Investigation of white matter pathology in ALS and PLS using tract-based spatial statistics

Microstructural Changes in the Corpus Callosum in Neurodegenerative Diseases

The corpus callosum, the largest white matter structure in the brain, plays a crucial role in interhemispheric communication and cognitive function. This review examines the microstructural changes observed in the corpus callosum across various neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis (ALS). New neuroimaging studies, mainly those that use diffusion tensor imaging (DTI) and advanced tractography methods, were put together to show how changes have happened in the organization of white matter and the connections between them. Some of the most common ways the corpus callosum breaks down are discussed, including less fractional anisotropy, higher mean diffusivity, and atrophy in certain regions. The relationship between these microstructural changes and cognitive decline, motor dysfunction, and disease progression is explored. Additionally, we consider the potential of corpus callosum imaging as a biomarker for early disease detection and monitoring. Studies show that people with these disorders have lower fractional anisotropy and higher mean diffusivity in the corpus callosum, often in ways that are specific to the disease. These changes often happen before gray matter atrophy and are linked to symptoms, which suggests that the corpus callosum could be used as an early sign of neurodegeneration. The review also highlights the implications of these findings for understanding disease mechanisms and developing therapeutic strategies. Future directions, including the application of advanced imaging techniques and longitudinal studies, are discussed to elucidate the role of corpus callosum degeneration in neurodegenerative processes. This review underscores the importance of the corpus callosum in understanding the pathophysiology of neurodegenerative diseases and its potential as a target for therapeutic interventions.

Primary lateral sclerosis: application and validation of the 2020 consensus diagnostic criteria in an expert opinion-based PLS cohort

BACKGROUND

Validation of the 2020 consensus criteria for primary lateral sclerosis (PLS) is essential for their use in clinical practice and future trials.

METHODS

In a large cohort of patients diagnosed with PLS by expert opinion prior to the new criteria with detailed clinical baseline evaluation (n=107) and longitudinal follow-up (n=63), we applied the new diagnostic criteria and analysed the clinical phenotype, electromyography (EMG), diagnostic accuracy and prognosis, adding neurofilaments and MRI as potential biomarkers.

RESULTS

The criteria for definite PLS were met by 28% and those for probable PLS by 19%, whereas 53% did not meet the full criteria at baseline, mainly due to the time, EMG and region criteria. Patients not meeting the criteria had less generalised upper motor neuron involvement but were otherwise similar in demographic and clinical characteristics. All patients with definite and probable PLS maintained PLS diagnosis during follow-up, while four patients not meeting the criteria developed clinical lower motor neuron involvement. Definite PLS cases showed improved survival compared with probable PLS and patients who did not meet the criteria. Despite a clinical PLS phenotype, fibrillation potentials/positive sharp waves and fasciculations in one or more muscles were a frequent EMG finding, with the extent and prognostic significance depending on disease duration. Serum neurofilament light and a multiparametric MRI fibre integrity Z-score correlated with clinical parameters and were identified as potential biomarkers.

CONCLUSION

Validation of the 2020 PLS consensus criteria revealed high diagnostic certainty and prognostic significance, supporting their value for research and clinical practice.

High angular diffusion tensor imaging estimation from minimal evenly distributed diffusion gradient directions

Diffusion-weighted Imaging (DWI) is a non-invasive imaging technique based on Magnetic Resonance Imaging (MRI) principles to measure water diffusivity and reveal details of the underlying brain micro-structure. By fitting a tensor model to quantify the directionality of water diffusion a Diffusion Tensor Image (DTI) can be derived and scalar measures, such as fractional anisotropy (FA), can then be estimated from the DTI to summarise quantitative microstructural information for clinical studies. In particular, FA has been shown to be a useful research metric to identify tissue abnormalities in neurological disease (e.g. decreased anisotropy as a proxy for tissue damage). However, time constraints in clinical practice lead to low angular resolution diffusion imaging (LARDI) acquisitions that can cause inaccurate FA value estimates when compared to those generated from high angular resolution diffusion imaging (HARDI) acquisitions. In this work, we propose High Angular DTI Estimation Network (HADTI-Net) to estimate an enhanced DTI model from LARDI with a set of minimal and evenly distributed diffusion gradient directions. Extensive experiments have been conducted to show the reliability and generalisation of HADTI-Net to generate high angular DTI estimation from any minimal evenly distributed diffusion gradient directions and to explore the feasibility of applying a data-driven method for this task. The code repository of this work and other related works can be found at https://mri-synthesis.github.io/.

Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis

BACKGROUND

Recent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord.

METHODS

We acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section.

RESULTS

We demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics.

CONCLUSIONS

Our findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.

Spinal cord motor disorders

Spinal cord diseases are frequently devastating due to the precipitous and often permanently debilitating nature of the deficits. Spastic or flaccid paraparesis accompanied by dermatomal and myotomal signatures complementary to the incurred deficits facilitates localization of the insult within the cord. However, laboratory studies often employing disease-specific serology, neuroradiology, neurophysiology, and cerebrospinal fluid analysis aid in the etiologic diagnosis. While many spinal cord diseases are reversible and treatable, especially when recognized early, more than ever, neuroscientists are being called to investigate endogenous mechanisms of neural plasticity. This chapter is a review of the embryology, neuroanatomy, clinical localization, evaluation, and management of adult and childhood spinal cord motor disorders.

Analysis of brain and spinal MRI measures in a common domain to investigate directional neurodegeneration in motor neuron disease

BACKGROUND

Magnetic resonance imaging (MRI) of the brain and cervical spinal cord is often performed in diagnostic evaluation of suspected motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). Analysis of MRI-derived tissue damage metrics in a common domain facilitates group-level inferences on pathophysiology. This approach was applied to address competing hypotheses of directionality of neurodegeneration, whether anterograde, cranio-caudal dying-forward from precentral gyrus or retrograde, dying-back.

METHODS

In this cross-sectional study, MRI was performed on 75 MND patients and 13 healthy controls. Precentral gyral thickness was estimated from volumetric T1-weighted images using FreeSurfer, corticospinal tract fractional anisotropy (FA) from diffusion tensor imaging using FSL, and cross-sectional cervical cord area between C1-C8 levels using Spinal Cord Toolbox. To analyse these multimodal data within a common domain, individual parameter estimates representing tissue damage at each corticospinal tract level were first converted to z-scores, referenced to healthy control norms. Mixed-effects linear regression models were then fitted to these z-scores, with gradients hypothesised to represent directionality of neurodegeneration.

RESULTS

At group-level, z-scores did not differ significantly between precentral gyral and intracranial corticospinal tract tissue damage estimates (regression coefficient - 0.24, [95% CI - 0.62, 0.14], p = 0.222), but step-changes were evident between intracranial corticospinal tract and C1 (1.14, [95% CI 0.74, 1.53], p < 0.001), and between C5 and C6 cord levels (0.98, [95% CI 0.58, 1.38], p < 0.001).

DISCUSSION

Analysis of brain and cervical spinal MRI data in a common domain enabled investigation of pathophysiological hypotheses in vivo. A cranio-caudal step-change in MND patients was observed, and requires further investigation in larger cohorts.

Simultaneous PET/MRI: The future gold standard for characterizing motor neuron disease-A clinico-radiological and neuroscientific perspective

Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives.

Medulla oblongata volume as a promising predictor of survival in amyotrophic lateral sclerosis

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Brainstem volumes reflect the disease severity expressed as ALSFRS-r (total score and its bulbar and spinal subscores).

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Medulla oblongata volume demonstrated a significant accuracy to discriminate long and short survivors ALS patients.

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Brainstem volumes may reflect the impairment of corticospinal and corticobulbar tracts as well as lower bulbar motor neurons. Furthermore, medulla oblongata could be used as an early predictor of survival in ALS patients.

Background

Unconventional magnetic resonance imaging studies of the brainstem have recently acquired a growing interest in amyotrophic lateral sclerosis (ALS) pathology since they provide a unique opportunity to evaluate motor tract degeneration and bulbar lower motor neuron involvement. The aim of this study was to investigate the role of brainstem structures as accurate biomarkers of disease severity and predictors of survival.

Materials and Methods

A total of 60 ALS patients and 30 healthy controls subjects (CS) were recruited in this study. Patients were divided in two subgroups according to the onset of the disease: 42 spinal (S-ALS) and 18 bulbar (B-ALS). All subjects underwent 3D-structural MRI. Brainstem volume both of the entire cohort of ALS patients and S-ALS and B-ALS onset were compared with those of CS. In addition the two ALS subgroups were tested for differences in brainstem volumes.

Volumetric, vertex-wise, and voxel-based approaches were implemented to assess correlations between MR structural features and clinical characteristics expressed as ALSFRS-r and its bulbar (ALSFSR-r-B) and spinal subscores (ALSFSR-r-S). ROC curves were performed to test the accuracy of midbrain, pons, and medulla oblongata volumes able to discriminate patients dichotomized into long and short survivors by using Two-Steps cluster analysis. Univariate and multivariate survival analyses were carried out to test the prognostic role of brainstem structures’ volume, trichotomized by applying a k-means clustering algorithm.

Results

Both the entire cohort of ALS patients and B-ALS and S-ALS showed significant lower volumes of both medulla oblongata and pons compared to CS. Furthermore, B-ALS showed a significant lower volume of medulla oblongata, compared to S-ALS. Lower score of ALSFRS-r correlated to atrophy in the anterior compartment of midbrain, pons, and medulla oblongata, as well as in the posterior portion of only this latter region. ALSFSR-r-S positively correlated with shape deformation and density reduction of the anterior portion of the entire brainstem, along the corticospinal tracts. ALSFSR-r-B instead showed a positive correlation with shape deformation of the floor of the fourth ventricle in the medulla oblongata and the crus cerebri in the midbrain. Only medulla oblongata volume demonstrated a significant accuracy to discriminate long and short survivors ALS patients (ROC AUC 0.76, p < 0.001). Univariate and multivariate analysis confirmed the survival predictive role of the medulla oblongata (log rank test p: 0.003).

Discussions

Our findings suggest that brainstem volume may reflect the impairment of corticospinal and corticobulbar tracts as well as lower bulbar motor neurons. Furthermore, medulla oblongata could be used as an early predictor of survival in ALS patients.

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.

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 Pathology in Motor Neuron Disease Phenotypes: Insights From Neuroimaging

Frontotemporal involvement has been extensively investigated in amyotrophic lateral sclerosis (ALS) but remains relatively poorly characterized in other motor neuron disease (MND) phenotypes such as primary lateral sclerosis (PLS), progressive muscular atrophy (PMA), spinal muscular atrophy (SMA), spinal bulbar muscular atrophy (SBMA), post poliomyelitis syndrome (PPS), and hereditary spastic paraplegia (HSP). This review focuses on insights from structural, metabolic, and functional neuroimaging studies that have advanced our understanding of extra-motor disease burden in these phenotypes. The imaging literature is limited in the majority of these conditions and frontotemporal involvement has been primarily evaluated by neuropsychology and post mortem studies. Existing imaging studies reveal that frontotemporal degeneration can be readily detected in ALS and PLS, varying degree of frontotemporal pathology may be captured in PMA, SBMA, and HSP, SMA exhibits cerebral involvement without regional predilection, and there is limited evidence for cerebral changes in PPS. Our review confirms the heterogeneity extra-motor pathology across the spectrum of MNDs and highlights the role of neuroimaging in characterizing anatomical patterns of disease burden in vivo. Despite the contribution of neuroimaging to MND research, sample size limitations, inclusion bias, attrition rates in longitudinal studies, and methodological constraints need to be carefully considered. Frontotemporal involvement is a quintessential clinical facet of MND which has important implications for screening practices, individualized management strategies, participation in clinical trials, caregiver burden, and resource allocation. The academic relevance of imaging frontotemporal pathology in MND spans from the identification of genetic variants, through the ascertainment of presymptomatic changes to the design of future epidemiology studies.

Primary Lateral Sclerosis: Clinical, radiological and molecular features

Primary Lateral Sclerosis (PLS) is an uncommon motor neuron disorder. Despite the well-recognisable constellation of clinical manifestations, the initial diagnosis can be challenging and therapeutic options are currently limited. There have been no recent clinical trials of disease-modifying therapies dedicated to this patient cohort and awareness of recent research developments is limited. The recent consensus diagnostic criteria introduced the category 'probable' PLS which is likely to curtail the diagnostic journey of patients. Extra-motor clinical manifestations are increasingly recognised, challenging the view of PLS as a 'pure' upper motor neuron condition. The post mortem literature of PLS has been expanded by seminal TDP-43 reports and recent PLS studies increasingly avail of meticulous genetic profiling. Research in PLS has gained unprecedented momentum in recent years generating novel academic insights, which may have important clinical ramifications.

Multidimensional analysis and detection of informative features in human brain white matter

The white matter contains long-range connections between different brain regions and the organization of these connections holds important implications for brain function in health and disease. Tractometry uses diffusion-weighted magnetic resonance imaging (dMRI) to quantify tissue properties along the trajectories of these connections. Statistical inference from tractometry usually either averages these quantities along the length of each fiber bundle or computes regression models separately for each point along every one of the bundles. These approaches are limited in their sensitivity, in the former case, or in their statistical power, in the latter. We developed a method based on the sparse group lasso (SGL) that takes into account tissue properties along all of the bundles and selects informative features by enforcing both global and bundle-level sparsity. We demonstrate the performance of the method in two settings: i) in a classification setting, patients with amyotrophic lateral sclerosis (ALS) are accurately distinguished from matched controls. Furthermore, SGL identifies the corticospinal tract as important for this classification, correctly finding the parts of the white matter known to be affected by the disease. ii) In a regression setting, SGL accurately predicts "brain age." In this case, the weights are distributed throughout the white matter indicating that many different regions of the white matter change over the lifespan. Thus, SGL leverages the multivariate relationships between diffusion properties in multiple bundles to make accurate phenotypic predictions while simultaneously discovering the most relevant features of the white matter.

Neuroimaging in primary lateral sclerosis

Increased interest in the underlying pathogenesis of primary lateral sclerosis (PLS) and its relationship to amyotrophic lateral sclerosis (ALS) has corresponded to a growing number of CNS imaging studies, especially in the past decade. Both its rarity and uncertainty of definite diagnosis prior to 4 years from symptom onset have resulted in PLS being less studied than ALS. In this review, we highlight most relevant papers applying magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET) to analyzing CNS changes in PLS, often in relation to ALS. In patients with PLS, mostly brain, but also spinal cord has been evaluated since significant neurodegeneration is essentially restricted to upper motor neuron (UMN) structures and related pathways. Abnormalities of cortex and subcortical white matter tracts have been identified by structural and functional MRI and MRS studies, while metabolic and cell-specific changes in PLS brain have been revealed using various PET radiotracers. Future neuroimaging studies will continue to explore the interface between the PLS-ALS continuum, identify more changes unique to PLS, apply novel MRI and MRS sequences showing greater structural and neurochemical detail, as well as expand the repertoire of PET radiotracers that reveal various cellular pathologies. Neuroimaging has the potential to play an important role in the evaluation of novel therapies for patients with PLS.

Evolution of white matter damage in amyotrophic lateral sclerosis

OBJECTIVE

To characterize disease evolution in amyotrophic lateral sclerosis using an event-based model designed to extract temporal information from cross-sectional data. Conventional methods for understanding mechanisms of rapidly progressive neurodegenerative disorders are limited by the subjectivity inherent in the selection of a limited range of measurements, and the need to acquire longitudinal data.

METHODS

The event-based model characterizes a disease as a series of events, each comprising a significant change in subject state. The model was applied to data from 154 patients and 128 healthy controls selected from five independent diffusion MRI datasets acquired in four different imaging laboratories between 1999 and 2016. The biomarkers modeled were mean fractional anisotropy values of white matter tracts implicated in amyotrophic lateral sclerosis. The cerebral portion of the corticospinal tract was divided into three segments.

RESULTS

Application of the model to the pooled datasets revealed that the corticospinal tracts were involved before other white matter tracts. Distal corticospinal tract segments were involved earlier than more proximal (i.e., cephalad) segments. In addition, the model revealed early ordering of fractional anisotropy change in the corpus callosum and subsequently in long association fibers.

INTERPRETATION

These findings represent data-driven evidence for early involvement of the corticospinal tracts and body of the corpus callosum in keeping with conventional approaches to image analysis, while providing new evidence to inform directional degeneration of the corticospinal tracts. This data-driven model provides new insight into the dynamics of neuronal damage in amyotrophic lateral sclerosis.

Primary lateral sclerosis: consensus diagnostic criteria

Primary lateral sclerosis (PLS) is a neurodegenerative disorder of the adult motor system. Characterised by a slowly progressive upper motor neuron syndrome, the diagnosis is clinical, after exclusion of structural, neurodegenerative and metabolic mimics. Differentiation of PLS from upper motor neuron-predominant forms of amyotrophic lateral sclerosis remains a significant challenge in the early symptomatic phase of both disorders, with ongoing debate as to whether they form a clinical and histopathological continuum. Current diagnostic criteria for PLS may be a barrier to therapeutic development, requiring long delays between symptom onset and formal diagnosis. While new technologies sensitive to both upper and lower motor neuron involvement may ultimately resolve controversies in the diagnosis of PLS, we present updated consensus diagnostic criteria with the aim of reducing diagnostic delay, optimising therapeutic trial design and catalysing the development of disease-modifying therapy.

Speech network regional involvement in bulbar ALS: a multimodal structural MRI study

Objective: To examine gray (GM) and white matter (WM) structural changes in regions of the speech network (SpN) in ALS patients with varying degree of bulbar disease. Methods: T1 and DTI images were obtained for 19 ALS participants and 13 neurologically-intact controls. Surface-based, volumetric, and DTI metrics were obtained for 6 regions-of-interest (ROIs) including the primary motor cortex (PMC), pars triangularis (parsT), pars opercularis (ParsO), posterior superior temporal gyrus (pSTG), and transverse temporal (TT). Disease-effects and brain-behavioral correlates between neuroanatomy and clinical measures of bulbar, limb, and overall disability were examined using linear models. Results: Structural changes were observed in the right oral and limb PMC and left ParsT, TT, and pSTG in ALS. Bulbar motor dysfunction was associated with WM abnormalities in the right oral PMC and left pSTG, and GM changes in bilateral TT. In contrast, symptom progression rate predicted GM and WM changes in bilateral pars opercularis (part of Broca's area). Grip strength and disease duration models were non-significant. Conclusions: The findings suggested that regions of the left-dominant SpN may be implicated in ALS and degeneration of these areas are related to bulbar disease severity. Involvement of regions that overlap across multiple connectomes such as Broca's area, however, may be dependent on the rate of disease progression. The work contributes to our understanding of bulbar ALS subtype, which is crucial for predicting disease progression, delivering targeted clinical care, and appropriate recruitment into clinical trials.

Biomarkers in Motor Neuron Disease: A State of the Art Review

Motor neuron disease can be viewed as an umbrella term describing a heterogeneous group of conditions, all of which are relentlessly progressive and ultimately fatal. The average life expectancy is 2 years, but with a broad range of months to decades. Biomarker research deepens disease understanding through exploration of pathophysiological mechanisms which, in turn, highlights targets for novel therapies. It also allows differentiation of the disease population into sub-groups, which serves two general purposes: (a) provides clinicians with information to better guide their patients in terms of disease progression, and (b) guides clinical trial design so that an intervention may be shown to be effective if population variation is controlled for. Biomarkers also have the potential to provide monitoring during clinical trials to ensure target engagement. This review highlights biomarkers that have emerged from the fields of systemic measurements including biochemistry (blood, cerebrospinal fluid, and urine analysis); imaging and electrophysiology, and gives examples of how a combinatorial approach may yield the best results. We emphasize the importance of systematic sample collection and analysis, and the need to correlate biomarker findings with detailed phenotype and genotype data.

Gray matter and white matter changes in non-demented amyotrophic lateral sclerosis patients with or without cognitive impairment: A combined voxel-based morphometry and tract-based spatial statistics whole-brain analysis

The phenotypic heterogeneity in amyotrophic lateral sclerosis (ALS) implies that patients show structural changes within but also beyond the motor cortex and corticospinal tract and furthermore outside the frontal lobes, even if frank dementia is not detected. The aim of the present study was to investigate both gray matter (GM) and white matter (WM) changes in non-demented amyotrophic lateral sclerosis (ALS) patients with or without cognitive impairment (ALS-motor and ALS-plus, respectively). Nineteen ALS-motor, 31 ALS-plus and 25 healthy controls (HC) underwent 3D-T1-weighted and 30-directional diffusion-weighted imaging on a 3 T MRI scanner. Voxel-based morphometry and tract-based spatial-statistics analysis were performed to examine GM volume (GMV) changes and WM differences in fractional anisotropy (FA), axial and radial diffusivity (AD, RD, respectively). Compared to HC, ALS-motor patients showed decreased GMV in frontal and cerebellar areas and increased GMV in right supplementary motor area, while ALS-plus patients showed diffuse GMV reduction in primary motor cortex bilaterally, frontotemporal areas, cerebellum and basal ganglia. ALS-motor patients had increased GMV in left precuneus compared to ALS-plus patients. We also found decreased FA and increased RD in the corticospinal tract bilaterally, the corpus callosum and extra-motor tracts in ALS-motor patients, and decreased FA and increased AD and RD in motor and several WM tracts in ALS-plus patients, compared to HC. Multimodal neuroimaging confirms motor and extra-motor GM and WM abnormalities in non-demented cognitively-impaired ALS patients (ALS-plus) and identifies early extra-motor brain pathology in ALS patients without cognitive impairment (ALS-motor).

Primary lateral sclerosis: a distinct entity or part of the ALS spectrum?

Primary lateral sclerosis (PLS) has been traditionally viewed as a distinct upper motor neuron condition (UMN) but is increasingly regarded as a sub-phenotype within the amyotrophic lateral sclerosis (ALS) spectrum. Despite established diagnostic criteria, formal diagnosis can be challenging and the protracted diagnostic journey and uncertainty about longer-term prognosis cause considerable distress to patients and caregivers. PLS patients are invariably excluded from ALS clinical trials, while PLS pharmacological trials are lacking. There remains an unmet need for diagnostic biomarkers for upper motor neuron predominant conditions and prognostic indicators regarding prognosis, survival, and risk of conversion to ALS. Validated biomarkers will not only have implications for individualized patient care but also serve as outcome measures in pharmaceutical trials. Given the paucity of post-mortem studies in PLS, novel pathological insights are generally inferred from state-of-the-art imaging studies. Computational neuroimaging has already contributed significantly to the characterization of PLS-associated pathology in vivo and has underscored the role of neuro-inflammation, the presence of extra-motor changes, and confirmed pathological patterns similar to ALS. This systematic review assesses the current state of PLS research across clinical, neuroimaging and neuropathological domains from a combined clinical and academic perspective. We discuss patterns of pathological overlap with other ALS phenotypes, examine if the biological processes of PLS warrant therapeutic strategies distinct from ALS, and evaluate the evidence that classes PLS as a distinct clinico-pathological entity.

Clinical and Radiological Markers of Extra-Motor Deficits in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is now universally recognized as a complex multisystem disorder with considerable extra-motor involvement. The neuropsychological manifestations of frontotemporal, parietal, and basal ganglia involvement in ALS have important implications for compliance with assistive devices, survival, participation in clinical trials, caregiver burden, and the management of individual care needs. Recent advances in neuroimaging have been instrumental in characterizing the biological substrate of heterogeneous cognitive and behavioral deficits in ALS. In this review we discuss the clinical and radiological aspects of cognitive and behavioral impairment in ALS focusing on the recognition, assessment, and monitoring of these symptoms.

Corticospinal tract degeneration in ALS unmasked in T1-weighted images using texture analysis

The purpose of this study was to investigate whether textures computed from T1-weighted (T1W) images of the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS) are associated with degenerative changes evaluated by diffusion tensor imaging (DTI). Nineteen patients with ALS and 14 controls were prospectively recruited and underwent T1W and diffusion-weighted magnetic resonance imaging. Three-dimensional texture maps were computed from T1W images and correlated with the DTI metrics within the CST. Significantly correlated textures were selected and compared within the CST for group differences between patients and controls using voxel-wise analysis. Textures were correlated with the patients' clinical upper motor neuron (UMN) signs and their diagnostic accuracy was evaluated. Voxel-wise analysis of textures and their diagnostic performance were then assessed in an independent cohort with 26 patients and 13 controls. Results showed that textures autocorrelation, energy, and inverse difference normalized significantly correlated with DTI metrics (p < .05) and these textures were selected for further analyses. The textures demonstrated significant voxel-wise differences between patients and controls in the centrum semiovale and the posterior limb of the internal capsule bilaterally (p < .05). Autocorrelation and energy significantly correlated with UMN burden in patients (p < .05) and classified patients and controls with 97% accuracy (100% sensitivity, 92.9% specificity). In the independent cohort, the selected textures demonstrated similar regional differences between patients and controls and classified participants with 94.9% accuracy. These results provide evidence that T1-based textures are associated with degenerative changes in the CST.

Imaging Biomarkers for the Diagnosis and Prognosis of Neurodegenerative Diseases. The Example of Amyotrophic Lateral Sclerosis

The term amyotrophic lateral sclerosis (ALS) comprises a heterogeneous group of fatal neurodegenerative disorders of largely unknown etiology characterized by the upper motor neurons (UMN) and/or lower motor neurons (LMN) degeneration. The development of brain imaging biomarkers is essential to advance in the diagnosis, stratification and monitoring of ALS, both in the clinical practice and clinical trials. In this review, the characteristics of an optimal imaging biomarker and common pitfalls in biomarkers evaluation will be discussed. Moreover, the development and application of the most promising brain magnetic resonance (MR) imaging biomarkers will be reviewed. Finally, the integration of both qualitative and quantitative multimodal brain MR biomarkers in a structured report will be proposed as a support tool for ALS diagnosis and stratification.

Traumatic Brain Injury Results in Cellular, Structural and Functional Changes Resembling Motor Neuron Disease

Traumatic brain injury (TBI) has been suggested to increase the risk of amyotrophic lateral sclerosis (ALS). However, this link remains controversial and as such, here we performed experimental moderate TBI in rats and assessed for the presence of ALS-like pathological and functional abnormalities at both 1 and 12 weeks post-injury. Serial in-vivo magnetic resonance imaging (MRI) demonstrated that rats given a TBI had progressive atrophy of the motor cortices and degeneration of the corticospinal tracts compared with sham-injured rats. Immunofluorescence analyses revealed a progressive reduction in neurons, as well as increased phosphorylated transactive response DNA-binding protein 43 (TDP-43) and cytoplasmic TDP-43, in the motor cortex of rats given a TBI. Rats given a TBI also had fewer spinal cord motor neurons, increased expression of muscle atrophy markers, and altered muscle fiber contractile properties compared with sham-injured rats at 12 weeks, but not 1 week, post-injury. All of these changes occurred in the presence of persisting motor deficits. These findings resemble some of the pathological and functional abnormalities common in ALS and support the notion that TBI can result in a progressive neurodegenerative disease process pathologically bearing similarities to a motor neuron disease.

Radial diffusivity as an imaging biomarker for early diagnosis of non-demented amyotrophic lateral sclerosis

OBJECTIVES

To explore the sensitivity of potential DTI-based biomarkers in detecting microstructural changes for whole-brain white matter in early stage amyotrophic lateral sclerosis (ALS), analyze the relationship between the DTI indices and disease status, and further clarify potential brain regions for disease monitoring and clinical assessment.

METHODS

Thirty-three non-demented ALS patients and 32 age- and gender-matched subjects participated in this study. DTI data were acquired via 3.0T MRI scanner. Maps of diffusion-related indices including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were obtained. Tract-based spatial statistics (TBSS) were used to investigate whole-brain white matter changes of each index. Correlation analyses between both brain-wide and volume-of-interest (VOI)-wide white matter alterations and clinical factors including ALSFRS-R scores, disease duration, and progression rate were performed.

RESULTS

Compared to healthy subjects, ALS patients showed significantly increased RD, MD and reduced FA, mainly along the corticospinal tract (CST) and the body of corpus callosum (CC). Increases in RD were broader than decreases in FA, in CST of both hemispheres. Meanwhile, involvement of several extra-motor regions was also revealed by RD. Significant positive correlation between ALSFRS-R scores and FA, negative correlation between ALSFRS-R and RD were found in left CST.

CONCLUSIONS

RD may be the most sensitive biomarker for the detection of early demyelination of white matter. Both RD and FA may serve as objective biomarkers for disease severity assessment. CST may be the most affected brain region in non-demented ALS.

KEY POINTS

• Changes in RD were broader than those in FA in bilateral CST. • Involvement of extra-motor regions was uncovered by RD. • FA and RD in CST were related to ALSFRS-R scores.

Shared facial emotion processing functional network findings in medication-naïve major depressive disorder and healthy individuals: detection by sICA

BACKGROUND

The fundamental mechanism underlying emotional processing in major depressive disorder (MDD) remains unclear. To better understand the neural correlates of emotional processing in MDD, we investigated the role of multiple functional networks (FNs) during emotional stimuli processing.

METHODS

Thirty-two medication-naïve subjects with MDD and 36 healthy controls (HCs) underwent an emotional faces fMRI task that included neutral, happy and fearful expressions. Spatial independent component analysis (sICA) and general linear model (GLM) were conducted to examine the main effect of task condition and group, and two-way interactions of group and task conditions.

RESULTS

In sICA analysis, MDD patients and HCs together showed significant differences in task-related modulations in five FNs across task conditions. One FN mainly involving the ventral medial prefrontal cortex showed lower activation during fearful relative to happy condition. Two FNs mainly involving the bilateral inferior frontal gyrus and temporal cortex, showed opposing modulation relative to the ventral medial prefrontal cortex FN, i.e., greater activation during fearful relative to happy condition. Two remaining FNs involving the fronto-parietal and occipital cortices, showed reduced activation during both fearful and happy conditions relative to the neutral condition. However, MDD and HCs did not show significant differences in expression-related modulations in any FNs in this sample.

CONCLUSIONS

SICA revealed differing functional activation patterns than typical GLM-based analyses. The sICA findings demonstrated unique FNs involved in processing happy and fearful facial expressions. Potential differences between MDD and HCs in expression-related FN modulation should be investigated further.

Diagnostic contribution of magnetic resonance imaging in an atypical presentation of motor neuron disease

Motor neuron disease (MND) is a neurodegenerative disease determining progressive and relentless motor deterioration involving both upper and lower motor neurons (UMN and LMN); several variants at onset are described. Here we describe a case of MND presenting as pure spastic monoparesis in which magnetic resonance imaging (MRI) gave a substantial contribution in confirming the diagnosis and assessing the severity of UMN involvement. An isolated pyramidal syndrome, with complete absence of LMN signs, is a rare phenotype in the context of MND (less than 4% of total cases), especially if restricted to only one limb. Several other elements made this case an unusual presentation of MND: the late age of onset (8^th decade), the subacute evolution of symptoms (raising the suspicion of an ischemic or inflammatory, rather than degenerative, etiology), the patient's past medical history (achalasia, erythema nodosum), the increase of inflammatory indices. Conventional MRI showed no focal lesions that could explain the clinical features; therefore, we used advanced MR sequences. Diffusion tensor imaging (DTI) evaluation evidenced bilateral impairment of corticospinal tract (CST) diffusion metrics, with clear right-left asymmetry, pointing to a neurodegenerative etiology, which clinically appeared less likely at that time. Magnetic resonance spectroscopy (MRS) showed a significant reduction of NAA/Cho + Cr ratio in the motor cortex (MC), further supporting the hypothesis of UMN degeneration. In conclusion, in this particular case of MND, whose nosographic framing has not been fully defined, advanced MRI techniques with DTI and MRS proved to be of great usefulness in confirming a diffuse UMN involvement, possibly at a more advanced stage than its clinical expression.

Structural MRI correlates of amyotrophic lateral sclerosis progression

PURPOSE

Amyotrophic lateral sclerosis (ALS) presents with varying degrees of brain degeneration that can extend beyond the corticospinal tract (CST). Furthermore, the clinical course and progression of ALS varies widely. Brain degeneration detected using structural MRI could reflect disease progression.

SUBJECTS AND METHODS

On study registration, 3-Tesla volumetric MRI and diffusion tensor imaging scans were obtained at baseline in 38 healthy controls and 67 patients with sporadic ALS. Patients had Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) scores of ≥36 and did not have the chromosome 9, open reading frame 72 repeat expansion. Six months later, changes in ALSFRS-R (ΔALSFRS-R) scores were calculated and patients were grouped into three categories, namely, patients with slow progression with ΔALSFRS-R scores ≤3 (n=19), intermediate progression with ΔALSFRS-R scores =4, 5 and 6 (n=36) and rapid progression with ΔALSFRS-R scores ≥7 (n=12). We analysed voxel-based morphometry and tract-based spatial statistics among these subgroups and controls.

RESULTS

In comparison with controls, patients with ALS showed grey matter atrophy and decreased fractional anisotropy beyond the motor cortex and CST, especially in the frontotemporal lobes and basal ganglia. Moreover, the degree of change was highly proportional to ΔALSFRS-R at the 6-month assessment.

CONCLUSION

A more rapid disease progression and poorer functional decline were associated with greater involvement of the extra-motor cortex and basal ganglia, suggesting that the spatial extent of brain involvement can be an indicator of the progression in ALS.

Patterns of symptom development in patients with motor neuron disease

OBJECTIVE

To investigate whether symptom development in motor neuron disease (MND) is a random or organized process.

METHODS

Six hundred patients with amyotrophic lateral sclerosis (ALS), upper motor neuron (UMN) or lower motor neuron (LMN) phenotypes were invited for a questionnaire concerning symptom development. A binomial test was used to examine distribution of symptoms from site of onset. Development of symptoms over time was evaluated by Kaplan-Meier analysis.

RESULTS

There were 470 respondents (ALS = 254; LMN = 100; UMN = 116). Subsequent symptoms were more often in the contralateral limb following unilateral limb onset (ALS: arms p = 1.05 × 10^-8, legs p < 2.86 × 10^-15; LMN phenotype: arms p = 6.74 × 10^-9, legs p = 6.26 × 10^-6; UMN phenotype: legs p = 4.07 × 10^-14). In patients with limb onset, symptoms occurred significantly faster in the contralateral limb, followed by the other limbs and lastly by the bulbar region. Patterns of non-contiguous symptom development were also reported: leg symptoms followed bulbar onset in 30%, and bulbar symptoms followed leg onset in 11% of ALS patients.

CONCLUSIONS

Preferred spread of symptoms from one limb to the contralateral limb, and to adjacent sites appears to be a characteristic of MND phenotypes, suggesting that symptom spread is organized, possibly involving axonal connectivity. Non-contiguous symptom development, however, is not uncommon, and may involve other factors.

Quantitative FLAIR MRI in Amyotrophic Lateral Sclerosis

RATIONALE AND OBJECTIVES

T2-weighted magnetic resonance imaging (MRI) hyperintensity assessed visually in the corticospinal tract (CST) lacks sensitivity for a diagnosis of amyotrophic lateral sclerosis (ALS). We sought to explore a quantitative approach to fluid-attenuated inversion recovery (FLAIR) MRI intensity across a range of ALS phenotypes.

MATERIALS AND METHODS

Thirty-three classical ALS patients, 10 with a flail arm presentation, and six with primary lateral sclerosis underwent MRI at 3 Tesla. Comparisons of quantitative FLAIR intensity in the CST and corpus callosum were made between 21 healthy controls and within patient phenotypic subgroups, some of whom were studied longitudinally.

RESULTS

Mean FLAIR intensity was greater in patient groups. The cerebral peduncle intensity provided the strongest subgroup classification. FLAIR intensity increased longitudinally. The rate of change of FLAIR within CST correlated with rate of decline in executive function and ALS functional rating score.

CONCLUSIONS

FLAIR MRI encodes quantifiable information of potential diagnostic, stratification, and monitoring value.

Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study

Diffusion tensor imaging (DTI) allows in vivo structural brain mapping and detection of microstructural disruption of white matter (WM). One of the commonly used parameters for grading the anisotropic diffusivity in WM is fractional anisotropy (FA). FA value helps to quantify the directionality of the local tract bundle. Therefore, FA images are being used in voxelwise statistical analyses (VSA). The present study used Tract-Based Spatial Statistics (TBSS) of FA images across subjects, and computes the mean skeleton map to detect voxelwise knowledge of the tracts yielding to groupwise comparison. The skeleton image illustrates WM structure and shows any changes caused by brain damage. The microstructure of WM in thalamic stroke is investigated, and the VSA results of healthy control and thalamic stroke patients are reported. It has been shown that several skeleton regions were affected subject to the presence of thalamic stroke (FWE, p < 0.05). Furthermore the correlation of quantitative EEG (qEEG) scores and neurophysiological tests with the FA skeleton for the entire test group is also investigated. We compared measurements that are related to the same fibers across subjects, and discussed implications for VSA of WM in thalamic stroke cases, for the relationship between behavioral tests and FA skeletons, and for the correlation between the FA maps and qEEG scores.Results obtained through the regression analyses did not exceed the corrected statistical threshold values for multiple comparisons (uncorrected, p < 0.05). However, in the regression analysis of FA values and the theta band activity of EEG, cingulum bundle and corpus callosum were found to be related. These areas are parts of the Default Mode Network (DMN) where DMN is known to be involved in resting state EEG theta activity. The relation between the EEG alpha band power values and FA values of the skeleton was found to support the cortico-thalamocortical cycles for both subject groups. Further, the neurophysiological tests including Benton Face Recognition (BFR), Digit Span test (DST), Warrington Topographic Memory test (WTMT), California Verbal Learning test (CVLT) has been regressed with the FA skeleton maps for both subject groups. Our results corresponding to DST task were found to be similar with previously reported findings for working memory and episodic memory tasks. For the WTMT, FA values of the cingulum (right) that plays a role in memory process was found to be related with the behavioral responses. Splenium of corpus callosum was found to be correlated for both subject groups for the BFR.

Pathology of callosal damage in ALS: An ex-vivo, 7 T diffusion tensor MRI study

OBJECTIVES

The goal of this study was to better understand the changes in tissue microstructure that underlie white matter diffusion changes in ALS patients.

METHODS

Diffusion tensor imaging was carried out in postmortem brains of 4 ALS patients and two subjects without neurological disease on a 7 T MRI scanner using steady-state free precession sequences. Fractional anisotropy (FA) was measured in the genu, body, and splenium of the corpus callosum in formalin-fixed hemispheres. FA of the body and genu was expressed as ratio to FA of the splenium, a region unaffected in ALS. After imaging, tissue sections of the same segments of the callosum were stained for markers of different tissue components. Coded image fields were rated for pathological changes by blinded raters.

RESULTS

The FA body/FA splenium ratio was reduced in ALS patients compared to controls. Patchy areas of myelin pallor and cells immunostained for CD68, a microglial-macrophage marker, were only observed in the body of the callosum of ALS patients. Blinded ratings showed increased CD68 + microglial cells in the body of the corpus callosum in ALS patients, especially those with C9orf72 mutations, and increased reactive astrocytes throughout the callosum.

CONCLUSION

Reduced FA of the corpus callosum in ALS results from complex changes in tissue microstructure. Callosal segments with reduced FA had large numbers of microglia-macrophages in addition to loss of myelinated axons and astrogliosis. Microglial inflammation contributed to reduced FA in ALS, and may contribute to a pro-inflammatory state, but further work is needed to determine their role.

White matter structural network abnormalities underlie executive dysfunction in amyotrophic lateral sclerosis

Research in amyotrophic lateral sclerosis (ALS) suggests that executive dysfunction, a prevalent cognitive feature of the disease, is associated with abnormal structural connectivity and white matter integrity. In this exploratory study, we investigated the white matter constructs of executive dysfunction, and attempted to detect structural abnormalities specific to cognitively impaired ALS patients. Eighteen ALS patients and 22 age and education matched healthy controls underwent magnetic resonance imaging on a 4.7 Tesla scanner and completed neuropsychometric testing. ALS patients were categorized into ALS cognitively impaired (ALSci, n = 9) and ALS cognitively competent (ALScc, n = 5) groups. Tract-based spatial statistics and connectomics were used to compare white matter integrity and structural connectivity of ALSci and ALScc patients. Executive function performance was correlated with white matter FA and network metrics within the ALS group. Executive function performance in the ALS group correlated with global and local network properties, as well as FA, in regions throughout the brain, with a high predilection for the frontal lobe. ALSci patients displayed altered local connectivity and structural integrity in these same frontal regions that correlated with executive dysfunction. Our results suggest that executive dysfunction in ALS is related to frontal network disconnectivity, which potentially mediates domain-specific, or generalized cognitive impairment, depending on the degree of global network disruption. Furthermore, reported co-localization of decreased network connectivity and diminished white matter integrity suggests white matter pathology underlies this topological disruption. We conclude that executive dysfunction in ALSci is associated with frontal and global network disconnectivity, underlined by diminished white matter integrity. Hum Brain Mapp 38:1249-1268, 2017. © 2016 Wiley Periodicals, Inc.

The corticospinal tract profile in amyotrophic lateral sclerosis

This work evaluates the potential in diagnostic application of a new advanced neuroimaging method, which delineates the profile of tissue properties along the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS), by means of diffusion tensor imaging (DTI). Twenty-four ALS patients and twenty-four demographically matched healthy subjects were enrolled in this study. The Automated Fiber Quantification (AFQ), a tool for the automatic reconstruction of white matter tract profiles, based on a deterministic tractography algorithm to automatically identify the CST and quantify its diffusion properties, was used. At a group level, the highest non-overlapping DTI-related differences were detected in the cerebral peduncle, posterior limb of the internal capsule, and primary motor cortex. Fractional anisotropy (FA) decrease and mean diffusivity (MD) and radial diffusivity (RD) increases were detected when comparing ALS patients to controls. The machine learning approach used to assess the clinical utility of this DTI tool revealed that, by combining all DTI metrics measured along tract between the cerebral peduncle and the corona radiata, a mean 5-fold cross validation accuracy of 80% was reached in discriminating ALS from controls. Our study provides a useful new neuroimaging tool to characterize ALS-related neurodegenerative processes by means of CST profile. We demonstrated that specific microstructural changes in the upper part of the brainstem might be considered as a valid biomarker. With further validations this method has the potential to be considered a promising step toward the diagnostic utility of DTI measures in ALS. Hum Brain Mapp 38:727-739, 2017. © 2016 Wiley Periodicals, Inc.

Altered cortical beta-band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis

Continuous rhythmic neuronal oscillations underpin local and regional cortical communication. The impact of the motor system neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) on the neuronal oscillations subserving movement might therefore serve as a sensitive marker of disease activity. Movement preparation and execution are consistently associated with modulations to neuronal oscillation beta (15–30 Hz) power. Cortical beta‐band oscillations were measured using magnetoencephalography (MEG) during preparation for, execution, and completion of a visually cued, lateralized motor task that included movement inhibition trials. Eleven “classical” ALS patients, 9 with the primary lateral sclerosis (PLS) phenotype, and 12 asymptomatic carriers of ALS‐associated gene mutations were compared with age‐similar healthy control groups. Augmented beta desynchronization was observed in both contra‐ and ipsilateral motor cortices of ALS patients during motor preparation. Movement execution coincided with excess beta desynchronization in asymptomatic mutation carriers. Movement completion was followed by a slowed rebound of beta power in all symptomatic patients, further reflected in delayed hemispheric lateralization for beta rebound in the PLS group. This may correspond to the particular involvement of interhemispheric fibers of the corpus callosum previously demonstrated in diffusion tensor imaging studies. We conclude that the ALS spectrum is characterized by intensified cortical beta desynchronization followed by delayed rebound, concordant with a broader concept of cortical hyperexcitability, possibly through loss of inhibitory interneuronal influences. MEG may potentially detect cortical dysfunction prior to the development of overt symptoms, and thus be able to contribute to the assessment of future neuroprotective strategies. Hum Brain Mapp 38:237–254, 2017. © 2016 Wiley Periodicals, Inc.

Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). Their findings are often inconsistent across different studies, perhaps because of several fundamental brain properties including functional heterogeneity, balanced excitation and inhibition (E/I), and sparseness of neuronal activities. These properties stipulate heterogeneous neuronal activities in the same voxels and likely limit the sensitivity and specificity of GLM. This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing datasets. The extant and new findings consistently demonstrate several novel features of brain functional organization not revealed by GLM. They include overlap of large-scale functional networks (FNs) and their concurrent opposite modulations, and no significant modulations in activity of most FNs across the whole brain during any task conditions. These novel features of brain functional organization are highly consistent with the brain's properties of functional heterogeneity, balanced E/I, and sparseness of neuronal activity, and may help reconcile inconsistent GLM findings.

The value of magnetic resonance imaging as a biomarker for amyotrophic lateral sclerosis: a systematic review

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal, rapidly progressive neurodegenerative disease that mainly affects the motor system. A number of potentially neuroprotective and neurorestorative disease-modifying drugs are currently in clinical development. At present, the evaluation of a drug's clinical efficacy in ALS is based on the ALS Functional Rating Scale Revised, motor tests and survival. However, these endpoints are general, variable and late-stage measures of the ALS disease process and thus require the long-term assessment of large cohorts. Hence, there is a need for more sensitive radiological biomarkers. Various sequences for magnetic resonance imaging (MRI) of the brain and spinal cord have may have value as surrogate biomarkers for use in future clinical trials. Here, we review the MRI findings in ALS, their clinical correlations, and their limitations and potential role as biomarkers.

METHODS

The PubMed database was screened to identify studies using MRI in ALS. We included general MRI studies with a control group and an ALS group and longitudinal studies even if a control group was lacking.

RESULTS

A total of 116 studies were analysed with MRI data and clinical correlations. The most disease-sensitive MRI patterns are in motor regions but the brain is more broadly affected.

CONCLUSION

Despite the existing MRI biomarkers, there is a need for large cohorts with long term MRI and clinical follow-up. MRI assessment could be improved by standardized MRI protocols with multicentre studies.

Primary Lateral Sclerosis

Primary lateral sclerosis is characterized by insidious onset of progressive upper motor neuron dysfunction in the absence of clinical signs of lower motor neuron involvement. Patients experience stiffness; decreased balance and coordination; mild weakness; and, if the bulbar region is affected, difficulty speaking and swallowing, and emotional lability. The diagnosis is made based on clinical history, typical examination findings, and diagnostic testing negative for other causes of upper motor neuron dysfunction. Electromyogram is normal, or only shows mild neurogenic findings in a few muscles, not meeting El Escorial criteria. Treatment is largely supportive.

Uncinate fasciculus microstructure and verbal episodic memory in amyotrophic lateral sclerosis: a diffusion tensor imaging and neuropsychological study

The present study evaluates the integrity of uncinate fasciculus (UF) and the association between UF microstructure and verbal episodic memory (as one of the cognitive functions linked to UF) in non-demented patients with amyotrophic lateral sclerosis (ALS) using diffusion tensor imaging (DTI). We studied 21 patients with ALS and 11 healthy, demographically-comparable volunteers. Fractional anisotropy, apparent diffusion coefficient, axial and radial diffusivity were the DTI metrics examined. Episodic memory was evaluated with Babcock Story Recall Test and Rey Auditory Verbal Learning Test (RAVLT) for patients; measures of immediate and delayed recall and retention for both tests and sum of words recalled through five learning trials for RAVLT were considered. Patients with ALS showed significant bilateral reduction of axial diffusivity in the UF as compared to controls. Furthermore, there were several significant relations between various DTI metrics (mostly in left hemisphere) and memory measures (specifically for the RAVLT). UF microstructural changes may contribute to ALS-related memory impairment, with word-list learning performance relying more upon the integrity of frontal and temporal connections than memory components associated with story recall.

Functional network overlap as revealed by fMRI using sICA and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity

Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.

Cerebro-cerebellar connectivity is increased in primary lateral sclerosis

Increased functional connectivity in resting state networks was found in several studies of patients with motor neuron disorders, although diffusion tensor imaging studies consistently show loss of white matter integrity. To understand the relationship between structural connectivity and functional connectivity, we examined the structural connections between regions with altered functional connectivity in patients with primary lateral sclerosis (PLS), a long-lived motor neuron disease. Connectivity matrices were constructed from resting state fMRI in 16 PLS patients to identify areas of differing connectivity between patients and healthy controls. Probabilistic fiber tracking was used to examine structural connections between regions of differing connectivity. PLS patients had 12 regions with increased functional connectivity compared to controls, with a predominance of cerebro-cerebellar connections. Increased functional connectivity was strongest between the cerebellum and cortical motor areas and between the cerebellum and frontal and temporal cortex. Fiber tracking detected no difference in connections between regions with increased functional connectivity. We conclude that functional connectivity changes are not strongly based in structural connectivity. Increased functional connectivity may be caused by common inputs, or by reduced selectivity of cortical activation, which could result from loss of intracortical inhibition when cortical afferents are intact.

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Functional connectivity is increased in primary lateral sclerosis.

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Functional connections with the cerebellum were prominent.

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Cortico-cerebellar connectivity correlated with clinical measures.

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No corresponding changes occurred in structural connectivity.

Tract-based spatial statistics of the olfactory brain in patients with multiple sclerosis

PURPOSE

To investigate diffusion tensor abnormalities, e.g. fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD), in olfactory structures of multiple sclerosis (MS) patients using diffusion tensor imaging (DTI).

METHODS

Institutional review board-approved prospective study on 30 MS patients and 12 healthy controls investigated with MRI including DTI. Central olfactory structures were labelled on each patient's and healthy contro''s DTI volume. The diffusion tensor was determined in the central olfactory structures in MS patients. Tract-based spatial statistics (TBSS) was used to quantify the streamlines outgoing from the olfactory structures and to quantify changes in FA, MD, and RD within olfactory structures. These brain changes were correlated with olfactory function measured as TDI (Threshold, Discrimination, Identification) scores in patients and compared to our own reference group of 30 healthy volunteers.

RESULTS

Central olfactory structures in the MNI (Montreal Neurological Institute) data volume comprise 4808 voxels (4808 mm(3)). TFCE (Threshold-free cluster enhancement) and cluster analysis of patients identified a total of 127 voxels in one cluster with a significantly decreased FA (p<0.05) and none for MD and RD within olfactory structures compared to healthy controls. The correlation with the age-normalised Identification subscore of the TDI score increased the significant number of voxels with decreased FA to 208 voxels, with increased MD to 370 and with increased RD 364 voxels at the same region.

CONCLUSION

The decrease in FA and increase of MD and RD correlate with the degree of identification impairment of olfactory function in MS patients and clusters of abnormalities were identified on a MNI data volume.

Voxel-based MRI intensitometry reveals extent of cerebral white matter pathology in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is characterized by progressive loss of upper and lower motor neurons. Advanced MRI techniques such as diffusion tensor imaging have shown great potential in capturing a common white matter pathology. However the sensitivity is variable and diffusion tensor imaging is not yet applicable to the routine clinical environment. Voxel-based morphometry (VBM) has revealed grey matter changes in ALS, but the bias-reducing algorithms inherent to traditional VBM are not optimized for the assessment of the white matter changes. We have developed a novel approach to white matter analysis, namely voxel-based intensitometry (VBI). High resolution T1-weighted MRI was acquired at 1.5 Tesla in 30 ALS patients and 37 age-matched healthy controls. VBI analysis at the group level revealed widespread white matter intensity increases in the corticospinal tracts, corpus callosum, sub-central, frontal and occipital white matter tracts and cerebellum. VBI results correlated with disease severity (ALSFRS-R) and patterns of cerebral involvement differed between bulbar- and limb-onset. VBI would be easily translatable to the routine clinical environment, and once optimized for individual analysis offers significant biomarker potential in ALS.

Impaired corticopontocerebellar tracts underlie pseudobulbar affect in motor neuron disorders

OBJECTIVE

The objectives of the study were (1) to determine the prevalence and characteristics of pseudobulbar affect (PBA) in patients with primary lateral sclerosis (PLS) and amyotrophic lateral sclerosis (ALS) in an outpatient clinic population, and (2) to test the hypothesis that damage of inputs to the cerebellum, leading to cerebellar dysmodulation, is associated with PBA.

METHODS

Chart review of all patients with PLS and ALS seen between 2000 and 2013. The examining neurologist documented the presence or absence of PBA in 87 patients. Forty-seven patients also had diffusion tensor imaging (DTI) studies. Tract-based spatial statistics were used to compare DTI of patients with and without PBA to identify altered white matter tracts associated with PBA.

RESULTS

Thirty-one of 50 patients with PLS and 12 of 37 patients with ALS had PBA. Psychiatric/emotional assessment found congruence between mood and affect during episodes, but excessive magnitude of the response. DTI studies of 25 PLS and 22 ALS patient brains showed reduced fractional anisotropy of the corticospinal and callosal white matter tracts in all patients. Patients with PBA additionally had increased mean diffusivity of white matter tracts underlying the frontotemporal cortex, the transverse pontine fibers, and the middle cerebellar peduncle.

CONCLUSIONS

PBA is common in PLS. Imaging findings showing disruption of corticopontocerebellar pathways support the hypothesis that PBA can be viewed as a "dysmetria" of emotional expression resulting from cerebellar dysmodulation.

Diffusion tensor tractography analysis of the corpus callosum fibers in amyotrophic lateral sclerosis

BACKGROUND AND PURPOSE

Involvement of the corpus callosum (CC) is reported to be a consistent feature of amyotrophic lateral sclerosis (ALS). We examined the CC pathology using diffusion tensor tractography analysis to identify precisely which fiber bundles are involved in ALS.

METHODS

Diffusion tensor imaging was performed in 14 sporadic ALS patients and 16 age-matched healthy controls. Whole brain tractography was performed using the multiple-region of interest (ROI) approach, and CC fiber bundles were extracted in two ways based on functional and structural relevance: (i) cortical ROI selection based on Brodmann areas (BAs), and (ii) the sulcal-gyral pattern of cortical gray matter using FreeSurfer software, respectively.

RESULTS

The mean fractional anisotropy (FA) values of the CC fibers interconnecting the primary motor (BA4), supplementary motor (BA6), and dorsolateral prefrontal cortex (BA9/46) were significantly lower in ALS patients than in controls, whereas those of the primary sensory cortex (BA1, BA2, BA3), Broca's area (BA44/45), and the orbitofrontal cortex (BA11/47) did not differ significantly between the two groups. The FreeSurfer ROI approach revealed a very similar pattern of abnormalities. In addition, a significant correlation was found between the mean FA value of the CC fibers interconnecting the primary motor area and disease severity, as assessed using the revised Amyotrophic Lateral Sclerosis Functional Rating Scale, and the clinical extent of upper motor neuron signs.

CONCLUSIONS

Our findings suggest that there is some degree of selectivity or a gradient in the CC pathology in ALS. The CC fibers interconnecting the primary motor and dorsolateral prefrontal cortices may be preferentially involved in ALS.

Widespread grey matter pathology dominates the longitudinal cerebral MRI and clinical landscape of amyotrophic lateral sclerosis

Menke/Koerner et al. use structural MRI to explore the extent of longitudinal changes in cerebral pathology in amyotrophic lateral sclerosis, and their relationship to clinical features. A characteristic white matter tract pathological signature is seen cross-sectionally, while cortical involvement dominates longitudinally. This has implications for the development of biomarkers for diagnosis versus therapeutic monitoring.

Diagnosis, stratification and monitoring of disease progression in amyotrophic lateral sclerosis currently rely on clinical history and examination. The phenotypic heterogeneity of amyotrophic lateral sclerosis, including extramotor cognitive impairments is now well recognized. Candidate biomarkers have shown variable sensitivity and specificity, and studies have been mainly undertaken only cross-sectionally. Sixty patients with sporadic amyotrophic lateral sclerosis (without a family history of amyotrophic lateral sclerosis or dementia) underwent baseline multimodal magnetic resonance imaging at 3 T. Grey matter pathology was identified through analysis of T₁-weighted images using voxel-based morphometry. White matter pathology was assessed using tract-based spatial statistics analysis of indices derived from diffusion tensor imaging. Cross-sectional analyses included group comparison with a group of healthy controls (n = 36) and correlations with clinical features, including regional disability, clinical upper motor neuron signs and cognitive impairment. Patients were offered 6-monthly follow-up MRI, and the last available scan was used for a separate longitudinal analysis (n = 27). In cross-sectional study, the core signature of white matter pathology was confirmed within the corticospinal tract and callosal body, and linked strongly to clinical upper motor neuron burden, but also to limb disability subscore and progression rate. Localized grey matter abnormalities were detected in a topographically appropriate region of the left motor cortex in relation to bulbar disability, and in Broca’s area and its homologue in relation to verbal fluency. Longitudinal analysis revealed progressive and widespread changes in the grey matter, notably including the basal ganglia. In contrast there was limited white matter pathology progression, in keeping with a previously unrecognized limited change in individual clinical upper motor neuron scores, despite advancing disability. Although a consistent core white matter pathology was found cross-sectionally, grey matter pathology was dominant longitudinally, and included progression in clinically silent areas such as the basal ganglia, believed to reflect their wider cortical connectivity. Such changes were significant across a range of apparently sporadic patients rather than being a genotype-specific effect. It is also suggested that the upper motor neuron lesion in amyotrophic lateral sclerosis may be relatively constant during the established symptomatic period. These findings have implications for the development of effective diagnostic versus therapeutic monitoring magnetic resonance imaging biomarkers. Amyotrophic lateral sclerosis may be characterized initially by a predominantly white matter tract pathological signature, evolving as a widespread cortical network degeneration.