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

Can hubs of the human connectome be identified consistently with diffusion MRI?

Recent years have seen a surge in the use of diffusion MRI to map connectomes in humans, paralleled by a similar increase in processing and analysis choices. Yet these different steps and their effects are rarely compared systematically. Here, in a healthy young adult population (n = 294), we characterized the impact of a range of analysis pipelines on one widely studied property of the human connectome: its degree distribution. We evaluated the effects of 40 pipelines (comparing common choices of parcellation, streamline seeding, tractography algorithm, and streamline propagation constraint) and 44 group-representative connectome reconstruction schemes on highly connected hub regions. We found that hub location is highly variable between pipelines. The choice of parcellation has a major influence on hub architecture, and hub connectivity is highly correlated with regional surface area in most of the assessed pipelines (ρ > 0.70 in 69% of the pipelines), particularly when using weighted networks. Overall, our results demonstrate the need for prudent decision-making when processing diffusion MRI data, and for carefully considering how different processing choices can influence connectome organization.

Noise reduction by multiple path neural network using Attention mechanisms with an emphasis on robustness against Errors: A pilot study on brain Diffusion-Weighted images

PURPOSE

In deep learning-based noise reduction, larger networks offer advanced and complex functionality by utilizing its greater degree of freedom, but come with increased unpredictability, raising the potential risk of unforeseen errors. Here, we introduce a novel denoising model for diffusion-weighted images that intentionally limits the network output freedom by incorporating multiple pathways with varying degrees of freedom, with the aim of minimizing the chance of unintended alterations to the input. The purpose of this pilot study is to assess the model's ability to perform effective denoising under the constraints.

METHODS

Images from 10 healthy volunteers were used. Key innovations in our model development include: (1) neural network architecture that separated the function for calculating the specific output values from the function for adjusting the calculation for each pixel and (2) training that optimised the network based on both image and secondary obtained diffusion tensor. The generated images were compared with the original ones by measuring the deviation from ground truth images (averaged across eight acquisitions).

RESULTS

The generated images demonstrated closer alignment with the ground truth images, both visually and statistically (Q < 0.05), compared to the original images. Furthermore, the advantage of the generated images over the original images was also found in the secondary obtained quantitative parameter maps with significance (Q < 0.05).

CONCLUSION

The usefulness of the proposed method was suggested because it was successful in improving both the quality of the generated images and accuracy of the major diffusion parameter maps under the given restrictions.

A unified global tractography framework for automatic visual pathway reconstruction

The human visual pathway starts from the retina, passes through the retinogeniculate visual pathway, the optic radiation, and finally connects to the primary visual cortex. Diffusion MRI tractography is the only technology that can noninvasively reconstruct the visual pathway. However, complete and accurate visual pathway reconstruction is challenging because of the skull base environment and complex fiber geometries. Specifically, the optic nerve within the complex skull base environment can cause abnormal diffusion signals. The crossing and fanning fibers at the optic chiasm, and a sharp turn of Meyer's loop at the optic radiation, contribute to complex fiber geometries of the visual pathway. A fiber trajectory distribution (FTD) function-based tractography method of our previous work and several high sensitivity tractography methods can reveal these complex fiber geometries, but are accompanied by false-positive fibers. Thus, the related studies of the visual pathway mostly applied the expert region of interest selection strategy. However, interobserver variability is an issue in reconstructing an accurate visual pathway. In this paper, we propose a unified global tractography framework to automatically reconstruct the visual pathway. We first extend the FTD function to a high-order streamline differential equation for global trajectory estimation. At the global level, the tractography process is simplified as the estimation of global trajectory distribution coefficients by minimizing the cost between trajectory distribution and the selected directions under the prior guidance by introducing the tractography template as anatomic priors. Furthermore, we use a deep learning-based method and tractography template prior information to automatically generate the mask for tractography. The experimental results demonstrate that our proposed method can successfully reconstruct the visual pathway with high accuracy.

Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review

Optic never fibers in the visual pathway play significant roles in vision formation. Damages of optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and neurological diseases; also, there is a need to prevent the optic nerve fibers from getting damaged in neurosurgery and radiation therapy. Reconstruction of optic nerve fibers from medical images can facilitate all these clinical applications. Although many computational methods are developed for the reconstruction of optic nerve fibers, a comprehensive review of these methods is still lacking. This paper described both the two strategies for optic nerve fiber reconstruction applied in existing studies, i.e., image segmentation and fiber tracking. In comparison to image segmentation, fiber tracking can delineate more detailed structures of optic nerve fibers. For each strategy, both conventional and AI-based approaches were introduced, and the latter usually demonstrates better performance than the former. From the review, we concluded that AI-based methods are the trend for optic nerve fiber reconstruction and some new techniques like generative AI can help address the current challenges in optic nerve fiber reconstruction.

Relationship among Connectivity of the Frontal Aslant Tract, Executive Functions, and Speech and Language Impairment in Children with Childhood Apraxia of Speech

Childhood apraxia of speech (CAS) is a subtype of motor speech disorder usually co-occurring with language impairment. A supramodal processing difficulty, involving executive functions (EFs), might contribute to the cognitive endophenotypes and behavioral manifestations. The present study aimed to profile the EFs in CAS, investigating the relationship between EFs, speech and language severity, and the connectivity of the frontal aslant tract (FAT), a white matter tract involved in both speech and EFs. A total of 30 preschool children with CAS underwent speech, language, and EF assessments and brain MRIs. Their FAT connectivity metrics were compared to those of 30 children without other neurodevelopmental disorders (NoNDs), who also underwent brain MRIs. Alterations in some basic EF components were found. Inhibition and working memory correlated with speech and language severity. Compared to NoND children, a weak, significant reduction in fractional anisotropy (FA) in the left presupplementary motor area (preSMA) FAT component was found. Only speech severity correlated and predicted FA values along with the FAT in both of its components, and visual-spatial working memory moderated the relationship between speech severity and FA in the left SMA. Our study supports the conceptualization of a composite and complex picture of CAS, not limited to the speech core deficit, but also involving high-order cognitive skills.

Automation and standardization of subject-specific region-of-interest segmentation for investigation of diffusion imaging in clinical populations

Diffusion weighted imaging (DWI) is key in clinical neuroimaging studies. In recent years, DWI has undergone rapid evolution and increasing applications. Diffusion magnetic resonance imaging (dMRI) is widely used to analyse group-level differences in white matter (WM), but suffers from limitations that can be particularly impactful in clinical groups where 1) structural abnormalities may increase erroneous inter-subject registration and 2) subtle differences in WM microstructure between individuals can be missed. It also lacks standardization protocols for analyses at the subject level. Region of Interest (ROI) analyses in native diffusion space can help overcome these challenges, with manual segmentation still used as the gold standard. However, robust automated approaches for the analysis of ROI-extracted native diffusion characteristics are limited. Subject-Specific Diffusion Segmentation (SSDS) is an automated pipeline that uses pre-existing imaging analysis methods to carry out WM investigations in native diffusion space, while overcoming the need to interpolate diffusion images and using an intermediate T1 image to limit registration errors and guide segmentation. SSDS is validated in a cohort of healthy subjects scanned three times to derive test-retest reliability measures and compared to other methods, namely manual segmentation and tract-based spatial statistics as an example of group-level method. The performance of the pipeline is further tested in a clinical population of patients with traumatic brain injury and structural abnormalities. Mean FA values obtained from SSDS showed high test-retest and were similar to FA values estimated from the manual segmentation of the same ROIs (p-value > 0.1). The average dice similarity coefficients (DSCs) comparing results from SSDS and manual segmentations was 0.8 ± 0.1. Case studies of TBI patients showed robustness to the presence of significant structural abnormalities, indicating its potential clinical application in the identification and diagnosis of WM abnormalities. Further recommendation is given regarding the tracts used with SSDS.

The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study

This study aimed to evaluate the use of diffusion kurtosis imaging (DKI) to detect microstructural abnormalities within the temporal pole (TP) and its temporopolar cortex in temporal lobe epilepsy (TLE) patients. DKI quantitative maps were obtained from fourteen lesional TLE and ten non-lesional TLE patients, along with twenty-three healthy controls. Data collected included mean (MK); radial (RK) and axial kurtosis (AK); mean diffusivity (MD) and axonal water fraction (AWF). Automated fiber quantification (AFQ) was used to quantify DKI measurements along the inferior longitudinal (ILF) and uncinate fasciculus (Unc). ILF and Unc tract profiles were compared between groups and tested for correlation with disease duration. To characterize temporopolar cortex microstructure, DKI maps were sampled at varying depths from superficial white matter (WM) towards the pial surface. Patients were separated according to the temporal lobe ipsilateral to seizure onset and their AFQ results were used as input for statistical analyses. Significant differences were observed between lesional TLE and controls, towards the most temporopolar segment of ILF and Unc proximal to the TP within the ipsilateral temporal lobe in left TLE patients for MK, RK, AWF and MD. No significant changes were observed with DKI maps in the non-lesional TLE group. DKI measurements correlated with disease duration, mostly towards the temporopolar segments of the WM bundles. Stronger differences in MK, RK and AWF within the temporopolar cortex were observed in the lesional TLE and noticeable differences (except for MD) in non-lesional TLE groups compared to controls. This study demonstrates that DKI has potential to detect subtle microstructural alterations within the temporopolar segments of the ILF and Unc and the connected temporopolar cortex in TLE patients including non-lesional TLE subjects. This could aid our understanding of the extrahippocampal areas, more specifically the temporal pole role in seizure generation in TLE and might inform surgical planning, leading to better seizure outcomes.

In vivo tractography of human locus coeruleus-relation to 7T resting state fMRI, psychological measures and single subject validity

The locus coeruleus (LC) in the brainstem as the main regulator of brain noradrenaline gains increasing attention because of its involvement in neurologic and psychiatric diseases and its relevance in general to brain function. In this study, we created a structural connectome of the LC nerve fibers based on in vivo MRI tractography to gain an understanding into LC connectivity and its impact on LC-related psychological measures. We combined our structural results with ultra-high field resting-state functional MRI to learn about the relationship between in vivo LC structural and functional connections. Importantly, we reveal that LC brain fibers are strongly associated with psychological measures of anxiety and alertness indicating that LC-noradrenergic connectivity may have an important role on brain function. Lastly, since we analyzed all our data in subject-specific space, we point out the potential of structural LC connectivity to reveal individual characteristics of LC-noradrenergic function on the single-subject level.

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.

Neural substrates of neuropsychological profiles in dystrophynopathies: A pilot study of diffusion tractography imaging

Introduction

Cognitive difficulties and neuropsychological alterations in Duchenne and Becker muscular dystrophy (DMD, BMD) boys are not yet sufficiently explored, although this topic could have a relevant impact, finding novel biomarkers of disease both at genetics and neuroimaging point of view. The current study aims to: 1) analyze the neuropsychological profile of a group of DMD and BMD boys without cognitive impairment with an assessment of their executive functions; 2) explore the structural connectivity in DMD, BMD, and age-matched controls focusing on cortico-subcortical tracts that connect frontal cortex, basal ganglia, and cerebellum via the thalamus; 3) explore possible correlations between altered structural connectivity and clinical neuropsychological measures.

Materials and methods

This pilot study included 15 boys (5 DMD subjects, 5 BMD subjects, and 5 age-matched typically developing, TD). They were assessed using a neuropsychological assessment protocol including cognitive and executive functioning assessment and performed a 1.5T MRI brain exam including advance Diffusion Weighted Imaging (DWI) method for tractography. Structural connectivity measurements were extracted along three specific tracts: Cortico-Ponto-Cerebellar Tract (CPCT), Cerebellar-Thalamic Tract (CTT), and Superior Longitudinal Fasciculus (SLF). Cortical-Spinal Tract (CST) was selected for reference, as control tract.

Results

Regarding intellectual functioning, a major impairment in executive functions compared to the general intellectual functioning was observed both for DMD (mean score = 86.20; SD = 11.54) and for BMD children (mean score = 88; SD = 3.67). Mean FA resulted tendentially always lower in DMD compared to both BMD and TD groups for all the examined tracts. The differences in FA were statistically significant for the right CTT (DMD vs BMD, p = 0.002, and DMD vs TD, p = 0.0015) and the right CPCT (DMD vs TD, p = 0.008). Concerning DMD, significant correlations emerged between FA-R-CTT and intellectual quotients (FIQ, p = 0.044; ρs = 0.821), and executive functions (Denomination Total, p = 0.044, ρs = 0.821; Inhibition Total, p = 0.019, ρs = 0.900). BMD showed a significant correlation between FA-R-CPCT and working memory index (p = 0.007; ρs = 0.949).

Discussion and conclusion

In this pilot study, despite the limitation of sample size, the findings support the hypothesis of the involvement of a cerebellar-thalamo-cortical loop for the neuropsychological profile of DMD, as the CTT and the CPCT are involved in the network and the related brain structures are known to be implied in executive functions. Our results suggest that altered WM connectivity and reduced fibre organization in cerebellar tracts, probably due to the lack of dystrophin in the brain, may render less efficient some neuropsychological functions in children affected by dystrophinopathies. The wider multicentric study could help to better establish the role of cerebellar connectivity in neuropsychological profile for dystrophinopathies, identifying possible novel diagnostic and prognostic biomarkers.

Axonal damage in the optic radiation assessed by white matter tract integrity metrics is associated with retinal thinning in multiple sclerosis

INTRODUCTION

White matter damage in the visual pathway is common in multiple sclerosis (MS) and is associated with retinal thinning, although the underlying mechanism of association remains unclear. The goal of this work was to evaluate the presence and extent of white matter tract integrity (WMTI) alterations in the optic radiation (OR) in people with MS and to investigate the association between WMTI metrics and retinal thinning in the eyes of MS patients without a history of optic neuritis (ON) as measured by optical coherence tomography (OCT). We hypothesized that WMTI metrics would reflect axonal damage that occurs in the OR in MS, and that axonal alterations revealed by WMTI would be associated with retinal thinning.

METHODS

Twenty-nine MS patients without previous ON in at least one eye and twenty-nine age-matched healthy controls (HC) were scanned on a dedicated high-gradient 3-Tesla MRI scanner with 300 mT/m maximum gradient strength using a multi-shell diffusion MRI protocol (b = 800, 1500, 2400 s/mm²). The patients were divided into two subgroups according to history without ON (N = 18) or with ON in one eye (N = 11). Diffusion tensor imaging (DTI) metrics and WMTI metrics derived from diffusion kurtosis imaging were assessed in normal-appearing white matter (NAWM) of the OR and in focal lesions. Retinal thickness in the eyes of MS patients was measured by OCT. Student's t-test was used to assess group differences between MRI metrics. Linear regression was used to study the relationship between OCT metrics, including retinal nerve fiber layer (RNFL) and combined ganglion cell and inner plexiform layer thickness (GCL/IPL), visual acuity measures and DTI and WMTI metrics.

RESULTS

OR NAWM in MS showed significantly decreased axonal water fraction (AWF) compared to HC (0.36 vs 0.39, p < 0.001), with similar trends observed in AWF of lesions compared to NAWM (0.27 vs 0.36, p < 0.001). Fractional anisotropy (FA) was lower in OR NAWM of MS patients compared to HC (0.49 vs 0.52, p < 0.001). In patients without ON, AWF was the only diffusion MRI metric that was significantly associated with average RNFL (r = 0.68, p = 0.005), adjusting for age, sex and disease duration and correcting for multiple comparisons. Of all the DTI and WMTI metrics, AWF was the strongest and most significant predictor of average RNFL thickness in MS patients without ON. There was no significant correlation between visual acuity scores and DTI or WMTI metrics after correction for multiple comparisons.

CONCLUSION

Axonal damage may be the substrate of previously observed DTI alterations in the OR, as supported by the significant reduction in AWF within both NAWM and lesions of the OR in MS. Our results support the concept that axonal damage is widespread throughout the visual pathway in MS and may be mediated through trans-synaptic degeneration.

XTRACT - Standardised protocols for automated tractography in the human and macaque brain

We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science.

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A new software package for standardised and automated cross-species tractography.

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Homologous white matter bundles in the human and macaque brain.

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Human white matter tract atlases generated from large datasets (1000 subjects).

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Tractography protocols are standardised, but preserve individual variability.

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Generalisability across datasets shown using the HCP and the UK Biobank data.

MS optic neuritis-induced long-term structural changes within the visual pathway

Background

The visual pathway is commonly involved in multiple sclerosis (MS), even in its early stages, including clinical episodes of optic neuritis (ON). The long-term structural damage within the visual compartment in patients with ON, however, is yet to be elucidated.

Objective

Our aim was to characterize visual system structure abnormalities using MRI along with optical coherence tomography (OCT) and pattern-reversal visual evoked potentials (VEPs) depending on a single history of ON.

Methods

Twenty-eight patients with clinically definitive MS, either with a history of a single ON (HON) or without such history and normal VEP findings (NON), were included. OCT measures comprised OCT-derived peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell/inner plexiform layer (GCIPL) thickness. Cortical and global gray and white matter, thalamic, and T2 lesion volumes were assessed using structural MRI. Diffusion-weighted MRI-derived measures included fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivity within the optic radiation (OR).

Results

Mean (SD) duration after ON was 8.3 (3.7) years. Compared with the NON group, HON patients showed significant RNFL (p = 0.01) and GCIPL thinning (p = 0.002). OR FA (p = 0.014), MD (p = 0.005), RD (p = 0.007), and AD (p = 0.004) were altered compared with NON. Global gray and white as well as other regional gray matter structures did not differ between the 2 groups.

Conclusion

A single history of ON induces long-term structural damage within the retina and OR suggestive of both retrograde and anterograde neuroaxonal degeneration.

Tractography in the presence of multiple sclerosis lesions

Accurate anatomical localisation of specific white matter tracts and the quantification of their tract-specific microstructural damage in conditions such as multiple sclerosis (MS) can contribute to a better understanding of symptomatology, disease evolution and intervention effects. Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis. Since MS lesions can interrupt the tractography algorithm’s tract reconstruction, clinical studies frequently resort to atlas-based approaches, which are convenient but ignorant to individual variability in tract size and shape. Here, we revisit the problem of individual tractography in MS, comparing tractography algorithms using: (i) The diffusion tensor framework; (ii) constrained spherical deconvolution (CSD); and (iii) damped Richardson-Lucy (dRL) deconvolution. Firstly, using simulated and in vivo data from 29 MS patients and 19 healthy controls, we show that the three tracking algorithms respond differentially to MS pathology. While the tensor-based approach is unable to deal with crossing fibres, CSD produces spurious streamlines, in particular in tissue with high fibre loss and low diffusion anisotropy. With dRL, streamlines are increasingly interrupted in pathological tissue. Secondly, we demonstrate that despite the effects of lesions on the fibre orientation reconstruction algorithms, fibre tracking algorithms are still able to segment tracts that pass through areas with a high prevalence of lesions. Combining dRL-based tractography with an automated tract segmentation tool on data from 131 MS patients, the corticospinal tracts and arcuate fasciculi could be reconstructed in more than 90% of individuals. Comparing tract-specific microstructural parameters (fractional anisotropy, radial diffusivity and magnetisation transfer ratio) in individually segmented tracts to those from a tract probability map, we show that there is no systematic disease-related bias in the individually reconstructed tracts, suggesting that lesions and otherwise damaged parts are not systematically omitted during tractography. Thirdly, we demonstrate modest anatomical correspondence between the individual and tract probability-based approach, with a spatial overlap between 35 and 55%. Correlations between tract-averaged microstructural parameters in individually segmented tracts and the probability-map approach ranged between r = .53 (p < .001) for radial diffusivity in the right cortico-spinal tract and r = .97 (p < .001) for magnetisation transfer ratio in the arcuate fasciculi. Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically reconstruct white matter tracts in MS. Individual tract segmentation in MS is feasible on a large scale and could prove a powerful tool for investigating diagnostic and prognostic markers.