Fiber estimation and tractography in diffusion MRI: development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values

Atlas-guided brain projection tracts: From regions of interest to tractography 3D rendering

The use of diffusion tensor imaging (DTI) has seen significant development over the last two decades, in particular with the development of the tractography of association tracts for preoperative planning of surgery. However, projection tracts are difficult to differentiate from one another and tractography studies have failed to reconstruct these ascending/descending pathways from/to the spinal cord. The present study proposes an atlas of regions of interest (ROIs) designed specifically for projection tracts tractography. Forty-nine healthy subjects were included in this prospective study. Brain DTI was acquired using the same 3 T MRI scanner, with 32 diffusion directions. Distortions were corrected using the FSL software package. ROIs were drawn using the anterior commissure (AC)-posterior commissure (PC) line on the following landmarks: the pyramid for the corticospinal tract, the medio-caudal part of the red nucleus for the rubrospinal tract, the pontine reticular nucleus for corticoreticular tract, the superior and inferior cerebellar peduncles for, respectively, the anterior and posterior spinocerebellar tract, the gracilis and cuneatus nucleus for the dorsal columns, and the ventro-posterolateral nucleus for the spinothalamic tract. Fiber tracking was performed using a deterministic algorithm using DSI Studio software. ROI coordinates, according to AC-PC line, were given for each tract. Tractography was obtained for each tract, allowing tridimensional rendering and comparison of tracking metrics between tracts. The present study reports the accurate design of specific ROIs for tractography of each projection tract. This could be a useful tool in order to differentiate projection tracts at the spinal cord level.

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain

We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 μm resolution (∼ 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.

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.

Abnormal wiring of the structural connectome in adults with ADHD

Current knowledge of white matter changes in large-scale brain networks in adult attention-deficit/hyperactivity disorder (ADHD) is scarce. We collected diffusion-weighted magnetic resonance imaging data in 40 adults with ADHD and 36 neurotypical controls and used constrained spherical deconvolution-based tractography to reconstruct whole-brain structural connectivity networks. We used network-based statistic (NBS) and graph theoretical analysis to investigate differences in these networks between the ADHD and control groups, as well as associations between structural connectivity and ADHD symptoms assessed with the Adult ADHD Self-Report Scale or performance in the Conners Continuous Performance Test 2 (CPT-2). NBS revealed decreased connectivity in the ADHD group compared to the neurotypical controls in widespread unilateral networks, which included subcortical and corticocortical structures and encompassed dorsal and ventral attention networks and visual and somatomotor systems. Furthermore, hypoconnectivity in a predominantly left-frontal network was associated with higher amount of commission errors in CPT-2. Graph theoretical analysis did not reveal topological differences between the groups or associations between topological properties and ADHD symptoms or task performance. Our results suggest that abnormal structural wiring of the brain in adult ADHD is manifested as widespread intrahemispheric hypoconnectivity in networks previously associated with ADHD in functional neuroimaging studies.

Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging-Tractography in Resective Brain Surgery: Lesion Coverage Strategies and Patient Outcomes

Diffusion tensor imaging (DTI)-tractography and functional magnetic resonance imaging (fMRI) have dynamically entered the presurgical evaluation context of brain surgery during the past decades, providing novel perspectives in surgical planning and lesion access approaches. However, their application in the presurgical setting requires significant time and effort and increased costs, thereby raising questions regarding efficiency and best use. In this work, we set out to evaluate DTI-tractography and combined fMRI/DTI-tractography during intra-operative neuronavigation in resective brain surgery using lesion-related preoperative neurological deficit (PND) outcomes as metrics. We retrospectively reviewed medical records of 252 consecutive patients admitted for brain surgery. Standard anatomical neuroimaging protocols were performed in 127 patients, 69 patients had additional DTI-tractography, and 56 had combined DTI-tractography/fMRI. fMRI procedures involved language, motor, somatic sensory, sensorimotor and visual mapping. DTI-tractography involved fiber tracking of the motor, sensory, language and visual pathways. At 1 month postoperatively, DTI-tractography patients were more likely to present either improvement or preservation of PNDs (p = 0.004 and p = 0.007, respectively). At 6 months, combined DTI-tractography/fMRI patients were more likely to experience complete PND resolution (p < 0.001). Low-grade lesion patients (N = 102) with combined DTI-tractography/fMRI were more likely to experience complete resolution of PNDs at 1 and 6 months (p = 0.001 and p < 0.001, respectively). High-grade lesion patients (N = 140) with combined DTI-tractography/fMRI were more likely to have PNDs resolved at 6 months (p = 0.005). Patients with motor symptoms (N = 80) were more likely to experience complete remission of PNDs at 6 months with DTI-tractography or combined DTI-tractography/fMRI (p = 0.008 and p = 0.004, respectively), without significant difference between the two imaging protocols (p = 1). Patients with sensory symptoms (N = 44) were more likely to experience complete PND remission at 6 months with combined DTI-tractography/fMRI (p = 0.004). The intraoperative neuroimaging modality did not have a significant effect in patients with preoperative seizures (N = 47). Lack of PND worsening was observed at 6 month follow-up in patients with combined DTI-tractography/fMRI. Our results strongly support the combined use of DTI-tractography and fMRI in patients undergoing resective brain surgery for improving their postoperative clinical profile.

Methods of diffusion MRI tractography for localization of the anterior optic pathway: A systematic review of validated methods

The anterior optic pathway (AOP) is a system of three structures (optic nerves, optic chiasma, and optic tracts) that convey visual stimuli from the retina to the lateral geniculate nuclei. A successful reconstruction of the AOP using tractography could be helpful in several clinical scenarios, from presurgical planning and neuronavigation of sellar and parasellar surgery to monitoring the stage of fiber degeneration both in acute (e.g., traumatic optic neuropathy) or chronic conditions that affect AOP structures (e.g., amblyopia, glaucoma, demyelinating disorders or genetic optic nerve atrophies). However, its peculiar anatomy and course, as well as its surroundings, pose a serious challenge to obtaining successful tractographic reconstructions. Several AOP tractography strategies have been adopted but no standard procedure has been agreed upon. We performed a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines in order to find the combinations of acquisition and reconstruction parameters that have been performed previously and have provided the highest rate of successful reconstruction of the AOP, in order to promote their routine implementation in clinical practice. For this purpose, we reviewed data regarding how the process of anatomical validation of the tractographies was performed. The Cochrane Handbook for Systematic Reviews of Interventions was used to assess the risk of bias and thus the study quality We identified thirty-nine studies that met our inclusion criteria, and only five were considered at low risk of bias and achieved over 80% of successful reconstructions. We found a high degree of heterogeneity in the acquisition and analysis parameters used to perform AOP tractography and different combinations of them can achieve satisfactory levels of anterior optic tractographic reconstruction both in real-life research and clinical scenarios. One thousand s/mm2 was the most frequently used b value, while both deterministic and probabilistic tractography algorithms performed morphological reconstruction of the tract satisfactorily, although probabilistic algorithms estimated a more realistic percentage of crossing fibers (45.6%) in healthy subjects. A wide heterogeneity was also found regarding the method used to assess the anatomical fidelity of the AOP reconstructions. Three main strategies can be found: direct visual direct visual assessment of the tractography superimposed to a conventional MR image, surgical evaluation, and computational methods. Because the latter is less dependent on a priori knowledge of the anatomy by the operator, computational methods of validation of the anatomy should be considered whenever possible.

Lung parenchyma transverse relaxation rates at 0.55 T

PURPOSE

To determine R₂ and R 2 ' $$ {R}_2^{\prime } $$ transverse relaxation rates in healthy lung parenchyma at 0.55 T. This is important in that it informs the design and optimization of new imaging methods for 0.55T lung MRI.

METHODS

Experiments were performed in 3 healthy adult volunteers on a prototype whole-body 0.55T MRI, using a custom free-breathing electrocardiogram-triggered, single-slice echo-shifted multi-echo spin echo (ES-MCSE) pulse sequence with respiratory navigation. Transverse relaxation rates R₂ and R 2 ' $$ {R}_2^{\prime } $$ and off-resonance ∆f were jointly estimated using nonlinear least-squares estimation. These measurements were compared against R₂ estimates from T₂ -prepared balanced SSFP (T₂ -Prep bSSFP) and R 2 * $$ {R}_2^{\ast } $$ estimates from multi-echo gradient echo, which are used widely but prone to error due to different subvoxel weighting.

RESULTS

The mean R₂ and R 2 ' $$ {R}_2^{\prime } $$ values of lung parenchyma obtained from ES-MCSE were 17.3 ± 0.7 Hz and 127.5 ± 16.4 Hz (T₂  = 61.6 ± 1.7 ms; T 2 ' $$ {\mathrm{T}}_2^{\prime } $$  = 9.5 ms ± 1.6 ms), respectively. The off-resonance estimates ranged from -60 to 30 Hz. The R₂ from T₂ -Prep bSSFP was 15.7 ± 1.7 Hz (T₂  = 68.6 ± 8.6 ms) and R 2 * $$ {R}_2^{\ast } $$ from multi-echo gradient echo was 131.2 ± 30.4 Hz ( T 2 * $$ {\mathrm{T}}_2^{\ast } $$  = 8.0 ± 2.5 ms). Paired t-test indicated that there is a significant difference between the proposed and reference methods (p < 0.05). The mean R₂ estimate from T₂ -Prep bSSFP was slightly smaller than that from ES-MCSE, whereas the mean R 2 ' $$ {R}_2^{\prime } $$ and R 2 * $$ {R}_2^{\ast } $$ estimates from ES-MCSE and multi-echo gradient echo were similar to each other across all subjects.

CONCLUSIONS

Joint estimation of transverse relaxation rates and off-resonance is feasible at 0.55 T with a free-breathing electrocardiogram-gated and navigator-gated ES-MCSE sequence. At 0.55 T, the mean R₂ of 17.3 Hz is similar to the reported mean R₂ of 16.7 Hz at 1.5 T, but the mean R 2 ' $$ {R}_2^{\prime } $$ of 127.5 Hz is about 5-10 times smaller than that reported at 1.5 T.

Visual outcomes after anterior temporal lobectomy and transsylvian selective amygdalohippocampectomy: A quantitative comparison of clinical and diffusion data

OBJECTIVE

Anterior temporal lobectomy (ATL) and transsylvian selective amygdalohippocampectomy (tsSAHE) are effective treatment strategies for intractable temporal lobe epilepsy but may cause visual field deficits (VFDs) by damaging the optic radiation (OpR). Due to the OpR's considerable variability and because it is indistinguishable from surrounding tissue without further technical guidance, it is highly vulnerable to iatrogenic injury. This imaging study uses a multimodal approach to assess visual outcomes after epilepsy surgery.

METHODS

We studied 62 patients who underwent ATL (n = 32) or tsSAHE (n = 30). Analysis of visual outcomes was conducted in four steps, including the assessment of (1) perimetry outcome (VFD incidence/extent, n = 44/40), (2) volumetric OpR tractography damage (n = 55), and the (3) relation of volumetric OpR tractography damage and perimetry outcome (n = 35). Furthermore, (4) fixel-based analysis (FBA) was performed to assess micro- and macrostructural changes within the OpR following surgery (n = 36).

RESULTS

Altogether, 56% of all patients had postoperative VFDs (78.9% after ATL, 36.36% after tsSAHE, p = .011). VFDs and OpR tractography damage tended to be more severe within the ATL group (ATL vs. tsSAHE, integrity of contralateral upper quadrant: 65% vs. 97%, p = .002; OpR tractography damage: 69.2 mm³ vs. 3.8 mm³ , p = .002). Volumetric OpR tractography damage could reliably predict VFD incidence (86% sensitivity, 78% specificity) and could significantly explain VFD extent (R²  = .47, p = .0001). FBA revealed a more widespread decline of fibre cross-section within the ATL group.

SIGNIFICANCE

In the context of controversial visual outcomes following epilepsy surgery, this study provides clinical as well as neuroimaging evidence for a higher risk and greater severity of postoperative VFDs after ATL compared to tsSAHE. Volumetric OpR tractography damage is a feasible parameter to reliably predict this morbidity in both treatment groups and may ultimately support personalized planning of surgical candidates. Advanced diffusion analysis tools such as FBA offer a structural explanation of surgically induced visual pathway damage, allowing noninvasive quantification and visualization of micro- and macrostructural tract affection.

Microstructural changes along the cingulum in young adolescents with psychotic experiences: An along-tract analysis

Psychotic experiences (PEs) such as hallucinations and delusions are common among young people without psychiatric diagnoses and are associated with connectivity and white matter abnormalities, particularly in the limbic system. Using diffusion magnetic resonance imaging (MRI) in adolescents with reported PEs and matched controls, we examined the cingulum white matter tract along its length rather than as the usually reported single indivisible structure. Complex regional differences in diffusion metrics were found along the bundle at key loci following Bonferroni significance adjustment (p < .00013) with moderate to large effect sizes (.11-.76) throughout all significant subsegments. In this prospective community-based cohort of school-age children, these findings suggest that white matter alterations in the limbic system may be more common in the general non-clinical adolescent population than previously thought. Such white matter alternations may only be uncovered using a similar more granular along-tract analysis of white matter tracts.

Reducing instability of inter-subject covariance of FDG uptake networks using structure-weighted sparse estimation approach

PURPOSE

Sparse inverse covariance estimation (SICE) is increasingly utilized to estimate inter-subject covariance of FDG uptake (FDG_cov) as proxy of metabolic brain connectivity. However, this statistical method suffers from the lack of robustness in the connectivity estimation. Patterns of FDG_cov were observed to be spatially similar with patterns of structural connectivity as obtained from DTI imaging. Based on this similarity, we propose to regularize the sparse estimation of FDG_cov using the structural connectivity.

METHODS

We retrospectively analyzed the FDG-PET and DTI data of 26 healthy controls, 41 patients with Alzheimer's disease (AD), and 30 patients with frontotemporal lobar degeneration (FTLD). Structural connectivity matrix derived from DTI data was introduced as a regularization parameter to assign individual penalties to each potential metabolic connectivity. Leave-one-out cross validation experiments were performed to assess the differential diagnosis ability of structure weighted SICE approach. A few approaches of structure weighted were compared with the standard SICE.

RESULTS

Compared to the standard SICE, structural weighting has shown more stable performance in the supervised classification, especially in the differentiation AD vs. FTLD (accuracy of 89-90%, while unweighted SICE only 85%). There was a significant positive relationship between the minimum number of metabolic connection and the robustness of the classification accuracy (r = 0.57, P < 0.001). Shuffling experiments showed significant differences between classification score derived with true structural weighting and those obtained by randomized structure (P < 0.05).

CONCLUSION

The structure-weighted sparse estimation can enhance the robustness of metabolic connectivity, which may consequently improve the differentiation of pathological phenotypes.

Obsessive compulsive symptom dimensions are linked to altered white-matter microstructure in a community sample of youth

Obsessive-compulsive symptoms (OCS) are common in school-aged children and predict the development of obsessive compulsive disorder (OCD). White-matter abnormalities have been described in OCD, but the white matter correlates of OCS in the developing brain are unclear. Some correlates of OCS (or a diagnosis of OCD) may reflect correlates of a transdiagnostic or even general psychopathology factor. We examined these questions in a large sample of typically developing youth (N = 1208), using a hierarchical analysis of fixel-based white matter measures in relation to OCS and general psychopathology. General psychopathology was associated with abnormalities in the posterior corpus callosum and forceps major in an age-dependent manner, suggesting altered maturation (specifically, hypermaturation in younger subjects). A unidimensional measure of OCS did not associate with any white-matter abnormalities, but analysis of separate OCS dimensions (derived from factor analysis within this sample) revealed the 'Bad Thoughts' dimension to associate with white-matter abnormalities in dorsal parietal white-matter and descending corticospinal tracts, and the 'Symmetry' dimension to associate with abnormalities in the anterior corpus callosum. Repetition/checking and Symmetry OCS were additionally associated with posterior abnormalities overlapping with the correlates of general psychopathology. Contamination symptoms had no white-matter correlates. Secondary analysis of fractional anisotropy (FA) revealed distinct white-matter abnormalities, suggesting that fixel-based and FA analyses identify distinct features of white matter relevant to psychopathology. These findings suggest that OCS dimensions correlate with dissociable abnormalities in white matter, implicating separable networks. Future studies should examine these white-matter signatures in a longitudinal framework.

A groupwise registration and tractography framework for cardiac myofiber architecture description by diffusion MRI: An application to the ventricular junctions

Background

Knowledge of the normal myocardial–myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented.

Methods

Three explanted sheep (ovine) hearts (size ~12×8×6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy …) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template.

Results

The template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 μm and 600 μm respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition.

Conclusions

A new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.

Associations Between White Matter Microstructures and Cognitive Functioning in 8-Year-Old Children: A Track-Weighted Imaging Study

PURPOSE

Quantitative tractography using diffusion-weighted magnetic resonance imaging data is widely used in characterizing white matter microstructure throughout childhood, but more studies are still needed to investigate comprehensive brain-behavior relationships between tract-specific white matter measures and multiple cognitive functions in children.

METHODS

In this study, we analyzed diffusion-weighted MRI data of 71 healthy 8-year-old children utilizing white matter tract-specific quantitative measures derived from diffusion-weighted MRI tractography based on a novel track-weighted imaging approach. Track density imaging, average path length map and 4 track-weighted diffusion tensor imaging measures including: mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for 63 white matter tracts. The track-weighted imaging measures were then correlated with a comprehensive set of neuropsychological test scores in different cognitive domains including intelligence, language, memory, academic skills, and executive functions to identify tract-specific brain-behavior relationships.

RESULTS

Significant correlations (P < .05, false discovery rate corrected; r = 0.27-0.57) were found in multiple white matter tracts, with a total of 40 correlations identified between various track-weighted imaging measures including average path length map, track-weighted imaging-fractional anisotropy, and neuropsychological test scores and subscales. Specifically, track-weighted imaging measures indicative of better white matter connectivity and/or microstructural development significantly correlated with higher IQ and better language abilities.

CONCLUSION

Our findings demonstrate the ability of track-weighted imaging measures in establishing associations between white matter and cognitive functioning in healthy children and can serve as a reference for normal brain/cognition relationships in young school-age children and further aid in identifying imaging biomarkers predictive of adverse neurodevelopmental outcomes.

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

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

Symptoms reported by Canadians posted in Havana are linked with reduced white matter fibre density

Diplomats representing the USA have reported with unusual neurologic symptoms and MRI changes after being posted in Havana, Cuba between late 2016 and 2018. Here, we examined white matter microstructure and network connectivity of individuals stationed in Havana, using diffusion-weighted MRI, fixel-based analysis and structural connectomics as implemented in MRtrix3. MRI data acquisition and clinical assessments were done in a total of 24 diplomats and their family members and 40 healthy controls. The diplomat data were grouped into an exposed cohort (n = 16) and an unexposed cohort (n = 10), and among these, two individuals were assessed before and after potential exposure. Fixel-based analysis revealed a reduction in fibre density in two specific regions: the fornix and the splenium, in exposed individuals, relative to unexposed individuals and healthy controls. Post hoc analyses showed the effect remained present (P < 0.05) in both regions when comparing exposed and unexposed diplomats; and reduced fibre density was correlated with longer time period stationed in Cuba after age correction. Reduction of fibre density was also found to be linked with clinical symptoms of persistent migraine, tinnitus, sound sensitivity and fatigue. Network statistical comparisons revealed decreased structural connectivity in two distinct networks, comprising subcortical and cortical systems in exposed individuals, relative to unexposed and normative data. While the cause for the differences between the groups remains unknown, our results reveal region-specific white matter injury, that is, significantly correlated with clinical symptoms.

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

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

Biophysical compartment models for single-shell diffusion MRI in the human brain: a model fitting comparison

Clinically oriented studies commonly acquire diffusion MRI (dMRI) data with a single non-zero b-value (i.e. single-shell) and diffusion weighting ofb=1000 s/mm². To produce microstructural parameter maps, the tensor model is usually used, despite known limitations. Although compartment models have demonstrated improved fits in multi-shell dMRI data, they are rarely used for single-shell parameter maps, where their effectiveness is unclear from the literature. Here, various compartment models combining isotropic balls and symmetric tensors were fitted to single-shell dMRI data to investigate model fitting optimization and extract the most information possible. Full testing was performed in 5 subjects, and 3 subjects with multi-shell data were included for comparison. The results were tested and confirmed in a further 50 subjects. The Markov chain Monte Carlo (MCMC) model fitting technique outperformed non-linear least squares. Using MCMC, the 2-fibre-orientation mono-exponential ball & stick model (BS_ME²) provided artifact-free, stable results, in little processing time. The analogous ball & zeppelin model (BZ²) also produced stable, low-noise parameter maps, though it required much greater computing resources (50 000 burn-in steps). In single-shell data, the gamma-distributed diffusivity ball & stick model (BS_GD²) underperformed relative to other models, despite being an often-used software default. It produced artifacts in the diffusivity maps even with extremely long processing times. Neither increased diffusion weighting nor a greater number of gradient orientations improved BS_GD²fits. In white matter (WM), the tensor produced the best fit as measured by Bayesian information criterion. This result contrasts with studies using multi-shell data. However, in crossing fibre regions the tensor confounded geometric effects with fractional anisotropy (FA): the planar/linear WM FA ratio was 49%, while BZ²and BS_ME²retained 76% and 83% of restricted fraction, respectively. As a result, the BZ²and BS_ME²models are strong candidates to optimize information extraction from single-shell dMRI studies.

Tractography methods and findings in brain tumors and traumatic brain injury

White matter fiber tracking using diffusion magnetic resonance imaging (dMRI) provides a noninvasive approach to map brain connections, but improving anatomical accuracy has been a significant challenge since the birth of tractography methods. Utilizing tractography in brain studies therefore requires understanding of its technical limitations to avoid shortcomings and pitfalls. This review explores tractography limitations and how different white matter pathways pose different challenges to fiber tracking methodologies. We summarize the pros and cons of commonly-used methods, aiming to inform how tractography and its related analysis may lead to questionable results. Extending these experiences, we review the clinical utilization of tractography in patients with brain tumors and traumatic brain injury, starting from tensor-based tractography to more advanced methods. We discuss current limitations and highlight novel approaches in the context of these two conditions to inform future tractography developments.

Widespread effects of dMRI data quality on diffusion measures in children

Diffusion magnetic resonance imaging (dMRI) datasets are susceptible to several confounding factors related to data quality, which is especially true in studies involving young children. With the recent trend of large‐scale multicenter studies, it is more critical to be aware of the varied impacts of data quality on measures of interest. Here, we investigated data quality and its effect on different diffusion measures using a multicenter dataset. dMRI data were obtained from 691 participants (5–17 years of age) from six different centers. Six data quality metrics—contrast to noise ratio, outlier slices, and motion (absolute, relative, translation, and rotational)—and four diffusion measures—fractional anisotropy, mean diffusivity, tract density, and length—were computed for each of 36 major fiber tracts for all participants. The results indicated that four out of six data quality metrics (all except absolute and translation motion) differed significantly between centers. Associations between these data quality metrics and the diffusion measures differed significantly across the tracts and centers. Moreover, these effects remained significant after applying recently proposed harmonization algorithms that purport to remove unwanted between‐site variation in diffusion data. These results demonstrate the widespread impact of dMRI data quality on diffusion measures. These tracts and measures have been routinely associated with individual differences as well as group‐wide differences between neurotypical populations and individuals with neurological or developmental disorders. Accordingly, for analyses of individual differences or group effects (particularly in multisite dataset), we encourage the inclusion of data quality metrics in dMRI analysis.

Comparison of diffusion signal models for fiber tractography in eloquent glioma surgery - determination of accuracy under awake craniotomy conditions

OBJECTIVE

Fiber tractography(FT) has become an important non-invasive tool to ensure maximal safe tumor resection in eloquent glioma surgery. Intraoperatively applied FT is still predominantly based on Diffusion Tensor Imaging(DTI). However, reconstruction schemes of high angular resolution diffusion imaging(HARDI) data for high resolution fiber tractography(HRFT) are gaining increasing attention. The aim of this prospective study was to compare the accuracy of sophisticated HRFT-models compared with DTI-FT.

METHODS

Ten patients with eloquent gliomas underwent surgery under awake craniotomy conditions. The localization of acquisition points(AP), representing deteriorations during intraoperative electrostimulation(IOM) and neuropsychological mapping, were documented. The offsets of AP to the respective fiber bundle were calculated. Probabilistic QBI- and CSD-FT were compared to DTI-FT for the major language-associated fiber bundles (superior longitudinal fasciclus (SLF) II-IV, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus/medial longitudinal fasciculus (ILF/MLF).

RESULTS

Among 186 offset values, 46% were located closer than 10mm to the estimated fiber bundle (CSD:36%; DTI:40% and QBI:60%). Moreover, only 10 offsets were further away than 30mm (5%). Lowest mean min-offsets (SLF: 7.7±7.9mm; IFOF: 12.7±8.3mm; ILF/MLF: 17.7±6.7mm) were found for QBI, indicating a significant advantage compared with CSD or DTI (p<0.001), respectively. No significant differences were found between CSD-, and DTI-FT offsets (p=0.105), albeit for the compound SLF exclusively (p<0.001).

CONCLUSIONS

Comparing HRFT techniques QBI and CSD with DTI, QBI delivered significantly better results with lowest offsets and good correlation to IOM results. Besides, QBI-FT was feasible for neurosurgical pre- and intraoperative applications. Our findings suggest that a combined approach of QBI-FT and IOM under awake craniotomy is considerable for best preservation of neurological function in the presented setting. Overall, the implementation of selected HRFT models into neuronavigation systems seems to be a promising tool in glioma surgery.

Structural connectivity changes in the cerebral pain matrix in burning mouth syndrome: a multi-shell, multi-tissue-constrained spherical deconvolution model analysis

PURPOSE

Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome. Previous studies have attempted to determine the brain connectivity features in BMS using functional and structural magnetic resonance imaging. However, no study has investigated the structural connectivity using multi-shell, multi-tissue-constrained spherical deconvolution (MSMT-CSD), anatomically constrained tractography (ACT), and spherical deconvolution informed filtering of tractograms (SIFT). Therefore, this study aimed to assess the differences in brain structural connectivity of patients with BMS and healthy controls using probabilistic tractography with these methods, and graph analysis.

METHODS

Fourteen patients with BMS and 11 age- and sex-matched healthy volunteers underwent 3-T magnetic resonance imaging. MSMT-CSD-based probabilistic structural connectivity was computed using the second-order integration over fiber orientation distributions algorithm based on nodes set in 84 anatomical cortical regions with ACT and SIFT. A t-test was performed for comparisons between the BMS and healthy control brain networks.

RESULTS

The betweenness centrality was significantly higher in the left insula, right amygdala, and right lateral orbitofrontal cortex and significantly lower in the right inferotemporal cortex in the BMS group than that in healthy controls. However, no significant difference was found in the clustering coefficient, node degree, and small-worldness between the two groups.

CONCLUSION

Graph analysis of brain probabilistic structural connectivity, based on diffusion imaging using an MSMT-CSD model with ACT and SIFT, revealed alterations in the regions comprising the pain matrix and medial pain ascending pathway. These results highlight the emotional-affective profile of BMS, which is a type of chronic pain syndrome.

Diffusion Tensor Imaging: A Promising New Technique for Accurate Identification of the Stria Medullaris and Habenula

The Stria Medullaris (SM) is a white-matter tract that contains afferent fibres that connect the cognitive-emotional areas in the forebrain to the Habenula (Hb). The Hb plays an important role in behavioral responses to reward, stress, anxiety, pain, and sleep through its action on neuromodulator systems. The Fasciculus Retroflexus (FR) forms the primary output of the Hb to the midbrain. The SM, Hb, and FR are part of a special pathway between the forebrain and the midbrain known as the Dorsal Diencephalic Conduction system (DDC). Hb dysfunction is accompanied by different types of neuropsychiatric disorders, such as schizophrenia, depression, and Treatment-Resistant Depression (TRD). Due to difficulties in the imaging assessment of the SM and HB in vivo, they had not been a focus of clinical studies until the invention of Diffusion Tensor Imaging (DTI), which has revolutionized the imaging and investigation of the SM and Hb. DTI has facilitated the imaging of the SM and Hb and has provided insights into their properties through the investigation of their monoamine dysregulation. DTI is a well-established technique for mapping brain microstructure and white matter tracts; it provides indirect information about the microstructural architecture and integrity of white matter in vivo, based on water diffusion properties in the intra- and extracellular space, such as Axial Diffusivity (AD), Radial Diffusivity (RD), mean diffusivity, and Fractional Anisotropy (FA). Neurosurgeons have recognized the potential value of DTI in the direct anatomical targeting of the SM and Hb prior to Deep Brain Stimulation (DBS) surgery for the treatment of certain neuropsychiatric conditions, such as TRD. DTI is the only non-invasive method that offers the possibility of visualization in vivo of the white-matter tracts and nuclei in the human brain. This review study summarizes the use of DTI as a promising new imaging method for accurate identification of the SM and Hb, with special emphasis on direct anatomical targeting of the SM and Hb prior to DBS surgery.

Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography

ABSTRACT

Imaging of trigeminal neuralgia (TN) has demonstrated key diffusion tensor imaging-based diffusivity alterations in the trigeminal nerve; however, imaging has primarily focused on the peripheral nerve segment because of previous limitations in reliably segmenting small fiber bundles across multiple subjects. We used Selective Automated Group Integrated Tractography to study 36 subjects with TN (right-sided pain) and 36 sex-matched controls to examine the trigeminal nerve (fifth cranial nerve [CN V]), pontine decussation (TPT), and thalamocortical fibers (S1). Gaussian process classifiers were trained by scrolling a moving window over CN V, TPT, and S1 tractography centroids. Fractional anisotropy (FA), generalized FA, radial diffusivity, axial diffusivity, and mean diffusivity metrics were evaluated for both groups, analyzing TN vs control groups and affected vs unaffected sides. Classifiers that performed at greater-than-or-equal-to 70% accuracy were included. Gaussian process classifier consistently demonstrated bilateral trigeminal changes, differentiating them from controls with an accuracy of 80%. Affected and unaffected sides could be differentiated from each other with 75% accuracy. Bilateral TPT could be distinguished from controls with at least 85% accuracy. TPT left-right classification achieved 98% accuracy. Bilateral S1 could be differentiated from controls, where the affected S1 radial diffusivity classifier achieved 87% accuracy. This is the first TN study that combines group-wise merged tractography, machine learning classification, and analysis of the complete trigeminal pathways from the peripheral fibers to S1 cortex. This analysis demonstrates that TN is characterized by bilateral abnormalities throughout the trigeminal pathway compared with controls and abnormalities between affected and unaffected sides. This full pathway tractography study of TN demonstrates bilateral changes throughout the trigeminal pathway and changes between affected and unaffected sides.

Age-Related Differences in White Matter: Understanding Tensor-Based Results Using Fixel-Based Analysis

Aging is associated with widespread alterations in cerebral white matter (WM). Most prior studies of age differences in WM have used diffusion tensor imaging (DTI), but typical DTI metrics (e.g., fractional anisotropy; FA) can reflect multiple neurobiological features, making interpretation challenging. Here, we used fixel-based analysis (FBA) to investigate age-related WM differences observed using DTI in a sample of 45 older and 25 younger healthy adults. Age-related FA differences were widespread but were strongly associated with differences in multi-fiber complexity (CX), suggesting that they reflected differences in crossing fibers in addition to structural differences in individual fiber segments. FBA also revealed a frontolimbic locus of age-related effects and provided insights into distinct microstructural changes underlying them. Specifically, age differences in fiber density were prominent in fornix, bilateral anterior internal capsule, forceps minor, body of the corpus callosum, and corticospinal tract, while age differences in fiber cross section were largest in cingulum bundle and forceps minor. These results provide novel insights into specific structural differences underlying major WM differences associated with aging.

Advances in functional and diffusion neuroimaging research into the long-term consequences of very preterm birth

Very preterm birth (<32 weeks of gestation) has been associated with lifelong difficulties in a variety of neurocognitive functions. Magnetic resonance imaging (MRI) combined with advanced analytical approaches have been employed in order to increase our understanding of the neurodevelopmental problems that many very preterm born individuals face as they grow up. In this review, we will focus on two novel imaging techniques that have explored relationships between specific brain mechanisms and behavioural outcomes. These are functional MRI, which maps regional, time-varying changes in brain metabolism and diffusion-weighted MRI, which measures the displacement of water molecules in tissue and provides quantitative information about tissue microstructure. Identifying the neurobiological underpinning of the long-term sequelae associated with very preterm birth could inform the development and implementation of preventative interventions (before any cognitive problem emerges) and could facilitate the identification of behavioural targets for improving the life course outcomes of very preterm individuals.

Diffusion Kurtosis Imaging Fiber Tractography of Major White Matter Tracts in Neurosurgery

Diffusion tensor imaging (DTI)-based fiber tractography is routinely used in clinical applications to visualize major white matter tracts, such as the corticospinal tract (CST), optic radiation (OR), and arcuate fascicle (AF). Nevertheless, DTI is limited due to its capability of resolving intra-voxel multi-fiber populations. Sophisticated models often require long acquisition times not applicable in clinical practice. Diffusion kurtosis imaging (DKI), as an extension of DTI, combines sophisticated modeling of the diffusion process with short acquisition times but has rarely been investigated in fiber tractography. In this study, DTI- and DKI-based fiber tractography of the CST, OR, and AF was investigated in healthy volunteers and glioma patients. For the CST, significantly larger tract volumes were seen in DKI-based fiber tractography. Similar results were obtained for the OR, except for the right OR in patients. In the case of the AF, results of both models were comparable with DTI-based fiber tractography showing even significantly larger tract volumes in patients. In the case of the CST and OR, DKI-based fiber tractography contributes to advanced visualization under clinical time constraints, whereas for the AF, other models should be considered.

Diffusion Tensor Imaging of the Sciatic Nerve as a Surrogate Marker for Nerve Functionality of the Upper and Lower Limb in Patients With Diabetes and Prediabetes

Background

Nerve damage in diabetic neuropathy (DN) is assumed to begin in the distal legs with a subsequent progression to hands and arms at later stages. In contrast, recent studies have found that lower limb nerve lesions in DN predominate at the proximal sciatic nerve and that, in the upper limb, nerve functions can be impaired at early stages of DN.

Materials and Methods

In this prospective, single-center cross-sectional study, participants underwent diffusion-weighted 3 Tesla magnetic resonance neurography in order to calculate the sciatic nerve’s fractional anisotropy (FA), a surrogate parameter for structural nerve integrity. Results were correlated with clinical and electrophysiological assessments of the lower limb and an examination of hand function derived from the Purdue Pegboard Test.

Results

Overall, 71 patients with diabetes, 11 patients with prediabetes and 25 age-matched control subjects took part in this study. In patients with diabetes, the sciatic nerve’s FA showed positive correlations with tibial and peroneal nerve conduction velocities (r = 0.62; p < 0.001 and r = 0.56; p < 0.001, respectively), and tibial and peroneal nerve compound motor action potentials (r = 0.62; p < 0.001 and r = 0.63; p < 0.001, respectively). Moreover, the sciatic nerve’s FA was correlated with the Pegboard Test results in patients with diabetes (r = 0.52; p < 0.001), prediabetes (r = 0.76; p < 0.001) and in controls (r = 0.79; p = 0.007).

Conclusion

This study is the first to show that the sciatic nerve’s FA is a surrogate marker for functional and electrophysiological parameters of both upper and lower limbs in patients with diabetes and prediabetes, suggesting that nerve damage in these patients is not restricted to the level of the symptomatic limbs but rather affects the entire peripheral nervous system.

In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T

BACKGROUND

Diffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed.

METHODS

A multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated.

RESULTS

The SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above.

CONCLUSION

The single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.

Test-retest reliability and long-term stability of three-tissue constrained spherical deconvolution methods for analyzing diffusion MRI data

PURPOSE

Several recent studies have used a three-tissue constrained spherical deconvolution pipeline to obtain quantitative metrics of brain tissue microstructure from diffusion-weighted MRI data. The three tissue compartments, consisting of white matter, gray matter, and CSF-like (free water) signals, are potentially useful in the evaluation of brain microstructure in a range of pathologies. However, the reliability and long-term stability of these metrics have not yet been evaluated.

METHODS

This study examined estimates of whole-brain microstructure for the three tissue compartments, in three separate test-retest cohorts. Each cohort had different lengths of time between baseline and retest, ranging from within the same scanning session in the shortest interval to 3 months in the longest interval. Each cohort was also collected with different acquisition parameters.

RESULTS

The CSF-like compartment displayed the greatest reliability across all cohorts, with intraclass correlation coefficient (ICC) values being above 0.95 in each cohort. White matter-like and gray matter-like compartments both demonstrated very high reliability in the immediate cohort (both ICC > 0.90); however, this declined in the 3-month interval cohort to both compartments having ICC > 0.80. Regional CSF-like signal fraction was examined in bilateral hippocampus and had an ICC > 0.80 in each cohort.

CONCLUSION

The three-tissue constrained spherical deconvolution techniques provide reliable and stable estimates of tissue-microstructure composition, up to 3 months longitudinally in a control population. This forms an important basis for further investigations using three-tissue constrained spherical deconvolution techniques to track changes in microstructure across a variety of brain pathologies.

Dentatorubrothalamic tract reduction using fixel-based analysis in corticobasal syndrome

PURPOSE

The word "fixel" refers to the specific fiber population within each voxel, and fixel-based analysis (FBA) is a recently developed technique that facilitates fiber tract-specific statistical analysis. The aim of the paper is to apply FBA to detect impaired fibers for corticobasal syndrome (CBS) especially in regions that contain multiple crossed fibers.

METHODS

FBA was performed in cohorts of participants clinically diagnosed with CBS (n = 10) and Parkinson's disease (n = 15) or in healthy controls (n = 9). The parameters of the diffusion weighted image were echo time, 83 ms; time, 8123.6 ms; flip angle, 90°; section thickness, 2 mm; b = 1000 s/mm²; and 32 axes. Diffusion tensor analysis was conducted using tract-based spatial statistics (TBSS), and white matter volume was estimated via voxel-based morphometry.

RESULTS

A comparison of PD or HC to CBS revealed a significant difference in the dentatorubrothalamic tract of the brainstem in FBA in addition to the affected regions in voxel-based morphometry and TBSS (family-wise error-corrected p < 0.05). Reduction of the white matter fibers crossing the brainstem could not be detected via microstructural changes identified using TBSS, but it was detected using FBA.

CONCLUSION

FBA has some advantages in determining the distribution of corticobasal syndrome lesions.

Altered thalamocortical structural connectivity in persons with schizophrenia and healthy siblings

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Thalamo-prefrontal structural connectivity reduced in persons with schizophrenia.

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Similar reduction in thalamo-prefrontal connectivity in healthy siblings.

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Thalamo-motor structural connectivity increased in persons with schizophrenia.

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No alterations in thalamo-motor structural connectivity in healthy siblings.

Schizophrenia has long been framed as a disorder of altered brain connectivity, with dysfunction in thalamocortical circuity potentially playing a key role in the development of the illness phenotype, including psychotic symptomatology and cognitive impairments. There is emerging evidence for functional and structural hypoconnectivity between thalamus and prefrontal cortex in persons with schizophrenia spectrum disorders, as well as hyperconnectivity between thalamus and sensory and motor cortices. However, it is unclear whether thalamocortical dysconnectivity is a general marker of vulnerability to schizophrenia or a specific mechanism of schizophrenia pathophysiology. This study aimed to answer this question by using diffusion-weighted imaging to examine thalamocortical structural connectivity in 22 persons with schizophrenia or schizoaffective disorder (SZ), 20 siblings of individuals with a schizophrenia spectrum disorder (SIB), and 44 healthy controls (HC) of either sex. Probabilistic tractography was used to quantify structural connectivity between thalamus and six cortical regions of interest. Thalamocortical structural connectivity was compared among the three groups using cross-thalamic and voxel-wise approaches. Thalamo-prefrontal structural connectivity was reduced in both SZ and SIB relative to HC, while SZ and SIB did not differ from each other. Thalamo-motor structural connectivity was increased in SZ relative to SIB and HC, while SIB and HC did not differ from each other. Hemispheric differences also emerged in thalamic connectivity with motor, posterior parietal, and temporal cortices across all groups. The results support the hypothesis that altered thalamo-prefrontal structural connectivity is a general marker of vulnerability to schizophrenia, whereas altered connectivity between thalamus and motor cortex is related to illness expression or illness-related secondary factors.

Cholinergic white matter pathways make a stronger contribution to attention and memory in normal aging than cerebrovascular health and nucleus basalis of Meynert

The integrity of the cholinergic system plays a central role in cognitive decline both in normal aging and neurological disorders including Alzheimer's disease and vascular cognitive impairment. Most of the previous neuroimaging research has focused on the integrity of the cholinergic basal forebrain, or its sub-region the nucleus basalis of Meynert (NBM). Tractography using diffusion tensor imaging data may enable modelling of the NBM white matter projections. We investigated the contribution of NBM volume, NBM white matter projections, small vessel disease (SVD), and age to performance in attention and memory in 262 cognitively normal individuals (39-77 years of age, 53% female). We developed a multimodal MRI pipeline for NBM segmentation and diffusion-based tracking of NBM white matter projections, and computed white matter hypointensities (WM-hypo) as a marker of SVD. We successfully tracked pathways that closely resemble the spatial layout of the cholinergic system as seen in previous post-mortem and DTI tractography studies. We found that high WM-hypo load was associated with older age, male sex, and lower performance in attention and memory. A high WM-hypo load was also associated with lower integrity of the cholinergic system above and beyond the effect of age. In a multivariate model, age and integrity of NBM white matter projections were stronger contributors than WM-hypo load and NBM volume to performance in attention and memory. We conclude that the integrity of NBM white matter projections plays a fundamental role in cognitive aging. This and other modern neuroimaging methods offer new opportunities to re-evaluate the cholinergic hypothesis of cognitive aging.

White matter tracing combined with electric field simulation - A patient-specific approach for deep brain stimulation

OBJECTIVE

Deep brain stimulation (DBS) in zona incerta (Zi) is used for symptom alleviation in essential tremor (ET). Zi is positioned along the dentato-rubro-thalamic tract (DRT). Electric field simulations with the finite element method (FEM) can be used for estimation of a volume where the stimulation affects the tissue by applying a fixed isolevel (VDBS). This work aims to develop a workflow for combined patient-specific electric field simulation and white matter tracing of the DRT, and to investigate the influence on the VDBS from different brain tissue models, lead design and stimulation modes. The novelty of this work lies in the combination of all these components.

METHOD

Patients with ET were implanted in Zi (lead 3389, n = 3, voltage mode; directional lead 6172, n = 1, current mode). Probabilistic reconstruction from diffusion MRI (dMRI) of the DRT (n = 8) was computed with FSL Toolbox. Brain tissue models were created for each patient (two homogenous, one heterogenous isotropic, one heterogenous anisotropic) and the respective VDBS (n = 48) calculated from the Comsol Multiphysics FEM simulations. The DRT and VDBS were visualized with 3DSlicer and superimposed on the preoperative T2 MRI, and the common volumes calculated. Dice Coefficient (DC) and level of anisotropy were used to evaluate and compare the brain models.

RESULT

Combined patient-specific tractography and electric field simulation was designed and evaluated, and all patients showed benefit from DBS. All VDBS overlapped the reconstructed DRT. Current stimulation showed prominent difference between the tissue models, where the homogenous grey matter deviated most (67 < DC < 69). Result from heterogenous isotropic and anisotropic models were similar (DC > 0.95), however the anisotropic model consistently generated larger volumes related to a greater extension of the electric field along the DBS lead. Independent of tissue model, the steering effect of the directional lead was evident and consistent.

CONCLUSION

A workflow for patient-specific electric field simulations in combination with reconstruction of DRT was successfully implemented. Accurate tissue classification is essential for electric field simulations, especially when using the current control stimulation. With an accurate targeting and tractography reconstruction, directional leads have the potential to tailor the electric field into the desired region.

Optimization of data acquisition and analysis for fiber ball imaging

The inverse Funk transform of high angular resolution diffusion imaging (HARDI) data provides an estimate for the fiber orientation density function (fODF) in white matter (WM). Since the inverse Funk transform is a straightforward linear transformation, this technique, referred to as fiber ball imaging (FBI), offers a practical means of calculating the fODF that avoids the need for a response function or nonlinear numerical fitting. Nevertheless, the accuracy of FBI depends on both the choice of b-value and the number of diffusion-encoding directions used to acquire the HARDI data. To inform the design of optimal scan protocols for its implementation, FBI predictions are investigated here with in vivo data from healthy adult volunteers acquired at 3 T for b-values spanning 1000 to 10,000 s/mm², for diffusion-encoding directions varying in number from 30 to 256 and for TE ranging from 90 to 120 ms. Our results suggest b-values above 4000 s/mm² with at least 64 diffusion-encoding directions are adequate to achieve reasonable accuracy with FBI for calculating axon-specific diffusion measures and for performing WM fiber tractography (WMFT).

Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we propose a fingerprinting-based methodology to identify these fiber directions in Orientation Distribution Functions, dubbed ODF-Fingerprinting (ODF-FP). In ODF-FP, fiber configurations are selected based on the similarity between measured ODFs and elements in a pre-computed library. In noisy ODFs, the library matching algorithm penalizes the more complex fiber configurations. ODF simulations and analysis of bootstrapped partial and whole-brain in vivo datasets show that the ODF-FP approach improves the detection of fiber pairs with small crossing angles while maintaining fiber direction precision, which leads to better tractography results. Rather than focusing on the ODF maxima, the ODF-FP approach uses the whole ODF shape to infer fiber directions to improve the detection of fiber bundles with small crossing angle. The resulting fiber directions aid tractography algorithms in accurately displaying neuronal tracts and calculating brain connectivity.

Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network

PURPOSE

In diffusion-weighted magnetic resonance imaging (DW-MRI), the fiber orientation distribution function (fODF) is of great importance for solving complex fiber configurations to achieve reliable tractography throughout the brain, which ultimately facilitates the understanding of brain connectivity and exploration of neurological dysfunction. Recently, multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) method has been explored for reconstructing full fODFs. To achieve a reliable fitting, similar to other model-based approaches, a large number of diffusion measurements is typically required for MSMT-CSD method. The prolonged acquisition is, however, not feasible in practical clinical routine and is prone to motion artifacts. To accelerate the acquisition, we proposed a method to reconstruct the fODF from downsampled diffusion-weighted images (DWIs) by leveraging the strong inference ability of the deep convolutional neural network (CNN).

METHODS

The method treats spherical harmonics (SH)-represented DWI signals and fODF coefficients as inputs and outputs, respectively. To compensate for the reduced gradient directions with reduced number of DWIs in acquisition in each voxel, its surrounding voxels are incorporated by the network for exploiting their spatial continuity. The resulting fODF coefficients are fitted with applying the CNN in a multi-target regression model. The network is composed of two convolutional layers and three fully connected layers. To obtain an initial evaluation of the method, we quantitatively measured its performance on a simulated dataset. Then, for in vivo tests, we employed data from 24 subjects from the Human Connectome Project (HCP) as training set and six subjects as test set. The performance of the proposed method was primarily compared to the super-resolved MSMT-CSD with the decreasing number of DWIs. The fODFs reconstructed by MSMT-CSD from all available 288 DWIs were used as training labels and the reference standard. The performance was quantitatively measured by the angular correlation coefficient (ACC) and the mean angular error (MAE).

RESULTS

For the simulated dataset, the proposed method exhibited the potential advantage over the model reconstruction. For the in vivo dataset, it achieved superior results over the MSMT-CSD in all the investigated cases, with its advantage more obvious when a limited number of DWIs were used. As the number of DWIs was reduced from 95 to 25, the median ACC ranged from 0.96 to 0.91 for the CNN, but 0.93 to 0.77 for the MSMT-CSD (with perfect score of 1). The angular error in the typical regions of interest (ROIs) was also much lower, especially in multi-fiber regions. The average MAE for the CNN method in regions containing one, two, three fibers was, respectively, 1.09°, 2.75°, and 8.35° smaller than the MSMT-CSD method. The visual inception of the fODF further confirmed this superiority. Moreover, the tractography results validated the effectiveness of the learned fODF, in preserving known major branching fibers with only 25 DWIs.

CONCLUSION

Experiments on HCP datasets demonstrated the feasibility of the proposed method in recovering fODFs from up to 11-fold reduced number of DWIs. The proposed method offers a new streamlined reconstruction procedure and exhibits promising potential in acquisition acceleration for the reconstruction of fODFs with good accuracy.

Verbal Fluency Is Affected by Altered Brain Lateralization in Adults Who Were Born Very Preterm

Language difficulties have been reported in children and adolescents who were born very preterm (<32 weeks’ gestation) and associated with an atypical lateralization of language processing, i.e., increased right-hemispheric engagement. This study used functional magnetic resonance imaging (fMRI) and spherical deconvolution tractography to study the hemodynamic responses associated with verbal fluency processing (easy and hard letter trials) and verbal fluency-related white matter fiber tracts in 64 very preterm born adults and 36 adult controls (mean age: 30 years). Tractography of the arcuate fasciculus (AF) and frontal aslant tract (FAT) was performed. Tracts were quantified in terms of mean volume, hindrance modulated orientational anisotropy, and lateralization, assessed using a laterality index (LI) to indicate hemispheric dominance. During verbal fluency fMRI, very preterm participants displayed decreased hemodynamic response suppression in both the Easy > Rest and Hard > Rest conditions, compared to controls, in superior temporal gyrus (STG), insula, thalamus, and sensorimotor cortex, particularly in the right hemisphere. At the whole-group level, decreased hemodynamic response suppression in the right sensorimotor cortex was associated with worse on-line performance on the hard letter trials. Increased left-laterality in the AF was present alongside increased right hemispheric hemodynamic response suppression in controls. When only right-handed participants were considered, decreased hemodynamic response suppression in the right STG during hard letter trials was related to weaker left and right FAT white matter integrity in the preterm group only. These results show that verbal fluency is affected by altered functional lateralization in adults who were born very preterm.

Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation

We review, systematize and discuss models of diffusion in neuronal tissue, by putting them into an overarching physical context of coarse-graining over an increasing diffusion length scale. From this perspective, we view research on quantifying brain microstructure as occurring along three major avenues. The first avenue focusses on transient, or time-dependent, effects in diffusion. These effects signify the gradual coarse-graining of tissue structure, which occurs qualitatively differently in different brain tissue compartments. We show that transient effects contain information about the relevant length scales for neuronal tissue, such as the packing correlation length for neuronal fibers, as well as the degree of structural disorder along the neurites. The second avenue corresponds to the long-time limit, when the observed signal can be approximated as a sum of multiple nonexchanging anisotropic Gaussian components. Here, the challenge lies in parameter estimation and in resolving its hidden degeneracies. The third avenue employs multiple diffusion encoding techniques, able to access information not contained in the conventional diffusion propagator. We conclude with our outlook on future directions that could open exciting possibilities for designing quantitative markers of tissue physiology and pathology, based on methods of studying mesoscopic transport in disordered systems.

Anatomically constrained tractography facilitates biologically plausible fiber reconstruction of the optic radiation in multiple sclerosis

Diffusion-weighted magnetic resonance imaging (dMRI) enables the microstructural characterization and reconstruction of white matter pathways in vivo non-invasively. However, dMRI only provides information on the orientation of potential fibers but not on their anatomical plausibility. To that end, recent methodological advances facilitate the effective use of anatomical priors in the process of fiber reconstruction, thus improving the accuracy of the results. Here, we investigated the potential of anatomically constrained tracking (ACT), a modular addition to the tractography software package MRtrix3, to accurately reconstruct the optic radiation, a commonly affected pathway in multiple sclerosis (MS). Diffusion MRI data were acquired from 28 MS patients and 22 age- and sex-matched healthy controls. For each participant, the optic radiation was segmented based on the fiber reconstruction obtained using ACT. When implementing ACT in MS, it proved essential to incorporate lesion maps to avoid incorrect reconstructions due to tissue-type misclassifications in lesional areas. The ACT-based results were compared with those obtained using two commonly used probabilistic fiber tracking procedures, based on FSL (FMRIB Software Library) and MRtrix3 without ACT. All three procedures enabled a reliable localization of the optic radiation in both MS patients and controls. However, for FSL and MRtrix3 without ACT it was necessary to place an additional waypoint halfway between the lateral geniculate nucleus and the primary visual cortex to filter out anatomically implausible tracks. In the case of ACT, the results with and without an additional waypoint were virtually identical, presumably because the employed anatomical constraints already prevented the occurrence of the most implausible tracks. Irrespective of the employed tractography procedure, increased diffusivity and decreased anisotropy were found in the optic radiation of the MS patients compared to the controls.

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Anatomical constraints improve tractography of the optic radiation in MS.

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In MS, lesion mapping is essential to implement sensible anatomical constraints.

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Patients showed increased diffusivity and decreased anisotropy in the OR.

White Matter Tissue Quantification at Low b-Values Within Constrained Spherical Deconvolution Framework

In the last decades, a number of Diffusion Weighted Imaging (DWI) based techniques have been developed to study non-invasively human brain tissues, especially white matter (WM). In this context, Constrained Spherical Deconvolution (CSD) is recognized as being able to accurately characterize water molecules displacement, as they emerge from the observation of MR diffusion weighted (MR-DW) images. CSD is suggested to be applied on MR-DW datasets consisting of b-values around 3,000 s/mm² and at least 45 unique diffusion weighting directions. Below such technical requirements, Diffusion Tensor Imaging (DT) remains the most widely accepted model. Unlike CSD, DTI is unable to resolve complex fiber geometries within the brain, thus affecting related tissues quantification. In addition, thanks to CSD, an index called Apparent Fiber Density (AFD) can be measured to estimate intra-axonal volume fraction within WM. In standard clinical settings, diffusion based acquisitions are well below such technical requirements. Therefore, in this study we wanted to extensively compare CSD and DTI model outcomes on really low demanding MR-DW datasets, i.e., consisting of a single shell (b-value = 1,000 s/mm²) and only 30 unique diffusion encoding directions. To this end, we performed deterministic and probabilistic tractographic reconstruction of two major WM pathways, namely the Corticospinal Tract and the Arcuate Fasciculus. We estimated and analyzed tensor based features as well as, for the first time, AFD interpretability in our data. By performing multivariate statistics and tract-based ROI analysis, we demonstrate that WM quantification is affected by both the diffusion model and threshold applied to noisy tractographic maps. Consistently with existing literature, we showed that CSD outperforms DTI even in our scenario. Most importantly, for the first time we address the problem of accuracy and interpretation of AFD in a low-demanding DW setup, and show that it is still a biological meaningful measure for the analysis of intra-axonal volume even in clinical settings.

Comparison of spatial normalization strategies of diffusion MRI data for studying motor outcome in subacute-chronic and acute stroke

A common means of studying motor recovery in stroke patients is to extract Diffusion Tensor Imaging (DTI) parameters from the corticospinal tract (CST) and correlate them with clinical outcome scores. To that purpose, conducting group-level analyses through spatial normalization has become a popular approach. However, the reliability of such analyses depends on the accuracy of the particular registration strategy employed. To date, most studies have employed scalar-based registration using either high-resolution T1 images or Fractional Anisotropy (FA) maps to warp diffusion data to a common space. However, more powerful registration algorithms exist for aligning major white matter structures, such as Fiber Orientation Distribution (FOD)-based registration. Regardless of the strategy chosen, automatic normalization algorithms are prone to distortions caused by stroke lesions. While lesion masking is a common means to lessen such distortions, the extent of its effect on tract-related DTI parameters and their correlation with motor outcome has yet to be determined. Here, we aimed to address these concerns by first investigating the effect of common T1 and FA-based registration as well as novel FOD-based registration algorithms with and without lesion masking on lesion load and DTI parameter extraction of the CST in datasets typically acquired for subacute-chronic and acute stroke patients. Second, we studied how differences in these procedures influenced correlation strength between CST damage (through DTI parameters) and motor outcome. Our results showed that, for high-quality subacute-chronic stroke data, FOD-based registration captured significantly higher lesion loads and significantly larger FA asymmetries in the CST. This was also associated with significantly stronger correlations in motor outcome with respect to T1 or FA-based registration methods. For acute data acquired in a clinical setting, there were few observed differences, suggesting that commonly employed FA-based registration is appropriate for group-level analyses.

High-resolution 3D diffusion tensor MRI of anesthetized rhesus macaque brain at 3T

Diffusion Magnetic Resonance Imaging (dMRI) has been widely used to investigate human brain microstructure and connectivity and its abnormalities in a variety of brain deficits, whether acute, neurodevelopmental or neurodegenerative. However, the biological interpretation and validation of dMRI data modelling is still a crucial challenge in the field. In this respect, achieving high spatial resolution in-vivo dMRI in the non-human primate to compare these observations both with human dMRI on the one hand and 'ground truth' microstructural and histological data on the other hand is of outmost importance. Here, we developed a dMRI pulse sequence based on 3D-multishot Echo Planar Imaging (3D-msEPI) on a 3T human clinical scanner. We demonstrate the feasibility of cerebral dMRI at an isotropic resolution of 0.5 mm in 4 anesthetized macaque monkeys. The added value of the high-resolution dMRI is illustrated by focusing on two aspects. First, we show an enhanced descriptive power of the fine substructure of the hippocampus. Second, we show a more physiological description of the interface between cortex grey matter, superficial and deep white matter. Overall, the high spatial resolution dMRI acquisition method proposed in this study is a significant achievement with respect to the state of the art of dMRI on anesthetized monkeys. This study highlights also the potential of very high-resolution dMRI to precisely capture the microstructure of thin cerebral structures such as the hippocampus and superficial white matter.

Autosomal dominant cerebellar ataxias: Imaging biomarkers with high effect sizes

Objective

As gene-based therapies may soon arise for patients with spinocerebellar ataxia (SCA), there is a critical need to identify biomarkers of disease progression with effect sizes greater than clinical scores, enabling trials with smaller sample sizes.

Methods

We enrolled a unique cohort of patients with SCA1 (n = 15), SCA2 (n = 12), SCA3 (n = 20) and SCA7 (n = 10) and 24 healthy controls of similar age, sex and body mass index. We collected longitudinal clinical and imaging data at baseline and follow-up (mean interval of 24 months). We performed both manual and automated volumetric analyses. Diffusion tensor imaging (DTI) and a novel tractography method, called fixel-based analysis (FBA), were assessed at follow-up. Effect sizes were calculated for clinical scores and imaging parameters.

Results

Clinical scores worsened as atrophy increased over time (p < 0.05). However, atrophy of cerebellum and pons showed very large effect sizes (>1.2) compared to clinical scores (<0.8). FBA, applied for the first time to SCA, was sensitive to microstructural cross-sectional differences that were not captured by conventional DTI metrics, especially in the less studied SCA7 group. FBA also showed larger effect sizes than DTI metrics.

Conclusion

This study showed that volumetry outperformed clinical scores to measure disease progression in SCA1, SCA2, SCA3 and SCA7. Therefore, we advocate the use of volumetric biomarkers in therapeutic trials of autosomal dominant ataxias. In addition, FBA showed larger effect size than DTI to detect cross-sectional microstructural alterations in patients relative to controls.

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Biomarkers are needed to test upcoming therapies for spinocerebellar ataxia.

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As spinocerebellar ataxias are rare, biomarkers with high effect sizes are needed.

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We identified imaging biomarkers with higher effect sizes than clinical scores.

Awakening Neuropsychiatric Research Into the Stria Medullaris: Development of a Diffusion-Weighted Imaging Tractography Protocol of This Key Limbic Structure

The Stria medullaris (SM) Thalami is a discrete white matter tract that directly connects frontolimbic areas to the habenula, allowing the forebrain to influence midbrain monoaminergic output. Habenular dysfunction has been shown in various neuropsychiatric conditions. However, there exists a paucity of research into the habenula’s principal afferent tract, the SM. Diffusion-weighted tractography may provide insights into the properties of the SM in vivo, opening up investigation of this tract in conditions of monoamine dysregulation such as depression, schizophrenia, addiction and pain. We present a reliable method for reconstructing the SM using diffusion-weighted imaging, and examine the effects of age and gender on tract diffusion metrics. We also investigate reproducibility of the method through inter-rater comparisons. In consultation with neuroanatomists, a Boolean logic gate protocol was developed for use in ExploreDTI to extract the SM from constrained spherical deconvolution based whole brain tractography. Particular emphasis was placed on the reproducibility of the tract, attention to crossing white matter tract proximity and anatomical consistency of anterior and posterior boundaries. The anterior commissure, pineal gland and mid point of the thalamus were defined as anatomical fixed points used for reconstruction. Fifty subjects were scanned using High Angular Resolution Diffusion Imaging (HARDI; 61 directions, b-value 1500 mm³). Following constrained spherical deconvolution whole brain tractography, two independent raters isolated the SM. Each output was checked, examined and cleaned for extraneous streamlines inconsistent with known anatomy of the tract by the rater and a neuroanatomist. A second neuroanatomist assessed tracts for face validity. The SM was reconstructed with excellent inter-rater reliability for dimensions and diffusion metrics. Gender had no effect on the dimensions or diffusion metrics, however radial diffusivity (RD) showed a positive correlation with age. Reliable identification and quantification of diffusion metrics of the SM invites further exploration of this key habenula linked structure in neuropsychiatric disorders such as depression, anxiety, chronic pain and addiction. The accurate anatomical localization of the SM may also aid preoperative stereotactic localization of the tract for deep brain stimulation (DBS) treatment.

Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI

We develop a general analytical and numerical framework for estimating intra- and extra-neurite water fractions and diffusion coefficients, as well as neurite orientational dispersion, in each imaging voxel. By employing a set of rotational invariants and their expansion in the powers of diffusion weighting, we analytically uncover the nontrivial topology of the parameter estimation landscape, showing that multiple branches of parameters describe the measurement almost equally well, with only one of them corresponding to the biophysical reality. A comprehensive acquisition shows that the branch choice varies across the brain. Our framework reveals hidden degeneracies in MRI parameter estimation for neuronal tissue, provides microstructural and orientational maps in the whole brain without constraints or priors, and connects modern biophysical modeling with clinical MRI.

Brain Regions Showing White Matter Loss in Huntington's Disease Are Enriched for Synaptic and Metabolic Genes

BACKGROUND

The earliest white matter changes in Huntington's disease are seen before disease onset in the premanifest stage around the striatum, within the corpus callosum, and in posterior white matter tracts. While experimental evidence suggests that these changes may be related to abnormal gene transcription, we lack an understanding of the biological processes driving this regional vulnerability.

METHODS

Here, we investigate the relationship between regional transcription in the healthy brain, using the Allen Institute for Brain Science transcriptome atlas, and regional white matter connectivity loss at three time points over 24 months in subjects with premanifest Huntington's disease relative to control participants. The baseline cohort included 72 premanifest Huntington's disease participants and 85 healthy control participants.

RESULTS

We show that loss of corticostriatal, interhemispheric, and intrahemispheric white matter connections at baseline and over 24 months in premanifest Huntington's disease is associated with gene expression profiles enriched for synaptic genes and metabolic genes. Corticostriatal gene expression profiles are predominately associated with motor, parietal, and occipital regions, while interhemispheric expression profiles are associated with frontotemporal regions. We also show that genes with known abnormal transcription in human Huntington's disease and animal models are overrepresented in synaptic gene expression profiles, but not in metabolic gene expression profiles.

CONCLUSIONS

These findings suggest a dual mechanism of white matter vulnerability in Huntington's disease, in which abnormal transcription of synaptic genes and metabolic disturbance not related to transcription may drive white matter loss.

Connectivity-enhanced diffusion analysis reveals white matter density disruptions in first episode and chronic schizophrenia

Reduced fractional anisotropy (FA) is a well-established correlate of schizophrenia, but it remains unclear whether these tensor-based differences are the result of axon damage and/or organizational changes and whether the changes are progressive in the adult course of illness. Diffusion MRI data were collected in 81 schizophrenia patients (54 first episode and 27 chronic) and 64 controls. Analysis of FA was combined with “fixel-based” analysis, the latter of which leverages connectivity and crossing-fiber information to assess both fiber bundle density and organizational complexity (i.e., presence and magnitude of off-axis diffusion signal). Compared with controls, patients with schizophrenia displayed clusters of significantly lower FA in the bilateral frontal lobes, right dorsal centrum semiovale, and the left anterior limb of the internal capsule. All FA-based group differences overlapped substantially with regions containing complex fiber architecture. FA within these clusters was positively correlated with principal axis fiber density, but inversely correlated with both secondary/tertiary axis fiber density and voxel-wise fiber complexity. Crossing fiber complexity had the strongest (inverse) association with FA (r = −0.82). When crossing fiber structure was modeled in the MRtrix fixel-based analysis pipeline, patients exhibited significantly lower fiber density compared to controls in the dorsal and posterior corpus callosum (central, postcentral, and forceps major). Findings of lower FA in patients with schizophrenia likely reflect two inversely related signals: reduced density of principal axis fiber tracts and increased off-axis diffusion sources. Whereas the former confirms at least some regions where myelin and or/axon count are lower in schizophrenia, the latter indicates that the FA signal from principal axis fiber coherence is broadly contaminated by macrostructural complexity, and therefore does not necessarily reflect microstructural group differences. These results underline the need to move beyond tensor-based models in favor of acquisition and analysis techniques that can help disambiguate different sources of white matter disruptions associated with schizophrenia.

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MRtrix3's fixel-based analysis pipeline performs crossing-fiber modeling and anatomically precise whole-brain white matter registration

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Axon bundle density and organizational complexity appear to underlie white matter alterations in first episode and chronic schizophrenia

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Results underline the need to incorporate techniques that can help disambiguate sources of white matter alterations