determined for participants (n=22) who underwent surgical tumor resection and radiation therapy and demographically matched with participants (n=22) who received surgical tumor resection only.

RESULTS

Analysis revealed that 2 years after treatment, the radiation treated group exhibited significantly lower fractional anisotropy and significantly higher radial diffusivity within the body of the corpus callosum compared to the group that did not receive radiation.

CONCLUSION

The findings indicate that pediatric brain tumor patients treated with radiation therapy may be at greater risk of experiencing long-term damage to the body of the corpus callosum than those treated with surgery alone.

Is Congenital Amusia a Disconnection Syndrome? A Study Combining Tract- and Network-Based Analysis

Previous studies on congenital amusia mainly focused on the impaired fronto-temporal pathway. It is possible that neural pathways of amusia patients on a larger scale are affected. In this study, we investigated changes in structural connections by applying both tract-based and network-based analysis to DTI data of 12 subjects with congenital amusia and 20 demographic-matched normal controls. TBSS (tract-based spatial statistics) was used to detect microstructural changes. The results showed that amusics had higher diffusivity indices in the corpus callosum, the right inferior/superior longitudinal fasciculus, and the right inferior frontal-occipital fasciculus (IFOF). The axial diffusivity values of the right IFOF were negatively correlated with musical scores in the amusia group. Network-based analysis showed that the efficiency of the brain network was reduced in amusics. The impairments of WM tracts were also found to be correlated with reduced network efficiency in amusics. This suggests that impaired WM tracts may lead to the reduced network efficiency seen in amusics. Our findings suggest that congenital amusia is a disconnection syndrome.

Diffusion Tensor Tractography of the Cerebellar Peduncles in Prematurely Born 7-Year-Old Children

The objective of this study was to correlate neurodevelopmental outcome of preterm-born children and their perinatal clinical and imaging characteristics with diffusion magnetic resonance imaging (MRI) measures of the three cerebellar peduncles at age 7. Included in this prospective longitudinal study were 140 preterm-born children (<30 weeks gestation) who underwent neurodevelopmental assessment (IQ, motor, language, working memory) and diffusion-weighted imaging (DWI) at age 7 years. White matter tracts in the superior, middle, and inferior cerebellar peduncles were delineated using regions of interest drawn on T2-weighted images and fractional anisotropy (FA) maps. Diffusion measures (mean diffusivity (MD) and FA) and tract volumes were calculated. Linear regression was used to assess relationships with outcome. The severity of white matter injury in the neonatal period was associated with lower FA in the right superior cerebellar peduncle (SCP) and lower tract volumes of both SCPs and middle cerebellar peduncles (MCPs). In the MCP, higher IQ was associated with lower MD in the whole group and higher FA in right-handed children. In the SCP, lower motor scores were associated with higher MD and higher language scores were associated with higher FA. These associations remained significant in multivariable models. This study adds to the body of literature detailing the importance of cerebellar involvement in cognitive function related to reciprocal connections with supratentorial structures.

Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks

Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the white matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor imaging (DTI) tractography to create probabilistic white matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks.

Methods: Whole-brain diffusion imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair.

Results: The resulting functionally-defined white matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/).

Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map white matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroimaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative white matter imaging signals) to these functional brain networks.

The involvement of supratentorial white matter in multiple system atrophy: a diffusion tensor imaging tractography study

It has been assumed that cognitive disorder and visual-spatial disturbance in multiple system atrophy of the predominantly cerebellar type (MSA-C) are attributable to degradation of cerebellar function. The purpose of this study was to use diffusion tensor imaging (DTI) tractography to determine if patients with MSA-C characterized in part by visual-spatial disorders and cognitive disorders have changes of the structural connectivity network of nerve fibers, and to further describe the structural connectivity network. The study included 20 patients with MSA-C and 30 age- and sex-matched healthy controls. A 1.5T magnetic resonance imaging (MRI) scanner was used to obtain images for DTI tractography. Image preprocessing was done by large deformation diffeomorphic metric mapping. Whole-brain connectivity analysis was carried out. The patients had decreased numbers of long association fibers connecting the right parietal lobe to the frontal lobe. The commissural fibers and short association fibers connecting the bilateral frontal and occipital lobes and the number of short association fibers at the bilateral frontal and occipital region were also decreased significantly. The patients had a significant decrease in fiber density in the cerebellum compared to the healthy subjects. Our results provide DTI evidence suggesting that frontal and occipital white matter is involved in patients with MSA-C. This finding may correlate with their clinical symptoms such as cognitive disturbance as well as visual-spatial impairment. Therefore, cognitive disturbance and visual-spatial deficits in MSA-C might not be due to cerebellar lesions only as is widely believed but also involve cerebral lesions.

Diffusion tensor imaging in abdominal organs

Initially, diffusion tensor imaging (DTI) was mainly applied in studies of the human brain to analyse white matter tracts. As DTI is outstanding for the analysis of tissue´s microstructure, the interest in DTI for the assessment of abdominal tissues has increased continuously in recent years. Tissue characteristics of abdominal organs differ substantially from those of the human brain. Further peculiarities such as respiratory motion and heterogenic tissue composition lead to difficult conditions that have to be overcome in DTI measurements. Thus MR measurement parameters have to be adapted for DTI in abdominal organs. This review article provides information on the technical background of DTI with a focus on abdominal imaging, as well as an overview of clinical studies and application of DTI in different abdominal regions. Copyright © 2015 John Wiley & Sons, Ltd.

The visual white matter: The application of diffusion MRI and fiber tractography to vision science

Visual neuroscience has traditionally focused much of its attention on understanding the response properties of single neurons or neuronal ensembles. The visual white matter and the long-range neuronal connections it supports are fundamental in establishing such neuronal response properties and visual function. This review article provides an introduction to measurements and methods to study the human visual white matter using diffusion MRI. These methods allow us to measure the microstructural and macrostructural properties of the white matter in living human individuals; they allow us to trace long-range connections between neurons in different parts of the visual system and to measure the biophysical properties of these connections. We also review a range of findings from recent studies on connections between different visual field maps, the effects of visual impairment on the white matter, and the properties underlying networks that process visual information supporting visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open datasets that are becoming available to study brain connectivity and white matter properties, and open source software for the analysis of these data.

Global Diffusion Tractography by Simulated Annealing

OBJECTIVE

Our goal is to develop a robust global tractography method for cardiac diffusion imaging.

METHODS

A graph is stretched over the whole myocardium to represent the fiber structure, and the solutions are minima of a graph energy measuring the fidelity to the data along with the fiber density and curvature. The optimization is performed by a variant of simulated annealing that offers increased design freedom without sacrificing theoretical convergence guarantees.

RESULTS

Numerical experiments on synthetic and real data demonstrate the capability of our tractography algorithm to deal with low angular resolution, highly noisy data. In particular, our algorithm outperforms the Bayesian model-based algorithm of Reisert et al. (NeuroImage, vol. 54, no. 2, 2011) and the graph-based algorithm of Frindel et al. (Magn. Reson. Med., vol. 64, no. 4, 2010) at the noise levels typical of in vivo imaging.

CONCLUSION

The proposed algorithm avoids the drawbacks of local techniques and is very robust to noise, which makes it a promising tool for in vivo diffusion imaging of moving organs.

SIGNIFICANCE

Our approach is global in terms of both the fiber structure representation and the minimization problem. It also allows us to adjust the trajectory density by simply changing the vertex-lattice spacing in the graph model, a desirable feature for multiresolution tractography analysis.

Evaluations of diffusion tensor image registration based on fiber tractography

Background

Diffusion Tensor Magnetic Resonance Imaging (DT-MRI, also known as DTI) measures the diffusion properties of water molecules in tissues and to date is one of the main techniques that can effectively study the microstructures of the brain in vivo. Presently, evaluation of DTI registration techniques is still in an initial stage of development.

Methods and results

In this paper, six well-known open source DTI registration algorithms: Elastic, Rigid, Affine, DTI-TK, FSL and SyN were applied on 11 subjects from an open-access dataset, among which one was randomly chosen as the template. Eight different fiber bundles of 10 subjects and the template were obtained by drawing regions of interest (ROIs) around various structures using deterministic streamline tractography. The performances of the registration algorithms were evaluated by computing the distances and intersection angles between fiber tracts, as well as the fractional anisotropy (FA) profiles along the fiber tracts. Also, the mean squared error (MSE) and the residual MSE (RMSE) of fibers originating from the registered subjects and the template were calculated to assess the registration algorithm. Twenty-seven different fiber bundles of the 10 subjects and template were obtained by drawing ROIs around various structures using probabilistic tractography. The performances of registration algorithms on this second tractography method were evaluated by computing the spatial correlation similarity of the fibers between subjects as well as between each subject and the template.

Conclusion

All experimental results indicated that DTI-TK performed the best under the study conditions, and SyN ranked just behind it.

Tractography in the clinics: Implementing a pipeline to characterize early brain development

In imaging studies of neonates, particularly in the clinical setting, diffusion tensor imaging-based tractography is typically unreliable due to the use of fast acquisition protocols that yield low resolution and signal-to-noise ratio (SNR). These image acquisition protocols are implemented with the aim of reducing motion artifacts that may be produced by the movement of the neonate's head during the scanning session. Furthermore, axons are not yet fully myelinated in these subjects. As a result, the water molecules' movements are not as constrained as in older brains, making it even harder to define structure using diffusion profiles. Here, we introduce a post-processing method that overcomes the difficulties described above, allowing the determination of reliable tracts in newborns. We tested our method using neonatal data and successfully extracted some of the limbic, association and commissural fibers, all of which are typically difficult to obtain by direct tractography. Geometrical and diffusion based features of the tracts are then utilized to compare premature babies to term babies. Our results quantify the maturation of white matter fiber tracts in neonates.

•

The proposed method enables consistent tractography in clinical datasets.

•

The tractography is used to structural positioning purposes

•

Geometrical features and diffusion variables in the tracts' paths are analyzed.

•

The gestational age was predicted with regressions in term and preterm babies.

•

The extracted features can be used as indexes of early neurodevelopment.

The evolving utility of diffusion tensor tractography in the surgical management of temporal lobe epilepsy: a review

BACKGROUND

Diffusion tensor imaging (DTI) is a relatively new imaging modality that has found many peri-operative applications in neurosurgery.

METHODS

A comprehensive survey of the applications of diffusion tensor imaging (DTI) in planning for temporal lobe epilepsy surgery was conducted. The presentation of this literature is supplemented by a case illustration.

RESULTS

The authors have found that DTI is well utilized in epilepsy surgery, primarily in the tractography of Meyer's loop. DTI has also been used to demonstrate extratemporal connections that may be responsible for surgical failure as well as perioperative planning. The tractographic anatomy of the temporal lobe is discussed and presented with original DTI pictures.

CONCLUSIONS

The uses of DTI in epilepsy surgery are varied and rapidly evolving. A discussion of the technology, its limitations, and its applications is well warranted and presented in this article.

Characterization of ten white matter tracts in a representative sample of Cuban population

Background

The diffusion tensor imaging technique (DTI) combined with tractography methods, has achieved the tridimensional reconstruction of white matter tracts in the brain. It allows their characterization in vivo in a non-invasive way. However, one of the largest sources of variability originates from the location of regions of interest, is therefore necessary schemes which make it possible to establish a protocol to be insensitive to variations in drawing thereof. The purpose of this paper is to stablish a reliable protocol to reconstruct ten prominent tracts of white matter and characterize them according to volume, fractional anisotropy and mean diffusivity. Also we explored the relationship among these factors with gender and hemispheric symmetry.

Methods

This study aims to characterize ten prominent tracts of white matter in a representative sample of Cuban population using this technique, including 84 healthy subjects. Diffusion tensors and subsequently fractional anisotropy and mean diffusivity maps were calculated from each subject’s DTI scans. The trajectory of ten brain tracts was estimated by using deterministic tractography methods of fiber tracking. In such tracts, the volume, the FA and MD were calculated, creating a reference for their study in the Cuban population. The interactions between these variables with age, cerebral hemispheres and gender factors were explored using Repeated Measure Analysis of Variance.

Results

The volume values showed that a most part of tracts have bigger volume in left hemisphere. Also, the data showed bigger values of MD for males than females in all the tracts, an inverse behavior than FA values.

Conclusions

This work showed that is possible reconstruct white matter tracts using a unique region of interest scheme defined from standard to native space. Also, this study indicates differing developmental trajectories in white matter for males and females and the importance of taking gender into account in developmental DTI studies and in underlie gender-related cognitive differences.

Electronic supplementary material

The online version of this article (doi:10.1186/s12880-016-0163-7) contains supplementary material, which is available to authorized users.

White matter integrity of cerebellar-cortical tracts in reading impaired children: A probabilistic tractography study

Little is known about the white matter integrity of cerebellar-cortical pathways in individuals with dyslexia. Building on previous findings of decreased volume in the anterior lobe of the cerebellum, we utilized novel cerebellar segmentation procedures and probabilistic tractography to examine tracts that connect the anterior lobe of the cerebellum and cortical regions typically associated with reading: the temporoparietal (TP), occipitotemporal (OT), and inferior frontal (IF) regions. The sample included 29 reading impaired children and 27 typical readers. We found greater fractional anisotropy (FA) for the poor readers in tracts connecting the cerebellum with TP and IF regions relative to typical readers. In the OT region, FA was greater for the older poor readers, but smaller for the younger ones. This study provides evidence for discrete, regionally-bound functions of the cerebellum and suggests that projections from the anterior cerebellum appear to have a regulatory effect on cortical pathways important for reading.

Visualization of Central Nervous System Nerve Communications Using Diffusion Tensor Imaging

Diffusion tensor imaging (DTI) is a magnetic resonance (MR) technique used to analyze diffusion anisotropy of the central nervous system (CNS) and can demonstrate subtle white matter anatomy. In particular, tractography is expected to be a unique, non-invasive tool to provide more pertinent insights into brain structure and orientation not accessible with conventional MRI. Data collection was performed in a normal volunteer on a 1.5-T MRI system using several techniques including six axis single-shot echo planar imaging (EPI), over six axis EPI, and periodically rotated overlapping parallel lines with enhanced reconstruction techniques. Tractography was generated by a continuous tracking method with our original software, Volume-One (for viewing volumetric image data) and VizDT-II (for analysis of DTI data). Using these data, estimated tracts were generated in arcuate fibers of cerebrum, cingulum, superior longitudinal fasciculus, uncinate fasciculus, inferior longitudinal fasciculus, corpus callosum, fornix, anterior thalamic radiation, central thalamic radiation, thalamo-parietal fibers, optic radiation, superior cerebellar peduncle, middle cerebellar peduncle, inferior cerebellar peduncle and intrinsic commissure paths of the hipoccampous. DTI including tractography allows differentiation between complex white matter tracts. The information regarding the detailed relationship may be useful for diagnosis of the location and extent of brain lesions, and preoperative planning.

Characterizing structural neural networks in de novo Parkinson disease patients using diffusion tensor imaging

Parkinson disease (PD) can be considered as a brain multisystemic disease arising from dysfunction in several neural networks. The principal aim of this study was to assess whether large-scale structural topological network changes are detectable in PD patients who have not been exposed yet to dopaminergic therapy (de novo patients). Twenty-one drug-naïve PD patients and thirty healthy controls underwent a 3T structural MRI. Next, Diffusion Tensor Imaging (DTI) and graph theoretic analyses to compute individual structural white-matter (WM) networks were combined. Centrality (degree, eigenvector centrality), segregation (clustering coefficient), and integration measures (efficiency, path length) were assessed in subject-specific structural networks. Moreover, Network-based statistic (NBS) was used to identify whether and which subnetworks were significantly different between PD and control participants. De novo PD patients showed decreased clustering coefficient and strength in specific brain regions such as putamen, pallidum, amygdala, and olfactory cortex compared with healthy controls. Moreover, NBS analyses demonstrated that two specific subnetworks of reduced connectivity characterized the WM structural organization of PD patients. In particular, several key pathways in the limbic system, basal ganglia, and sensorimotor circuits showed reduced patterns of communications when comparing PD patients to controls. This study shows that PD is characterized by a disruption in the structural connectivity of several motor and non-motor regions. These findings provide support to the presence of disconnectivity mechanisms in motor (basal ganglia) as well as in non-motor (e.g., limbic, olfactory) circuits at an early disease stage of PD. Hum Brain Mapp 37:4500-4510, 2016. © 2016 Wiley Periodicals, Inc.

Symmetrical Location Characteristics of Corticospinal Tract Associated With Hand Movement in the Human Brain: A Probabilistic Diffusion Tensor Tractography

The purpose of this study is to elucidate the symmetrical characteristics of corticospinal tract (CST) related with hand movement in bilateral hemispheres using probabilistic fiber tracking method. Seventeen subjects were participated in this study. Fiber tracking was performed with 2 regions of interest, hand activated functional magnetic resonance imaging (fMRI) results and pontomedullary junction in each cerebral hemisphere. Each subject's extracted fiber tract was normalized with a brain template. To measure the symmetrical distributions of the CST related with hand movement, the laterality and anteriority indices were defined in upper corona radiata (CR), lower CR, and posterior limb of internal capsule. The measured laterality and anteriority indices between the hemispheres in each different brain location showed no significant differences with P < 0.05. There were significant differences in the measured indices among 3 different brain locations in each cerebral hemisphere with P < 0.001. Our results clearly showed that the hand CST had symmetric structures in bilateral hemispheres. The probabilistic fiber tracking with fMRI approach demonstrated that the hand CST can be successfully extracted regardless of crossing fiber problem. Our analytical approaches and results seem to be helpful for providing the database of CST somatotopy to neurologists and clinical researches.

Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study

Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, "tractography") approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template-using high-dimensional, non-linear warping methods-we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses.

Characterizations of resting-state modulatory interactions in the human brain

Functional connectivity between two brain regions, measured using functional MRI (fMRI), has been shown to be modulated by other regions even in a resting state, i.e., without performing specific tasks. We aimed to characterize large-scale modulatory interactions by performing region-of-interest (ROI)-based physiophysiological interaction analysis on resting-state fMRI data. Modulatory interactions were calculated for every possible combination of three ROIs among 160 ROIs sampling the whole brain. Firstly, among all of the significant modulatory interactions, there were considerably more negative than positive effects; i.e., in more cases, an increase of activity in one region was associated with decreased functional connectivity between two other regions. Next, modulatory interactions were categorized as to whether the three ROIs were from one single network module, two modules, or three different modules (defined by a modularity analysis on their functional connectivity). Positive modulatory interactions were more represented than expected in cases in which the three ROIs were from a single module, suggesting an increase within module processing efficiency through positive modulatory interactions. In contrast, negative modulatory interactions were more represented than expected in cases in which the three ROIs were from two modules, suggesting a tendency of between-module segregation through negative modulatory interactions. Regions that were more likely to have modulatory interactions were then identified. The numbers of significant modulatory interactions for different regions were correlated with the regions' connectivity strengths and connection degrees. These results demonstrate whole-brain characteristics of modulatory interactions and may provide guidance for future studies of connectivity dynamics in both resting state and task state.

Anisotropic Smoothing Improves DT-MRI-Based Muscle Fiber Tractography

Purpose

To assess the effect of anisotropic smoothing on fiber tracking measures, including pennation angle, fiber tract length, and fiber tract number in the medial gastrocnemius (MG) muscle in healthy subjects using diffusion-weighted magnetic resonance imaging (DW-MRI).

Materials and Methods

3T DW-MRI data were used for muscle fiber tractography in the MG of healthy subjects. Anisotropic smoothing was applied at three levels (5%, 10%, 15%), and pennation angle, tract length, fiber tract number, fractional anisotropy, and principal eigenvector orientation were quantified for each smoothing level.

Results

Fiber tract length increased with pre-fiber tracking smoothing, and local heterogeneities in fiber direction were reduced. However, pennation angle was not affected by smoothing.

Conclusion

Modest anisotropic smoothing (10%) improved fiber-tracking results, while preserving structural features.

Individual variability in the anatomical distribution of nodes participating in rich club structural networks

With recent advances in computational analyses of structural neuroimaging, it is possible to comprehensively map neural connectivity, i.e., the brain connectome. The architectural organization of the connectome is believed to play an important role in several biological processes. Central to the conformation of the connectome are connectivity hubs, which are likely to be organized in accordance with the rich club phenomenon, as evidenced by graph theory analyses of neural architecture. It is yet unclear whether rich club connectivity hubs are consistently organized in the same anatomical framework across healthy adults. We constructed the brain connectome from 43 healthy adults, based on T1-weighted and diffusion tensor MRI data. Probabilistic fiber tractography was used to evaluate connectivity between each possible pair of cortical anatomical regions of interest. Connectivity hubs were identified in accordance with the rich club phenomenon applied to binarized matrices, and the variability in frequency of hub participation was assessed node-wise across all subjects. The anatomical location of nodes participating in rich club networks was fairly consistent across subjects. The most common locations for rich club nodes were identified in integrative areas, such as the cingulate and pericingulate regions, medial aspect of the occipital areas and precuneus; or else, they were found in important and specialized brain regions (such as the oribitofrontal cortex, caudate, fusiform gyrus, and hippocampus). Marked anatomical consistency exists across healthy brains in terms of nodal participation and location of rich club networks. The consistency of connections between integrative areas and specialized brain regions highlights a fundamental connectivity pattern shared among healthy brains. We propose that approaching brain connectivity with this framework of anatomical consistencies may have clinical implications for early detection of individual variability.

Normal development of human brain white matter from infancy to early adulthood: a diffusion tensor imaging study

Diffusion tensor imaging (DTI), which measures the magnitude of anisotropy of water diffusion in white matter, has recently been used to visualize and quantify parameters of neural tracts connecting brain regions. In order to investigate the developmental changes and sex and hemispheric differences of neural fibers in normal white matter, we used DTI to examine 52 healthy humans ranging in age from 2 months to 25 years. We extracted the following tracts of interest (TOIs) using the region of interest method: the corpus callosum (CC), cingulum hippocampus (CGH), inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus (SLF). We measured fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD). Approximate values and changes in growth rates of all DTI parameters at each age were calculated and analyzed using LOESS (locally weighted scatterplot smoothing). We found that for all TOIs, FA increased with age, whereas ADC, AD and RD values decreased with age. The turning point of growth rates was at approximately 6 years. FA in the CC was greater than that in the SLF, ILF and CGH. Moreover, FA, ADC and AD of the splenium of the CC (sCC) were greater than in the genu of the CC (gCC), whereas the RD of the sCC was lower than the RD of the gCC. The FA of right-hemisphere TOIs was significantly greater than that of left-hemisphere TOIs. In infants, growth rates of both FA and RD were larger than those of AD. Our data show that developmental patterns differ by TOIs and myelination along with the development of white matter, which can be mainly expressed as an increase in FA together with a decrease in RD. These findings clarify the long-term normal developmental characteristics of white matter microstructure from infancy to early adulthood.

Peripheral nerves and plexus: imaging by MR-neurography and high-resolution ultrasound. Curr Opin Neurol. 2014;27:370-379. [PMID: 24978367 DOI: 10.1097/wco.0000000000000111]

PURPOSE OF REVIEW

The purpose of this study is to review advances in magnetic resonance (MR)-neurography and nerve-ultrasound for the precise visualization and localization of nerve lesions not only in nerve trauma or mass lesions, but also in entrapment-related and spontaneously occurring intrinsic neuropathies. These advances may improve the understanding and classification of peripheral neuropathies.

RECENT FINDINGS

Diagnostic studies of MR-neurography and high-resolution ultrasound in entrapment-neuropathies consistently report accurate determination and localization of symptomatic nerve entrapment. Additionally, the longitudinal sampling of nerve-T2-signal over larger areas of coverage has become technically feasible. With this approach, more complex patterns of spatial lesion dispersion in nonfocal neuropathies could be observed with reliable lesion image contrast at the level of individual nerve fascicles. Imaging detection of fascicular lesions allows for more accurate localization, because fascicular lesion types represent a specific pitfall for clinical-electrophysiological examinations. Fascicular hypoechogenicity of high-resolution ultrasound is the correlate of nerve-T2-signal lesions, but contrast is inferior and difficult to quantify. Therefore, nerve enlargement remains the main diagnostic criterion in high-resolution ultrasound. Diffusion-tensor-MR-neurography provides quantitative estimates of fiber structure, which were shown to correlate with aging and focal entrapment.

SUMMARY

High-resolution nerve imaging with extended anatomical coverage is feasible and improves the topographic description of spatial lesion dispersion which is particularly relevant for the discrimination between focal and nonfocal neuropathies.

Diffusion tensor imaging of neurofibromatosis bright objects in children with neurofibromatosis type 1

Neurofibromatosis bright objects (NBOs) are poorly understood. This article aimed to investigate: 1) differences in fractional anisotropy (FA) between NBOs based in gray matter (GM) and white matter (WM), and 2) the relationship between NBOs and the affected white matter tracts. Fourteen NF1 patients were included in this study. Apparent diffusion coefficient (ADC), FA, radial diffusivity (RD) and eigenvalues were used to compare NBOs and matching contralateral normal-appearing sites (NAS). Diffusion tensor imaging scalars were also compared with age-matched healthy controls. Fiber tractography was performed to assess NBO-induced changes in WM trajectories. ADC values were higher for GM and WM NBOs than for NAS and controls. FA values were lower in GM and WM NBOs compared with controls. In all regions, eigenvalues were higher in NBOs than in NAS and controls. Only three out of 18 NOBs appeared to disrupt WM tracts. ADC, λ2 and RD values of WM NBOs were higher in symptomatic compared to asymptomatic patients. Increased ADC, RD and eigenvalues and decreased FA values in NBOs can be explained by myelin and axonal damage. Increased ADC values and RD in WM NBOs correlated with the presence of symptoms. Tract integrity predominated in our study.

Human brain asymmetry in microstructural connectivity demonstrated by diffusional kurtosis imaging

Structural asymmetry of whole brain white matter (WM) pathways, i.e., the connectome, has been demonstrated using fiber tractography based on diffusion tensor imaging (DTI). However, DTI-based tractography fails to resolve axonal fiber bundles that intersect within an imaging voxel, and therefore may not fully characterize the extent of asymmetry. The goal of this study was to assess structural asymmetry with tractography based on diffusional kurtosis imaging (DKI), which improves upon DTI-based tractography by delineating intravoxel crossing fibers. DKI images were obtained from 42 healthy subjects. By using automatic segmentation, gray matter (GM) was parcellated into anatomically defined regions of interest (ROIs). WM pathways were reconstructed with both DKI- and DTI-based tractography. The connectivity between the ROIs was quantified with the streamlines connecting the ROIs. The asymmetry index (AI) was utilized to quantify hemispheric differences in the connectivity of cortical ROIs and of links interconnecting cortical ROIs. Our results demonstrated that leftward asymmetrical ROIs and links were observed in frontal, parietal, temporal lobes, and insula. Rightward asymmetrical ROI and links were observed in superior frontal lobe, cingulate cortex, fusiform, putamen, and medial temporal lobe. Interestingly, these observed structural asymmetries were incompletely identified with DTI-based tractography. These results suggest that DKI-based tractography can improve the identification of asymmetrical connectivity patterns, thereby serving as an additional tool in the evaluation of the structural bases of functional lateralization.

Reproducibility of graph metrics of human brain structural networks

Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. The reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are used to examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm.

Comparison of twice refocused spin echo versus stimulated echo diffusion tensor imaging for tracking muscle fibers

PURPOSE

To compare the precision of measuring the pennation angle and fiber length in the vastus lateralis (VL) using two distinctly different diffusion tensor imaging (DTI) sequences.

MATERIALS AND METHODS

We imaged the thigh of 10 normal subjects on a 3T magnetic resonance (MR) imager with twice refocused spin echo (TRSE) and stimulated echo (STEAM) DTI-MRI techniques. Both techniques took the same total acquisition time and employed the same diffusion weighting and gradient directions. Using the diffusion tensor images produced by each sequence, muscle fiber bundles were tracked from the aponeurosis by following the first eigenvector of the diffusion tensor. From these tracks we calculated the pennation angle and fiber length.

RESULTS

The STEAM acquisition resulted in significantly higher signal-to-noise ratio (SNR), lower apparent diffusion coefficient (ADC), higher fractional anisotropy (FA) values, and longer fibers than TRSE. Although no difference in the pennation angle between the two acquisitions was found, the TRSE sequence had a significantly greater within-subject dispersion in the pennation angle of tracked fibers, which may indicate a reduction in the coherence of fiber bundles.

CONCLUSION

DTI of muscle using a STEAM acquisition resulted in significant improvements in the SNR and FA, resulting in tracking a larger number of muscle fiber bundles over longer distances and with less within-subject dispersion.

Tailoring neurophysiological strategies with clinical context enhances resection and safety and expands indications in gliomas involving motor pathways

BACKGROUND

Resection of motor pathway gliomas requires the intraoperative recognition of essential cortical-subcortical motor structures. The degree of involvement of motor structures is variable, and increases as result of treatments patients are submitted to. Intraoperative neurophysiology offers various stimulation modalities, which efficiency is based on the ability to recognize essential sites with the highest possible resolution in most clinical conditions. Two stimulation paradigms evolved for intraoperative guidance of motor tumors removal: the 60 Hz-technique [low frequency (LF)] and the pulse-technique [high frequency-(HF)], delivered by bipolar or monopolar probe respectively. Most surgical teams rely on to either of the 2 techniques. The key point is the integration of the choice of the stimulation modality with the clinical context.

METHODS

In 591 tumors involving the corticospinal tract, the use of HF and LF was tailored to the clinical context defined by patient clinical history and tumor features (by imaging). The effect was evaluated on the feasibility of mapping, the impact on immediate and permanent morbidity, the extent of resection, and the number of patients treated.

RESULTS

By integrating the choice of the probe and the stimulation protocol with patient clinical history and tumor characteristics, the best probe-frequency match was identified for the different sets of clinical conditions. This integrative approach allows increasing the extent of resection and patient functional integrity, and greatly expands the number of patients who could benefit from surgery.

CONCLUSIONS

The integration of stimulation modalities with clinical context enhances the extent and safety of resection and expands the population of patients who could benefit from surgical treatment.