Neuroimaging Endpoints in Amyotrophic Lateral Sclerosis

Causal relationship between imaging-derived phenotypes and neurodegenerative diseases: a Mendelian randomization study

Neurodegenerative diseases are incurable conditions that lead to gradual and progressive deterioration of brain function in patients. With the aging population, the prevalence of these diseases is expected to increase, posing a significant economic burden on society. Imaging techniques play a crucial role in the diagnosis and monitoring of neurodegenerative diseases. This study utilized a two-sample Mendelian randomization (MR) analysis to assess the causal relationship between different imaging-derived phenotypes (IDP) in the brain and neurodegenerative diseases. Multiple MR methods were employed to minimize bias and obtain reliable estimates of the potential causal relationship between the variable exposures of interest and the outcomes. The study found potential causal relationships between different IDPs and Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), and frontotemporal dementia (FTD). Specifically, the study identified potential causal relationships between 2 different types of IDPs and AD, 8 different types of IDPs and PD, 11 different types of imaging-derived phenotypes and ALS, 1 type of IDP and MS, and 1 type of IDP and FTD. This study provides new insights for the prevention, diagnosis, and treatment of neurodegenerative diseases, offering important clues for understanding the pathogenesis of these diseases and developing relevant intervention strategies.

Novel approaches to assessing upper motor neuron dysfunction in motor neuron disease/amyotrophic lateral sclerosis: IFCN handbook chapter

Identifying upper motor neuron (UMN) dysfunction is fundamental to the diagnosis and understanding of disease pathogenesis in motor neuron disease (MND). The clinical assessment of UMN dysfunction may be difficult, particularly in the setting of severe muscle weakness. From a physiological perspective, transcranial magnetic stimulation (TMS) techniques provide objective biomarkers of UMN dysfunction in MND and may also be useful to interrogate cortical and network function. Single, paired- and triple pulse TMS techniques have yielded novel diagnostic and prognostic biomarkers in MND, and have provided important pathogenic insights, particularly pertaining to site of disease onset. Cortical hyperexcitability, as heralded by reduced short interval intracortical inhibition (SICI) and increased short interval intracortical facilitation, has been associated with the onset of lower motor neuron degeneration, along with patterns of disease spread, development of specific clinical features such as the split hand phenomenon, and may provide an indication about the rate of disease progression. Additionally, reduction of SICI has emerged as a potential diagnostic aid in MND. The triple stimulation technique (TST) was shown to enhance the diagnostic utility of conventional TMS measures in detecting UMN dysfunction in MND. Separately, sophisticated brain imaging techniques have uncovered novel biomarkers of neurodegeneration that have bene associated with progression. The present review will discuss the utility of TMS and brain neuroimaging derived biomarkers of UMN dysfunction in MND, focusing on recently developed TMS techniques and advanced neuroimaging modalities that interrogate structural and functional integrity of the corticomotoneuronal system, with an emphasis on pathogenic, diagnostic, and prognostic utility.

Cervical and thoracic spinal cord gray matter atrophy is associated with disability in patients with amyotrophic lateral sclerosis

BACKGROUND AND PURPOSE

In amyotrophic lateral sclerosis (ALS), there is an unmet need for more precise patient characterization through quantitative, ideally operator-independent, assessments of disease extent and severity. Radially sampled averaged magnetization inversion recovery acquisitions (rAMIRA) magnetic resonance imaging enables gray matter (GM) and white matter (WM) area quantitation in the cervical and thoracic spinal cord (SC) with optimized contrast. We aimed to investigate rAMIRA-derived SC GM and SC WM areas and their association with clinical phenotype and disability in ALS.

METHODS

A total of 36 patients with ALS (mean [SD] age 61.7 [12.6] years, 14 women) and 36 healthy, age- and sex-matched controls (HCs; mean [SD] age 63.1 [12.1] years, 14 women) underwent two-dimensional axial rAMIRA imaging at the inter-vertebral disc levels C2/3-C5/C6 and the lumbar enlargement level Tmax. ALS Functional Rating Scale-revised (ALSFRS-R) score, muscle strength, and sniff nasal inspiratory pressure (SNIP) were assessed.

RESULTS

Compared to HCs, GM and WM areas were reduced in patients at all cervical levels (p < 0.0001). GM area (p = 0.0001), but not WM area, was reduced at Tmax. Patients with King's Stage 3 showed significant GM atrophy at all levels, while patients with King's Stage 1 showed significant GM atrophy selectively at Tmax. SC GM area was significantly associated with muscle force at corresponding myotomes. GM area at C3/C4 was associated with ALSFRS-R (p < 0.001) and SNIP (p = 0.0016).

CONCLUSION

Patients with ALS assessed by rAMIRA imaging show significant cervical and thoracic SC GM and SC WM atrophy. SC GM area correlates with muscle strength and clinical disability. GM area reduction at Tmax may be an early disease sign. Longitudinal studies are warranted.

Longitudinal Changes in the Retinal Nerve Fiber Layer Thickness in Amyotrophic Lateral Sclerosis and Parkinson's Disease

BACKGROUND AND PURPOSE

There is increasing evidence that the anterior visual pathways are involved in neurodegenerative diseases including amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD). This study investigated longitudinal changes in retinal nerve fiber layer (RNFL) thickness in patients with ALS and PD with the aim of better understanding their roles as biomarkers of disease progression.

METHODS

This study recruited 21 ALS patients, 19 age-matched PD patients, and 21 agematched healthy controls. Patient demographics and clinical scores relating to the respective diseases were documented. The RNFL thickness was measured using optical coherence tomography at baseline and after 6 months.

RESULTS

At baseline, the RNFL in the superior quadrant was significantly thinner in the patients with ALS than in healthy controls (109.90±22.41 µm vs. 127.81±17.05 µm [mean±standard deviation], p=0.008). The RNFL thickness did not differ significantly between the ALS and PD patients or between the PD patients and healthy controls. At 6 months, there was further significant RNFL thinning in patients with ALS, for both the overall thickness (baseline: median=94.5 µm, range=83.0-106.0 µm; follow-up: median=93.5 µm, range=82.5-104.5 µm, p=0.043) and the thickness in the inferior quadrant (median=126 µm, range=109.5-142.5 µm; and median=117.5 µm, range=98.5-136.5 µm; respectively, p=0.032). However, these changes were not correlated with the ALS functional scores. In contrast, the patients with PD did not demonstrate a significant change in RNFL thickness between the two time points.

CONCLUSIONS

The RNFL thickness is a promising biomarker of disease progression in patients with ALS but not in those with PD, which has a slower disease progression.

Evidence based on Mendelian randomization and colocalization analysis strengthens causal relationships between structural changes in specific brain regions and risk of amyotrophic lateral sclerosis

Background

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the degeneration of motor neurons in the brain and spinal cord with a poor prognosis. Previous studies have observed cognitive decline and changes in brain morphometry in ALS patients. However, it remains unclear whether the brain structural alterations contribute to the risk of ALS. In this study, we conducted a bidirectional two-sample Mendelian randomization (MR) and colocalization analysis to investigate this causal relationship.

Methods

Summary data of genome-wide association study were obtained for ALS and the brain structures, including surface area (SA), thickness and volume of subcortical structures. Inverse-variance weighted (IVW) method was used as the main estimate approach. Sensitivity analysis was conducted detect heterogeneity and pleiotropy. Colocalization analysis was performed to calculate the posterior probability of causal variation and identify the common genes.

Results

In the forward MR analysis, we found positive associations between the SA in four cortical regions (lingual, parahippocampal, pericalcarine, and middle temporal) and the risk of ALS. Additionally, decreased thickness in nine cortical regions (caudal anterior cingulate, frontal pole, fusiform, inferior temporal, lateral occipital, lateral orbitofrontal, pars orbitalis, pars triangularis, and pericalcarine) was significantly associated with a higher risk of ALS. In the reverse MR analysis, genetically predicted ALS was associated with reduced thickness in the bankssts and increased thickness in the caudal middle frontal, inferior parietal, medial orbitofrontal, and superior temporal regions. Colocalization analysis revealed the presence of shared causal variants between the two traits.

Conclusion

Our results suggest that altered brain morphometry in individuals with high ALS risk may be genetically mediated. The causal associations of widespread multifocal extra-motor atrophy in frontal and temporal lobes with ALS risk support the notion of a continuum between ALS and frontotemporal dementia. These findings enhance our understanding of the cortical structural patterns in ALS and shed light on potentially viable therapeutic targets.

Fluid biomarkers for amyotrophic lateral sclerosis: a review

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the loss of upper and lower motor neurons. Presently, three FDA-approved drugs are available to help slow functional decline for patients with ALS, but no cure yet exists. With an average life expectancy of only two to five years after diagnosis, there is a clear need for biomarkers to improve the care of patients with ALS and to expedite ALS treatment development. Here, we provide a review of the efforts made towards identifying diagnostic, prognostic, susceptibility/risk, and response fluid biomarkers with the intent to facilitate a more rapid and accurate ALS diagnosis, to better predict prognosis, to improve clinical trial design, and to inform interpretation of clinical trial results. Over the course of 20 + years, several promising fluid biomarker candidates for ALS have emerged. These will be discussed, as will the exciting new strategies being explored for ALS biomarker discovery and development.

Corticospinal fibers with different origins impair in amyotrophic lateral sclerosis: A neurite orientation dispersion and density imaging study

AIMS

To investigate microstructural impairments of corticospinal tracts (CSTs) with different origins in amyotrophic lateral sclerosis (ALS) using neurite orientation dispersion and density imaging (NODDI).

METHODS

Diffusion-weighted imaging data acquired from 39 patients with ALS and 50 controls were used to estimate NODDI and diffusion tensor imaging (DTI) models. Fine maps of CST subfibers originating from the primary motor area (M1), premotor cortex, primary sensory area, and supplementary motor area (SMA) were segmented. NODDI metrics (neurite density index [NDI] and orientation dispersion index [ODI]) and DTI metrics (fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) were computed.

RESULTS

The patients with ALS showed microstructural impairments (reflected by NDI, ODI, and FA reductions and MD, AD, and RD increases) in CST subfibers, especially in M1 fibers, which correlated with disease severity. Compared with other diffusion metrics, NDI yielded a higher effect size and detected the greatest extent of CST subfibers damage. Logistic regression analyses based on NDI in M1 subfiber yielded the best diagnostic performance compared with other subfibers and the whole CST.

CONCLUSIONS

Microstructural impairment of CST subfibers (especially those originating from M1) is the key feature of ALS. The combination of NODDI and CST subfibers analysis may improve diagnosing performance for ALS.

Advances in molecular pathology, diagnosis, and treatment of amyotrophic lateral sclerosis

Although the past two decades have produced exciting discoveries in the genetics and pathology of amyotrophic lateral sclerosis (ALS), progress in developing an effective therapy remains slow. This review summarizes the critical discoveries and outlines the advances in disease characterization, diagnosis, imaging, and biomarkers, along with the current status of approaches to ALS care and treatment. Additional knowledge of the factors driving disease progression and heterogeneity will hopefully soon transform the care for patients with ALS into an individualized, multi-prong approach able to prevent disease progression sufficiently to allow for a dignified life with limited disability.

Regulation of cortical hyperexcitability in amyotrophic lateral sclerosis: focusing on glial mechanisms

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the loss of both upper and lower motor neurons, resulting in muscle weakness, atrophy, paralysis, and eventually death. Motor cortical hyperexcitability is a common phenomenon observed at the presymptomatic stage of ALS. Both cell-autonomous (the intrinsic properties of motor neurons) and non-cell-autonomous mechanisms (cells other than motor neurons) are believed to contribute to cortical hyperexcitability. Decoding the pathological relevance of these dynamic changes in motor neurons and glial cells has remained a major challenge. This review summarizes the evidence of cortical hyperexcitability from both clinical and preclinical research, as well as the underlying mechanisms. We discuss the potential role of glial cells, particularly microglia, in regulating abnormal neuronal activity during the disease progression. Identifying early changes such as neuronal hyperexcitability in the motor system may provide new insights for earlier diagnosis of ALS and reveal novel targets to halt the disease progression.

An Exploratory Trial of EPI-589 in Amyotrophic Lateral Sclerosis (EPIC-ALS): Protocol for a Multicenter, Open-Labeled, 24-Week, Single-Group Study

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder, with its currently approved drugs, including riluzole and edaravone, showing limited therapeutic effects. Therefore, safe and effective drugs are urgently necessary. EPI-589 is an orally available, small-molecule, novel redox-active agent characterized by highly potent protective effects against oxidative stress with high blood-brain barrier permeability. Given the apparent oxidative stress and mitochondrial dysfunction involvement in the pathogenesis of ALS, EPI-589 may hold promise as a therapeutic agent.

OBJECTIVE

This protocol aims to describe the design and rationale for the EPI-589 Early Phase 2 Investigator-Initiated Clinical Trial for ALS (EPIC-ALS).

METHODS

EPIC-ALS is an explorative, open-labeled, single-arm trial that evaluates the safety and tolerability of EPI-589 in patients with ALS. This trial consists of 12-week run-in, 24-week treatment, and 4-week follow-up periods. Patients will receive 500 mg of EPI-589 3 times daily over the 24-week treatment period. Clinical assessments include the mean monthly change of Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised total score. The biomarkers are selected to analyze the effect on oxidative stress and neuronal damage. The plasma biomarkers are 8-hydroxy-2'-deoxyguanosine (8-OHdG), 3-nitrotyrosine (3-NT), neurofilament light chain (NfL), phosphorylated neurofilament heavy chain (pNfH), homocysteine, and creatinine. The cerebrospinal fluid biomarkers are 8-OHdG, 3-NT, NfL, pNfH, and ornithine. The magnetic resonance biomarkers are fractional anisotropy in the corticospinal tract and N-acetylaspartate in the primary motor area.

RESULTS

This trial began data collection in September 2021 and is expected to be completed in October 2023.

CONCLUSIONS

This study can provide useful data to understand the characteristics of EPI-589.

TRIAL REGISTRATION

Japan Primary Registries Network jRCT2061210031; tinyurl.com/2p84emu6.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/42032.

Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis: Machine Learning for Biomarker Development

Diffusion tensor imaging (DTI) allows the in vivo imaging of pathological white matter alterations, either with unbiased voxel-wise or hypothesis-guided tract-based analysis. Alterations of diffusion metrics are indicative of the cerebral status of patients with amyotrophic lateral sclerosis (ALS) at the individual level. Using machine learning (ML) models to analyze complex and high-dimensional neuroimaging data sets, new opportunities for DTI-based biomarkers in ALS arise. This review aims to summarize how different ML models based on DTI parameters can be used for supervised diagnostic classifications and to provide individualized patient stratification with unsupervised approaches in ALS. To capture the whole spectrum of neuropathological signatures, DTI might be combined with additional modalities, such as structural T1w 3-D MRI in ML models. To further improve the power of ML in ALS and enable the application of deep learning models, standardized DTI protocols and multi-center collaborations are needed to validate multimodal DTI biomarkers. The application of ML models to multiparametric MRI/multimodal DTI-based data sets will enable a detailed assessment of neuropathological signatures in patients with ALS and the development of novel neuroimaging biomarkers that could be used in the clinical workup.

Advances in the neuroimaging of motor disorders

Neuroimaging is a valuable adjunct to the history and examination in the evaluation of motor system disorders. Conventional imaging with computed tomography or magnetic resonance imaging depicts important anatomic information and helps to identify imaging patterns which may support diagnosis of a specific motor disorder. Advanced imaging techniques can provide further detail regarding volume, functional, or metabolic changes occurring in nervous system pathology. This chapter is an overview of the advances in neuroimaging with particular emphasis on both standard and less well-known advanced imaging techniques and findings, such as diffusion tensor imaging or volumetric studies, and their application to specific motor disorders. In addition, it provides reference to emerging imaging biomarkers in motor system disorders such as Parkinson disease, amyotrophic lateral sclerosis, and Huntington disease, and briefly reviews the neuroimaging findings in different causes of myelopathy and peripheral nerve disorders.

Investigating neurological symptoms of infectious diseases like COVID-19 leading to a deeper understanding of neurodegenerative disorders such as Parkinson's disease

Apart from common respiratory symptoms, neurological symptoms are prevalent among patients with COVID-19. Research has shown that infection with SARS-CoV-2 accelerated alpha-synuclein aggregation, induced Lewy-body-like pathology, caused dopaminergic neuron senescence, and worsened symptoms in patients with Parkinson's disease (PD). In addition, SARS-CoV-2 infection can induce neuroinflammation and facilitate subsequent neurodegeneration in long COVID, and increase individual vulnerability to PD or parkinsonism. These findings suggest that a post-COVID-19 parkinsonism might follow the COVID-19 pandemic. In order to prevent a possible post-COVID-19 parkinsonism, this paper reviewed neurological symptoms and related findings of COVID-19 and related infectious diseases (influenza and prion disease) and neurodegenerative disorders (Alzheimer's disease, PD and amyotrophic lateral sclerosis), and discussed potential mechanisms underlying the neurological symptoms and the relationship between the infectious diseases and the neurodegenerative disorders, as well as the therapeutic and preventive implications in the neurodegenerative disorders. Infections with a relay of microbes (SARS-CoV-2, influenza A viruses, gut bacteria, etc.) and prion-like alpha-synuclein proteins over time may synergize to induce PD. Therefore, a systematic approach that targets these pathogens and the pathogen-induced neuroinflammation and neurodegeneration may provide cures for neurodegenerative disorders. Further, antiviral/antimicrobial drugs, vaccines, immunotherapies and new therapies (e.g., stem cell therapy) need to work together to treat, manage or prevent these disorders. As medical science and technology advances, it is anticipated that better vaccines for SARS-CoV-2 variants, new antiviral/antimicrobial drugs, effective immunotherapies (alpha-synuclein antibodies, vaccines for PD or parkinsonism, etc.), as well as new therapies will be developed and made available in the near future, which will help prevent a possible post-COVID-19 parkinsonism in the 21st century.

Synaptic proteomics reveal distinct molecular signatures of cognitive change and C9ORF72 repeat expansion in the human ALS cortex

Increasing evidence suggests synaptic dysfunction is a central and possibly triggering factor in Amyotrophic Lateral Sclerosis (ALS). Despite this, we still know very little about the molecular profile of an ALS synapse. To address this gap, we designed a synaptic proteomics experiment to perform an unbiased assessment of the synaptic proteome in the ALS brain. We isolated synaptoneurosomes from fresh-frozen post-mortem human cortex (11 controls and 18 ALS) and stratified the ALS group based on cognitive profile (Edinburgh Cognitive and Behavioural ALS Screen (ECAS score)) and presence of a C9ORF72 hexanucleotide repeat expansion (C9ORF72-RE). This allowed us to assess regional differences and the impact of phenotype and genotype on the synaptic proteome, using Tandem Mass Tagging-based proteomics. We identified over 6000 proteins in our synaptoneurosomes and using robust bioinformatics analysis we validated the strong enrichment of synapses. We found more than 30 ALS-associated proteins in synaptoneurosomes, including TDP-43, FUS, SOD1 and C9ORF72. We identified almost 500 proteins with altered expression levels in ALS, with region-specific changes highlighting proteins and pathways with intriguing links to neurophysiology and pathology. Stratifying the ALS cohort by cognitive status revealed almost 150 specific alterations in cognitively impaired ALS synaptic preparations. Stratifying by C9ORF72-RE status revealed 330 protein alterations in the C9ORF72-RE +ve group, with KEGG pathway analysis highlighting strong enrichment for postsynaptic dysfunction, related to glutamatergic receptor signalling. We have validated some of these changes by western blot and at a single synapse level using array tomography imaging. In summary, we have generated the first unbiased map of the human ALS synaptic proteome, revealing novel insight into this key compartment in ALS pathophysiology and highlighting the influence of cognitive decline and C9ORF72-RE on synaptic composition.

Longitudinal monitoring of amyotrophic lateral sclerosis by diffusion tensor imaging: Power calculations for group studies

Introduction

Diffusion tensor imaging (DTI) can be used to map disease progression in amyotrophic lateral sclerosis (ALS) and therefore is a promising candidate for a biomarker in ALS. To this end, longitudinal study protocols need to be optimized and validated regarding group sizes and time intervals between visits. The objective of this study was to assess the influences of sample size, the schedule of follow-up measurements, and measurement uncertainties on the statistical power to optimize longitudinal DTI study protocols in ALS.

Patients and methods

To estimate the measurement uncertainty of a tract-of–interest-based DTI approach, longitudinal test-retest measurements were applied first to a normal data set. Then, DTI data sets of 80 patients with ALS and 50 healthy participants were analyzed in the simulation of longitudinal trajectories, that is, longitudinal fractional anisotropy (FA) values for follow-up sessions were simulated for synthetic patient and control groups with different rates of FA decrease in the corticospinal tract. Monte Carlo simulations of synthetic longitudinal study groups were used to estimate the statistical power and thus the potentially needed sample sizes for a various number of scans at one visit, different time intervals between baseline and follow-up measurements, and measurement uncertainties.

Results

From the simulation for different longitudinal FA decrease rates, it was found that two scans per session increased the statistical power in the investigated settings unless sample sizes were sufficiently large and time intervals were appropriately long. The positive effect of a second scan per session on the statistical power was particularly pronounced for FA values with high measurement uncertainty, for which the third scan per session increased the statistical power even further.

Conclusion

With more than one scan per session, the statistical power of longitudinal DTI studies can be increased in patients with ALS. Consequently, sufficient statistical power can be achieved even with limited sample sizes. An improved longitudinal DTI study protocol contributes to the detection of small changes in diffusion metrics and thereby supports DTI as an applicable and reliable non-invasive biomarker in ALS.

Utility of the ALSFRS-R for predicting ALS and comorbid disease neuropathology: The Veterans Affairs Biorepository Brain Bank

INTRODUCTION/AIMS

The amyotrophic lateral sclerosis (ALS) functional rating scale-revised (ALSFRS-R) is commonly used to track ALS disease progression; however, there are gaps in the literature regarding the extent to which the ALSFRS-R relates to underlying central nervous system (CNS) pathology. The current study explored the association between ALSFRS-R (total and subdomain) scores and postmortem neuropathology (both ALS-specific and comorbid disease).

METHODS

Within our sample of 93 military veterans with autopsy-confirmed ALS, we utilized hierarchical cluster analysis (HCA) to identify discrete profiles of motor dysfunction based on ALSFRS-R subdomain scores. We examined whether emergent clusters were associated with neuropathology. Separate analyses of variance and covariance with post-hoc comparisons were performed to examine relevant cluster differences.

RESULTS

Analyses revealed significant correlations between ALSFRS-R total and subdomain scores with some, but not all, neuropathological variables. The HCA illustrated three groups: Cluster 1-predominantly diffuse functional impairment; Cluster 2-spared respiratory/bulbar and impaired motor function; and Cluster 3-spared bulbar and impaired respiratory, and fine and gross motor function. Individuals in Cluster 1 (and to a lesser degree, Cluster 3) exhibited greater accumulation of ALS-specific neuropathology and less comorbid neuropathology than those in Cluster 2.

DISCUSSION

These results suggest that discrete patterns of motor dysfunction based on ALSFRS-R subdomain scores are related to postmortem neuropathology. Findings support use of ALSFRS-R subdomain scores to capture the heterogeneity of clinical presentation and disease progression in ALS, and may assist researchers in identifying endophenotypes for separate assessment in clinical trials.

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.

Dynamic Alterations in Functional Connectivity Density in Amyotrophic Lateral Sclerosis: A Resting-State Functional Magnetic Resonance Imaging Study

Background and Aims

Current knowledge on the temporal dynamics of the brain functional organization in amyotrophic lateral sclerosis (ALS) is limited. This is the first study on alterations in the patterns of dynamic functional connection density (dFCD) involving ALS.

Methods

We obtained resting-state functional magnetic resonance imaging (fMRI) data from 50 individuals diagnosed with ALS and 55 healthy controls (HCs). We calculated the functional connectivity (FC) between a given voxel and all other voxels within the entire brain and yield the functional connection density (FCD) value per voxel. dFCD was assessed by sliding window correlation method. In addition, the standard deviation (SD) of dFCD across the windows was computed voxel-wisely to measure dFCD variability. The difference in dFCD variability between the two groups was compared using a two-sample t-test following a voxel-wise manner. The receiver operating characteristic (ROC) curve was used to assess the between-group recognition performance of the dFCD variability index.

Results

The dFCD variability was significantly reduced in the bilateral precentral and postcentral gyrus compared with the HC group, whereas a marked increase was observed in the left middle frontal gyrus of ALS patients. dFCD variability exhibited moderate potential (areas under ROC curve = 0.753-0.837, all P < 0.001) in distinguishing two groups.

Conclusion

ALS patients exhibit aberrant dynamic property in brain functional architecture. The dFCD evaluation improves our understanding of the pathological mechanisms underlying ALS and may assist in its diagnosis.

Cortical Hyperexcitability in the Driver’s Seat in ALS

Amyotrophic lateral sclerosis (ALS) is a fatal disease characterized by the degeneration of cortical and spinal motor neurons. With no effective treatment available to date, patients face progressive paralysis and eventually succumb to the disease due to respiratory failure within only a few years. Recent research has revealed the multifaceted nature of the mechanisms and cell types involved in motor neuron degeneration, thereby opening up new therapeutic avenues. Intriguingly, two key features present in both ALS patients and rodent models of the disease are cortical hyperexcitability and hyperconnectivity, the mechanisms of which are still not fully understood. We here recapitulate current findings arguing for cell autonomous and non-cell autonomous mechanisms causing cortical excitation and inhibition imbalance, which is involved in the degeneration of motor neurons in ALS. Moreover, we will highlight recent evidence that strongly indicates a cardinal role for the motor cortex as a main driver and source of the disease, thus arguing for a corticofugal trajectory of the pathology.

Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics

Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional connectivity between brain regions by linear methods highlight the role of brain function. These studies have yet to be combined with brain structure and nonlinear functional features. We investigate the role of linear and nonlinear functional brain features, and the benefit of combining brain structure and function for ALS classification. ALS patients (N = 97) and healthy controls (N = 59) underwent structural and functional resting state magnetic resonance imaging. Based on key hubs of resting state networks, we defined three feature sets comprising brain volume, resting state functional connectivity (rsFC), as well as (nonlinear) resting state dynamics assessed via recurrent neural networks. Unimodal and multimodal random forest classifiers were built to classify ALS. Out-of-sample prediction errors were assessed via five-fold cross-validation. Unimodal classifiers achieved a classification accuracy of 56.35-61.66%. Multimodal classifiers outperformed unimodal classifiers achieving accuracies of 62.85-66.82%. Evaluating the ranking of individual features' importance scores across all classifiers revealed that rsFC features were most dominant in classification. While univariate analyses revealed reduced rsFC in ALS patients, functional features more generally indicated deficits in information integration across resting state brain networks in ALS. The present work undermines that combining brain structure and function provides an additional benefit to diagnostic classification, as indicated by multimodal classifiers, while emphasizing the importance of capturing both linear and nonlinear functional brain properties to identify discriminative biomarkers of ALS.

Biomedical signals and machine learning in amyotrophic lateral sclerosis: a systematic review

INTRODUCTION

The use of machine learning (ML) techniques in healthcare encompasses an emerging concept that envisages vast contributions to the tackling of rare diseases. In this scenario, amyotrophic lateral sclerosis (ALS) involves complexities that are yet not demystified. In ALS, the biomedical signals present themselves as potential biomarkers that, when used in tandem with smart algorithms, can be useful to applications within the context of the disease.

METHODS

This Systematic Literature Review (SLR) consists of searching for and investigating primary studies that use ML techniques and biomedical signals related to ALS. Following the definition and execution of the SLR protocol, 18 articles met the inclusion, exclusion, and quality assessment criteria, and answered the SLR research questions.

DISCUSSIONS

Based on the results, we identified three classes of ML applications combined with biomedical signals in the context of ALS: diagnosis (72.22%), communication (22.22%), and survival prediction (5.56%).

CONCLUSIONS

Distinct algorithmic models and biomedical signals have been reported and present promising approaches, regardless of their classes. In summary, this SLR provides an overview of the primary studies analyzed as well as directions for the construction and evolution of technology-based research within the scope of ALS.

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.

MRI-guided histology of TDP-43 knock-in mice implicates parvalbumin interneuron loss, impaired neurogenesis and aberrant neurodevelopment in amyotrophic lateral sclerosis-frontotemporal dementia

Amyotrophic lateral sclerosis and frontotemporal dementia are overlapping diseases in which MRI reveals brain structural changes in advance of symptom onset. Recapitulating these changes in preclinical models would help to improve our understanding of the molecular causes underlying regionally selective brain atrophy in early disease. We therefore investigated the translational potential of the TDP-43Q331K knock-in mouse model of amyotrophic lateral sclerosis-frontotemporal dementia using MRI. We performed in vivo MRI of TDP-43Q331K knock-in mice. Regions of significant volume change were chosen for post-mortem brain tissue analyses. Ex vivo computed tomography was performed to investigate skull shape. Parvalbumin neuron density was quantified in post-mortem amyotrophic lateral sclerosis frontal cortex. Adult mutants demonstrated parenchymal volume reductions affecting the frontal lobe and entorhinal cortex in a manner reminiscent of amyotrophic lateral sclerosis-frontotemporal dementia. Subcortical, cerebellar and brain stem regions were also affected in line with observations in pre-symptomatic carriers of mutations in C9orf72, the commonest genetic cause of both amyotrophic lateral sclerosis and frontotemporal dementia. Volume loss was also observed in the dentate gyrus of the hippocampus, along with ventricular enlargement. Immunohistochemistry revealed reduced parvalbumin interneurons as a potential cellular correlate of MRI changes in mutant mice. By contrast, microglia was in a disease activated state even in the absence of brain volume loss. A reduction in immature neurons was found in the dentate gyrus, indicative of impaired adult neurogenesis, while a paucity of parvalbumin interneurons in P14 mutant mice suggests that TDP-43Q331K disrupts neurodevelopment. Computerized tomography imaging showed altered skull morphology in mutants, further suggesting a role for TDP-43Q331K in development. Finally, analysis of human post-mortem brains confirmed a paucity of parvalbumin interneurons in the prefrontal cortex in sporadic amyotrophic lateral sclerosis and amyotrophic lateral sclerosis linked to C9orf72 mutations. Regional brain MRI changes seen in human amyotrophic lateral sclerosis-frontotemporal dementia are recapitulated in TDP-43Q331K knock-in mice. By marrying in vivo imaging with targeted histology, we can unravel cellular and molecular processes underlying selective brain vulnerability in human disease. As well as helping to understand the earliest causes of disease, our MRI and histological markers will be valuable in assessing the efficacy of putative therapeutics in TDP-43Q331K knock-in mice.

Magnetic resonance metrics to evaluate the effect of therapy in amyotrophic lateral sclerosis: the experience with edaravone

BACKGROUND

Edaravone was approved as a new treatment for amyotrophic lateral sclerosis (ALS), although there are different opinions on its effectiveness. Magnetic resonance (MRI) measures appear promising as diagnostic and prognostic indicators of disease. However, published studies on MRI using to monitor treatment efficacy in ALS are lacking.

PURPOSE

The objective of this study was to investigate changes in brain MRI measures in patients treated with edaravone.

METHODS

Thirteen ALS patients assuming edaravone (ALS-EDA) underwent MRI at baseline (T0) and after 6 months (T6) to measure cortical thickness (CT) and fractional anisotropy (FA) of white matter (WM) tracts. MRI data of ALS-EDA were compared at T0 with those of 12 control subjects (CS), and at T6 with those of 11 ALS patients assuming only riluzole (ALS-RIL), extracted from our ALS cohort using a propensity-score-matching. A longitudinal MRI analysis was performed in ALS-EDA between T6 and T0.

RESULTS

At T0, ALS-EDA showed a cortical widespread thinning in both hemispheres, particularly in the bilateral precentral gyrus, and a reduction of FA in bilateral corticospinal tracts, in comparison to CS. Thinning in bilateral precentral cortex and significant widespread reduction of FA in several WM tracts were observed in ALS-EDA at T6 compared to T0. At T6, no significant differences in MRI measures of ALS-EDA versus ALS-RIL were found.

CONCLUSIONS

Patients treated with edaravone showed progression of damage in the motor cortex and several WM tracts, at a six-month follow-up. Moreover, this study showed no evidence of a difference between edaravone and riluzole.

Amide signal intensities may be reduced in the motor cortex and the corticospinal tract of ALS patients

OBJECTIVES

The aim of the study is to assess amide concentration changes in ALS patients compared with healthy controls by using quantitative amide proton transfer (APT) and multiparameter magnetic resonance imaging, and testing its correlation with clinical scores.

METHODS

Sixteen ALS patients and sixteen healthy controls were recruited as part of the Canadian ALS Neuroimaging Consortium, and multimodal magnetic resonance imaging was performed at 3 T, including APT and diffusion imaging. Lorentz fitting was used to quantify the amide effect. Clinical disability was evaluated using the revised ALS functional rating scale (ALSFRS-R), and its correlation with image characteristics was assessed. The diagnostic performance of different imaging parameters was evaluated with receiver operating characteristic analysis.

RESULTS

Our results showed that the amide peak was significantly different between the motor cortex and other gray matter territories within the brain of ALS patients (p < 0.001). Compared with controls, amide signal intensities in ALS were significantly reduced in the motor cortex (p < 0.001) and corticospinal tract (p = 0.046), while abnormalities were not detected using routine imaging methods. There was no significant correlation between amide and ALSFRS-R score. The diagnostic accuracy of the amide peak was superior to that of diffusion imaging.

CONCLUSIONS

This study demonstrated changes of amide signal intensities in the motor cortex and corticospinal tract of ALS patients.

KEY POINTS

• The neurodegenerative disease amyotrophic lateral sclerosis (ALS) has a lack of objective imaging indicators for diagnosis and assessment. • Analysis of amide proton transfer imaging revealed changes in the motor cortex and corticospinal tract of ALS patients that were not visible on standard magnetic resonance imaging. • The diagnostic accuracy of the amide peak was superior to that of diffusion imaging.

Improving clinical trial outcomes in amyotrophic lateral sclerosis

Individuals who are diagnosed with amyotrophic lateral sclerosis (ALS) today face the same historically intransigent problem that has existed since the initial description of the disease in the 1860s - a lack of effective therapies. In part, the development of new treatments has been hampered by an imperfect understanding of the biological processes that trigger ALS and promote disease progression. Advances in our understanding of these biological processes, including the causative genetic mutations, and of the influence of environmental factors have deepened our appreciation of disease pathophysiology. The consequent identification of pathogenic targets means that the introduction of effective therapies is becoming a realistic prospect. Progress in precision medicine, including genetically targeted therapies, will undoubtedly change the natural history of ALS. The evolution of clinical trial designs combined with improved methods for patient stratification will facilitate the translation of novel therapies into the clinic. In addition, the refinement of emerging biomarkers of therapeutic benefits is critical to the streamlining of care for individuals. In this Review, we synthesize these developments in ALS and discuss the further developments and refinements needed to accelerate the introduction of effective therapeutic approaches.

Dysfunction in nonsense-mediated decay, protein homeostasis, mitochondrial function, and brain connectivity in ALS-FUS mice with cognitive deficits

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) represent two ends of the same disease spectrum of adult-onset neurodegenerative diseases that affect the motor and cognitive functions, respectively. Multiple common genetic loci such as fused in sarcoma (FUS) have been identified to play a role in ALS and FTD etiology. Current studies indicate that FUS mutations incur gain-of-toxic functions to drive ALS pathogenesis. However, how the disease-linked mutations of FUS affect cognition remains elusive. Using a mouse model expressing an ALS-linked human FUS mutation (R514G-FUS) that mimics endogenous expression patterns, we found that FUS proteins showed an age-dependent accumulation of FUS proteins despite the downregulation of mouse FUS mRNA by the R514G-FUS protein during aging. Furthermore, these mice developed cognitive deficits accompanied by a reduction in spine density and long-term potentiation (LTP) within the hippocampus. At the physiological expression level, mutant FUS is distributed in the nucleus and cytosol without apparent FUS aggregates or nuclear envelope defects. Unbiased transcriptomic analysis revealed a deregulation of genes that cluster in pathways involved in nonsense-mediated decay, protein homeostasis, and mitochondrial functions. Furthermore, the use of in vivo functional imaging demonstrated widespread reduction in cortical volumes but enhanced functional connectivity between hippocampus, basal ganglia and neocortex in R514G-FUS mice. Hence, our findings suggest that disease-linked mutation in FUS may lead to changes in proteostasis and mitochondrial dysfunction that in turn affect brain structure and connectivity resulting in cognitive deficits.

Imaging Neurochemistry and Brain Structure Tracks Clinical Decline and Mechanisms of ALS in Patients

Background: Oxidative stress and protein aggregation are key mechanisms in amyotrophic lateral sclerosis (ALS) disease. Reduced glutathione (GSH) is the most important intracellular antioxidant that protects neurons from reactive oxygen species. We hypothesized that levels of GSH measured by MR spectroscopic imaging (MRSI) in the motor cortex and corticospinal tract are linked to clinical trajectory of ALS patients.

Objectives: Investigate the value of GSH imaging to probe clinical decline of ALS patients in combination with other neurochemical and structural parameters.

Methods: Twenty-four ALS patients were imaged at 3 T with an advanced MR protocol. Mapping GSH levels in the brain is challenging, and for this purpose, we used an optimized spectral-edited 3D MRSI sequence with real-time motion and field correction to image glutathione and other brain metabolites. In addition, our imaging protocol included (i) an adiabatic T1ρ sequence to image macromolecular fraction of brain parenchyma, (ii) diffusion tensor imaging (DTI) for white matter tractography, and (iii) high-resolution anatomical imaging.

Results: We found GSH in motor cortex (r = −0.431, p = 0.04) and corticospinal tract (r = −0.497, p = 0.016) inversely correlated with time between diagnosis and imaging. N-Acetyl-aspartate (NAA) in motor cortex inversely correlated (r = −0.416, p = 0.049), while mean water diffusivity (r = 0.437, p = 0.033) and T1ρ (r = 0.482, p = 0.019) positively correlated with disease progression measured by imputed change in revised ALS Functional Rating Scale. There is more decrease in the motor cortex than in the white matter for GSH compared to NAA, glutamate, and glutamine.

Conclusions: Our study suggests that a panel of biochemical and structural imaging biomarkers defines a brain endophenotype, which can be used to time biological events and clinical progression in ALS patients. Such a quantitative brain endophenotype may stratify ALS patients into more homogeneous groups for therapeutic interventions compared to clinical criteria.

A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS

OBJECTIVE

To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS).

METHODS

Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center.

RESULTS

Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe.

CONCLUSIONS

Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes and, to a lesser degree, in the corticopontine/corticorubral tracts and corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS.

CLINICALTRIALSGOV IDENTIFIER

NCT02405182.

Structural MRI outcomes and predictors of disease progression in amyotrophic lateral sclerosis

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Serial diffusion tensor (DT) MRI showed progression of white matter pathology in ALS.

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Early involvement of motor fibers and later spread to extra-motor regions was found.

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DT MRI measures of damage to the motor networks showed consistent worsening.

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These correlated with clinical progression and long-term functional prognosis.

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No significant cortical thinning was detected either at baseline or over time.

Background and aims

Considering the great heterogeneity of amyotrophic lateral sclerosis (ALS), the identification of accurate prognostic predictors is fundamental for both the clinical practice and the design of treatment trials. This study aimed to explore the progression of clinical and structural brain changes in patients with ALS, and to assess magnetic resonance imaging (MRI) measures of brain damage as predictors of subsequent functional decline.

Methods

50 ALS patients underwent clinical evaluations and 3 T MRI scans at regular intervals for a maximum of 2 years (total MRI scans = 164). MRI measures of cortical thickness, as well as diffusion tensor (DT) metrics of microstructural damage along white matter (WM) tracts were obtained. Voxel-wise regression models and longitudinal mixed-effects models were used to test the relationship between clinical decline and baseline and longitudinal MRI features.

Results

The rate of decline of the ALS Functional Rating Scale revised (ALSFRS-r) was significantly associated with the rate of fractional anisotropy (FA) decrease in the body of the corpus callosum (CC). Corticospinal tract (CST) and CC-body alterations had a faster progression in patients with higher baseline ALSFRS-r scores and greater CC-body disruption at baseline. Lower FA of the cerebral peduncle was associated with faster subsequent clinical progression.

Conclusions

In this longitudinal study, we identified a significant association between measures of WM damage of the motor tracts and functional decline in ALS patients. Our data suggest that a multiparametric approach including DT MRI measures of brain damage would provide an optimal method for an accurate stratification of ALS patients into prognostic classes.

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.

Assessment of the Corticospinal Tract Profile in Pure Lower Motor Neuron Disease: A Diffusion Tensor Imaging Study

AIM

The aim of this study was to evaluate the corticospinal tract (CST) diffusion profile in pure lower motor neuron disease (pLMND) patients who at baseline did not show any clinical or electrophysiological involvement of upper motor neurons (UMN), and in amyotrophic lateral sclerosis (ALS) patients.

MATERIALS AND METHODS

Fifteen ALS patients with delayed central motor conduction time (CMCT) and 14 pLMND patients with normal CMCT were enrolled together with 15 healthy controls. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were obtained. The tract profile of CST was reconstructed with the automated fiber quantification tool and its diffusion properties were quantified voxel-by-voxel and then compared pairwise between groups. Moreover, a random forest (RF) classifier was trained to evaluate the ability of CST diffusion metrics in distinguishing pairwise the groups from the controls.

RESULTS

ALS patients presented wide microstructural abnormalities in the entire CST as assessed by FA decrease and RD increase while pLMND patients showed focal FA decrease and a larger AD increase in the cerebral peduncle and posterior limb of the internal capsule in comparison with controls. RF revealed that diffusion tensor imaging (DTI) metrics accurately distinguished ALS patients and pLMND patients from controls (96.67 and 95.71% accuracy, respectively).

CONCLUSIONS

Our study demonstrates that the CST was impaired in both ALS and pLMND patients, thus suggesting that DTI metrics are a reliable tool in detecting subtle changes of UMN in pLMND patients, also in the absence of clinical and CMCT abnormalities.

Quantitative Brain Sodium MRI Depicts Corticospinal Impairment in Amyotrophic Lateral Sclerosis

Background Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that mainly affects the upper and lower motor neurons. Recent sodium (²³Na) MRI studies have shown that abnormal sodium concentration is related to neuronal suffering in neurodegenerative conditions. Purpose To use ²³Na MRI to investigate abnormal sodium concentrations and map their distribution in the brains of study participants with ALS as compared with healthy control subjects. Materials and Methods Twenty-seven participants with ALS (mean age, 54 years ± 10 [standard deviation], eight women) and 30 healthy control subjects (mean age, 50 years ± 10; 16 women) were prospectively recruited between September 2015 and October 2017 and were examined by using conventional proton MRI and sodium MRI at 3 T. Voxel-based statistical mapping was used to compare quantitative whole-brain total sodium concentration (TSC) maps in participants with ALS with those in control subjects and to localize regions of abnormal elevated TSC. Potential overlap of abnormal elevated TSC with regions of atrophy as detected with ¹H MRI also was investigated. Results Voxel-based statistical mapping analyses revealed higher sodium concentration in motor regions (bilateral precentral gyri, corticospinal tracts, and the corpus callosum) of participants with ALS (two-sample t test, P < .005; age and sex as covariates). In these regions, mean TSC was higher in participants with ALS (mean, 45.6 mmol/L wet tissue ± 3.2) than in control subjects (mean, 41.8 mmol/L wet tissue ± 2.7; P < .001; Cohen d = 1.28). Brain regions showing higher TSC represented a volume of 15.4 cm³ that did not overlap with gray matter atrophy occupying a volume of 16.9 cm³. Elevated TSC correlated moderately with corticospinal conduction failure assessed with transcranial magnetic stimulation in the right upper limb (Spearman ρ = -0.57; 95% confidence interval: -0.78, -0.16; P = .005; n = 23). Conclusion Quantitative ²³Na MRI is sensitive to alterations of brain sodium homeostasis within disease-relevant regions in patients with amyotrophic lateral sclerosis (ALS). This supports further investigation of abnormal sodium concentration as a potential marker of neurodegenerative processes in patients with ALS that could be used as a secondary endpoint in clinical trials. © RSNA, 2019 Online supplemental material is available for this article.

Are Circulating Cytokines Reliable Biomarkers for Amyotrophic Lateral Sclerosis?

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that has no effective treatment. The lack of any specific biomarker that can help in the diagnosis or prognosis of ALS has made the identification of biomarkers an urgent challenge. Multiple panels have shown alterations in levels of numerous cytokines in ALS, supporting the contribution of neuroinflammation to the progressive motor neuron loss. However, none of them is fully sensitive and specific enough to become a universal biomarker for ALS. This review gathers the numerous circulating cytokines that have been found dysregulated in both ALS animal models and patients. Particularly, it highlights the opposing results found in the literature to date, and points out another potential application of inflammatory cytokines as therapeutic targets.

Deterministic-tractography-based approach for diagnosis and disease monitoring of amyotrophic lateral sclerosis

OBJECTIVES

Upper and lower motor neuron signs are required for the diagnosis of amyotrophic lateral sclerosis. The detection of upper motor neuron signs is key for the diagnosis, as quite a few patients with amyotrophic lateral sclerosis lack upper motor neuron signs during the course of disease. This study sought to investigate whether deterministic tractography of the corticospinal tract, reflecting upper motor neuron signs, could be a surrogate biomarker for amyotrophic lateral sclerosis.

PATIENTS AND METHODS

Fifteen patients with amyotrophic lateral sclerosis and ten controls underwent imaging on a 3.0 T MRI. The corticospinal tract was reconstructed using deterministic tractography, and the track number was calculated. We analyzed the differences between the groups and the relationship between the track number and disease severity, disease duration, progression rate or upper motor neuron signs.

RESULTS

A reduction in the track number of the corticospinal tract was found in amyotrophic lateral sclerosis compared with controls (Student's t test, P =  0.008). The sensitivity and specificity were 0.67 and 0.9, respectively. The track number correlated with disease severity alone (r = 0.71, P =  0.003), and significantly associated with upper motor neuron signs (P =  0.004).

CONCLUSIONS

These findings suggest that the deterministic-tractography-based approach is a potential biomarker for the diagnosis and disease monitoring of amyotrophic lateral sclerosis.

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.

Positron Emission Tomography Molecular Imaging Biomarkers for Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with limited treatment options. Despite decades of therapeutic development, only two modestly efficacious disease-modifying drugs-riluzole and edaravone-are available to ALS patients. Biomarkers that can facilitate ALS diagnosis, aid in prognosis, and measure drug pharmacodynamics are needed to accelerate therapeutic development for patients with ALS. Positron emission tomography (PET) imaging has promise as a biomarker for ALS because it permits visualization of central nervous system (CNS) pathology in individuals living with ALS. The availability of PET radioligands that target a variety of potential pathophysiological mechanisms-including cerebral metabolism, neuroinflammation, neuronal dysfunction, and oxidative stress-has enabled dynamic interrogation of molecular changes in ALS, in both natural history studies and human clinical trials. PET imaging has potential as a diagnostic biomarker that can establish upper motor neuron (UMN) pathology in ALS patients without overt UMN symptoms, as a prognostic biomarker that might help stratify patients for clinical trials, and as a pharmacodynamic biomarker that measures the biological effect of investigational drugs in the brain and spinal cord. In this Review, we discuss progress made with 30 years of PET imaging studies in ALS and consider future research needed to establish PET imaging biomarkers for ALS therapeutic development.

Stochastic Rank Aggregation for the Identification of Functional Neuromarkers

The main challenge in analysing functional magnetic resonance imaging (fMRI) data from extended samples of subject (N > 100) is to extract as much relevant information as possible from big amounts of noisy data. When studying neurodegenerative diseases with resting-state fMRI, one of the objectives is to determine regions with abnormal background activity with respect to a healthy brain and this is often attained with comparative statistical models applied to single voxels or brain parcels within one or several functional networks. In this work, we propose a novel approach based on clustering and stochastic rank aggregation to identify parcels that exhibit a coherent behaviour in groups of subjects affected by the same disorder and apply it to default-mode network independent component maps from resting-state fMRI data sets. Brain voxels are partitioned into parcels through k-means clustering, then solutions are enhanced by means of consensus techniques. For each subject, clusters are ranked according to their median value and a stochastic rank aggregation method, TopKLists, is applied to combine the individual rankings within each class of subjects. For comparison, the same approach was tested on an anatomical parcellation. We found parcels for which the rankings were different among control subjects and subjects affected by Parkinson's disease and amyotrophic lateral sclerosis and found evidence in literature for the relevance of top ranked regions in default-mode brain activity. The proposed framework represents a valid method for the identification of functional neuromarkers from resting-state fMRI data, and it might therefore constitute a step forward in the development of fully automated data-driven techniques to support early diagnoses of neurodegenerative diseases.

Emerging Magnetic Resonance Imaging Techniques and Analysis Methods in Amyotrophic Lateral Sclerosis

Objective markers of disease sensitive to the clinical activity, symptomatic progression, and underlying substrates of neurodegeneration are highly coveted in amyotrophic lateral sclerosis in order to more eloquently stratify the highly heterogeneous phenotype and facilitate the discovery of effective disease modifying treatments for patients. Magnetic resonance imaging (MRI) is a promising, non-invasive biomarker candidate whose acquisition techniques and analysis methods are undergoing constant evolution in the pursuit of parameters which more closely represent biologically-applicable tissue changes. Neurite Orientation Dispersion and Density Imaging (NODDI; a form of diffusion imaging), and quantitative Magnetization Transfer Imaging (qMTi) are two such emerging modalities which have each broadened the understanding of other neurological disorders and have the potential to provide new insights into structural alterations initiated by the disease process in ALS. Furthermore, novel neuroimaging data analysis approaches such as Event-Based Modeling (EBM) may be able to circumvent the requirement for longitudinal scanning as a means to comprehend the dynamic stages of neurodegeneration in vivo. Combining these and other innovative imaging protocols with more sophisticated techniques to analyse ever-increasing datasets holds the exciting prospect of transforming understanding of the biological processes and temporal evolution of the ALS syndrome, and can only benefit from multicentre collaboration across the entire ALS research community.

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.

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.

Cord cross-sectional area at foramen magnum as a correlate of disability in amyotrophic lateral sclerosis

Spinal cord atrophy is one of the hallmarks of amyotrophic lateral sclerosis (ALS); however, it is not routinely assessed in routine clinical practice. In the present study, we evaluated whether spinal cord cross-sectional area measured at the foramen magnum level using a magnetic resonance imaging head scan represents a clinically meaningful measure to be added to the whole-brain volume assessment. Using an active surface approach, we measured the cord area at the foramen magnum and brain parenchymal fraction on T1-weighted three-dimensional spoiled gradient recalled head scans in two groups of subjects: 23 patients with ALS (males/females, 13/10; mean ± standard deviation [SD] age 61.7 ± 10.3 years; median ALS Functional Rating Scale-Revised score 39, range 27-46) and 18 age- and sex-matched healthy volunteers (mean ± SD age 55.7 ± 10.2 years). Spinal cord area at the foramen magnum was significantly less in patients than in control subjects and was significantly correlated with disability as measured with the ALS Functional Rating Scale-Revised (ρ = 0.593, p <  0.005). This correlation remained significant after taking into account inter-individual differences in brain parenchymal fraction (ρ = 0.684, p <  0.001). Our data show that spinal cord area at the foramen magnum correlates with disability in ALS independently of whole-brain atrophy, thus indicating its potential as a disease biomarker.

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.

Beyond fractional anisotropy in amyotrophic lateral sclerosis: the value of mean, axial, and radial diffusivity and its correlation with electrophysiological conductivity changes

PURPOSE

This paper aims to analyze the contribution of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in the detection of microstructural abnormalities in amyotrophic lateral sclerosis (ALS) and to evaluate the degree of agreement between structural and functional changes through concomitant diffusion tensor imaging (DTI), transcranial magnetic stimulation (TMS), and clinical assessment.

METHODS

Fourteen patients with ALS and 11 healthy, age- and gender-matched controls were included. All participants underwent magnetic resonance imaging including DTI. TMS was additionally performed in ALS patients. Differences in the distribution of DTI-derived measures were assessed using tract-based spatial statistical (TBSS) and volume of interest (VOI) analyses. Correlations between clinical, imaging, and neurophysiological findings were also assessed through TBSS.

RESULTS

ALS patients showed a significant increase in AD and MD involving the corticospinal tract (CST) and the pre-frontal white matter in the right posterior limb of the internal capsule (p < 0.05) when compared to the control group using TBSS, confirmed by VOI analyses. VOI analyses also showed increased AD in the corpus callosum (p < 0.05) in ALS patients. Fractional anisotropy (FA) in the right CST correlated significantly with upper motor neuron (UMN) score (r = - 0.79, p < 0.05), and right abductor digiti minimi central motor conduction time was highly correlated with RD in the left posterior internal capsule (r = - 0.81, p < 0.05). No other significant correlation was found.

CONCLUSION

MD, AD, and RD, besides FA, are able to further detect and characterize neurodegeneration in ALS. Furthermore, TMS and DTI appear to have a role as complementary diagnostic biomarkers of UMN dysfunction.

Increased cerebral functional connectivity in ALS: A resting-state magnetoencephalography study

Objective

We sought to assess cortical function in amyotrophic lateral sclerosis (ALS) using noninvasive neural signal recording.

Methods

Resting-state magnetoencephalography was used to measure power fluctuations in neuronal oscillations from distributed cortical parcels in 24 patients with ALS and 24 healthy controls. A further 9 patients with primary lateral sclerosis and a group of 15 asymptomatic carriers of genetic mutations associated with ALS were also studied.

Results

Increased functional connectivity, particularly from the posterior cingulate cortex, was demonstrated in both patient groups compared to healthy controls. Directionally similar patterns were also evident in the asymptomatic genetic mutation carrier group.

Conclusion

Increased cortical functional connectivity elevation is a quantitative marker that reflects ALS pathology across its clinical spectrum, and may develop during the presymptomatic period. The amelioration of pathologic magnetoencephalography signals might be a marker sensitive enough to provide proof-of-principle in the development of future neuroprotective therapeutics.

Regulatory-accepted drug development tools are needed to accelerate innovative CNS disease treatments

Central Nervous System (CNS) diseases represent one of the most challenging therapeutic areas for successful drug approvals. Developing quantitative biomarkers as Drug Development Tools (DDTs) can catalyze the path to innovative treatments, and improve the chances of drug approvals. Drug development and healthcare management requires sensitive, reliable, validated, and regulatory accepted biomarkers and endpoints. This review highlights the regulatory paths and considerations for developing DDTs required to advance biomarker and endpoint use in clinical development (e.g., consensus CDISC [Clinical Data Interchange Standards Consortium] data standards, precompetitive sharing of anonymized patient-level data, and continual alignment with regulators). Summarized is the current landscape of biomarkers in a range of CNS diseases including Alzheimer disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, Autism Spectrum Disorders, Depression, Huntington's disease, Multiple Sclerosis and Traumatic Brain Injury. Advancing DDTs for these devastating diseases that are both validated and qualified will require an integrated, cross-consortium approach to accelerate the delivery of innovative CNS therapeutics.

Synapse loss in the prefrontal cortex is associated with cognitive decline in amyotrophic lateral sclerosis

In addition to motor neurone degeneration, up to 50% of amyotrophic lateral sclerosis (ALS) patients present with cognitive decline. Understanding the neurobiological changes underlying these cognitive deficits is critical, as cognitively impaired patients exhibit a shorter survival time from symptom onset. Given the pathogenic role of synapse loss in other neurodegenerative diseases in which cognitive decline is apparent, such as Alzheimer’s disease, we aimed to assess synaptic integrity in the ALS brain. Here, we have applied a unique combination of high-resolution imaging of post-mortem tissue with neuropathology, genetic screening and cognitive profiling of ALS cases. Analyses of more than 1 million synapses using two complimentary high-resolution techniques (electron microscopy and array tomography) revealed a loss of synapses from the prefrontal cortex of ALS patients. Importantly, synapse loss was significantly greater in cognitively impaired cases and was not due to cortical atrophy, nor associated with dementia-associated neuropathology. Interestingly, we found a trend between pTDP-43 pathology and synapse loss in the frontal cortex and discovered pTDP-43 puncta at a subset of synapses in the ALS brains. From these data, we postulate that synapse loss in the prefrontal cortex represents an underlying neurobiological substrate of cognitive decline in ALS.

A review of cervical spine MRI in ALS patients

Rationale. In recent years, significant advances have been made on the subject of MRI examination techniques, which have opened new avenues of research regarding the spinal involvement in amyotrophic lateral sclerosis (ALS). Objective. Our objective was to compile and analyze the available literature data, concerning the MRI of the cervical spine in ALS, detailing the metrics and their significance in diagnosis and follow-up. Methods and results. We have conducted an extensive search on the subject using literature data published over the last fifteen years, correlating it with our own experience. In ALS, there is a permanent interest in developing new biomarkers that might be sensitive to spatial and temporal patterns of neurodegeneration, which will permit early diagnosis and hopefully lead to new therapeutic approaches. Both diffusion tensor imaging (DTI) and spinal cord morphometry (especially spinal atrophy) reflect different aspects of the disease and correlate with clinical deterioration. Newer approaches like inhomogeneous magnetization transfer (ihMTR) and multiparametric analysis seem to have better sensitivity, are more appropriate for follow-up, and lend themselves to prognostic conclusions. Discussion. We conclude that MRI is a constantly expanding field, a unique non-invasive tool with immense potential in evaluating the in vivo evolution of the neurodegenerative ALS process, both structurally and functionally, with high hopes for the future. Abbreviations: ALS - amyotrophic lateral sclerosis, UMN - upper motor neuron, LMN - lower motor neuron, EMG - electromyography, CST - cortico-spinal tract, FLAIR - fluid-attenuated inversion recovery, MND - motor neuron disease, DTI - Diffusion tensor imaging, FA - fractional anisotropy, MD - mean diffusivity, ihMTR - inhomogeneous magnetization transfer, fMRI - functional MRI.

The two-year progression of structural and functional cerebral MRI in amyotrophic lateral sclerosis

MRI has emerged as one of several urgently needed candidate disease progression biomarkers for the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), not least due to its unique ability to non-invasively assess structural and functional cerebral pathology. We sought to identify the extent of detectable change in cerebral MRI metrics over a more prolonged period.

Analysis of multi-modal MRI data was performed in a cohort of sixteen patients (13 ALS and 3 with primary lateral sclerosis) in whom it was possible to acquire six-monthly images over two years. Structural brain changes were assessed using voxel-based morphometry of grey matter and shape analysis of sub-cortical grey matter structures, tract-based spatial statistics of diffusion tensor imaging (DTI) metrics optimized for longitudinal analysis in the white matter, as well as whole brain voxel-wise statistics of DTI metrics. Changes in resting state functional MRI (rs-fMRI) were investigated via independent component and dual regression analyses of functional connectivity (FC), controlled for confounding effects of grey matter decline. Both linear changes with time and brain changes correlated with revised ALS functional rating score (ALSFRS-R) decline were studied.

Widespread and progressive reductions in grey matter were observed in the precentral gyri and posterior cingulate cortex, as well as progressive local atrophy of the thalamus, caudate, and pallidum bilaterally, and right putamen, hippocampus and amygdala. The most prominent DTI tract-based changes were in the superior longitudinal fasciculi and corpus callosum. More widespread areas of DTI changes included the thalami and caudate nuclei, hippocampi and parahippocampal gyri, insular cortices, anterior and posterior cingulate gyri, frontal operculum and cerebellum. FC decreases were noted between the sensorimotor resting state network and the frontal pole, between a network comprising both thalami and an area in the visual cortex, in relation to both time from baseline and ALSFRS-R decline. FC increases between the left primary motor cortex and left fronto-parietal network were seen for both statistical approaches.

A longer period of follow-up, though necessarily involving more slowly-progressive cases, demonstrated widespread changes in both grey and white matter structural MRI measures. The mixed picture of regional decreases and increases in FC is compatible with compensatory change, in what should be viewed as a brain-based disease characterised by larger-scale disintegration of motor and frontal projection cerebral networks.

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Analysis of serial MRI data (6-monthly over 2 years) was performed in ALS patients.

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Widespread progressive structural and functional brain changes were observed.

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Changes during this unprecedented study period involved basal ganglia regions.

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The results revealed novel longitudinal functional connectivity insights.