Opportunities and pitfalls in the quantification of fiber integrity: what can we gain from Q-ball imaging?

Q-ball high-resolution fiber tractography of language associated tracts: quantitative evaluation of applicability for glioma resections

BACKGROUND

To date, fiber tractography (FT) is predominantly based on diffusion tensor imaging (DTI). High angular resolution diffusion imaging (HARDI)-based reconstructions have become a focus of interest, enabling the resolution of intravoxel fiber crossing. However, experience with high resolution tractography (HRFT) for neurosurgical applications is still limited to a few reports. This prospectively designed feasibility study shares our initial experience using an analytical q-ball approach (QBI) for FT of language-associated pathways in comparison with DTI-FT, focussing on a quantitative analysis and evaluation of its applicability in clinical routine.

METHODS

Probabilistic QBI-, and DTI-FT were performed for the major components of the language-associated fiber bundles (superior longitudinal fasciculus, inferior fronto-occipital fasciculus, medial/inferior longitudinal faciculus) in 11 patients with eloquent gliomas. The data was derived from a routine DWI sequence (b=1000s/mm2, 64 gradient directions). Quantitative analysis evaluated tract volume (TV), tract length (TL) and tract density (TD). Results were correlated to tumor and edema size.

RESULTS

Quantitative analysis showed larger TV and TL of the overall fiber object using QBI-FT compared with DTI-FT (TV: 16.45±1.85 vs. 10.07±1.15cm3; P<0.0001; TL: 81.95±6.14 vs. 72.06±6.92 mm; P=0.0011). Regarding overall TD, DTI delivered significantly higher values (40.57±6.59 vs. 60.98±15.94 points/voxel; P=0.0118). Bland-Altman analysis illustrated a systematic advantage to yield lager TV and TL via QBI compared with DTI for all reconstructed pathways. The results were independent of tumor or edema volume.

CONCLUSIONS

QBI proved to be suitable for an application in the neurosurgical setting without additional expense for the patient. Quantitative analysis of FT reveals larger overall TV, longer TL with lower TD using QBI compared with DTI, suggesting the better depiction of marginal and terminal fibers according to neuroanatomical knowledge. This emphasizes the known limitation of DTI to underestimate the dimensions of a pathway. Rather than relying on DTI, sophisticated HRFT techniques should be considered for preoperative planning and intraoperative guidance in selected cases of eloquent glioma surgery.

Lipid and smooth muscle architectural pathology in the rabbit atherosclerotic vessel wall using Q-space cardiovascular magnetic resonance

BACKGROUND

Atherosclerosis is an arterial vessel wall disease characterized by slow, progressive lipid accumulation, smooth muscle disorganization, and inflammatory infiltration. Atherosclerosis often remains subclinical until extensive inflammatory injury promotes vulnerability of the atherosclerotic plaque to rupture with luminal thrombosis, which can cause the acute event of myocardial infarction or stroke. Current bioimaging techniques are unable to capture the pathognomonic distribution of cellular elements of the plaque and thus cannot accurately define its structural disorganization.

METHODS

We applied cardiovascular magnetic resonance spectroscopy (CMRS) and diffusion weighted CMR (DWI) with generalized Q-space imaging (GQI) analysis to architecturally define features of atheroma and correlated these to the microscopic distribution of vascular smooth muscle cells (SMC), immune cells, extracellular matrix (ECM) fibers, thrombus, and cholesteryl esters (CE). We compared rabbits with normal chow diet and cholesterol-fed rabbits with endothelial balloon injury, which accelerates atherosclerosis and produces advanced rupture-prone plaques, in a well-validated rabbit model of human atherosclerosis.

RESULTS

Our methods revealed new structural properties of advanced atherosclerosis incorporating SMC and lipid distributions. GQI with tractography portrayed the locations of these components across the atherosclerotic vessel wall and differentiated multi-level organization of normal, pro-inflammatory cellular phenotypes, or thrombus. Moreover, the locations of CE were differentiated from cellular constituents by their higher restrictive diffusion properties, which permitted chemical confirmation of CE by high field voxel-guided CMRS.

CONCLUSIONS

GQI with tractography is a new method for atherosclerosis imaging that defines a pathological architectural signature for the atheromatous plaque composed of distributed SMC, ECM, inflammatory cells, and thrombus and lipid. This provides a detailed transmural map of normal and inflamed vessel walls in the setting of atherosclerosis that has not been previously achieved using traditional CMR techniques. Although this is an ex-vivo study, detection of micro and mesoscale level vascular destabilization as enabled by GQI with tractography could increase the accuracy of diagnosis and assessment of treatment outcomes in individuals with atherosclerosis.

Quantification of changes in white matter tract fibers in idiopathic normal pressure hydrocephalus based on diffusion spectrum imaging

PURPOSE

Patients with idiopathic normal pressure hydrocephalus (iNPH) present white-matter abnormalities. The analytical methods described to date only measure mean diffusion parameter alterations of iNPH-specific brain regions or in a certain fasciculus. This study quantitatively analyzed whether iNPH-tract abnormalities are confined to specific sections or involve entire fibers based on diffusion spectrum imaging (DSI).

METHOD

Twenty-two patients with iNPH and 20 normally aging subjects were included. The 18 main tracts in the brain of each subject were extracted, and the diffusion parameters of 100 equidistant nodes on each fiber were calculated to quantitatively evaluate integrity changes in different regions along these tracts. Two diffusion metrics were measured, i.e., general fractional anisotropy (GFA) and fractional anisotropy (FA).

RESULTS

Compared to normally aging (P < 0.05), in iNPH, the GFA and FA of the left uncinate fasciculus and FA of the bilateral superior longitudinal fasciculus 1 were reduced in areas where the entire fiber was involved (%nodes with significant differences > 90%). Most other fasciculi detected presented GFA or FA alterations limited to specific regions. Increased and decreased GFA or FA co-occurred in different sections of the same fibers, including the corticospinal tract and left thalamic radiation posterior in iNPH.

CONCLUSIONS

Few iNPH fibers presented diffusion abnormalities involving nearly all tracts. Most fiber abnormalities in iNPH were confined to specific areas, and different parts of the same fasciculus showed diverse diffusion alterations in few cases. This DSI-based tract analysis provided detailed information on iNPH white-matter changes.

Trigeminal Nerve White Matter Fiber Abnormalities in Primary Trigeminal Neuralgia: A Diffusion Spectrum Imaging Study

OBJECTIVE

Diffusion spectrum imaging (DSI) was used to quantitatively study the changes in the trigeminal cistern segment in patients with trigeminal neuralgia (TN) and to further explore the value of acquiring DSI data from patients with TN.

METHODS

To achieve high-resolution fiber tracking, 60 patients with TN and 35 healthy controls (HCs) were scanned with conventional magnetic resonance imaging (MRI) and DSI. The patients and the members of the control group were compared within and between groups. The correlations between quantitative parameters of DSI and the visual analog scale (VAS), and symptom duration and responsible vessel types were analyzed.

RESULTS

Compared with unaffected side of patients in the TN group, the affected side showed significantly decreased quantitative anisotropy (QA) (p < 0.001), fractional anisotropy (FA) (p = 0.001), and general FA (GFA) (p < 0.001). The unaffected side exhibited significantly decreased QA (p + 0.001), FA (p = 0.001), and GFA (p < 0.001) and significantly increased axial diffusivity (AD) (p = 0.036) compared with the affected side of patients in the TN group and the average values of HCs. There were significantly decreased QA (p = 0.046) and FA (p = 0.008) between the unaffected side of patients and the average values of HCs. GFA can evidently distinguish arteries, veins, and features of unaffected side in TN patients.

CONCLUSION

Using high-resolution fiber tracking technology, DSI can provide quantitative information that can be used to detect the integrity of trigeminal white matter in patients with TN and can improve the understanding of the disease mechanism.

Group-Level Ranking-Based Hubness Analysis of Human Brain Connectome Reveals Significant Interhemispheric Asymmetry and Intraparcel Heterogeneities

Objective: Graph theory applications are commonly used in connectomics research to better understand connectivity architecture and characterize its role in cognition, behavior and disease conditions. One of the numerous open questions in the field is how to represent inter-individual differences with graph theoretical methods to make inferences for the population. Here, we proposed and tested a simple intuitive method that is based on finding the correlation between the rank-ordering of nodes within each connectome with respect to a given metric to quantify the differences/similarities between different connectomes.

Methods: We used the diffusion imaging data of the entire HCP-1065 dataset of the Human Connectome Project (HCP) (n = 1,065 subjects). A customized cortical subparcellation of HCP-MMP atlas (360 parcels) (yielding a total of 1,598 ROIs) was used to generate connectivity matrices. Six graph measures including degree, strength, coreness, betweenness, closeness, and an overall “hubness” measure combining all five were studied. Group-level ranking-based aggregation method (“measure-then-aggregate”) was used to investigate network properties on population level.

Results: Measure-then-aggregate technique was shown to represent population better than commonly used aggregate-then-measure technique (overall r_s: 0.7 vs 0.5). Hubness measure was shown to highly correlate with all five graph measures (r_s: 0.88–0.99). Minimum sample size required for optimal representation of population was found to be 50 to 100 subjects. Network analysis revealed a widely distributed set of cortical hubs on both hemispheres. Although highly-connected hub clusters had similar distribution between two hemispheres, average ranking values of homologous parcels of two hemispheres were significantly different in 71% of all cortical parcels on group-level.

Conclusion: In this study, we provided experimental evidence for the robustness, limits and applicability of a novel group-level ranking-based hubness analysis technique. Graph-based analysis of large HCP dataset using this new technique revealed striking hemispheric asymmetry and intraparcel heterogeneities in the structural connectivity of the human brain.

White matter microstructural integrity correlates of emotion dysregulation in children with ADHD: A diffusion imaging tractography study

BACKGROUND

Emotion dysregulation (ED) is prevalent in youths with attention-deficit hyperactivity disorder (ADHD) and causes more social impairment and poor adaptive function. Alterations in the integrity of white matter (WM) tracts might have important implications for affective processing related to ED. However, little is known about the WM correlates underpinning ED in ADHD.

METHODS

Using diffusion spectrum image tractography, we obtained generalized fractional anisotropy (GFA) values of 76 WM tracts in 77 children with ADHD and 105 typically developing controls (TDC). ED severity was defined by the dysregulation profile from the child behavior checklist. Canonical correlation analysis (CCA) was performed to identify modes that relate WM microstructural property to ED severity and cognitive measures.

RESULTS

The application of CCA identified one significant mode (r = 0.638, FWE-corrected p = 0.046) of interdependencies between WM property patterns and diagnosis, ADHD total symptom levels, dysregulation by diagnosis interaction, and full-scale intellectual quotient (FIQ). GFA values of 19 WM tracts that were linked to affective-processing, sensory-processing and integration, and cognitive control circuitry were positively correlated with ED severity in TDC but negatively correlated with ED severity in ADHD. ADHD symptom severity and diagnosis were negatively associated with the GFA patterns of this set of tract bundles. In contrast, FIQ was positively correlated with this set of tract bundles.

CONCLUSIONS

This study used the CCA to show that children with ADHD and TDC had distinct multivariate associations between ED severity (diagnosis by ED interaction) and microstructural property in a set of WM tracts. These tracts interconnect the cortical regions that are principally involved in emotion processing, integration, and cognitive control in multiple brain systems. The WM microstructure integrity impairment might be an essential correlate of emotion dysregulation in ADHD.

Posterior Precuneus is Highly Connected to Medial Temporal Lobe Revealed by Tractography and White Matter Dissection

The precuneus, involved in various cognitive processes, is considered to form the midline core of the default mode network (DMN), while the medial temporal lobe (MTL) is a subsystem of the DMN. Until now, the anatomical study of the precuneus-MTL connection is limited in humans. One possible reason is the precuneus' territory of the posteromedial cortex (PMC) is inconsistent across studies. The primary purpose of this study is to investigate the structural connectivity (SC) of precuneus-MTL, focusing on its anatomical organization using the Human Connectome Project Multi-modal Parcellation (HCP MMP) atlas. We first conducted the quantitative tractography analyses using the HCP dataset. The major streamlines originated from the posterior precuneus and were projected to the MTL extensively. Next, to complement the tractography data, we conducted the white matter dissection in the post-mortem human brain. We observed the major fiber bundles arise from the posterior precuneus extending to the anterior parahippocampal gyrus, which could support our tractography results. Then we analyzed the relationship between SC and resting-state functional connectivity (rsFC) of the precuneus-MTL. Although the SC-rsFC correlation was scarce on the whole, the posterior precuneus (POS2, 7Pm, 7m) showed a relatively high correlation (r = 0.38349, p < 0.05) with the posterior MTL (PreS, H, ProS, PHA1, PHA2). Our findings suggest the posterior precuneus is highly connected to MTL structurally, which could have an effect on the resting-state functional connectivity. In addition, the precuneus might consist of the heterogeneous connectivity-based subdivisions.

Enhanced White Matter Fiber Tracts in Advanced Jazz Improvisers

Human cognition and behavior arise from neuronal interactions over brain structural networks. These neuronal interactions cause changes in structural networks over time. How a creative activity such as musical improvisation performance changes the brain structure is largely unknown. In this diffusion magnetic resonance imaging study, we examined the brain’s white matter fiber properties in previously identified functional networks and compared the findings between advanced jazz improvisers and non-musicians. We found that, for advanced improvisers compared with non-musicians, the normalized quantitative anisotropy (NQA) is elevated in the lateral prefrontal areas and supplementary motor area, and the underlying white matter fiber tracts connecting these areas. This enhancement of the diffusion anisotropy along the fiber pathway connecting the lateral prefrontal and supplementary motor is consistent with the functional networks during musical improvisation tasks performed by expert jazz improvisers. These findings together suggest that experts’ creative skill is associated with the task-relevant, long-timescale brain structural network changes, in support of related cognitive underpinnings.

Integrity of the Prefronto-striato-thalamo-prefrontal Loop Predicts Tai Chi Chuan Training Effects on Cognitive Task-switching in Middle-aged and Older Adults

Tai Chi Chuan (TCC) exercise has been shown to improve cognitive task-switching performance in older adults, but the extent of this positive effect varies among individuals. Past research also shows that brain white matter integrity could predict behavioral gains of cognitive and motor learning. Therefore, in this randomized controlled trial (NCT02270320), we examined whether baseline integrity of three target white matter tract groups was predictive of task-switching improvement after 12-week TCC training in middle-aged and older adults. Thirty-eight eligible participants were randomly assigned to a TCC group (n = 19) and a control group (n = 19). Cognitive task-switching and physical performances were collected before and after training. Brain diffusion spectrum MR images were acquired before training and the general fractional anisotropy (GFA) of each target white matter tract group was calculated to indicate baseline white matter integrity of that group. Correlation and regression analyses between these GFAs and post-training task-switching improvement were analyzed using adjusted p-values. After 12 weeks, significant task-switching and physical performance improvements were found only in the TCC group. Moreover, higher baseline GFA of the prefronto-striato-thalamo-prefrontal loop fibers (r = −0.63, p = 0.009), but not of the prefronto-parietal/occipital (r = −0.55, p = 0.026) and callosal (r = −0.35, p = 0.189) fiber groups, was associated with greater reductions of task-switching errors after the TCC training. Multiple regression analysis revealed that baseline GFA of the prefronto-striato-thalamo-prefrontal loop fibers was the only independent white matter integrity predictor of task-switching error reductions after TCC training (β = −0.620, adjusted R² change = 0.265, p = 0.009). These findings not only highlight the important role of baseline integrity of the prefronto-striatal circuits in influencing the extent of positive cognitive task-switching effects from short-term TCC training, but also implicate that preserving good white matter integrity in the aging process may be crucial in order to gain the best cognitive effects of exercise interventions.

Aberrant Maturation of the Uncinate Fasciculus Follows Exposure to Unpredictable Patterns of Maternal Signals

Across species, unpredictable patterns of maternal behavior are emerging as novel predictors of aberrant cognitive and emotional outcomes later in life. In animal models, exposure to unpredictable patterns of maternal behavior alters brain circuit maturation and cognitive and emotional outcomes. However, whether exposure to such signals in humans alters the development of brain pathways is unknown. In mother-child dyads, we tested the hypothesis that exposure to more unpredictable maternal signals in infancy is associated with aberrant maturation of corticolimbic pathways. We focused on the uncinate fasciculus, the primary fiber bundle connecting the amygdala to the orbitofrontal cortex and a key component of the medial temporal lobe-prefrontal cortex circuit. Infant exposure to unpredictable maternal sensory signals was assessed at 6 and 12 months. Using high angular resolution diffusion imaging, we quantified the integrity of the uncinate fasciculus using generalized fractional anisotropy (GFA). Higher maternal unpredictability during infancy presaged greater uncinate fasciculus GFA in children 9-11 years of age (n = 69, 29 female). In contrast to the uncinate, GFA of a second corticolimbic projection, the hippocampal cingulum, was not associated with maternal unpredictability. Addressing the overall functional significance of the uncinate and cingulum relationships, we found that the resulting imbalance of medial temporal lobe-prefrontal cortex connectivity partially mediated the association between unpredictable maternal sensory signals and impaired episodic memory function. These results suggest that unbalanced maturation of corticolimbic circuits is a mechanism by which early unpredictable sensory signals may impact cognition later in life.SIGNIFICANCE STATEMENT Our prior work across species demonstrated that unpredictable patterns of maternal care are associated with compromised memory function. However, the neurobiological mechanisms by which this occurs in humans remain unknown. Here, we identify an association of exposure to unpredictable patterns of maternal sensory signals with the integrity of corticolimbic circuits involved in emotion and cognition using state-of-the-art diffusion imaging techniques and analyses. We find that exposure to early unpredictability is associated with higher integrity of the uncinate fasciculus with no effect on a second corticolimbic pathway, the cingulum. The resulting imbalance of corticolimbic circuit development is a novel mediator of the association between unpredictable patterns of maternal care and poorer episodic memory.

Association of self-regulation with white matter correlates in boys with and without autism spectrum disorder

Previous studies demonstrated distinct neural correlates underpinning impaired self-regulation (dysregulation) between individuals with autism spectrum disorder (ASD) and typically developing controls (TDC). However, the impacts of dysregulation on white matter (WM) microstructural property in ASD and TDC remain unclear. Diffusion spectrum imaging was acquired in 59 ASD and 62 TDC boys. We investigated the relationship between participants’ dysregulation levels and microstructural property of 76 WM tracts in a multivariate analysis (canonical correlation analysis), across diagnostic groups. A single mode of brain-behavior co-variation was identified: participants were spread along a single axis linking diagnosis, dysregulation, diagnosis-by-dysregulation interaction, and intelligence to a specific WM property pattern. This mode corresponds to diagnosis-distinct correlates underpinning dysregulation, which showed higher generalized fractional anisotropy (GFA) associated with less dysregulation in ASD but greater dysregulation in TDC, in the tracts connecting limbic and emotion regulation systems. Moreover, higher GFA of the tracts implicated in memory, attention, sensorimotor processing, and perception associated with less dysregulation in TDC but worse dysregulation in ASD. No shared WM correlates of dysregulation between ASD and TDC were identified. Corresponding to previous studies, we demonstrated that ASD and TDC have broad distinct white matter microstructural property underpinning self-regulation.

Developmental Differences of Structural Connectivity and Effective Connectivity in Semantic Judgments of Chinese Characters

Previous studies have investigated the developmental differences of semantic processing regarding brain activation between adults and children. However, little is known about whether the patterns of structural connectivity and effective connectivity differ between adults and children during semantic processing. Functional magnetic resonance imaging (fMRI), diffusion spectrum imaging (DSI), and dynamic causal modeling (DCM) were used to study the developmental differences of brain activation, structural connectivity, and effective connectivity during semantic judgments. Twenty-six children (8- to 12-year-olds) and 26 adults were asked to indicate if character pairs were related in meaning. Compared to children, adults showed greater activation in the left ventral inferior frontal gyrus (IFG) and left middle temporal gyrus (MTG). Also, adults had significantly greater structural connectivity in the left ventral pathway (inferior frontal occipital fasciculus, IFOF) than children. Moreover, adults showed significantly stronger bottom-up effects from left fusiform gyrus (FG) to ventral IFG than children in the related condition. In conclusion, our findings suggest that age-related increases in brain activation (ventral IFG and MTG), IFOF, and effective connectivity (from FG to ventral IFG) might be associated with the bottom-up influence of orthographic representations on retrieving semantic representations for processing Chinese characters.

Brain microstructural abnormalities in type 2 diabetes mellitus: A systematic review of diffusion tensor imaging studies

Type 2 diabetes mellitus (T2DM) is associated with deficits in the structure and function of the brain. Diffusion tensor imaging (DTI) is a highly sensitive method for characterizing cerebral tissue microstructure. Using PRISMA guidelines, we identified 29 studies which have demonstrated widespread brain microstructural impairment and topological network disorganization in patients with T2DM. Most consistently reported structures with microstructural abnormalities were frontal, temporal, and parietal lobes in the lobar cluster; corpus callosum, cingulum, uncinate fasciculus, corona radiata, and internal and external capsules in the white matter cluster; thalamus in the subcortical cluster; and cerebellum. Microstructural abnormalities were correlated with pathological derangements in the endocrine profile as well as deficits in cognitive performance in the domains of memory, information-processing speed, executive function, and attention. Altogether, the findings suggest that the detrimental effects of T2DM on cognitive functions might be due to microstructural disruptions in the central neural structures.

Neuroepigenetic signatures of age and sex in the living human brain

Age- and sex-related alterations in gene transcription have been demonstrated, however the underlying mechanisms are unresolved. Neuroepigenetic pathways regulate gene transcription in the brain. Here, we measure in vivo expression of the epigenetic enzymes, histone deacetylases (HDACs), across healthy human aging and between sexes using [¹¹C]Martinostat positron emission tomography (PET) neuroimaging (n = 41). Relative HDAC expression increases with age in cerebral white matter, and correlates with age-associated disruptions in white matter microstructure. A post mortem study confirmed that HDAC1 and HDAC2 paralogs are elevated in white matter tissue from elderly donors. There are also sex-specific in vivo HDAC expression differences in brain regions associated with emotion and memory, including the amygdala and hippocampus. Hippocampus and white matter HDAC expression negatively correlates with emotion regulation skills (n = 23). Age and sex are associated with HDAC expression in vivo, which could drive age- and sex-related transcriptional changes and impact human behavior.

Gene transcription is known to vary with age and sex, although the underlying mechanisms are unresolved. Here, the authors show that epigenetic enzymes known as HDACs, which regulate gene transcription, are increasingly expressed with age in the living human brain, with sex differences also observed.

Modelling white matter with spherical deconvolution: How and why?

Since the realization that diffusion MRI can probe the microstructural organization and orientation of biological tissue in vivo and non-invasively, a multitude of diffusion imaging methods have been developed and applied to study the living human brain. Diffusion tensor imaging was the first model to be widely adopted in clinical and neuroscience research, but it was also clear from the beginning that it suffered from limitations when mapping complex configurations, such as crossing fibres. In this review, we highlight the main steps that have led the field of diffusion imaging to move from the tensor model to the adoption of diffusion and fibre orientation density functions as a more effective way to describe the complexity of white matter organization within each brain voxel. Among several techniques, spherical deconvolution has emerged today as one of the main approaches to model multiple fibre orientations and for tractography applications. Here we illustrate the main concepts and the reasoning behind this technique, as well as the latest developments in the field. The final part of this review provides practical guidelines and recommendations on how to set up processing and acquisition protocols suitable for spherical deconvolution.

Alterations in white matter microstructure and regional volume are related to motor functions in boys with autism spectrum disorder

BACKGROUND

Altered inter-regional structural connectivity related to higher cognitive functions has been commonly reported in individuals with autism spectrum disorder (ASD). However, whether these alterations similarly involve cortico-cerebellar motor circuitries remains largely elusive.

METHODS

Using a cross-modality approach accounting for in-scanner motion levels, we investigated white matter (WM) properties in motor circuits of 55 boys with ASD (aged 8-18 years) and 68 age-matched typically developing boys. Regional WM volumes in the primary motor, supplementary motor, somatosensory, and cerebellar areas were investigated using voxel-based morphometry. Diffusion spectrum imaging tractography was used to estimate WM integrity of the corticospinal, cortico-ponto-cerebellar (including fronto-ponto-cerebellar and parieto-ponto-cerebellar), and dentato-rubro-thalamo-cortical tracts. The reaction time test in the Cambridge Neuropsychological Test Automated Battery was used to assess motor performances.

RESULTS

Boys with ASD had shorter movement time, increased WM volumes in the left somatosensory area, but decreased generalized fractional anisotropy value in the left parieto-ponto-cerebellar tract, compared to controls. A positive correlation between movement time and microstructural properties of the left parieto-ponto-cerebellar tract was found in boys with ASD.

CONCLUSIONS

As the first study to demonstrate altered WM properties in the left somatosensory area, and its descending pathway connecting to the cerebellum in ASD, current results may highlight a potential new target of interventions for motor performance in ASD.

Impaired Callosal Motor Fiber Integrity and Upper Extremity Motor Impairment Are Associated With Stroke Lesion Location

BACKGROUND

Damage to the callosal motor fibers (CMFs) may affect motor recovery in patients with stroke. However, whether the severity of CMF impairment varies with lesion locations remains unclear.

OBJECTIVE

To investigate (1) whether CMF impairment occurs after stroke and whether the impairment varies with lesion locations and (2) the associations of CMF impairment and upper extremity (UE) motor impairment.

METHODS

Twenty-nine patients with lesions involving the corticospinal tract (CST) were categorized into 2 groups: lesions involving the CMFs (CMF group, n = 15), and lesions not involving the CMFs (non-CMF group, n = 14). Thirteen healthy adults served as the control group. Tract integrity, assessed by the mean generalized fractional anisotropy (mGFA) using diffusion spectrum imaging, of the CMFs and the CST above the internal capsule (CST_ABOVE) of the ipsilesional hemisphere were compared.

RESULTS

After accounting for the effect of lesion load on the CST, the CMF group exhibited a significantly lower mGFA of the CMFs than did the control and non-CMF groups (post hoc P = .005 and .001, respectively). No significant difference was observed between the non-CMF and control groups (post hoc P = .999). The CST and CMF impairment accounted for 56% of the variance of UE motor impairment in the CMF group ( P = .007), whereas no significant association was observed in the non-CMF group ( P = .570).

CONCLUSIONS

CMF impairment after stroke depends on lesion locations and CMF integrity has an incremental contribution to the severity of UE motor impairment in the CMF group.

Cerebro-Cerebellar Pathways for Verbal Working Memory

The current study examined the structural and functional connectivity of the cerebro-cerebellar network of verbal working memory as proposed by Chen and Desmond (2005a). Diffusion spectrum imaging was employed to establish structural connectivity between cerebro-cerebellar regions co-activated during a verbal working memory task. The inferior frontal gyrus, inferior parietal lobule, pons, thalamus, superior cerebellum and inferior cerebellum were used as regions of interest to reconstruct and segment the contralateral white matter cerebro-cerebellar circuitry. The segmented pathways were examined further to establish the relationship between structural and effective connectivity as well as the relationship between structural connectivity and verbal working memory performance. No direct relationship between structural and effective connectivity was found but the results demonstrated that structural connectivity is indirectly related to effective connectivity as DCM models that resembled more closely with underlying white matter pathways had a higher degree of model inference confidence. Additionally, it was demonstrated that the structural connectivity of the ponto-cerebellar tract was associated with individual differences in response time for verbal working memory. The findings of the study contribute to further our understanding of the relationship between structural and functional connectivity and the impact of variability in verbal working memory performance.

Altered frontal aslant tracts as a heritable neural basis of social communication deficits in autism spectrum disorder: A sibling study using tract-based automatic analysis

Investigating social behaviors and brain structural alterations in unaffected siblings of individuals with autism spectrum disorder (ASD) may help identify intermediate phenotypes of social communication deficits in ASD. This study hypothesized that such intermediate phenotypes could be identified in white matter tracts of the social communication model that exhibited reduced tract integrity and associations with social communication deficits. Boys with ASD (N = 30), unaffected male siblings (N = 27), and typically developing (TD) boys (N = 30) underwent clinical evaluation and MRI scanning. Group differences in generalized fractional anisotropy (GFA) values, a white matter integrity index derived from diffusion MRI data, and the relationships of GFA with the Social Responsiveness Scale (SRS) scores and the Child Behavior Checklist (CBCL/4-18) scores were investigated. Significant differences were found in the GFA values of the frontal aslant tract (FAT) among the three groups, with the decreasing order of GFA from TD to siblings to ASD. The GFA values of the FAT were associated with the social communication scores (on the SRS) in the sibling group, and those of the superior longitudinal fasciculus III were associated with the social problems scores (on the CBCL/4-18) in the boys with ASD. Due to the altered tract integrity and association with social communication deficits in the unaffected siblings of individuals with ASD, the FAT might be a heritable neural basis for social communication deficits of ASD. Autism Res 2019, 12: 225-238 © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is a group of highly heritable disorders with social communication deficits as one of the core symptoms. This study aimed to identify a neural trait of social communication deficits in individuals with ASD. We investigated brain structural alterations and their associations with social communication scores in unaffected siblings of individuals with ASD. The siblings' frontal aslant tract was found to be impaired, and this tract showed a significant association with the social communication scores. Our findings support that the frontal aslant tract might be a potential neural trait of social communication deficits in ASD.

Advances in microstructural diffusion neuroimaging for psychiatric disorders

Understanding the neuropathological underpinnings of mental disorders such as schizophrenia, major depression, and bipolar disorder is an essential step towards the development of targeted treatments. Diffusion MRI studies utilizing the diffusion tensor imaging (DTI) model have been extremely successful to date in identifying microstructural brain abnormalities in individuals suffering from mental illness, especially in regions of white matter, although identified abnormalities have been biologically non-specific. Building on DTI's success, in recent years more advanced diffusion MRI methods have been developed and applied to the study of psychiatric populations, with the aim of offering increased sensitivity to subtle neurological abnormalities, as well as improved specificity to candidate pathologies such as demyelination and neuroinflammation. These advanced methods, however, usually come at the cost of prolonged imaging sequences or reduced signal to noise, and they are more difficult to evaluate compared with the more simplified approach taken by the now common DTI model. To date, a limited number of advanced diffusion MRI methods have been employed to study schizophrenia, major depression and bipolar disorder populations. In this review we survey these studies, compare findings across diverse methods, discuss the main benefits and limitations of the different methods, and assess the extent to which the application of more advanced diffusion imaging approaches has led to novel and transformative information with regards to our ability to better understand the etiology and pathology of mental disorders.

Diffusion spectrum imaging in white matter microstructure in subjects with type 2 diabetes

This study aimed to investigate the feasibility and clinical applicability of Diffusion Spectrum Imaging (DSI) for quantitative detection of white matter microstructural integrity. Twenty-seven patients with type 2 diabetes mellitus (T2DM; aged 60.6±7.6 years) and 21 healthy controls (HC; aged 56.1±7.8 years) underwent high-resolution T1-weighted imaging and DSI scanning. Cognitive function scores were obtained using such instruments as the Montreal Cognitive Assessment (MoCA). The fasting blood glucose, glycated hemoglobin, and total cholesterol (CHO) of T2DM were measured. The bilateral uncinate fasciculus and superior cingulum bundle were reconstructed by DSI tractography. Statistical analysis was performed using SPSS 21.0 software and P<0.05 was considered significant. Generalized fractional anisotropy (GFA) values were significantly decreased in the left uncinate fasciculus (t = −2.915, p = 0.005) and right superior cingulum bundle (t = −2.604, p = 0.012) in T2DM patients compared with the healthy controls (p<0.05). The MoCA (t = −3.339, p = 0.002) and CDT (t = −3.039, p = 0.004) scores of T2DM were significantly lower than those of healthy controls. Meanwhile, the GFA value of the right superior cingulum bundle was negatively associated with VFT score (r = −0.475, p = 0.012), and that of the right superior cingulum bundle was negatively associated with blood CHO level (r = −0.458, p = 0.016). DSI tractography is capable of evaluating the microstructural integrity of the white matter bundle in T2DM and is related to clinical cognitive scores and related biochemical indices; therefore, it can help to predict early white matter abnormalities in T2DM.

A comparison of three fiber tract delineation methods and their impact on white matter analysis

Diffusion magnetic resonance imaging (dMRI) is an important method for studying white matter connectivity in the brain in vivo in both healthy and clinical populations. Improvements in dMRI tractography algorithms, which reconstruct macroscopic three-dimensional white matter fiber pathways, have allowed for methodological advances in the study of white matter; however, insufficient attention has been paid to comparing post-tractography methods that extract white matter fiber tracts of interest from whole-brain tractography. Here we conduct a comparison of three representative and conceptually distinct approaches to fiber tract delineation: 1) a manual multiple region of interest-based approach, 2) an atlas-based approach, and 3) a groupwise fiber clustering approach, by employing methods that exemplify these approaches to delineate the arcuate fasciculus, the middle longitudinal fasciculus, and the uncinate fasciculus in 10 healthy male subjects. We enable qualitative comparisons across methods, conduct quantitative evaluations of tract volume, tract length, mean fractional anisotropy, and true positive and true negative rates, and report measures of intra-method and inter-method agreement. We discuss methodological similarities and differences between the three approaches and the major advantages and drawbacks of each, and review research and clinical contexts for which each method may be most apposite. Emphasis is given to the means by which different white matter fiber tract delineation approaches may systematically produce variable results, despite utilizing the same input tractography and reliance on similar anatomical knowledge.

Blue-Light Therapy following Mild Traumatic Brain Injury: Effects on White Matter Water Diffusion in the Brain

Mild traumatic brain injury (mTBI) is a common and often inconspicuous wound that is frequently associated with chronic low-grade symptoms and cognitive dysfunction. Previous evidence suggests that daily blue wavelength light therapy may be effective at reducing fatigue and improving sleep in patients recovering from mTBI. However, the effects of light therapy on recovering brain structure remain unexplored. In this study, we analyzed white matter diffusion properties, including generalized fractional anisotropy, and the quantity of water diffusion in isotropic (i.e., isotropic diffusion) and anisotropic fashion (i.e., quantitative anisotropy, QA) for fibers crossing 11 brain areas known to be significantly affected following mTBI. Specifically, we investigated how 6 weeks of daily morning blue light exposure therapy (compared to an amber-light placebo condition) impacted changes in white matter diffusion in individuals with mTBI. We observed a significant impact of the blue light treatment (relative to the placebo) on the amount of water diffusion (QA) for multiple brain areas, including the corpus callosum, anterior corona radiata, and thalamus. Moreover, many of these changes were associated with improvements in sleep latency and delayed memory. These findings suggest that blue wavelength light exposure may serve as one of the potential non-pharmacological treatments for facilitating structural and functional recovery following mTBI; they also support the use of QA as a reliable neuro-biomarker for mTBI therapies.

The challenge of mapping the human connectome based on diffusion tractography

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Though tractography is widely used, it has not been systematically validated. Here, authors report results from 20 groups showing that many tractography algorithms produce both valid and invalid bundles.

Temperature and concentration calibration of aqueous polyvinylpyrrolidone (PVP) solutions for isotropic diffusion MRI phantoms

To use the "apparent diffusion coefficient" (Dapp) as a quantitative imaging parameter, well-suited test fluids are essential. In this study, the previously proposed aqueous solutions of polyvinylpyrrolidone (PVP) were examined and temperature calibrations were obtained. For example, at a temperature of 20°C, Dapp ranged from 1.594 (95% CI: 1.593, 1.595) μm2/ms to 0.3326 (95% CI: 0. 3304, 0.3348) μm2/ms for PVP-concentrations ranging from 10% (w/w) to 50% (w/w) using K30 polymer lengths. The temperature dependence of Dapp was found to be so strong that a negligence seems not advisable. The temperature dependence is descriptively modelled by an exponential function exp(c2 (T - 20°C)) and the determined c2 values are reported, which can be used for temperature calibration. For example, we find the value 0.02952 K-1 for 30% (w/w) PVP-concentration and K30 polymer length. In general, aqueous PVP solutions were found to be suitable to produce easily applicable and reliable Dapp-phantoms.

Reduced tract integrity of the model for social communication is a neural substrate of social communication deficits in autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with social communication deficits as one of the core symptoms. Recently, a five-level model for the social communication has been proposed in which white matter tracts corresponding to each level of the model are identified. Given that the model for social communication subserves social language functions, we hypothesized that the tract integrity of the model for social communication may be reduced in ASD, and the reduction may be related to social communication deficits.

METHODS

Sixty-two right-handed boys with ASD and 55 typically developing (TD) boys received clinical evaluations, intelligence tests, the Social Communication Questionnaire (SCQ), and MRI scans. Generalized fractional anisotropy (GFA) was measured by diffusion spectrum imaging to indicate the microstructural integrity of the tracts for each level of the social communication model. Group difference in the tract integrity and its relationship with the SCQ subscales of social communication and social interaction were investigated.

RESULTS

We found that the GFA values of the superior longitudinal fasciculus III (SLF III, level 1) and the frontal aslant tracts (FAT, level 2) were decreased in ASD compared to TD. Moreover, the GFA values of the SLF III and the FAT were associated with the social interaction subscale in ASD.

CONCLUSIONS

The tract integrity of the model for social communication is reduced in ASD, and the reduction is associated with impaired social interaction. Our results support that reduced tract integrity of the model for social communication might be a neural substrate of social communication deficits in ASD.

Hippocampal Atrophy Is Associated with Altered Hippocampus-Posterior Cingulate Cortex Connectivity in Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis

BACKGROUND AND PURPOSE

Unilateral mesial temporal lobe epilepsy and hippocampal sclerosis have structural and functional abnormalities in the mesial temporal regions. To gain insight into the pathophysiology of the epileptic network in mesial temporal lobe epilepsy with hippocampal sclerosis, we aimed to clarify the relationships between hippocampal atrophy and the altered connection between the hippocampus and the posterior cingulate cortex in patients with mesial temporal lobe epilepsy with hippocampal sclerosis.

MATERIALS AND METHODS

Fifteen patients with left mesial temporal lobe epilepsy with hippocampal sclerosis and 15 healthy controls were included in the study. Multicontrast MR imaging, including high-resolution T1WI, diffusion spectrum imaging, and resting-state fMRI, was performed to measure the hippocampal volume, structural connectivity of the inferior cingulum bundle, and intrinsic functional connectivity between the hippocampus and the posterior cingulate cortex, respectively.

RESULTS

Compared with controls, patients had decreased left hippocampal volume (volume ratio of the hippocampus and controls, 0.366% ± 0.029%; patients, 0.277% ± 0.063%, corrected P = .002), structural connectivity of the bilateral inferior cingulum bundle (generalized fractional anisotropy, left: controls, 0.234 ± 0.020; patients, 0.193 ± 0.022, corrected P = .0001, right: controls, 0.226 ± 0.022; patients, 0.208 ± 0.017, corrected P = .047), and intrinsic functional connectivity between the left hippocampus and the left posterior cingulate cortex (averaged z-value: controls, 0.314 ± 0.152; patients, 0.166 ± 0.062). The left hippocampal volume correlated with structural connectivity positively (standardized β = 0.864, P = .001), but it had little correlation with intrinsic functional connectivity (standardized β = -0.329, P = .113). On the contralesional side, the hippocampal volume did not show any significant correlation with structural connectivity or intrinsic functional connectivity (F_2,12 = 0.284, P = .757, R² = 0.045).

CONCLUSIONS

In left mesial temporal lobe epilepsy with hippocampal sclerosis, the left inferior cingulum bundle undergoes degeneration in tandem with the left hippocampal volume, whereas intrinsic functional connectivity seems to react by compensating the loss of connectivity. Such insight might be helpful in understanding the development of the epileptic network in left mesial temporal lobe epilepsy with hippocampal sclerosis.

Merged Group Tractography Evaluation with Selective Automated Group Integrated Tractography

Introduction: Tractography analysis in group-based studies across large populations has been difficult to implement. We propose Selective Automated Group Integrated Tractography (SAGIT), an automated group tractography software platform that incorporates multiple diffusion magnetic resonance imaging (dMRI) practices which will allow great accessibility to group-wise dMRI. We use a merged tractography approach that permits evaluation of tractography datasets at the group level. We also introduce an image normalized overlap score (NOS) that measures the quality of the group tractography results. We deploy SAGIT to evaluate deterministic and probabilistic constrained spherical deconvolution (CST det , CST prob ) tractography, eXtended Streamline Tractography (XST), and diffusion tensor tractography (DTT) in their ability to delineate different neuroanatomy, as well as validating NOS across these different brain regions. Materials and methods: Magnetic resonance sequences were acquired from 42 healthy adults. Anatomical and group registrations were performed using Automated Normalization Tools. Cortical segmentation was performed using FreeSurfer. Four tractography algorithms were used to delineate six sets of neuroanatomy: fornix, facial/vestibular-cochlear cranial nerve complex, vagus nerve, rubral-cerebellar decussation, optic radiation, and auditory radiation. The tracts were generated both with and without region of interest filters. The generated visual reports were then evaluated by five neuroscientists. Results: At a group level, merged tractography demonstrated that different methods have different fiber distribution characteristics. CST prob is prone to false-positives, and thereby suitable in anatomy with strong priors. CST det and XST are more conservative, but have greater difficulty resolving hemispherical decussation and distant crossing projections. DTT consistently shows the worst reproducibility across the anatomies. Linear regression of rater scores against NOS shows significant (p < 0.05) correlation of the two sets of scores in filtered tractography. However, correlations are not significant (p > 0.05) for unfiltered tractography. Conclusion: The tractography results demonstrated reliable and consistent performance of SAGIT across multiple subjects and techniques. Through SAGIT, we quantifiably demonstrated that different algorithms showed different strengths and weaknesses at a group level. While no single algorithm seems to be suitable for all anatomical tasks, it is useful to consider the use of a mix of algorithms for different anatomical segments. SAGIT appears to be a promising group-wise tractography analysis approach for this purpose.

Deficient visuospatial working memory functions and neural correlates of the default-mode network in adolescents with autism spectrum disorder

In addition to the essential features of autism spectrum disorder (ASD), namely social communication deficits and repetitive behaviors, individuals with ASD may suffer from working memory deficits and an altered default-mode network (DMN). We hypothesized that an altered DMN is related to working memory deficits in those with ASD. A total of 37 adolescents with ASD and 36 age- and IQ-matched typically developing (TD) controls were analyzed. Visuospatial working memory performance was assessed using pattern recognition memory (PRM), spatial recognition memory (SRM), and paired-associates learning (PAL) tasks. The intrinsic functional connectivity (iFC) of the DMN was indexed by the temporal correlations between the resting-state functional magnetic resonance imaging signals of pairs of DMN regions, including those between the posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC) and between the PCC and parahippocampi (PHG). The corresponding structural connectivity of the DMN was indexed by the generalized fractional anisotropy (GFA) of the dorsal and ventral cingulum bundles on the basis of diffusion spectrum imaging data. The results showed that ASD adolescents exhibited delayed correct responses in PRM and SRM tasks and committed more errors in the PAL task than the TD controls did. The delayed responses during the PRM and SRM tasks were negatively correlated with bilateral PCC-mPFC iFCs, and PAL performance was negatively correlated with right PCC-PHG iFC in ASD adolescents. Furthermore, ASD adolescents showed significant lower GFA in the right cingulum bundles than the TD group did; the GFA value was negatively correlated with SRM performance in ASD. Our results provide empirical evidence for deficient visuospatial working memory and corresponding neural correlates within the DMN in adolescents with ASD. Autism Res 2016, 9: 1058-1072. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Primary and secondary alterations of white matter connectivity in schizophrenia: A study on first-episode and chronic patients using whole-brain tractography-based analysis

Schizophrenia is a debilitating mental disorder that is associated with an impaired connection of cerebral white matter. Studies on patients with chronic and first-episode schizophrenia have found widespread white matter abnormalities. However, it is unclear whether the altered connections are inherent in or secondary to the disease. Here, we sought to identify white matter tracts with altered connections and to distinguish primary or secondary alterations among 74 fiber tracts across the whole brain using an automatic tractography-based analysis method. Thirty-one chronic, 25 first-episode patients with schizophrenia and 31 healthy controls were recruited to receive diffusion spectrum magnetic resonance imaging at 3T. Seven tracts were found to exhibit significant differences between the groups; they included the right arcuate fasciculus, bilateral fornices, left superior longitudinal fasciculus I, and fibers of the corpus callosum to the bilateral dorsolateral prefrontal cortices (DLPFC), bilateral temporal poles, and bilateral hippocampi. Post-hoc between-group analyses revealed that the connection of the callosal fibers to the bilateral DLPFC was significantly decreased in chronic patients but not in first-episode patients. In a stepwise regression analysis, the decline of the tract connection was significantly predicted by the duration of illness. In contrast, the remaining six tracts showed significant alterations in both first-episode and chronic patients and did not associate with clinical variables. In conclusion, reduced white matter connectivity of the callosal fibers to the bilateral DLPFC may be a secondary change that degrades progressively in the chronic stage, whereas alterations in the other six tracts may be inherent in the disease.

Strengths and weaknesses of state of the art fiber tractography pipelines--A comprehensive in-vivo and phantom evaluation study using Tractometer

Many different tractography approaches and corresponding isolated evaluation attempts have been presented over the last years, but a comparative and quantitative evaluation of tractography algorithms still remains a challenge, particularly in-vivo. The recently presented evaluation framework Tractometer is the first attempt to approach this challenge in a quantitative, comparative, persistent and open-access way. Tractometer is currently based on the evaluation of several global connectivity and tract-overlap metrics on hardware phantom data. The work presented in this paper focuses on extending Tractometer with a metric that enables the assessment of the local consistency of tractograms with the underlying image data that is not only applicable to phantom dataset but allows the quantitative and purely data-driven evaluation of in-vivo tractography. We furthermore present an extensive reference-based evaluation study of 25,000 tractograms obtained on phantom and in-vivo datasets using the presented local metric as well as all the methods already established in Tractometer. The experiments showed that the presented local metric successfully reflects the behavior of in-vivo tractography under different conditions and that it is consistent with the results of previous studies. Additionally our experiments enabled a multitude of conclusions with implications for fiber tractography in general, including recommendations regarding optimal choice of a local modeling technique, tractography algorithm, and parameterization, confirming and complementing the results of earlier studies.

Automatic whole brain tract-based analysis using predefined tracts in a diffusion spectrum imaging template and an accurate registration strategy

Automated tract-based analysis of diffusion MRI is an important tool for investigating tract integrity of the cerebral white matter. Current template-based automatic analyses still lack a comprehensive list of tract atlas and an accurate registration method. In this study, tract-based automatic analysis (TBAA) was developed to meet the demands. Seventy-six major white matter tracts were reconstructed on a high-quality diffusion spectrum imaging (DSI) template, and an advanced two-step registration strategy was proposed by incorporating anatomical information of the gray matter from T1-weighted images in addition to microstructural information of the white matter from diffusion-weighted images. The automatic analysis was achieved by establishing a transformation between the DSI template and DSI dataset of the subject derived from the registration strategy. The tract coordinates in the template were transformed to native space in the individual's DSI dataset, and the microstructural properties of major tract bundles were sampled stepwise along the tract coordinates of the subject's DSI dataset. In a validation study of eight well-known tracts, our results showed that TBAA had high geometric agreement with manual tracts in both deep and superficial parts but significantly smaller measurement variability than manual method in functional difference. Additionally, the feasibility of the method was demonstrated by showing tracts with altered microstructural properties in patients with schizophrenia. Fifteen major tract bundles were found to have significant differences after controlling the family-wise error rate. In conclusion, the proposed TBAA method is potentially useful in brain-wise investigations of white matter tracts, particularly for a large cohort study.

Altered cortical structures and tract integrity of the mirror neuron system in association with symptoms of schizophrenia

The mirror neuron system (MNS) may be implicated in schizophrenia. This study investigated MNS structures, including the pars opercularis (Pop), the supramarginal gyrus (SMg), the third branch of the superior longitudinal fasciculus, and callosal fibers interconnecting bilateral Pop (CC-Pop) and SMg (CC-SMg), and clarified their relationships with positive and negative symptoms of schizophrenia. Participants comprised 32 schizophrenia patients and 32 matched controls who received T1-weighted structural magnetic resonance imaging (MRI, T1WI) and diffusion spectrum imaging (DSI). The cortical measures were computed from the T1WI data. Tract integrity was assessed using a tractography-based analysis of the generalized fractional anisotropy (GFA) derived from the DSI data. Pearson׳s correlations and multiple linear regression analysis were used to investigate the associations between MNS structures and positive and negative symptom scores of schizophrenia. Cortical thickness in bilateral Pop and SMg were significantly thinner and mean GFA of CC-Pop was significantly decreased in patients. Negative symptoms were significantly correlated with left SMg volume, and positive symptoms were significantly correlated with right SMg thickness. Multiple linear regression analysis showed left SMg volume to be the strongest contributor to the negative symptoms. The association between left SMg volume and negative symptoms may reflect the degree of social cognition impairment in schizophrenia.

Altered Cortical Thickness and Tract Integrity of the Mirror Neuron System and Associated Social Communication in Autism Spectrum Disorder

Previous studies using neural activity recording and neuroimaging techniques have reported functional deficits in the mirror neuron system (MNS) for individuals with autism spectrum disorder (ASD). However, a few studies focusing on gray and white matter structures of the MNS have yielded inconsistent results. The current study recruited adolescents and young adults with ASD (aged 15-26 years) and age-matched typically developing (TD) controls (aged 14-25 years). The cortical thickness (CT) and microstructural integrity of the tracts connecting the regions forming the classical MNS were investigated. High-resolution T1-weighted imaging and diffusion spectrum imaging were performed to quantify the CT and tract integrity, respectively. The structural covariance of the CT of the MNS regions revealed a weaker coordination of the MNS network in ASD. A strong correlation was found between the integrity of the right frontoparietal tracts and the social communication subscores measured by the Chinese version of the Social Communication Questionnaire. The results showed that there were no significant mean differences in the CTs and tract integrity between the ASD and TD groups, but revealed a moderate or even reverse age effect on the frontal MNS structures in ASD. In conclusion, aberrant structural coordination may be an underlying factor affecting the function of the MNS in ASD patients. The association between the right frontoparietal tracts and social communication performance implies a neural correlate of communication processing in the autistic brain. This study provides evidence of abnormal MNS structures and their influence on social communication in individuals with ASD.

Regional White Matter Variation Associated with Domain-specific Metacognitive Accuracy

The neural mechanisms that mediate metacognitive ability (the capacity to accurately reflect on one's own cognition and experience) remain poorly understood. An important question is whether metacognitive capacity is a domain-general skill supported by a core neuroanatomical substrate or whether regionally specific neural structures underlie accurate reflection in different cognitive domains. Providing preliminary support for the latter possibility, recent findings have shown that individual differences in metacognitive ability in the domains of memory and perception are related to variation in distinct gray matter volume and resting-state functional connectivity. The current investigation sought to build on these findings by evaluating how metacognitive ability in these domains is related to variation in white matter microstructure. We quantified metacognitive ability across memory and perception domains and used diffusion spectrum imaging to examine the relation between high-resolution measurements of white matter microstructure and individual differences in metacognitive accuracy in each domain. We found that metacognitive accuracy for perceptual decisions and memory were uncorrelated across individuals and that metacognitive accuracy in each domain was related to variation in white matter microstructure in distinct brain areas. Metacognitive accuracy for perceptual decisions was associated with increased diffusion anisotropy in white matter underlying the ACC, whereas metacognitive accuracy for memory retrieval was associated with increased diffusion anisotropy in the white matter extending into the inferior parietal lobule. Together, these results extend previous findings linking metacognitive ability in the domains of perception and memory to variation in distinct brain structures and connections.

Brain connectivity and novel network measures for Alzheimer's disease classification

We compare a variety of different anatomic connectivity measures, including several novel ones, that may help in distinguishing Alzheimer's disease (AD) patients from controls. We studied diffusion-weighted magnetic resonance imaging from 200 subjects scanned as part of the Alzheimer's Disease Neuroimaging Initiative. We first evaluated measures derived from connectivity matrices based on whole-brain tractography; next, we studied additional network measures based on a novel flow-based measure of brain connectivity, computed on a dense 3-dimensional lattice. Based on these 2 kinds of connectivity matrices, we computed a variety of network measures. We evaluated the measures' ability to discriminate disease with a repeated, stratified 10-fold cross-validated classifier, using support vector machines, a supervised learning algorithm. We tested the relative importance of different combinations of features based on the accuracy, sensitivity, specificity, and feature ranking of the classification of 200 people into normal healthy controls and people with early or late mild cognitive impairment or AD.

Reduced structural integrity and functional lateralization of the dorsal language pathway correlate with hallucinations in schizophrenia: a combined diffusion spectrum imaging and functional magnetic resonance imaging study

Recent studies suggest that structural and functional alterations of the language network are associated with auditory verbal hallucinations (AVHs) in schizophrenia. However, the ways in which the underlying structure and function of the network are altered and how these alterations are related to each other remain unclear. To elucidate this, we used diffusion spectrum imaging (DSI) to reconstruct the dorsal and ventral pathways and employed functional magnetic resonance imaging (fMRI) in a semantic task to obtain information about the functional activation in the corresponding regions in 18 patients with schizophrenia and 18 matched controls. The results demonstrated decreased structural integrity in the left ventral, right ventral and right dorsal tracts, and decreased functional lateralization of the dorsal pathway in schizophrenia. There was a positive correlation between the microstructural integrity of the right dorsal pathway and the functional lateralization of the dorsal pathway in patients with schizophrenia. Additionally, both functional lateralization of the dorsal pathway and microstructural integrity of the right dorsal pathway were negatively correlated with the scores of the delusion/hallucination symptom dimension. Our results suggest that impaired structural integrity of the right dorsal pathway is related to the reduction of functional lateralization of the dorsal pathway, and these alterations may aggravate AVHs in schizophrenia.

Toward tract-specific fractional anisotropy (TSFA) at crossing-fiber regions with clinical diffusion MRI

PURPOSE

White matter fractional anisotropy (FA), a measure suggesting microstructure, is significantly underestimated with single diffusion tensor model at crossing-fiber regions (CFR). We propose a tract-specific FA (TSFA), corrected for the effects of crossing-fiber geometry and free water at CFR, and adapted for tract analysis with diffusion MRI (dMRI) in clinical research.

METHODS

At CFR voxels, the proposed technique estimates free water fraction (fiso ) as a linear function of mean apparent diffusion coefficient (mADC), fits the dual tensors and estimates TSFA. Digital phantoms were designed for testing the accuracy of fiso and fitted dual-anisotropies at CFR. The technique was applied to clinical dMRI of normal subjects and hereditary spastic paraplegia (HSP) patients to test the effectiveness of TSFA.

RESULTS

Phantom simulation showed unbiased estimates of dual-tensor anisotropies at CFR and high accuracy of fiso as a linear function of mADC. TSFA at CFR was highly consistent to the single tensor FA at non-CFR within the same tract with normal human dMRI. Additional HSP imaging biomarkers with significant correlation to clinical motor function scores could be identified with TSFA.

CONCLUSION

Results suggest the potential of the proposed technique in estimating unbiased TSFA at CFR and conducting tract analysis in clinical research.

White matter abnormalities associated with military PTSD in the context of blast TBI

Mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common among recent military veterans and involve substantial symptom overlap, making clinical distinction and effective intervention difficult. Emerging evidence of cerebral white matter abnormalities associated with mTBI may provide a biological measure to inform diagnosis and treatment, but the potentially confounding effects between PTSD and mTBI have largely gone unexamined. We collected diffusion imaging data from 133 recently-deployed American service members who developed PTSD and/or sustained mTBI, or had neither condition. Effects of PTSD and mTBI on traditional tensor-based measures of cerebral white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) were compared in anatomical regions of interest and individual voxels throughout the brain. Generalized FA (GFA), which allows for multiple fiber orientations per voxel, was also included to improve sensitivity in white matter areas containing crossing or diverging axon bundles. PTSD was consistently associated with high GFA in select brain regions, greater likelihood of regions and voxels with abnormally low MD, and a greater number of voxels with abnormally high FA, while mTBI was associated with fewer high MD regions. Overall, PTSD was associated with more restricted diffusion (low MD) and greater anisotropy (high GFA) in regions of crossing/diverging fibers poorly characterized by a single tensor (FA), suggesting that interstitial fibers may be involved. Contrary to earlier results in a sample without PTSD, mTBI was not associated with anisotropy abnormalities, perhaps indicating the cooccurrence of PTSD and mTBI requires special consideration with regard to structural brain connectivity.

Altered integrity of the right arcuate fasciculus as a trait marker of schizophrenia: a sibling study using tractography-based analysis of the whole brain

Trait markers of schizophrenia aid the dissection of the heterogeneous phenotypes into distinct subtypes and facilitate the genetic underpinning of the disease. The microstructural integrity of the white matter tracts could serve as a trait marker of schizophrenia, and tractography-based analysis (TBA) is the current method of choice. Manual tractography is time-consuming and limits the analysis to preselected fiber tracts. Here, we sought to identify a trait marker of schizophrenia from among 74 fiber tracts across the whole brain using a novel automatic TBA method. Thirty-one patients with schizophrenia, 31 unaffected siblings and 31 healthy controls were recruited to undergo diffusion spectrum magnetic resonance imaging at 3T. Generalized fractional anisotropy (GFA), an index reflecting tract integrity, was computed for each tract and compared among the three groups. Ten tracts were found to exhibit significant differences between the groups with a linear, stepwise order from controls to siblings to patients; they included the right arcuate fasciculus, bilateral fornices, bilateral auditory tracts, left optic radiation, the genu of the corpus callosum, and the corpus callosum to the bilateral dorsolateral prefrontal cortices, bilateral temporal poles, and bilateral hippocampi. Posthoc between-group analyses revealed that the GFA of the right arcuate fasciculus was significantly decreased in both the patients and unaffected siblings compared to the controls. Furthermore, the GFA of the right arcuate fasciculus exhibited a trend toward positive symptom scores. In conclusion, the right arcuate fasciculus may be a candidate trait marker and deserves further study to verify any genetic association.

Automatic clustering and population analysis of white matter tracts using maximum density paths

We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

White matter tract integrity of frontostriatal circuit in attention deficit hyperactivity disorder: association with attention performance and symptoms

The frontostriatal circuit has been postulated to account for the core symptoms such as inattention in attention deficit/hyperactivity disorder (ADHD). This study investigated the white matter integrity of frontostriatal fiber tracts using diffusion spectrum imaging (DSI) tractography and its correlations with measures of multi-dimensional aspects of inattention based on psychiatric interview and attention tasks in 25 children with ADHD and 25 matched typically developing (TD) children. All the subjects were assessed with comprehensive psychiatric interviews and the Conner's Continuous Performance Test (CCPT). DSI data were acquired on a 3-Tesla MRI system. The frontostriatal fiber pathways were reconstructed by deterministic tractography, and generalized fractional anisotropy values were measured along individual targeted tracts to investigate alterations in microstructure integrity. Children with ADHD performed worse than TD children in the dimensions of focused attention, sustained attention, impulsivity, and vigilance of the CCPT, and showed impaired integrity in four bilateral frontostriatal tracts, namely the dorsolateral-caudate, medial prefrontal-caudate, orbitofrontal-caudate, and ventrolateral-caudate tracts, and in global white matter as well. The integrity of the left orbitofronto-caudate tract was associated with the symptom of inattention in children with ADHD, compatible with the attention deficit and motivational dysfunction theories in ADHD. The integrity of the frontostriatal tracts was associated with the attention performance only in TD children, suggestive of possible recruitment of tracts other than the frontostriatal tracts implicated in attention deficits in children with ADHD. In conclusion, our results demonstrate the functional involvement of the frontostriatal circuit with respect to clinical symptoms and attention performance.

Deterministic diffusion fiber tracking improved by quantitative anisotropy

Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T₁-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics.

Differences of inter-tract correlations between neonates and children around puberty: a study based on microstructural measurements with DTI

The human brain development is a complicated yet well-organized process. Metrics derived from diffusion tensor imaging (DTI), including fractional anisotropy (FA), radial (RD), axial (AxD), and mean diffusivity (MD), have been used to noninvasively access the microstructural development of human brain white matter (WM). At birth, most of the major WM tracts are apparent but in a relatively disorganized pattern. Brain maturation is a process of establishing an organized pattern of these major WM tracts. However, how the linkage pattern of major WM tracts changes during development remains unclear. In this study, DTI data of 26 neonates and 28 children around puberty were acquired. 10 major WM tracts, representing four major tract groups involved in distinctive brain functions, were traced with DTI tractography for all 54 subjects. With the 10 by 10 correlation matrices constructed with Spearman's pairwise inter-tract correlations and based on tract-level measurements of FA, RD, AxD, and MD of both age groups, we assessed if the inter-tract correlations become stronger from birth to puberty. In addition, hierarchical clustering was performed based on the pairwise correlations of WM tracts to reveal the clustering pattern for each age group and pattern shift from birth to puberty. Stronger and enhanced microstructural inter-tract correlations were found during development from birth to puberty. The linkage patterns of two age groups differ due to brain development. These changes of microstructural correlations from birth to puberty suggest inhomogeneous but organized myelination processes which cause the reshuffled inter-tract correlation pattern and make homologous tracts tightly clustered. It opens a new window to study WM tract development and can be potentially used to investigate atypical brain development due to neurological or psychiatric disorders.

Increased global and local efficiency of human brain anatomical networks detected with FLAIR-DTI compared to non-FLAIR-DTI

Diffusion-weighted MRI (DW-MRI), the only non-invasive technique for probing human brain white matter structures in vivo, has been widely used in both fundamental studies and clinical applications. Many studies have utilized diffusion tensor imaging (DTI) and tractography approaches to explore the topological properties of human brain anatomical networks by using the single tensor model, the basic model to quantify DTI indices and tractography. However, the conventional DTI technique does not take into account contamination by the cerebrospinal fluid (CSF), which has been known to affect the estimated DTI measures and tractography in the single tensor model. Previous studies have shown that the Fluid-Attenuated Inversion Recovery (FLAIR) technique can suppress the contribution of the CSF to the DW-MRI signal. We acquired DTI datasets from twenty-two subjects using both FLAIR-DTI and conventional DTI (non-FLAIR-DTI) techniques, constructed brain anatomical networks using deterministic tractography, and compared the topological properties of the anatomical networks derived from the two types of DTI techniques. Although the brain anatomical networks derived from both types of DTI datasets showed small-world properties, we found that the brain anatomical networks derived from the FLAIR-DTI showed significantly increased global and local network efficiency compared with those derived from the conventional DTI. The increases in the network regional topological properties derived from the FLAIR-DTI technique were observed in CSF-filled regions, including the postcentral gyrus, periventricular regions, inferior frontal and temporal gyri, and regions in the visual cortex. Because brain anatomical networks derived from conventional DTI datasets with tractography have been widely used in many studies, our findings may have important implications for studying human brain anatomical networks derived from DW-MRI data and tractography.