Impaired structural motor connectome in amyotrophic lateral sclerosis

Graph network measures reveal distinct white matter abnormalities in motor and extra-motor brain regions of two UMN-predominant ALS subtypes

BACKGROUND

Routine clinical magnetic resonance imaging (MRI) shows bilateral corticospinal tract (CST) hyperintensity in some patients with upper motor neuron (UMN)-predominant ALS (ALS-CST+) but not in others (ALS-CST-). Although, similar in their UMN features, the ALS-CST+ patient group is significantly younger in age, has faster disease progression and shorter survival than the ALS-CST- patient group. Reasons for the differences are unclear.

METHOD

In order to evaluate more objective MRI measures of these ALS subgroups, we used diffusion tensor images (DTI) obtained using single shot echo planar imaging sequence from 1.5 T Siemens MRI Scanner. We performed an exploratory whole brain white matter (WM) network analysis using graph theory approach on 45 ALS patients (ALS-CST+) (n = 21), and (ALS-CST-) (n = 24) and neurological controls (n = 14).

RESULTS

Significant (p < 0.05) differences in nodal degree measure between ALS patients and controls were observed in motor and extra motor regions, supplementary motor area, subcortical WM regions, cerebellum and vermis. Importantly, WM network abnormalities were significantly (p < 0.05) different between ALS-CST+ and ALS-CST- subgroups. Compared to neurologic controls, both ALS subgroups showed hubs in the right superior occipital gyrus and cuneus as well as significantly (p < 0.05) reduced small worldness supportive of WM network damage.

CONCLUSIONS

Significant differences between ALS-CST+ and ALS-CST- subgroups of WM network abnormalities, age of onset, symptom duration prior to MRI, and progression rate suggest these patients represent distinct clinical phenotypes and possibly pathophysiologic mechanisms of ALS.

Strong intercorrelations among global graph-theoretic indices of structural connectivity in the human brain

Graph-theoretic metrics derived from neuroimaging data have been heralded as powerful tools for uncovering neural mechanisms of psychological traits, psychiatric disorders, and neurodegenerative diseases. In N = 8,185 human structural connectomes from UK Biobank, we examined the extent to which 11 commonly-used global graph-theoretic metrics index distinct versus overlapping information with respect to interindividual differences in brain organization. Using unthresholded, FA-weighted networks we found that all metrics other than Participation Coefficient were highly intercorrelated, both with each other (mean |r| = 0.788) and with a topologically-naïve summary index of brain structure (mean edge weight; mean |r| = 0.873). In a series of sensitivity analyses, we found that overlap between metrics is influenced by the sparseness of the network and the magnitude of variation in edge weights. Simulation analyses representing a range of population network structures indicated that individual differences in global graph metrics may be intrinsically difficult to separate from mean edge weight. In particular, Closeness, Characteristic Path Length, Global Efficiency, Clustering Coefficient, and Small Worldness were nearly perfectly collinear with one another (mean |r| = 0.939) and with mean edge weight (mean |r| = 0.952) across all observed and simulated conditions. Global graph-theoretic measures are valuable for their ability to distill a high-dimensional system of neural connections into summary indices of brain organization, but they may be of more limited utility when the goal is to index separable components of interindividual variation in specific properties of the human structural connectome.

Comparison of Diagnostic Performance and Image Quality between Topup-Corrected and Standard Readout-Segmented Echo-Planar Diffusion-Weighted Imaging for Cholesteatoma Diagnostics

This study compares the diagnostic performance and image quality of single-shot turbo spin-echo DWI (tseDWI), standard readout-segmented DWI (rsDWI), and a modified rsDWI version (topupDWI) for cholesteatoma diagnostics. Thirty-four patients with newly suspected unilateral cholesteatoma were examined on a 1.5 Tesla MRI scanner. Diagnostic performance was evaluated by calculating and comparing the sensitivity and specificity using histopathological results as the standard of reference. Image quality was independently reviewed by two readers using a 5-point Likert scale evaluating image distortions, susceptibility artifacts, image resolution, lesion conspicuity, and diagnostic confidence. Twenty-five cholesteatomas were histologically confirmed after surgery and originated in the study group. TseDWI showed the highest sensitivity with 96% (95% confidence interval (CI): 88–100%), followed by topupDWI with 92% (95% CI: 81–100%) for both readers. The sensitivity for rsDWI was 76% (95% CI: 59–93%) for reader 1 and 84% (95% CI: 70–98%) for reader 2, respectively. Both tseDWI and topupDWI revealed a specificity of 100% (95% CI: 66–100%) and rsDWI of 89% (95% CI: 52–100%). Both tseDWI and topupDWI showed fewer image distortions and susceptibility artifacts compared to rsDWI. Image resolution was consistently rated best for topupDWI, followed by rsDWI, which both outperformed tseDWI. TopupDWI and tseDWI showed comparable results for lesions’ conspicuity and diagnostic confidence, both outperforming rsDWI. Modified readout-segmented DWI using the topup-correction method is preferable to standard rsDWI and may be regarded as an accurate alternative to single-shot turbo spin-echo DWI in cholesteatoma diagnostics.

Longitudinal Effects of Asymptomatic C9orf72 Carriership on Brain Morphology

OBJECTIVE

We investigated effects of C9orf72 repeat expansion and gene expression on longitudinal cerebral changes before symptom onset.

METHODS

We enrolled 79 asymptomatic family members (AFMs) from 9 families with C9orf72 repeat expansion. Twenty-eight AFMs carried the mutation (C9+). Participants had up to 3 magnetic resonance imaging (MRI) scans, after which we compared motor cortex and motor tracts between C9+ and C9- AFMs using mixed effects models, incorporating kinship to correct for familial relations and lessen effects of other genetic factors. We also compared cortical, subcortical, cerebellar, and connectome structural measurements in a hypothesis-free analysis. We correlated regional C9orf72 expression in donor brains with the pattern of cortical thinning in C9+ AFMs using meta-regression. For comparison, we included 42 C9+ and 439 C9- patients with amyotrophic lateral sclerosis (ALS) in this analysis.

RESULTS

C9+ AFM motor cortex had less gyrification and was thinner than in C9- AFMs, without differences in motor tracts. Whole brain analysis revealed thinner cortex and less gyrification in parietal, occipital, and temporal regions, smaller thalami and right hippocampus, and affected frontotemporal connections. Thinning of bilateral precentral, precuneus, and left superior parietal cortex was faster in C9+ than in C9- AFMs. Higher C9orf72 expression correlated with thinner cortex in both C9+ AFMs and C9+ ALS patients.

INTERPRETATION

In asymptomatic C9orf72 repeat expansion carriers, brain MRI reveals widespread features suggestive of impaired neurodevelopment, along with faster decline of motor and parietal cortex than found in normal aging. C9orf72 expression might play a role in cortical development, and consequently explain the specific brain abnormalities of mutation carriers. ANN NEUROL 2022.

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = -7.40), and the MiToS (p = 0.0025; β = -4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho = -0.6041, p = 0.0003) and MiToS scales (Spearman's rho = -0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.

Graph theory network analysis provides brain MRI evidence of a partial continuum of neurodegeneration in patients with UMN-predominant ALS and ALS-FTD

OBJECTIVE

Our routine clinical neuroimaging showed hyperintense signal along the corticospinal tract only in some but not all patients with upper motor neuron (UMN)-predominant ALS. ALS patients with CST hyperintensity (ALS-CST+) and those without CST hyperintensity (ALS-CST-) present with nearly identical clinical UMN-predominant symptoms. Some previous studies have suggested that ALS patients with frontotemporal dementia (FTD) are on a continuum with ALS patients without FTD, while others have not. We aimed to determine whether: (a) ALS-CST+, ALS-CST-, and ALS-FTD patients show differential sites of predominant neurodegeneration occurring primarily cortically in the perikaryon or subcortically in the white matter (WM), or (b) UMN-predominant ALS is on a continuum with ALS-FTD.

METHODS

Exploratory whole brain grey matter (GM) voxel-based morphometry and WM network analysis using graph theory approach were performed. In this exploratory study, MRI data from 58 ALS patients (ALS-FTD, n = 15; ALS-CST+, n = 19; ALS-CST-, n = 24) and 14 neurological controls were obtained.

RESULTS

Significant differences in degree measures (evaluating WM networks) were observed between ALS patients and controls in frontal, motor, extra-motor, subcortical, and cerebellar regions. GM atrophy was observed only in the ALS-FTD subgroup and not in the other ALS subgroups.

CONCLUSION

Although WM network disruption by the ALS disease process showed different patterns between ALS-CST+, ALS-CST-, and ALS-FTD subgroups, there were some overlaps, particularly in prefrontal regions and between ALS-CST+ and ALS-FTD patients. Our preliminary findings suggest a partial continuum of, at least, WM degeneration between these subgroups with predominance of cortical pathology ("neuronopathy") in ALS-FTD patients and subcortical WM pathology ("axonopathy") in ALS-CST+ and ALS-CST- patients.

Modeling seeding and neuroanatomic spread of pathology in amyotrophic lateral sclerosis

The neurodegenerative disorder amyotrophic lateral sclerosis (ALS) is characterized by the progressive loss of upper and lower motor neurons, with pathological involvement of cerebral motor and extra-motor areas in a clinicopathological spectrum with frontotemporal dementia (FTD). A key unresolved issue is how the non-random distribution of pathology in ALS reflects differential network vulnerability, including molecular factors such as regional gene expression, or preferential spread of pathology via anatomical connections. A system of histopathological staging of ALS based on the regional burden of TDP-43 pathology observed in postmortem brains has been supported to some extent by analysis of distribution of in vivo structural MRI changes. In this paper, computational modeling using a Network Diffusion Model (NDM) was used to investigate whether a process of focal pathological 'seeding' followed by structural network-based spread recapitulated postmortem histopathological staging and, secondly, whether this had any correlation to the pattern of expression of a panel of genes implicated in ALS across the healthy brain. Regionally parcellated T1-weighted MRI data from ALS patients (baseline n=79) was studied in relation to a healthy control structural connectome and a database of associated regional cerebral gene expression. The NDM provided strong support for a structural network-based basis for regional pathological spread in ALS, but no simple relationship to the spatial distribution of ALS-related genes in the healthy brain. Interestingly, OPTN gene was identified as a significant but a weaker non-NDM contributor within the network-gene interaction model (LASSO). Intriguingly, the critical seed regions for spread within the model were not within the primary motor cortex but basal ganglia, thalamus and insula, where NDM recapitulated aspects of the postmortem histopathological staging system. Within the ALS-FTD clinicopathological spectrum, non-primary motor structures may be among the earliest sites of cerebral pathology.

Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.

Effect of the Minor C Allele of CNTN4 rs2619566 on Medial Hypothalamic Connectivity in Early-Stage Patients of Chinese Han Ancestry with Sporadic Amyotrophic Lateral Sclerosis

OBJECTIVE

Clinical symptoms such as major defects in energy metabolism may involve the hypothalamus in amyotrophic lateral sclerosis (ALS) patients. Our recent study discovered that the single-nucleotide polymorphisms (SNPs) of rs2619566, rs79609816 and rs10260404 are associated with sporadic ALS (sALS). Thus, this study aims to investigate the hypothalamic functional reorganization and its association with the above polymorphisms risk alleles in sALS patients of Chinese Han ancestry.

METHODS

Forty-four sALS patients (28 males/16 females) and 40 healthy subjects (HS; 28 males/12 females) underwent resting-state functional MRI, genotyping and clinical assessments. A two-sample t test (P < 0.01, GRF correction at P < 0.05) was performed to compare hypothalamic connectivity for group-level analysis in disease diagnosis and genotype, and then the genotype-diagnosis interaction effect was assessed. Finally, Spearman correlation analyses were performed to assess the relationship between the altered functional connectivity and their clinical characteristics.

RESULTS

The sALS patients showed a short disease duration (median = 12 months). Regarding the diagnosis effect, the sALS patients showed widespread hypothalamic hyperconnectivity with the left superior temporal gyrus/middle temporal gyrus, right inferior frontal gyrus, and left precuneus/posterior cingulate gyrus. For the genotype effect of SNPs, hyperconnectivity was observed in only the medial hypothalamus when the sALS patients harboring the minor C allele of rs2619566 in contactin-4 (CNTN4), while the sALS patients with the TT allele showed a hyperconnectivity network in the right lateral hypothalamus. This connectivity pattern was not observed in other SNPs. No significant genotype-diagnosis interaction was found. Moreover, altered functional connectivity was not significantly correlated with clinical characteristics (P : 0.11-0.90).

CONCLUSION

These results demonstrated widespread hypothalamic hyperconnectivity in sALS. The risk allele C of the CNTN4 gene may therefore influence functional reorganization of the medial hypothalamus. The effects of the CNTN4 rs2619566 polymorphism may exist in the hypothalamic functional connectivity of patients with sALS.

Silencing of Activity During Hypoxia Improves Functional Outcomes in Motor Neuron Networks in vitro

The effects of hypoxia, or reduced oxygen supply, to brain tissue can be disastrous, leading to extensive loss of function. Deoxygenated tissue becomes unable to maintain healthy metabolism, which leads to increased production of reactive oxygen species (ROS) and loss of calcium homoeostasis, with damaging downstream effects. Neurons are a highly energy demanding cell type, and as such they are highly sensitive to reductions in oxygenation and some types of neurons such as motor neurons are even more susceptible to hypoxic damage. In addition to the immediate deleterious effects hypoxia can have on neurons, there can be delayed effects which lead to increased risk of developing neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), even if no immediate consequences are apparent. Furthermore, impairment of the function of various hypoxia-responsive factors has been shown to increase the risk of developing several neurodegenerative disorders. Longitudinal assessment of electrophysiological network activity is underutilised in assessing the effects of hypoxia on neurons and how their activity and communication change over time following a hypoxic challenge. This study utilised multielectrode arrays and motor neuron networks to study the response to hypoxia and the subsequent development of the neuronal activity over time, as well as the effect of silencing network activity during the hypoxic challenge. We found that motor neuron networks exposed to hypoxic challenge exhibited a delayed fluctuation in multiple network activity parameters compared to normoxic networks. Silencing of activity during the hypoxic challenge leads to maintained bursting activity, suggesting that functional outcomes are better maintained in these networks and that there are activity-dependent mechanisms involved in the network damage following hypoxia.

White matter microstructural impairments in amyotrophic lateral sclerosis: A mean apparent propagator MRI study

Background

White matter (WM) impairment is a hallmark of amyotrophic lateral sclerosis (ALS). This study evaluated the capacity of mean apparent propagator magnetic resonance imaging (MAP-MRI) for detecting ALS-related WM alterations.

Methods

Diffusion images were obtained from 52 ALS patients and 51 controls. MAP-derived indices [return-to-origin/-axis/-plane probability (RTOP/RTAP/RTPP) and non-Gaussianity (NG)/perpendicular/parallel NG (NG_⊥/NG_||)] were computed. Measures from diffusion tensor/kurtosis imaging (DTI/DKI) and neurite orientation dispersion and density imaging (NODDI) were also obtained. Voxel-wise analysis (VBA) was performed to determine differences in these parameters. Relationship between MAP parameters and disease severity (assessed by the revised ALS Functional Rating Scale (ALSFRS-R)) was evaluated by Pearson’s correlation analysis in a voxel-wise way. ALS patients were further divided into two subgroups: 29 with limb-only involvement and 23 with both bulbar and limb involvement. Subgroup analysis was then conducted to investigate diffusion parameter differences related to bulbar impairment.

Results

The VBA (with threshold of P < 0.05 after family-wise error correction (FWE)) showed that ALS patients had significantly decreased RTOP/RTAP/RTPP and NG/ NG_⊥/NG_|| in a set of WM areas, including the bilateral precentral gyrus, corona radiata, posterior limb of internal capsule, midbrain, middle corpus callosum, anterior corpus callosum, parahippocampal gyrus, and medulla. MAP-MRI had the capacity to capture WM damage in ALS, which was higher than DTI and similar to DKI/NODDI. RTOP/RTAP/NG/NG_⊥/NG_|| parameters, especially in the bilateral posterior limb of internal capsule and middle corpus callosum, were significantly correlated with ALSFRS-R (with threshold of FWE-corrected P < 0.05). The VBA (with FWE-corrected P < 0.05) revealed the significant RTAP reduction in subgroup with both bulbar and limb involvement, compared with those with limb-only involvement.

Conclusions

Microstructural impairments in corticospinal tract and corpus callosum represent the consistent characteristic of ALS. MAP-MRI could provide alternative measures depicting ALS-related WM alterations, complementary to the common diffusion imaging methods.

Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis

OBJECTIVE

There is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.

METHODS

Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.

RESULTS

Compared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient Cp (P = 0.0034, t = 2.98), normalized clustering coefficient γ (P = 0.039, t = 2.08), and small-worldness σ (P = 0.038, t = 2.10) at the global network level. The patients also showed decreased regional centralities in motor and non-motor systems including the frontal, temporal and subcortical regions. Using the single-subject structural connection matrix, our classification model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%.

CONCLUSION

Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.

Frontotemporal degeneration in amyotrophic lateral sclerosis (ALS): a longitudinal MRI one-year study

OBJECTIVE

Advanced neuroimaging techniques may offer the potential to monitor disease progression in amyotrophic lateral sclerosis (ALS), a neurodegenerative, multisystem disease that still lacks therapeutic outcome measures. We aim to investigate longitudinal functional and structural magnetic resonance imaging (MRI) changes in a cohort of patients with ALS monitored for one year after diagnosis.

METHODS

Resting state functional MRI, diffusion tensor imaging (DTI), and voxel-based morphometry analyses were performed in 22 patients with ALS examined by six-monthly MRI scans over one year.

RESULTS

During the follow-up period, patients with ALS showed reduced functional connectivity only in some extramotor areas, such as the middle temporal gyrus in the left frontoparietal network after six months and in the left middle frontal gyrus in the default mode network after one year without showing longitudinal changes of cognitive functions. Moreover, after six months, we reported in the ALS group a decreased fractional anisotropy (P = .003, Bonferroni corrected) in the right uncinate fasciculus. Conversely, we did not reveal significant longitudinal changes of functional connectivity in the sensorimotor network, as well as of gray matter (GM) atrophy or of DTI metrics in motor areas, although clinical measures of motor disability showed significant decline throughout the three time points.

CONCLUSION

Our findings highlighted that progressive impairment of extramotor frontotemporal networks may precede the appearance of executive and language dysfunctions and GM changes in ALS. Functional connectivity changes in cognitive resting state networks might represent candidate radiological markers of disease progression.

Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis

Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.

The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure

Myelin plays a crucial role in how well information travels between brain regions. Complementing the structural connectome, obtained with diffusion MRI tractography, with a myelin-sensitive measure could result in a more complete model of structural brain connectivity and give better insight into white-matter myeloarchitecture. In this work we weight the connectome by the longitudinal relaxation rate (R1), a measure sensitive to myelin, and then we assess its added value by comparing it with connectomes weighted by the number of streamlines (NOS). Our analysis reveals differences between the two connectomes both in the distribution of their weights and the modular organization. Additionally, the rank-based analysis shows that R1 can be used to separate transmodal regions (responsible for higher-order functions) from unimodal regions (responsible for low-order functions). Overall, the R1-weighted connectome provides a different perspective on structural connectivity taking into account white matter myeloarchitecture.

In the present work, we show that by using a myelin-sensitive measure we can complement the diffusion MRI-based connectivity and provide a different picture of the brain organization. We show that the R1-weighted average distribution does not follow the same trend as the number of streamlines strength distribution, and the two connectomes exhibit different modular organization. We also show that unimodal cortical regions tend to be connected by more streamlines, but the connections exhibit a lower R1-weighted average, while the transmodal regions have higher R1-weighted average but fewer streamlines. This could imply that the unimodal regions require more connections with lower myelination, whereas the transmodal regions rely on connections with higher myelination.

Ultra-high field (7T) functional magnetic resonance imaging in amyotrophic lateral sclerosis: a pilot study

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Participants with ALS exhibited impaired function between the cortex and cerebellum.

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The cerebellum is associated with complex motor and cognitive processing tasks.

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These findings add to the growing number of ALS reports implicating the cerebellum.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the central nervous system that results in a progressive loss of motor function and ultimately death. It is critical, yet also challenging, to develop non-invasive biomarkers to identify, localize, measure and/or track biological mechanisms implicated in ALS. Such biomarkers may also provide clues to identify potential molecular targets for future therapeutic trials. Herein we report on a pilot study involving twelve participants with ALS and nine age-matched healthy controls who underwent high-resolution resting state functional magnetic resonance imaging at an ultra-high field of 7 Tesla. A group-level whole-brain analysis revealed a disruption in long-range functional connectivity between the superior sensorimotor cortex (in the precentral gyrus) and bilateral cerebellar lobule VI. Post hoc analyses using atlas-derived left and right cerebellar lobule VI revealed decreased functional connectivity in ALS participants that predominantly mapped to bilateral postcentral and precentral gyri. Cerebellar lobule VI is a transition zone between anterior motor networks and posterior non-motor networks in the cerebellum, and is associated with a wide range of key functions including complex motor and cognitive processing tasks. Our observation of the involvement of cerebellar lobule VI adds to the growing number of studies implicating the cerebellum in ALS. Future avenues of scientific investigation should consider how high-resolution imaging at 7T may be leveraged to visualize differences in functional connectivity disturbances in various genotypes and phenotypes of ALS along the ALS-frontotemporal dementia spectrum.

Degeneration of gray and white matter differs between hypometabolic and hypermetabolic brain regions in a patient with ALS-FTD: a longitudinal MRI - PET multimodal study

OBJECTIVE

[18F]-fluoro-2-deoxy-d-glucose positron emission tomography (18F-FDG PET) imaging and magnetic resonance imaging (MRI) of brain in ALS patients with frontotemporal lobe dementia (ALS-FTD) reveal hypometabolism and hypermetabolism, as well as gray matter (GM) and white matter (WM) abnormalities in different brain regions, respectively. Hypometabolism arising from neuronal dysfunction or loss is the most recognized pathophysiologic change in neurodegeneration, whereas mechanisms underlying hypermetabolism remain unclear. We hypothesize that hypometabolic and hypermetabolic brain regions in ALS-FTD represent differential degeneration of GM and WM structures, as revealed by co-registered MRI in a two time-point longitudinal multimodal study. Methods: A 69-year-old female with ALS-FTD underwent 18F-FDG PET, diffusion tensor imaging (DTI), and T1-weighted MRI at baseline (15 months after symptom onset), and 20.4 months later. Cerebral glucose metabolism rate, cortical thickness, cortical area, and WM network changes were measured longitudinally. Results and conclusion: The patient had symptoms and signs of bulbar-onset upper motor neuron (UMN)-predominant ALS with language and behavioral dysfunction. Evaluation at baseline showed bulbar dysfunction, and impaired language and executive function. At follow-up, worsened bulbar and other motor functions, and prominent FTD both reflected significant progression. Cortical thickness and surface area showed differential involvement in the hypometabolic and hypermetabolic regions. WM connections from frontal regions to other brain regions were completely absent by graph theory-based network analysis when compared to temporal regions indicating prominent frontal lobe degeneration. Structural neuroimaging reveals different patterns of GM and WM involvement in the hypometabolic and hypermetabolic brain regions in a patient with ALS-FTD.

2-Deoxy-2-[18 F]fluoro-d-glucose positron emission tomography, cortical thickness and white matter graph network abnormalities in brains of patients with amyotrophic lateral sclerosis and frontotemporal dementia suggest early neuronopathy rather than axonopathy

BACKGROUND AND PURPOSE

Amyotrophic lateral sclerosis (ALS) is a motor neuron disorder, although extra-motor degeneration is well recognized, especially in frontotemporal regions manifested as ALS with frontotemporal dementia (ALS-FTD). Previous neuroimaging studies of the brains of ALS-FTD patients have measured abnormalities of either grey matter (GM) or white matter (WM) structures but not of both together. Therefore, the aim was to evaluate both GM and WM in the same ALS-FTD patient using functional and structural neuroimaging. By doing so, insights could be gained into whether neurodegeneration in ALS-FTD is primarily a neuronopathy or axonopathy.

METHODS

After high-resolution brain 2-deoxy-2-[¹⁸ F]fluoro-D-glucose (¹⁸ F-FDG) positron emission tomography (PET) and magnetic resonance imaging (MRI) scans were obtained in ALS-FTD patients and in age- and sex-matched neurological controls, changes in metabolic rate, cortical thickness (CT) and WM network analysis using graph theory were analyzed.

RESULTS

Significant reductions in ¹⁸ F-FDG PET metabolism, CT and WM connections were observed in motor and extra-motor brain regions of ALS-FTD patients compared to controls. Both CT and underlying WM networks were abnormal in frontal, temporal, parietal and occipital lobes of ALS-FTD patients with 86 of 90 brain regions showing reductions of CT.

CONCLUSION

Abnormalities in significantly fewer WM networks underlying the affected cortical regions suggest that neurodegeneration in brains of ALS-FTD patients is primarily a 'neuronopathy' rather than an 'axonopathy.'

Multimodal longitudinal study of structural brain involvement in amyotrophic lateral sclerosis

OBJECTIVE

To understand the progressive nature of amyotrophic lateral sclerosis (ALS) by investigating differential brain patterns of gray and white matter involvement in clinically or genetically defined subgroups of patients using cross-sectional, longitudinal, and multimodal MRI.

METHODS

We assessed cortical thickness, subcortical volumes, and white matter connectivity from T1-weighted and diffusion-weighted MRI in 292 patients with ALS (follow-up: n = 150) and 156 controls (follow-up: n = 72). Linear mixed-effects models were used to assess changes in structural brain measurements over time in patients compared to controls.

RESULTS

Patients with a C9orf72 mutation (n = 24) showed widespread gray and white matter involvement at baseline, and extensive loss of white matter integrity in the connectome over time. In C9orf72-negative patients, we detected cortical thinning of motor and frontotemporal regions, and loss of white matter integrity of connections linked to the motor cortex. Patients with spinal onset displayed widespread white matter involvement at baseline and gray matter atrophy over time, whereas patients with bulbar onset started out with prominent gray matter involvement. Patients with unaffected cognition or behavior displayed predominantly motor system involvement, while widespread cerebral changes, including frontotemporal regions with progressive white matter involvement over time, were associated with impaired behavior or cognition. Progressive loss of gray and white matter integrity typically occurred in patients with shorter disease durations (<13 months), independent of progression rate.

CONCLUSIONS

Heterogeneity of phenotype and C9orf72 genotype relates to distinct patterns of cerebral degeneration. We demonstrate that imaging studies have the potential to monitor disease progression and early intervention may be required to limit cerebral degeneration.

Multicomponent diffusion analysis reveals microstructural alterations in spinal cord of a mouse model of amyotrophic lateral sclerosis ex vivo

The microstructure changes associated with degeneration of spinal axons in amyotrophic lateral sclerosis (ALS) may be reflected in altered water diffusion properties, potentially detectable with diffusion-weighted (DW) MRI. Prior work revealed the classical mono-exponential model fails to precisely depict decay in DW signal at high b-values. In this study, we aim to investigate signal decay behaviors at ultra-high b-values for non-invasive assessment of spinal cord alterations in the transgenic SOD1^G93A mouse model of ALS. A multiexponential diffusion analysis using regularized non-negative least squares (rNNLS) algorithm was applied to a series of thirty DW MR images with b-values ranging from 0 to 858,022 s/mm² on ex vivo spinal cords of transgenic SOD1^G93A and age-matched control mice. We compared the distributions of measured diffusion coefficient fractions between the groups. The measured diffusion weighted signals in log-scale showed non-linear decay behaviors with increased b-values. Faster signal decays were observed with diffusion gradients applied parallel to the long axis of the spinal cord compared to when oriented in the transverse direction. Multiexponential analysis at the lumbar level in the spinal cord identified ten subintervals. A significant decrease of diffusion coefficient fractions was found in the ranges of [1.63×10⁻⁸,3.70×10⁻⁶] mm²/s (P = 0.0002) and of [6.01×10⁻⁶,4.20×10⁻⁵] mm²/s (P = 0.0388) in SOD1^G93A mice. Anisotropic diffusion signals persisted at ultra-high b-value DWIs of the mouse spinal cord and multiexponential diffusion analysis offers the potential to evaluate microstructural alterations of ALS-affected spinal cord non-invasively.

Phenotypic variability in ALS-FTD and effect on survival

OBJECTIVE

To determine if survival and cognitive profile is affected by initial presentation in amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD) (motor vs cognitive), we compared survival patterns in ALS-FTD based on initial phenotypic presentation and their cognitive profile compared to behavioral variant FTD (bvFTD).

METHODS

Cognitive/behavioral profiles were examined in 98 patients (59 ALS-FTD and 39 bvFTD). The initial presentation of ALS-FTD was categorized into either motor or cognitive. Survival was calculated from initial symptom onset. MRI brain atrophy patterns were examined using a validated visual rating scale.

RESULTS

In the ALS-FTD group, 41 (69%) patients were categorized as having an initial cognitive presentation and 18 (31%) a motor presentation. Patients with motor presentation experienced a significantly shorter median survival of 2.7 years compared to 4.4 years (p < 0.001) in those with a cognitive presentation. No differences between motor vs cognitive onset ALS-FTD were found on cognitive testing. When compared to bvFTD, ALS-FTD-cognitive presentation was characterized by reduced language function (p < 0.001), verbal fluency (p = 0.001), and naming (p = 0.007). Both motor and cognitive onset ALS-FTD showed reduced emotion processing (p = 0.01) and exhibited greater motor cortex and dorsal lateral prefrontal cortex atrophy than bvFTD. Increased motor cortex atrophy was associated with 1.5-fold reduction in survival.

CONCLUSIONS

Initial motor presentation in ALS-FTD leads to faster progression than in those with a cognitive presentation, despite similar overall cognitive deficits. These findings suggest that disease progression in ALS-FTD may be critically linked to physiologic and motor changes.

Mirror Movements in Amyotrophic Lateral Sclerosis: A Combined Study Using Diffusion Tensor Imaging and Transcranial Magnetic Stimulation

Objective: Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disorder predominantly affecting the motor system. In a number of patients, mirror movements (MMs) suggest involvement of transcallosal fiber tracts in conjunction with upper motor neuron involvement. The aim of the study was to elucidate functional and structural alterations of callosal integrity in ALS patients with MMs. Methods: Nineteen patients with ALS displaying MMs and 20 controls underwent clinical assessment, transcranial magnetic stimulation (TMS), and diffusion tensor imaging (DTI). TBSS (tract based spatial statistics) was performed. We investigated ipsilateral silent period (iSP) as a measure of transcallosal inhibition, and diffusion changes in the corpus callosum and corticospinal tract (CST) as measure of structural integrity. Results: In ALS patients TMS revealed a longer mean iSP latency than controls. Twelve ALS patients (63.2%) showed loss of iSP, but none of the controls. Using region of interest analysis, fractional anisotropy (FA) values of the CST were significantly lower in ALS patients compared with controls, but diffusion parameters of the corpus callosum did not differ between patients and controls. The lack of diffusion changes in the corpus callosum was confirmed in whole brain tract based statistics, assessing FA as well as mean, radial, and axial diffusivity. There was a significant negative correlation between resting motor threshold and FA values of the CST, but not between iSP and FA of the corpus callosum. Conclusion: In conclusion the study failed to show microstructural changes in the corpus callosum in conjunction with MMs. One possible reason may be that functional disturbance of transcallosal pathways precede microstructural changes in the corpus callosum.

A new parameter to discriminate amyotrophic lateral sclerosis patients from healthy participants by motor cortical excitability changes

INTRODUCTION

We sought a combination of abnormalities to define a more sensitive measure of cortical excitability in amyotrophic lateral sclerosis (ALS).

METHODS

The automatic threshold tracking method was employed to assess the resting motor threshold, intracortical facilitation (ICF), short-interval intracortical inhibition (SICI), and short-interval intracortical faciilitation (SICF) in patients and controls.

RESULTS

SICF at interstimulus intervals (ISI) between 1 and 1.8 ms and 2 and 3 ms as well as average SICI and SICI at ISIs of 1 and 2.5 ms were significantly reduced in ALS. The SICI curve was altered, displaying a solitary peak. Discriminant analysis revealed that the combination of SICI 2.5 ms and the mean SICF between 1 and 1.8 ms ISIs was the most sensitive parameter to distinguish patients with ALS from healthy participants.

DISCUSSION

Along with the reduced SICI and its altered shape, connectivity between motor cortical circuits is changed in ALS. Combination with SICF increases the diagnostic utility of SICI in ALS.

Advanced neuroimaging approaches in amyotrophic lateral sclerosis: refining the clinical diagnosis

Introduction: In the last decade, multiparametric magnetic resonance imaging (MRI) has achieved tremendous advances in applications to amyotrophic lateral sclerosis (ALS) to increase the understanding of the associated pathophysiology. The aim of this review is to summarize recent progress in the development of MRI-based techniques aiming to support the clinical diagnosis in ALS.Areas covered: The review of structural and functional MRI applications to ALS and its variants (restricted phenotypes) is focused on the potential of MRI techniques which contribute to the diagnostic work-up of patients with the clinical presentation of a motor neuron disease. The potential of specific MRI methods for patient diagnosis and monitoring is discussed, and the future design of clinical MRI applications to ALS is conceptualized.Expert opinion: Current multiparametric MRI allows for the use as a clinical biological marker and a technical instrument in the clinical diagnosis of patients with ALS and also of patients with ALS variants. Composite neuroimaging indices of specific anatomical areas derived from different MRI techniques might guide in the diagnostic applications to ALS. Such a development of ALS-specific MRI-based composite scores with sufficient discriminative power versus ALS mimics at an individual level requires standardized advanced protocols and comprehensive analysis approaches.

The effect of network thresholding and weighting on structural brain networks in the UK Biobank

Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44-77 years), we constructed whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that: 1) measures derived from unthresholded matrices yielded the weakest age-associations (0.033 ​≤ ​|β| ​≤ ​0.409); and 2) the most commonly-used level of proportional-thresholding from the literature (retaining 68.7% of all possible connections) yielded significantly weaker age-associations (0.070 ​≤ ​|β| ​≤ ​0.406) than the consistency-based approach which retained only 30% of connections (0.140 ​≤ ​|β| ​≤ ​0.409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC ​= ​0.84), when matched at 70% network sparsity. Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ​≤ ​|0.068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ​≤ ​|0.219|, p ​< ​0.001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.

Structural Connectivity Alterations in Amyotrophic Lateral Sclerosis: A Graph Theory Based Imaging Study

Background

Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive neurodegenerative disorder. Diffusion magnetic resonance imagining (MRI) studies have consistently showed widespread alterations in both motor and non-motor brain regions. However, connectomics and graph theory based approaches have shown inconsistent results. Hub-centered lesion patterns and their impact on local and large-scale brain networks remain to be established. The objective of this work is to characterize topological properties of structural brain connectivity in ALS using an array of local, global and hub-based network metrics.

Materials and Methods

Magnetic resonance imagining data were acquired from 25 patients with ALS and 26 age-matched healthy controls. Structural network graphs were constructed from diffusion tensor MRI. Network-based statistics (NBS) and graph theory metrics were used to compare structural networks without a priori regions of interest.

Results

Patients with ALS exhibited global network alterations with decreased global efficiency (Eglob) (p = 0.03) and a trend of reduced whole brain mean degree (p = 0.05) compared to controls. Six nodes showed significantly decreased mean degree in ALS: left postcentral gyrus, left interparietal and transverse parietal sulcus, left calcarine sulcus, left occipital temporal medial and lingual sulcus, right precentral gyrus and right frontal inferior sulcus (p < 0.01). Hub distribution was comparable between the two groups. There was no selective hub vulnerability or topological reorganization centered on these regions as the hub disruption index (κ) was not significant for the relevant metrics (degree, local efficiency and betweenness centrality). Using NBS, we identified an impaired motor subnetwork of 11 nodes and 10 edges centered on the precentral and the paracentral nodes (p < 0.01). Significant clinical correlations were identified between degree in the frontal area and the disease progression rate of ALS patients (p < 0.01).

Conclusion

Our study provides evidence that alterations of structural connectivity in ALS are primarily driven by node degree and white matter tract degeneration within an extended network around the precentral and the paracentral areas without hub-centered reorganization.

Cross-sectional and longitudinal assessment of the upper cervical spinal cord in motor neuron disease

Background

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease characterized by both upper and lower motor neuron degeneration. While neuroimaging studies of the brain can detect upper motor neuron degeneration, these brain MRI scans also include the upper part of the cervical spinal cord, which offers the possibility to expand the focus also towards lower motor neuron degeneration. Here, we set out to investigate cross-sectional and longitudinal disease effects in the upper cervical spinal cord in patients with ALS, progressive muscular atrophy (PMA: primarily lower motor neuron involvement) and primary lateral sclerosis (PLS: primarily upper motor neuron involvement), and their relation to disease severity and grey and white matter brain measurements.

Methods

We enrolled 108 ALS patients without C9orf72 repeat expansion (ALS C9–), 26 ALS patients with C9orf72 repeat expansion (ALS C9+), 28 PLS patients, 56 PMA patients and 114 controls. During up to five visits, longitudinal T1-weighted brain MRI data were acquired and used to segment the upper cervical spinal cord (UCSC, up to C3) and individual cervical segments (C1 to C4) to calculate cross-sectional areas (CSA). Using linear (mixed-effects) models, the CSA differences were assessed between groups and correlated with disease severity. Furthermore, a relationship between CSA and brain measurements was examined in terms of cortical thickness of the precentral gyrus and white matter integrity of the corticospinal tract.

Results

Compared to controls, CSAs at baseline showed significantly thinner UCSC in all groups in the MND spectrum. Over time, ALS C9– patients demonstrated significant thinning of the UCSC and, more specifically, of segment C3 compared to controls. Progressive thinning over time was also observed in C1 of PMA patients, while ALS C9+ and PLS patients did not show any longitudinal changes. Longitudinal spinal cord measurements showed a significant relationship with disease severity and we found a significant correlation between spinal cord and motor cortex thickness or corticospinal tract integrity for PLS and PMA, but not for ALS patients.

Discussion

Our findings demonstrate atrophy of the upper cervical spinal cord in the motor neuron disease spectrum, which was progressive over time for all but PLS patients. Cervical spinal cord imaging in ALS seems to capture different disease effects than brain neuroimaging. Atrophy of the cervical spinal cord is therefore a promising additional biomarker for both diagnosis and disease progression and could help in the monitoring of treatment effects in future clinical trials.

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Atrophy of upper cervical spinal cord is shown in the motor neuron disease spectrum.

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Progressive cervical spinal cord thinning occurs over time for all but PLS patients.

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Cervical spinal cord imaging is a potential biomarker for disease progression in ALS.

Cortical correlates of behavioural change in amyotrophic lateral sclerosis

BACKGROUND

Behavioural changes in amyotrophic lateral sclerosis (ALS) are heterogeneous. The study aim was to identify the behavioural profiles of non-demented patients with ALS and their neuroimaging correlates and to elucidate if they are comparable to those reported in studies of the behavioural-variant of frontotemporal dementia (bvFTD).

METHODS

Behavioural changes of 102 non-demented patients with ALS were assessed through the Frontal Behavioural Inventory (FBI), a 24-item scale assessing different behavioural modifications, mainly chosen from the core clinical features of FTD. Principal component analysis (PCA) was used to detect distinct clusters of behavioural changes based on FBI subscores. The cortical thinning related to each behavioural profile was analysed in 29 patients with ALS. Cronbach's α was used to test the reliability of bvFTD-related FBI clustering in our cohort.

RESULTS

Sixty patients with ALS had FBI score≥1. PCA identified three phenotypic clusters loading on disinhibited/hostile, dysexecutive and apathetic FBI subscores. Imaging analyses revealed that the thinning of bilateral orbitofrontal cortex was related to apathy, the right frontotemporal and cingular cortex to the disinhibited/hostile profile and the left precuneus cortex to the dysexecutive behaviours. The bvFTD-associated aggressive profile reliably applied to our cohort.

CONCLUSIONS

In non-demented patients with ALS, different behavioural profiles could be identified. The right frontotemporal and cingular cortex thinning was the hallmark of the behavioural profile mostly overlapping that described in bvFTD. Our findings provide the unbiased identification of determinants relevant for a novel stratification of patients with ALS based on their behavioural impairment, which might be useful as proxy of cognitive decline.

White Matter Microstructure Breakdown in the Motor Neuron Disease Spectrum: Recent Advances Using Diffusion Magnetic Resonance Imaging

Motor neuron disease (MND) is a fatal progressive neurodegenerative disorder characterized by the breakdown of the motor system. The clinical spectrum of MND encompasses different phenotypes classified according to the relative involvement of the upper or lower motor neurons (LMN) and the presence of genetic or cognitive alterations, with clear prognostic implications. However, the pathophysiological differences of these phenotypes remain largely unknown. Recently, magnetic resonance imaging (MRI) has been recognized as a helpful in-vivo MND biomarker. An increasing number of studies is applying advanced neuroimaging techniques in order to elucidate the pathophysiological processes and to identify quantitative outcomes to be used in clinical trials. Diffusion tensor imaging (DTI) is a non-invasive method to detect white matter alterations involving the upper motor neuron and extra-motor white matter tracts. According to this background, the aim of this review is to highlight the key role of MRI and especially DTI, summarizing cross-sectional and longitudinal results of different approaches applied in MND. Current literature suggests that DTI is a promising tool in order to define anatomical “signatures” of the different phenotypes of MND and to track in vivo the progressive spread of pathological proteins aggregates.

Test-Retest Reliability of Graph Theoretic Metrics in Adolescent Brains

Graph theory analysis of structural brain networks derived from diffusion tensor imaging (DTI) has become a popular analytical method in neuroscience, enabling advanced investigations of neurological and psychiatric disorders. The purpose of this study was to investigate (1) the effects of edge weighting schemes and (2) the effects of varying interscan periods on graph metrics within the adolescent brain. We compared a binary (B) network definition with three weighting schemes: fractional anisotropy (FA), streamline count, and streamline count with density and length correction (SDL). Two commonly used global and two local graph metrics were examined. The analysis was conducted with two groups of adolescent volunteers who received DTI scans either 12 weeks apart (16.62 ± 1.10 years) or within the same scanning session (30 min apart) (16.65 ± 1.14 years). The intraclass correlation coefficient was used to assess test-retest reliability and the coefficient of variation (CV) was used to assess precision. On average, each edge scheme produced reliable results at both time intervals. Weighted measures outperformed binary measures, with SDL weights producing the most reliable metrics. All edge schemes except FA displayed high CV values, leaving FA as the only edge scheme that consistently showed high precision while also producing reliable results. Overall findings suggest that FA weights are more suited for DTI connectome studies in adolescents.

Neurodegeneration of brain networks in the amyotrophic lateral sclerosis-frontotemporal lobar degeneration (ALS-FTLD) continuum: evidence from MRI and MEG studies

Brain imaging techniques, especially those based on magnetic resonance imaging (MRI) and magnetoencephalography (MEG), have been increasingly applied to study multiple large-scale distributed brain networks in healthy people and neurological patients. With regard to neurodegenerative disorders, amyotrophic lateral sclerosis (ALS), clinically characterized by the predominant loss of motor neurons and progressive weakness of voluntary muscles, and frontotemporal lobar degeneration (FTLD), the second most common early-onset dementia, have been proven to share several clinical, neuropathological, genetic, and neuroimaging features. Specifically, overlapping or mildly diverging brain structural and functional connectivity patterns, mostly evaluated by advanced MRI techniques-such as diffusion tensor and resting-state functional MRI (DT-MRI, RS-fMRI)-have been described comparing several ALS and FTLD populations. Moreover, though only pioneering, promising clues on connectivity patterns in the ALS-FTLD continuum may derive from MEG investigations. We will herein overview the current state of knowledge concerning the most advanced neuroimaging findings associated with clinical and genetic patterns of neurodegeneration across the ALS-FTLD continuum, underlying the possibility that network-based approaches may be useful to develop novel biomarkers of disease for adequately designing and monitoring more appropriate treatment strategies.

Abnormal topological organization of structural covariance networks in amyotrophic lateral sclerosis

Neuroimaging studies of patients with amyotrophic lateral sclerosis (ALS) have shown widespread alterations in structure, function, and connectivity in both motor and non-motor brain regions, suggesting multi-systemic neurobiological abnormalities that might impact large-scale brain networks. Here, we examined the alterations in the topological organization of structural covariance networks of ALS patients (N = 60) compared with normal controls (N = 60). We found that structural covariance networks of ALS patients showed a consistent rearrangement towards a regularized architecture evidenced by increased path length, clustering coefficient, small-world index, and modularity, as well as decreased global efficiency, suggesting inefficient global integration and increased local segregation. Locally, ALS patients showed decreased nodal degree and betweenness in the gyrus rectus and/or Heschl's gyrus, and increased betweenness in the supplementary motor area, triangular part of the inferior frontal gyrus, supramarginal gyrus and posterior cingulate cortex. In addition, we identified a different number and distribution of hubs in ALS patients, showing more frontal and subcortical hubs than in normal controls. In conclusion, we reveal abnormal topological organization of structural covariance networks in ALS patients, and provide network-level evidence for the concept that ALS is a multisystem disorder with a cerebral involvement extending beyond the motor areas.

Biomarkers in Neurodegenerative Diseases

The past decade has seen tremendous efforts in biomarker discovery and validation for neurodegenerative diseases. The source and type of biomarkers has continued to grow for central nervous system diseases, from biofluid-based biomarkers (blood or cerebrospinal fluid (CSF)), to nucleic acids, tissue, and imaging. While DNA remains a predominant biomarker used to identify familial forms of neurodegenerative diseases, various types of RNA have more recently been linked to familial and sporadic forms of neurodegenerative diseases during the past few years. Imaging approaches continue to evolve and are making major contributions to target engagement and early diagnostic biomarkers. Incorporation of biomarkers into drug development and clinical trials for neurodegenerative diseases promises to aid in the development and demonstration of target engagement and drug efficacy for neurologic disorders. This review will focus on recent advancements in developing biomarkers for clinical utility in Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

Age-Related Changes in Topological Degradation of White Matter Networks and Gene Expression in Chronic Schizophrenia

Current hypotheses stipulate core symptoms of schizophrenia (SZ) result from the brain's incapacity to integrate neural processes. Converging diffusion magnetic resonance imaging and graph theory studies provide evidence of macrostructural alterations in SZ. However, age-related topological changes within and between white matter (WM) networks and its relationship to gene expression with disease progression remain incompletely understood. This cross-sectional study uses network modeling to investigate changes in WM network organization with disease progression in chronic SZ as well its relationship with gene expression in healthy brains. First, we replicate prior findings demonstrating altered global WM network topology in SZ. Novel results show significantly altered age-related network degradation patterns in patients compared with controls. Specifically, controls show stereotyped, linear global network decline with age. In contrast, patients show nonlinear network decline with age. Further analysis reveals lack of significant topological decline in younger adult patients, which is subsequently followed by stereotyped linear decline in older adult patients. Node-specific analyses show significant topological differences in frontal and limbic regions of younger adult patients compared with age-matched controls, which become less pronounced with age in older adult patients compared with age-matched controls. Lastly, we show several gene expression profiles, including DISC1, are associated with age-related changes in WM disconnectivity. Together, these findings provide novel WM topological and genetic evidence supporting neurodevelopmental models of SZ, suggesting that network remodeling continues throughout the third decade of life before stabilizing.

Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study

Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (β = 0.132, pFDR = 0.040), arcuate (β = 0.291, pFDR = 0.040), anterior thalamic radiations (β = 0.215, pFDR = 0.040) and cingulum (β = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (β = -0.039, pFDR = 0.048) and strength (β = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.

Models of Network Spread and Network Degeneration in Brain Disorders

Network analysis can provide insight into key organizational principles of brain structure and help identify structural changes associated with brain disease. Though static differences between diseased and healthy networks are well characterized, the study of network dynamics, or how brain networks change over time, is increasingly central to understanding ongoing brain changes throughout disease. Accordingly, we present a short review of network models of spread, network dynamics, and network degeneration. Borrowing from recent suggestions, we divide this review into two processes by which brain networks can change: dynamics on networks, which are functional and pathological consequences taking place atop a static structural brain network; and dynamics of networks, which constitutes a changing structural brain network. We focus on diffusion magnetic resonance imaging-based structural or anatomic connectivity graphs. We address psychiatric disorders like schizophrenia; developmental disorders like epilepsy; stroke; and Alzheimer's disease and other neurodegenerative diseases.

Abnormal Functional Connectivity Density in Amyotrophic Lateral Sclerosis

Purpose: Amyotrophic lateral sclerosis (ALS) is a motor neuro-degenerative disorder that also damages extra-motor neural pathways. A significant proportion of existing evidence describe alterations in the strengths of functional connectivity, whereas the changes in the density of these functional connections have not been explored. Therefore, our study seeks to identify ALS-induced alternations in the resting-state functional connectivity density (FCD).

Methods: Two groups comprising of 38 ALS patients and 35 healthy participants (age and gender matched) were subjected to the resting-state functional magnetic resonance imaging (MRI) scanning. An ultra-fast graph theory method known as FCD mapping was utilized to calculate the voxel-wise short- and long-range FCD values of the brain for each participant. FCD values of patients and controls were compared based on voxels in order to discern cerebral regions that possessed significant FCD alterations. For areas demonstrating a group effect of atypical FCD in ALS, seed-based functional connectivity analysis was then investigated. Partial correlation analyses were carried out between aberrant FCDs and several clinical variables, controlling for age, gender, and total intracranial volume.

Results: Patients with ALS were found to have decreased short-range FCD in the primary motor cortex and increased long-range FCD in the premotor cortex. Extra-motor areas that also displayed extensive FCD alterations encompassed the temporal cortex, insula, cingulate gyrus, occipital cortex, and inferior parietal lobule. Seed-based correlation analysis further demonstrated that these regions also possessed disrupted functional connectivity. However, no significant correlations were identified between aberrant FCDs and clinical variables.

Conclusion: FCD changes in the regions identified represent communication deficits and impaired functional brain dynamics, which might underlie the motor, motor control, language, visuoperceptual and high-order cognitive deficits in ALS. These findings support the fact that ALS is a disorder affecting multiple systems. We gain a deeper insight of the neural mechanisms underlying ALS.

Implications of structural and functional brain changes in amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that causes progressive muscle weakness and disability, eventually leading to death. Heterogeneity of disease has become a major barrier to understanding key clinical questions such as prognosis and disease spread, and has disadvantaged clinical trials in search of therapeutic intervention. Patterns of disease have been explored through recent advances in neuroimaging, elucidating structural, molecular and functional changes. Unique brain signatures have emerged that have lent a greater understanding of critical disease mechanisms, offering opportunities to improve diagnosis, guide prognosis, and establish candidate biomarkers to direct future therapeutic strategies. Areas covered: This review explores patterns of cortical and subcortical change in ALS through advanced neuroimaging techniques and discusses the implications of these findings. Expert commentary: Cortical and subcortical signatures and patterns of atrophy are now consistently recognised, providing important pathophysiological insight into this heterogenous disease. The spread of cortical change, particularly involving frontotemporal networks, correlates with cognitive impairment and poorer prognosis. Cortical differences are also evident between ALS phenotypes and genotypes, which may partly explain the heterogeneity of prognosis. Ultimately, multimodal approaches with larger cohorts will be needed to provide sensitive biomarkers of disease spread at the level of the individual patient.

Neuroimaging in amyotrophic lateral sclerosis: current and emerging uses

INTRODUCTION

Several neuroimaging techniques have been used to define in vivo markers of pathological alterations underlying amyotrophic lateral sclerosis (ALS). Growing evidence supports the use of magnetic resonance imaging (MRI) and positron emission tomography (PET) for the non-invasive detection of central nervous system involvement in patients with ALS. Areas covered: A comprehensive overview of structural and functional neuroimaging applications in ALS is provided, focusing on motor and extra-motor involvement in the brain and the spinal cord. Implications for pathogenetic models, patient diagnosis, prognosis, monitoring, and the design of clinical trials are discussed. Expert commentary: State-of-the-art neuroimaging techniques provide fundamental instruments for the detection and quantification of upper motor neuron and extra-motor brain involvement in ALS, with relevance for both pathophysiologic investigation and clinical practice. Network-based analysis of structural and functional connectivity alterations and multimodal approaches combining several neuroimaging measures are promising tools for the development of novel diagnostic and prognostic markers to be used at the individual patient level.

Central and non-central networks, cognition, clinical symptoms, and polygenic risk scores in schizophrenia

Schizophrenia is a complex disorder that may be the result of aberrant connections between specific brain regions rather than focal brain abnormalities. Here, we investigate the relationships between brain structural connectivity as described by network analysis, intelligence, symptoms, and polygenic risk scores (PGRS) for schizophrenia in a group of patients with schizophrenia and a group of healthy controls. Recently, researchers have shown an interest in the role of high centrality networks in the disorder. However, the importance of non-central networks still remains unclear. Thus, we specifically examined network-averaged fractional anisotropy (mean edge weight) in central and non-central subnetworks. Connections with the highest betweenness centrality within the average network (>75% of centrality values) were selected to represent the central subnetwork. The remaining connections were assigned to the non-central subnetwork. Additionally, we calculated graph theory measures from the average network (connections that occur in at least 2/3 of participants). Density, strength, global efficiency, and clustering coefficient were significantly lower in patients compared with healthy controls for the average network (p_FDR  < 0.05). All metrics across networks were significantly associated with intelligence (p_FDR  < 0.05). There was a tendency towards significance for a correlation between intelligence and PGRS for schizophrenia (r = -0.508, p = 0.052) that was significantly mediated by central and non-central mean edge weight and every graph metric from the average network. These results are consistent with the hypothesis that intelligence deficits are associated with a genetic risk for schizophrenia, which is mediated via the disruption of distributed brain networks. Hum Brain Mapp 38:5919-5930, 2017. © 2017 Wiley Periodicals, Inc.

Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017. © 2017 Wiley Periodicals, Inc.

Whole-brain structural connectivity in dyskinetic cerebral palsy and its association with motor and cognitive function

Dyskinetic cerebral palsy (CP) has long been associated with basal ganglia and thalamus lesions. Recent evidence further points at white matter (WM) damage. This study aims to identify altered WM pathways in dyskinetic CP from a standardized, connectome-based approach, and to assess structure-function relationship in WM pathways for clinical outcomes. Individual connectome maps of 25 subjects with dyskinetic CP and 24 healthy controls were obtained combining a structural parcellation scheme with whole-brain deterministic tractography. Graph theoretical metrics and the network-based statistic were applied to compare groups and to correlate WM state with motor and cognitive performance. Results showed a widespread reduction of WM volume in CP subjects compared to controls and a more localized decrease in degree (number of links per node) and fractional anisotropy (FA), comprising parieto-occipital regions and the hippocampus. However, supramarginal gyrus showed a significantly higher degree. At the network level, CP subjects showed a bilateral pathway with reduced FA, comprising sensorimotor, intraparietal and fronto-parietal connections. Gross and fine motor functions correlated with FA in a pathway comprising the sensorimotor system, but gross motor also correlated with prefrontal, temporal and occipital connections. Intelligence correlated with FA in a network with fronto-striatal and parieto-frontal connections, and visuoperception was related to right occipital connections. These findings demonstrate a disruption in structural brain connectivity in dyskinetic CP, revealing general involvement of posterior brain regions with relative preservation of prefrontal areas. We identified pathways in which WM integrity is related to clinical features, including but not limited to the sensorimotor system. Hum Brain Mapp 38:4594-4612, 2017. © 2017 Wiley Periodicals, Inc.

Aberrant interhemispheric homotopic functional and structural connectivity in amyotrophic lateral sclerosis

OBJECTIVE

Amyotrophic lateral sclerosis (ALS) is an idiopathic and fatal neurodegenerative disease of the human motor system. While microstructural alterations in corpus callosum (CC) have been identified as a consistent feature of ALS, studies directly examining interhemispheric neural connectivity are still lacking. To shed more light on the pathophysiology of ALS, the present study aims to examine alterations of interhemispheric structural and functional connectivity in individuals with ALS.

METHODS

Diffusion tensor imaging (DTI) and resting-state functional MRI (rfMRI) data were acquired from 38 individuals with ALS and 35 gender-matched and age-matched control subjects. Indices of interhemispheric functional and structural neural connection were derived with analyses of voxel mirrored homotopic connectivity (VMHC) and probabilistic fibre tracking.

RESULTS

The rfMRI has revealed extensive reductions of VMHC associated with ALS in brain regions of the precentral and postcentral gyrus, the paracentral lobule, the superior temporal gyrus, the middle cingulate gyrus, the putamen and the superior parietal lobules. With DTI, the analysis has also revealed reductions of interhemispheric structural connectivity through the CC subregions II, III and V in patients with ALS. Additionally, interhemispheric functional connectivity of the bilateral precentral gyri positively correlated with fractional anisotropy values of the CC subregion III, which structurally connects the bilateral motor cortices.

CONCLUSIONS

The present data provided direct evidence confirming and extending the view of impaired interhemispheric neural communications mediated by CC, providing a new perspective for examinations and understanding the pathophysiology of ALS.

Enhanced structural connectivity within a brain sub-network supporting working memory and engagement processes after cognitive training

The structural connectome provides relevant information about experience and training-related changes in the brain. Here, we used network-based statistics (NBS) and graph theoretical analyses to study structural changes in the brain as a function of cognitive training. Fifty-six young women were divided in two groups (experimental and control). We assessed their cognitive function before and after completing a working memory intervention using a comprehensive battery that included fluid and crystallized abilities, working memory and attention control, and we also obtained structural MRI images. We acquired and analyzed diffusion-weighted images to reconstruct the anatomical connectome and we computed standardized changes in connectivity as well as group differences across time using NBS. We also compared group differences relying on a variety of graph-theory indices (clustering, characteristic path length, global and local efficiency and strength) for the whole network as well as for the sub-network derived from NBS analyses. Finally, we calculated correlations between these graph indices and training performance as well as the behavioral changes in cognitive function. Our results revealed enhanced connectivity for the training group within one specific network comprised of nodes/regions supporting cognitive processes required by the training (working memory, interference resolution, inhibition, and task engagement). Significant group differences were also observed for strength and global efficiency indices in the sub-network detected by NBS. Therefore, the connectome approach is a valuable method for tracking the effects of cognitive training interventions across specific sub-networks. Moreover, this approach allowsfor the computation of graph theoretical network metricstoquantifythetopological architecture of the brain networkdetected. The observed structural brain changes support the behavioral results reported earlier (see Colom, Román, et al., 2013).

Whole-Brain High-Resolution Structural Connectome: Inter-Subject Validation and Application to the Anatomical Segmentation of the Striatum

The present study describes extraction of high-resolution structural connectome (HRSC) in 99 healthy subjects, acquired and made available by the Human Connectome Project. Single subject connectomes were then registered to the common surface space to allow assessment of inter-individual reproducibility of this novel technique using a leave-one-out approach. The anatomic relevance of the surface-based connectome was examined via a clustering algorithm, which identified anatomic subdivisions within the striatum. The connectivity of these striatal subdivisions were then mapped on the cortical and other subcortical surfaces. Findings demonstrate that HRSC analysis is robust across individuals and accurately models the actual underlying brain networks related to the striatum. This suggests that this method has the potential to model and characterize the healthy whole-brain structural network at high anatomic resolution.

Widespread temporo-occipital lobe dysfunction in amyotrophic lateral sclerosis

Recent studies suggest that amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) lie on a single clinical continuum. However, previous neuroimaging studies have found only limited involvement of temporal lobe regions in ALS. To better delineate possible temporal lobe involvement in ALS, the present study aimed to examine changes in functional connectivity across the whole brain, particularly with regard to extra-motor regions, in a group of 64 non-demented ALS patients and 38 healthy controls. To assess between-group differences in connectivity, we computed edge-level statistics across subject-specific graphs derived from resting-state functional MRI data. In addition to expected ALS-related decreases in functional connectivity in motor-related areas, we observed extensive changes in connectivity across the temporo-occipital cortex. Although ALS patients with comorbid FTD were deliberately excluded from this study, the pattern of connectivity alterations closely resembles patterns of cerebral degeneration typically seen in FTD. This evidence for subclinical temporal dysfunction supports the idea of a common pathology in ALS and FTD.