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

Myelin measurement in amyotrophic lateral sclerosis with synthetic MRI: A potential diagnostic and predictive method

BACKGROUND

Myelin damage has recently been highlighted as a major causative factor of amyotrophic lateral sclerosis (ALS). Although myelin damage has been pathologically identified in ALS, it has not been clinically evaluated. This study aimed to quantify myelin volume using synthetic MRI to evaluate myelin damage in patients with ALS, and determine its association with clinical parameters.

METHODS

We evaluated patients with ALS (n = 35) and individuals (n = 16) without intracranial disease using synthetic magnetic resonance imaging (MRI) and measured total myelin volume (TMV), myelin fraction (MYF), and myelin partial volume (VMY) in the cerebral peduncle and the posterior limb of the internal capsule (PLIC). We also investigated factors associated with acquired quantitative values.

RESULTS

The TMV was significantly lower in the patients with ALS than in the control group (P = 0.045). The TMV (r = 0.42, P = 0.013) and MYF (r = 0.34, P = 0.047) significantly correlated with Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) scores in the patients, and MYF was independent of the traditional white matter lesion grading score. The VMY of the PLIC was significantly lower in the ALS than the control group (P = 0.018), and the ALS group significantly correlated with ALSFRS-R scores (r = 0.36, P = 0.033).

CONCLUSIONS

Myelin damage can be quantified by synthetic MRI as reduced myelin volume, with the possibility of predicting prognoses in patients with ALS. Furthermore, myelin measurements in the PLIC might be a novel diagnostic marker for ALS.

Surface-based Analyses of Diffusional Kurtosis Imaging in Amyotrophic Lateral Sclerosis: Relationship with Onset Subtypes

PURPOSE

Here, we aimed to characterize the cortical and subcortical microstructural alterations in the brains of patients with amyotrophic lateral sclerosis (ALS). In particular, we compared these features between bulbar-onset ALS (b-ALS) and limb-onset ALS (l-ALS).

METHODS

Diffusion MRI data (b = 0, 700, 2000 ms/mm2, 1.7-mm isotropic voxel) from 28 patients with ALS (9 b-ALS and 19 l-ALS) and 17 healthy control subjects (HCs) were analyzed. Diffusional kurtosis imaging (DKI) metrics were sampled at the mid-cortical and subcortical surfaces. We used permutation testing with a nonparametric combination of mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) to assess intergroup differences over the cerebrum. We also carried out an atlas-based analysis focusing on Brodmann Area 4 and 6 (primary motor and premotor areas) and investigated the correlation between MRI metrics and clinical parameters.

RESULTS

At both the mid-cortical and subcortical surfaces, b-ALS was associated with significantly greater MD, smaller FA, and smaller MK in the motor and premotor areas than HC. In contrast, the patients with l-ALS showed relatively moderate differences relative to HCs. The ALS Functional Rating Scale-Revised bulbar subscore was significantly correlated with the diffusion metrics in Brodmann Area 4.

CONCLUSION

The distribution of abnormalities over the cerebral hemispheres and the more severe microstructural alteration in b-ALS compared to l-ALS were in good agreement with findings from postmortem histology. Our results suggest the feasibility of surface-based DKI analyses for exploring brain microstructural pathologies in ALS. The observed differences between b-ALS and l-ALS and their correlations with functional bulbar impairment support the clinical relevance of DKI measurement in the cortical and juxtacortical regions of patients with ALS.

Assessment of Cerebral White Matter Involvement in Amyotrophic Lateral Sclerosis Patients With Disease Progression and Cognitive Impairment by Fixel-Based Analysis and Neurite Orientation Dispersion and Density Imaging

BACKGROUND

Previous studies using emerging diffusion MRI techniques have revealed damage to the white matter (WM) microstructure in amyotrophic lateral sclerosis (ALS), particularly the influence of crossed fibers, but there is a lack of subgroup analyses.

PURPOSE

To detect WM microstructural changes in ALS patients using fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI) MRI.

STUDY TYPE

Prospective.

POPULATION

Thirty-six ALS patients (aged 60.50 ± 9.5 years) and 25 healthy controls (HCs) (aged 58.90 ± 8.1 years).

FIELD STRENGTH/SEQUENCE

3 T; NODDI and FBA (b-values = 0, 1000, and 2500 seconds/mm2).

ASSESSMENT

Subgroups were performed according to progression rate and cognition, including fast and slow progression (FP/SP), ALS with and without cognitive impairment (ALS-ci/ALS-nci). Fiber density (FD), fiber-bundle cross-section (FC), combined fiber density and cross-section (FDC), neurite density index (NDI), orientation dispersion index (ODI), isotropic volume fraction (ISO), and fractional anisotropy (FA) were calculated and their correlation with clinical variables examined.

STATISTICAL TESTING

Chi-square test, Mann-Whitney U test, two-sample t test, partial correlation analysis, and false discovery rate (FDR) corrected. A P-value <0.05 was considered significant.

RESULTS

ALS patients had lower FD and FDC values predominantly in the corticospinal tract (CST) and corpus callosum (CC) regions, as well as lower NDI value in the CC, radial crown, and internal capsule compared to HCs. Subgroup analysis based on progression rate and cognitive function showed significant differences in FBA results. The FC in the right CST region was significantly lower in the FP than SP, and the FD in the CC region was significantly lower in the ALS-ci than ALS-nci. Furthermore, a negative correlation was found between the mean FC value and the rate of progression in ALS patients (r = -0.408).

DATA CONCLUSION

FBA is a powerful tool for detecting complex cerebral WM microstructural damage for evaluating ALS cognition and disease progression.

Diffusion tensor imaging biomarkers and clinical assessments in amyotrophic lateral sclerosis (ALS) patients: an exploratory study

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive loss of upper and lower motor neurons. Biomarkers are needed to improve diagnosis, gauge progression, and evaluate treatment. Diffusion tensor imaging (DTI) is a promising biomarker for detecting microstructural alterations in the white matter tracts. This study aimed to assess DTI metrics as biomarkers and to examine their relationship with clinical assessments in patients with ALS. Eleven patients with ALS and 21 healthy controls (HCs) underwent 3T MRI with DTI. DTI metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), were compared between key motor and extra-motor tract groups. Group comparisons and correlations between DTI metrics also correlated with clinical scores of disability (ALSFRS-R), muscle strength (dynamometry), and motor unit loss (MUNIX). Widespread differences were found between patients with ALS and HCs in DTI metrics, including decreased FA and increased diffusivity metrics. However, MD and RD are more sensitive metrics for detecting white matter changes in patients with ALS. Significant interhemispheric correlations between the tract DTI metrics were also observed. DTI metrics showed symmetry between the hemispheres and correlated with the clinical assessments. MD, RD, and AD increases significantly correlated with lower ALSFRS-R and MUNIX scores and weaker dynamometry results. DTI reveals microstructural damage along the motor and extra-motor regions in ALS patients. DTI metrics can serve as quantitative neuroimaging biomarkers for diagnosis, prognosis, monitoring of progression, and treatment. Combined analysis of imaging, electrodiagnostic, and functional biomarkers shows potential for characterizing disease pathophysiology and progression.

ComBating inter-site differences in field strength: harmonizing preclinical traumatic brain injury MRI data

Integrating datasets from multiple sites and scanners can increase statistical power for neuroimaging studies but can also introduce significant inter-site confounds. We evaluated the effectiveness of ComBat, an empirical Bayes approach, to combine longitudinal preclinical MRI data acquired at 4.7 or 9.4 T at two different sites in Australia. Male Sprague Dawley rats underwent MRI on Days 2, 9, 28, and 150 following moderate/severe traumatic brain injury (TBI) or sham injury as part of Project 1 of the NIH/NINDS-funded Centre Without Walls EpiBioS4Rx project. Diffusion-weighted and multiple-gradient-echo images were acquired, and outcomes included QSM, FA, and ADC. Acute injury measures including apnea and self-righting reflex were consistent between sites. Mixed-effect analysis of ipsilateral and contralateral corpus callosum (CC) summary values revealed a significant effect of site on FA and ADC values, which was removed following ComBat harmonization. Bland-Altman plots for each metric showed reduced variability across sites following ComBat harmonization, including for QSM, despite appearing to be largely unaffected by inter-site differences and no effect of site observed. Following harmonization, the combined inter-site data revealed significant differences in the imaging metrics consistent with previously reported outcomes. TBI resulted in significantly reduced FA and increased susceptibility in the ipsilateral CC, and significantly reduced FA in the contralateral CC compared with sham-injured rats. Additionally, TBI rats also exhibited a reversal in ipsilateral CC ADC values over time with significantly reduced ADC at Day 9, followed by increased ADC 150 days after injury. Our findings demonstrate the need for harmonizing multi-site preclinical MRI data and show that this can be successfully achieved using ComBat while preserving phenotypical changes due to TBI.

Temporal and spatial progression of microstructural cerebral degeneration in ALS: A multicentre longitudinal diffusion tensor imaging study

OBJECTIVE

The corticospinal tract (CST) reveals progressive microstructural alterations in ALS measurable by DTI. The aim of this study was to evaluate fractional anisotropy (FA) along the CST as a longitudinal marker of disease progression in ALS.

METHODS

The study cohort consisted of 114 patients with ALS and 110 healthy controls from the second prospective, longitudinal, multicentre study of the Canadian ALS Neuroimaging Consortium (CALSNIC-2). DTI and clinical data from a harmonized protocol across 7 centres were collected. Thirty-nine ALS patients and 61 controls completed baseline and two follow-up visits and were included for longitudinal analyses. Whole brain-based spatial statistics and hypothesis-guided tract-of-interest analyses were performed for cross-sectional and longitudinal analyses.

RESULTS

FA was reduced at baseline and longitudinally in the CST, mid-corpus callosum (CC), frontal lobe, and other ALS-related tracts, with alterations most evident in the CST and mid-CC. CST and pontine FA correlated with functional impairment (ALSFRS-R), upper motor neuron function, and clinical disease progression rate. Reduction in FA was largely located in the upper CST; however, the longitudinal decline was greatest in the lower CST. Effect sizes were dependent on region, resulting in study group sizes between 17 and 31 per group over a 9-month interval. Cross-sectional effect sizes were maximal in the upper CST; whereas, longitudinal effect sizes were maximal in mid-callosal tracts.

CONCLUSIONS

Progressive microstructural alterations in ALS are most prominent in the CST and CC. DTI can provide a biomarker of cerebral degeneration in ALS, with longitudinal changes in white matter demonstrable over a reasonable observation period, with a feasible number of participants, and within a multicentre framework.

Bidirectional two-sample Mendelian randomization analyses support causal relationships between structural and diffusion imaging-derived phenotypes and the risk of major neurodegenerative diseases

Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer's disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.

Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing

Neuroimaging biomarkers have shown high potential to map the disease processes in the application to neurodegenerative diseases (NDD), e.g., diffusion tensor imaging (DTI). For DTI, the implementation of a standardized scanning and analysis cascade in clinical trials has potential to be further optimized. Over the last few years, various approaches to improve DTI applications to NDD have been developed. The core issue of this review was to address considerations and limitations of DTI in NDD: we discuss suggestions for improvements of DTI applications to NDD. Based on this technical approach, a set of recommendations was proposed for a standardized DTI scan protocol and an analysis cascade of DTI data pre-and postprocessing and statistical analysis. In summary, considering advantages and limitations of the DTI in NDD we suggest improvements for a standardized framework for a DTI-based protocol to be applied to future imaging studies in NDD, towards the goal to proceed to establish DTI as a biomarker in clinical trials in neurodegeneration.

Impact of follow ups, time interval and study duration in diffusion & myelin MRI clinical study in MS

It is currently unknown how quantitative diffusion and myelin MRI designs affect the results of a longitudinal study. We used two independent datasets containing 6 monthly MRI measurements from 20 healthy controls and 20 relapsing-remitting multiple sclerosis (RR-MS) patients. Six designs were tested, including 3 MRI acquisitions, either over 6 months or over a shorter study duration, with balanced (same interval) or unbalanced (different interval) time intervals between MRI acquisitions. First, we show that in RR-MS patients, the brain changes over time obtained with 3 MRI acquisitions were similar to those observed with 5 MRI acquisitions and that designs with an unbalanced time interval showed the highest similarity, regardless of study duration. No significant brain changes were found in the healthy controls over the same periods. Second, the study duration affects the sample size in the RR-MS dataset; a longer study requires more subjects and vice versa. Third, the number of follow-up acquisitions and study duration affect the sensitivity and specificity of the associations with clinical parameters, and these depend on the white matter bundle and MRI measure considered. Together, this suggests that the optimal design depends on the assumption of the dynamics of change in the target population and the accuracy required to capture these dynamics. Thus, this work provides a better understanding of key factors to consider in a longitudinal study and provides clues for better strategies in clinical trial design.

Structural and microstructural neuroimaging signature of C9orf72-associated ALS: A multiparametric MRI study

BACKGROUND

ALS patients with hexanucleotide expansion in C9orf72 are characterized by a specific clinical phenotype, including more aggressive disease course and cognitive decline. Computerized multiparametric MRI with gray matter volumetry and diffusion tensor imaging (DTI) to analyze white matter structural connectivity is a potential in vivo biomarker.

OBJECTIVE

The objective of this study was to develop a multiparametric MRI signature in a large cohort of ALS patients with C9orf72 mutations. The aim was to investigate how morphological features of C9orf72-associated ALS differ in structural MRI and DTI compared to healthy controls and ALS patients without C9orf72 mutations.

METHODS

Atlas-based volumetry (ABV) and whole brain-based DTI-based analyses were performed in a cohort of n = 51 ALS patients with C9orf72 mutations and compared with both n = 51 matched healthy controls and n = 51 C9orf72 negative ALS patients, respectively. Subsequently, Spearman correlation analysis of C9orf72 ALS patients' data with clinical parameters (age of onset, sex, ALS-FRS-R, progression rate, survival) as well as ECAS and p-NfH in CSF was performed.

RESULTS

The whole brain voxel-by-voxel comparison of fractional anisotropy (FA) maps between C9orf72 ALS patients and controls showed significant bilateral alterations in axonal structures of the white matter at group level, primarily along the corticospinal tracts and in fibers projecting to the frontal lobes. For the frontal lobes, these alterations were also significant between C9orf72 positive and C9orf72 negative ALS patients. In ABV, patients with C9orf72 mutations showed lower volumes of the frontal, temporal, and parietal lobe, with the lowest values in the gray matter of the superior frontal and the precentral gyrus, but also in hippocampi and amygdala. Compared to C9orf72 negative ALS, the differences were shown to be significant for cerebral gray matter (p = 0.04), especially in the frontal (p = 0.01) and parietal lobe (p = 0.01), and in the thalamus (p = 0.004). A correlation analysis between ECAS and averaged regional FA values revealed significant correlations between cognitive performance in ECAS and frontal association fibers. Lower FA values in the frontal lobes were associated with worse performance in all cognitive domains measured (language, verbal fluency, executive functions, memory and spatial perception). In addition, there were significant negative correlations between age of onset and atlas-based volumetry results for gray matter.

CONCLUSIONS

This study demonstrates a distinct pattern of DTI alterations of the white matter and ubiquitous volume reductions of the gray matter early in the disease course of C9orf72-associated ALS. Alterations were closely linked to a more aggressive cognitive phenotype. These results are in line with an expected pTDP43 propagation pattern of cortical affection and thus strengthen the hypothesis that an underlying developmental disorder is present in ALS with C9orf72 expansions. Thus, multiparametric MRI could contribute to the assessment of the disease as an in vivo biomarker even in the early phase of the disease.

Sleep disorders and white matter integrity in patients with sporadic amyotrophic lateral sclerosis

This study aimed to explore the characteristics of sleep disorders and their relationship with abnormal white-matter integrity in patients with sporadic amyotrophic lateral sclerosis. One hundred and thirty-six patients and 80 healthy controls were screened consecutively, and 56 patients and 43 healthy controls were ultimately analyzed. Sleep disorders were confirmed using the Pittsburgh sleep quality index, the Epworth sleepiness scale, and polysomnography; patients were classified into those with poor and good sleep quality. White-matter integrity was assessed using diffusion tensor imaging and compared between groups to identify the white-matter tracts associated with sleep disorders. The relationship between scores on the Pittsburgh sleep quality index and impaired white-matter tracts was analyzed using multiple regression. Poor sleep quality was more common in patients (adjusted odds ratio, 4.26; p = 0.005). Compared to patients with good sleep quality (n = 30), patients with poor sleep quality (n = 26; 46.4%) showed decreased fractional anisotropy, increased mean diffusivity, and increased radial diffusivity of projection and commissural fibers, and increased radial diffusivity of the right thalamus. The Pittsburgh score showed the best fit with the mean fractional anisotropy of the right anterior limb of the internal capsule (r = - 0.355, p = 0.011) and the mean radial diffusivity of the right thalamus (r = 0.309, p = 0.028). We conclude that sleep disorders are common in patients with sporadic amyotrophic lateral sclerosis and are associated with reduced white-matter integrity. The pathophysiology of amyotrophic lateral sclerosis may contribute directly to sleep disorders.

Brain imaging signatures in amyotrophic lateral sclerosis: Correlation with peripheral motor degeneration

OBJECTIVE

This study aimed to explore the clinical significance of brain imaging signatures in the context of clinical neurological deficits in association with upper and lower motor neuron degeneration in amyotrophic lateral sclerosis (ALS).

METHODS

We performed brain MRI examinations to quantitatively evaluate (1) gray matter volume and (2) white matter tract fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Image-derived indices were correlated with (1) global neurological deficits of MRC muscle strength sum score, revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R), and forced vital capacity (FVC), and (2) focal scores of University of Pennsylvania Upper motor neuron score (Penn score) and the summation of compound muscle action potential Z scores (CMAP Z sum score).

RESULTS

There were 39 ALS patients and 32 control subjects matched for age and gender. Compared to controls, ALS patients had a lower gray matter volume in the precentral gyrus of the primary motor cortex, which was correlated with FA of corticofugal tracts. The gray matter volume of the precentral gyrus was correlated with FVC, MRC sum score, and CMAP Z sum score, while the FA of the corticospinal tract was linearly associated with CMAP Z sum score and Penn score on multivariate linear regression model.

INTERPRETATION

This study indicated that clinical assessment of muscle strength and routine measurements on nerve conduction studies provided surrogate markers of brain structural changes for ALS. Furthermore, these findings suggested parallel involvement of both upper and lower motor neurons in ALS.

Sequential alterations in diffusion metrics as correlates of disease severity in amyotrophic lateral sclerosis

BACKGROUND AND OBJECTIVE

The neuropathology of amyotrophic lateral sclerosis (ALS) follows a regional distribution pattern in the brain with four stages. Using diffusion tensor imaging (DTI), this pattern can be translated into a tract-based staging scheme to assess cerebral progression in vivo. This study investigates the association between the sequential alteration pattern and disease severity in patients with ALS.

METHODS

DTI data of 325 patients with ALS and 130 healthy controls were analyzed in a tract of interest (TOI)-based approach. Patients were categorized according to their ALS-FRS-R scores into groups with declining functionality. The fractional anisotropy (FA) values in the tracts associated with neuropathological stages were group-wise compared with healthy controls.

RESULTS

The FA in the tracts associated with ALS stages showed a decrease which could be related to the disease severity stratification, i.e., at the group level, the lower the ALS-FRS-R of the categorized patient group, the higher was the effect size of the stage-related tract. In the patient group with the highest ALS-FRS-R, Cohen's d showed a medium effect size in the corticospinal tract and small effect sizes in the other stage-related tracts. Overall, the lower the ALS-FRS-R of the categorized patient group the higher was the effect size of the comparison with healthy controls.

CONCLUSION

The progression of white matter alterations across tracts according to the model of sequential tract involvement is associated with clinical disease severity in patients with ALS, suggesting the use of staging-based DTI as a technical marker for disease progression.

CAPTURE ALS: the comprehensive analysis platform to understand, remedy and eliminate ALS

The absence of disease modifying treatments for amyotrophic lateral sclerosis (ALS) is in large part a consequence of its complexity and heterogeneity. Deep clinical and biological phenotyping of people living with ALS would assist in the development of effective treatments and target specific biomarkers to monitor disease progression and inform on treatment efficacy. The objective of this paper is to present the Comprehensive Analysis Platform To Understand Remedy and Eliminate ALS (CAPTURE ALS), an open and translational platform for the scientific community currently in development. CAPTURE ALS is a Canadian-based platform designed to include participants' voices in its development and through execution. Standardized methods will be used to longitudinally characterize ALS patients and healthy controls through deep clinical phenotyping, neuroimaging, neurocognitive and speech assessments, genotyping and multisource biospecimen collection. This effort plugs into complementary Canadian and international initiatives to share common resources. Here, we describe in detail the infrastructure, operating procedures, and long-term vision of CAPTURE ALS to facilitate and accelerate translational ALS research in Canada and beyond.

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS

OBJECTIVES

To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS).

METHODS

Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed.

RESULTS

ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance.

CONCLUSIONS

Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation.

KEY POINTS

• Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

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.

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.

Neuropathology and neuroanatomy of TDP-43 amyotrophic lateral sclerosis

PURPOSE OF REVIEW

Intracellular inclusions consisting of the abnormal TDP-43 protein and its nucleocytoplasmic mislocalization in selected cell types are hallmark pathological features of sALS. Descriptive (histological, morphological), anatomical, and molecular studies all have improved our understanding of the neuropathology of sporadic amyotrophic lateral sclerosis (sALS). This review highlights some of the latest developments in the field.

RECENT FINDINGS

Increasing evidence exists from experimental models for the prion-like nature of abnormal TDP-43, including a strain-effect, and with the help of neuroimaging-based studies, for spreading of disease along corticofugal connectivities in sALS. Progress has also been made with respect to finding and establishing reliable biomarkers (neurofilament levels, diffusor tensor imaging).

SUMMARY

The latest findings may help to elucidate the preclinical phase of sALS and to define possible mechanisms for delaying or halting disease development and progression.

Microstructural changes of the vestibulocochlear nerve in patients with Ménière's disease using diffusion tensor imaging

Objective

To evaluate the microstructural changes of the vestibulocochlear nerve in patients with Ménière's disease.

Methods

A total of 26 subjects, 13 patients with MD and 13 healthy controls, underwent diffusion tensor imaging (DTI) on a 3T scanner. The independent sample t-test was used to compare the differences in fractional anisotropy (FA) and apparent diffusion coefficient (ADC) between the two groups. A Pearson correlation was used between DTI and the dizziness handicap inventory (DHI) scores.

Results

There was a significant decrease in FA and an increase in ADC of the vestibulocochlear nerve in MD patients compared with healthy controls (P = 0.04, P = 0.001). FA had negative correlations with the DHI score (r = −0.62, P = 0.02) and DHI-functional score (r = −0.64, P = 0.02).

Conclusion

These results are the first evidence of possible changes in the microstructure of the vestibulocochlear nerves in patients with MD. DTI is a potential technique for evaluating the vestibulocochlear nerve in patients with MD.

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.

Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness

There is a growing demand for reliable biomarkers to monitor disease progression in Amyotrophic Lateral Sclerosis (ALS) that also take the heterogeneity of ALS into account. In this study, we explored the association between Magnetic Resonance Imaging (MRI)-derived measures of cortical thickness (CT) and subcortical grey matter (GM) volume with D50 model parameters. T1-weighted MRI images of 72 Healthy Controls (HC) and 100 patients with ALS were analyzed using Surface-based Morphometry for cortical structures and Voxel-based Morphometry for subcortical Region-Of-Interest analyses using the Computational Anatomy Toolbox (CAT12). In Inter-group contrasts, these parameters were compared between patients and HC. Further, the D50 model was used to conduct subgroup-analyses, dividing patients by a) Phase of disease covered at the time of MRI-scan and b) individual overall disease aggressiveness. Finally, correlations between GM and D50 model-derived parameters were examined. Inter-group analyses revealed ALS-related cortical thinning compared to HC located mainly in frontotemporal regions and a decrease in GM volume in the left hippocampus and amygdala. A comparison of patients in different phases showed further cortical and subcortical GM atrophy along with disease progression. Correspondingly, regression analyses identified negative correlations between cortical thickness and individual disease covered. However, there were no differences in CT and subcortical GM between patients with low and high disease aggressiveness. By application of the D50 model, we identified correlations between cortical and subcortical GM atrophy and ALS-related functional disability, but not with disease aggressiveness. This qualifies CT and subcortical GM volume as biomarkers representing individual disease covered to monitor therapeutic interventions in ALS.

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.

Relaxation-weighted 23Na magnetic resonance imaging maps regional patterns of abnormal sodium concentrations in amyotrophic lateral sclerosis

Objectives:

Multiparametric magnetic resonance imaging (MRI) is established as a technical instrument for the characterisation of patients with amyotrophic lateral sclerosis (ALS). The contribution of relaxation-weighted sodium (²³NaR) MRI remains to be defined. The aim of this study is to apply ²³NaR MRI to investigate brain sodium homeostasis and map potential alterations in patients with ALS as compared with healthy controls.

Materials and Methods:

Seventeen patients with ALS (mean age 61.1 ± 11.4 years, m/f = 9/8) and 10 healthy control subjects (mean age 60.3 ± 15.3 years, m/f = 6/4) were examined by ²³NaR MRI at 3 T. Regional sodium maps were obtained by the calculation of the weighted difference from two image data sets with different echo times (TE₁ = 0.3 ms, TE₂ = 25 ms). Voxel-based analysis of the relaxation-weighted maps, together with ²³Na concentration maps for comparison, was performed.

Results:

ROI-based analyses of relaxation-weighted brain sodium concentration maps demonstrated increased sodium concentrations in the upper corticospinal tracts and in the frontal lobes in patients with ALS; no differences between ALS patients and controls were found in reference ROIs, where no involvement in ALS-associated neurodegeneration could be anticipated.

Conclusion:

²³NaR MRI mapped regional alterations within disease-relevant areas in ALS which correspond to the stages of the central nervous system (CNS) pathology, providing evidence that the technique is a potential biological marker of the cerebral neurodegenerative process in ALS.

A multivariate Bayesian classification algorithm for cerebral stage prediction by diffusion tensor imaging in amyotrophic lateral sclerosis

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Novel DTI-based classification of ALS disease stages by a Bayesian approach is applied.

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Bayesian classification algorithm improves threshold-based staging method.

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Step forward in MRI-based patient stratification in ALS in vivo.

Background and Objective

Diffusion tensor imaging (DTI) can be used to tract-wise map correlates of the sequential disease progression and, therefore, to assess disease stages of amyotrophic lateral sclerosis (ALS) in vivo. According to a threshold-based sequential scheme, a classification of ALS patients into disease stages is possible, however, several patients cannot be staged for methodological reasons. This study aims to implement a multivariate Bayesian classification algorithm for disease stage prediction at an individual ALS patient level based on DTI metrics of involved tract systems to improve disease stage mapping.

Methods

The analysis of fiber tracts involved in each stage of ALS was performed in 325 ALS patients and 130 age- and gender-matched healthy controls. Based on Bayes’ theorem and in accordance with the sequential disease progression, a multistage classifier was implemented. Patients were categorized into in vivo DTI stages using the threshold-based method and the Bayesian algorithm. By the margin of confidence, the reliability of the Bayesian categorizations was accessible.

Results

Based on the Bayesian multistage classifier, 88% of all ALS patients could be assigned into an ALS stage compared to 77% using the threshold-based staging scheme. Additionally, the confidence of all classifications could be estimated.

Conclusions

By the application of the multi-stage Bayesian classifier, an individualized in vivo cerebral staging of ALS patients was possible based on the sequentially involved tract systems and, furthermore, the reliability of the respective classifications could be determined. The Bayesian classification algorithm is an improvement of the threshold-based staging method and could provide a framework for extending the DTI-based in vivo cerebral staging in ALS.

Multimodal in vivo staging in amyotrophic lateral sclerosis using artificial intelligence

Background

The underlying neuropathological process of amyotrophic lateral sclerosis (ALS) can be classified in a four‐stage sequential pTDP‐43 cerebral propagation scheme. Using diffusion tensor imaging (DTI), in vivo imaging of these stages has already been shown to be feasible for the specific corticoefferent tract systems. Because both cognitive and oculomotor dysfunctions are associated with microstructural changes at the brain level in ALS, a cognitive and an oculomotor staging classification were developed, respectively. The association of these different in vivo staging schemes has not been attempted to date.

Methods

A total of 245 patients with ALS underwent DTI, video‐oculography, and cognitive testing using Edinburgh Cognitive and Behavioral ALS Screen (ECAS). A set of tract‐related diffusion metrics, cognitive, and oculomotor parameters was selected for further analysis. Hierarchical and k‐means clustering algorithms were used to obtain an optimal cluster solution.

Results

According to cluster analysis, differentiation of patients with ALS into four clusters resulted: Cluster A showed the highest fractional anisotropy (FA) values and thereby the best performances in executive oculomotor tasks and cognitive tests, whereas cluster D showed the lowest FA values, the lowest ECAS scores, and the worst executive oculomotor performance across all clusters. Clusters B and C showed intermediate results regarding parameter values.

Discussion

In a multimodal dataset of technical assessments of brain structure and function in ALS, an artificial intelligence‐based cluster analysis showed high congruence of DTI, executive oculomotor function, and neuropsychological performance for mapping in vivo correlates of neuropathological spreading.

Segmental alterations of the corpus callosum in motor neuron disease: A DTI and texture analysis in 575 patients

INTRODUCTION

Within the core neuroimaging signature of amyotrophic lateral sclerosis (ALS), the corpus callosum (CC) is increasingly recognized as a consistent feature. The aim of this study was to investigate the sensitivity and specificity of the microstructural segmental CC morphology, assessed by diffusion tensor imaging (DTI) and high-resolution T1-weighted (T1w) imaging, in a large cohort of ALS patients including different clinical phenotypes.

METHODS

In a single-centre study, 575 patients with ALS (classical phenotype, N  = 432; restricted phenotypes primary lateral sclerosis (PLS) N = 55, flail arm syndrome (FAS) N = 45, progressive bulbar palsy (PBP) N = 22, lower motor neuron disease (LMND) N = 21) and 112 healthy controls underwent multiparametric MRI, i.e. volume-rendering T1w scans and DTI. Tract-based fractional anisotropy statistics (TFAS) was applied to callosal tracts of CC areas I-V, identified from DTI data (tract-of-interest (TOI) analysis), and texture analysis was applied to T1w data. In order to further specify the callosal alterations, a support vector machine (SVM) algorithm was used to discriminate between motor neuron disease patients and controls.

RESULTS

The analysis of white matter integrity revealed predominantly FA reductions for tracts of the callosal areas I, II, and III (with highest reductions in callosal area III) for all ALS patients and separately for each phenotype when compared to controls; texture analysis demonstrated significant alterations of the parameters entropy and homogeneity for ALS patients and all phenotypes for the CC areas I, II, and III (with again highest reductions in callosal area III) compared to controls. With SVM applied on multiparametric callosal parameters of area III, a separation of all ALS patients including phenotypes from controls with 72% sensitivity and 73% specificity was achieved. These results for callosal area III parameters could be improved by an SVM of six multiparametric callosal parameters of areas I, II, and III, achieving a separation of all ALS patients including phenotypes from controls with 84% sensitivity and 85% specificity.

DISCUSSION

The multiparametric MRI texture and DTI analysis demonstrated substantial alterations of the frontal and central CC with most significant alterations in callosal area III (motor segment) in ALS and separately in all investigated phenotypes (PLS, FAS, PBP, LMND) in comparison to controls, while no significant differences were observed between ALS and its phenotypes. The combination of the texture and the DTI parameters in an unbiased SVM-based approach might contribute as a neuroimaging marker for the assessment of the CC in ALS, including subtypes.

Recent advances in the diagnosis and prognosis of amyotrophic lateral sclerosis

The diagnosis of amyotrophic lateral sclerosis can be challenging due to its heterogeneity in clinical presentation and overlap with other neurological disorders. Diagnosis early in the disease course can improve outcomes as timely interventions can slow disease progression. An evolving awareness of disease genotypes and phenotypes and new diagnostic criteria, such as the recent Gold Coast criteria, could expedite diagnosis. Improved prognosis, such as that achieved with the survival model from the European Network for the Cure of ALS, could inform the patient and their family about disease course and improve end-of-life planning. Novel staging and scoring systems can help monitor disease progression and might potentially serve as clinical trial outcomes. Lastly, new tools, such as fluid biomarkers, imaging modalities, and neuromuscular electrophysiological measurements, might increase diagnostic and prognostic accuracy.

The Digital Brain Bank, an open access platform for post-mortem imaging datasets

Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

Pathophysiological Underpinnings of Extra-Motor Neurodegeneration in Amyotrophic Lateral Sclerosis: New Insights From Biomarker Studies

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) lie at opposing ends of a clinical, genetic, and neuropathological continuum. In the last decade, it has become clear that cognitive and behavioral changes in patients with ALS are more frequent than previously recognized. Significantly, these non-motor features can impact the diagnosis, prognosis, and management of ALS. Partially overlapping neuropathological staging systems have been proposed to describe the distribution of TAR DNA-binding protein 43 (TDP-43) aggregates outside the corticospinal tract. However, the relationship between TDP-43 inclusions and neurodegeneration is not absolute and other pathophysiological processes, such as neuroinflammation (with a prominent role of microglia), cortical hyperexcitability, and synaptic dysfunction also play a central role in ALS pathophysiology. In the last decade, imaging and biofluid biomarker studies have revealed important insights into the pathophysiological underpinnings of extra-motor neurodegeneration in the ALS-FTLD continuum. In this review, we first summarize the clinical and pathophysiological correlates of extra-motor neurodegeneration in ALS. Next, we discuss the diagnostic and prognostic value of biomarkers in ALS and their potential to characterize extra-motor neurodegeneration. Finally, we debate about how biomarkers could improve the diagnosis and classification of ALS. Emerging imaging biomarkers of extra-motor neurodegeneration that enable the monitoring of disease progression are particularly promising. In addition, a growing arsenal of biofluid biomarkers linked to neurodegeneration and neuroinflammation are improving the diagnostic accuracy and identification of patients with a faster progression rate. The development and validation of biomarkers that detect the pathological aggregates of TDP-43 in vivo are notably expected to further elucidate the pathophysiological underpinnings of extra-motor neurodegeneration in ALS. Novel biomarkers tracking the different aspects of ALS pathophysiology are paving the way to precision medicine approaches in the ALS-FTLD continuum. These are essential steps to improve the diagnosis and staging of ALS and the design of clinical trials testing novel disease-modifying treatments.

Sensitivity of brain MRI and neurological examination for detection of upper motor neurone degeneration in amyotrophic lateral sclerosis

OBJECTIVES

To investigate sensitivity of brain MRI and neurological examination for detection of upper motor neuron (UMN) degeneration in patients with amyotrophic lateral sclerosis (ALS).

METHODS

We studied 192 patients with ALS and 314 controls longitudinally. All patients visited our centre twice and underwent full neurological examination and brain MRI. At each visit, we assessed UMN degeneration by measuring motor cortex thickness (CT) and pyramidal tract fibre density (FD) corresponding to five body regions (bulbar region and limbs). For each body region, we measured degree of clinical UMN and lower motor neuron (LMN) symptom burden using a validated scoring system.

RESULTS

We found deterioration over time of CT of motor regions (p≤0.0081) and progression of UMN signs of bulbar region and left arm (p≤0.04). FD was discriminative between controls and patients with moderate/severe UMN signs (all regions, p≤0.034), but did not change longitudinally. Higher clinical UMN burden correlated with reduced CT, but not lower FD, for the bulbar region (p=2.2×10^-10) and legs (p≤0.025). In the arms, we found that severe LMN signs may reduce the detectability of UMN signs (p≤0.043). With MRI, UMN degeneration was detectable before UMN signs became clinically evident (CT: p=1.1×10^-10, FD: p=6.3×10^-4). Motor CT, but not FD, deteriorated more than UMN signs during the study period.

CONCLUSIONS

Motor CT is a more sensitive measure of UMN degeneration than UMN signs. Motor CT and pyramidal tract FD are discriminative between patients and controls. Brain MRI can monitor UMN degeneration before signs become clinically evident. These findings promote MRI as a potential biomarker for UMN progression in clinical trials in ALS.

Multiparametric Microstructural MRI and Machine Learning Classification Yields High Diagnostic Accuracy in Amyotrophic Lateral Sclerosis: Proof of Concept

The potential of multiparametric quantitative neuroimaging has been extensively discussed as a diagnostic tool in amyotrophic lateral sclerosis (ALS). In the past, the integration of multimodal, quantitative data into a useful diagnostic classifier was a major challenge. With recent advances in the field, machine learning in a data driven approach is a potential solution: neuroimaging biomarkers in ALS are mainly observed in the cerebral microstructure, with diffusion tensor imaging (DTI) and texture analysis as promising approaches. We set out to combine these neuroimaging markers as age-corrected features in a machine learning model with a cohort of 502 subjects, divided into 404 patients with ALS and 98 healthy controls. We calculated a linear support vector classifier (SVC) which is a very robust model and then verified the results with a multilayer perceptron (MLP)/neural network. Both classifiers were able to separate ALS patients from controls with receiver operating characteristic (ROC) curves showing an area under the curve (AUC) of 0.87-0.88 ("good") for the SVC and 0.88-0.91 ("good" to "excellent") for the MLP. Among the coefficients of the SVC, texture data contributed the most to a correct classification. We consider these results as a proof of concept that demonstrated the power of machine learning in the application of multiparametric quantitative neuroimaging data to ALS.

Feature selection from magnetic resonance imaging data in ALS: a systematic review

Background:

With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection.

Methods:

We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported.

Results:

Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS.

Conclusions:

These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.

Involvement of cortico-efferent tracts in flail arm syndrome: a tract-of-interest-based DTI study

Background

Flail arm syndrome is a restricted phenotype of motor neuron disease that is characterized by progressive, predominantly proximal weakness and atrophy of the upper limbs.

Objective

The study was designed to investigate specific white matter alterations in diffusion tensor imaging (DTI) data from flail arm syndrome patients using a hypothesis-guided tract-of-interest-based approach to identify in vivo microstructural changes according to a neuropathologically defined amyotrophic lateral sclerosis (ALS)-related pathology of the cortico-efferent tracts.

Methods

DTI-based white matter mapping was performed both by an unbiased voxel-wise statistical comparison and by a hypothesis-guided tract-wise analysis of fractional anisotropy (FA) maps according to the neuropathological ALS-propagation pattern for 43 flail arm syndrome patients vs 43 ‘classical’ ALS patients vs 40 matched controls.

Results

The analysis of white matter integrity demonstrated regional FA reductions for the flail arm syndrome group predominantly along the CST. In the tract-specific analysis according to the proposed sequential cerebral pathology pattern of ALS, the flail arm syndrome patients showed significant alterations of the specific tract systems that were identical to ‘classical’ ALS if compared to controls.

Conclusions

The DTI study including the tract-of-interest-based analysis showed a microstructural involvement pattern in the brains of flail arm syndrome patients, supporting the hypothesis that flail arm syndrome is a phenotypical variant of ALS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10854-6.

Evaluation of White Matter Tracts Fractional Anisotropy Using Tract-Based Spatial Statistics and Its correlation with Amyotrophic Lateral Sclerosis Functional Rating Scale Score in Patients with Motor Neuron Disease

Background Motor neuron diseases cause progressive degeneration of upper and lower motor neurons. No Indian studies are available on diffusion tensor imaging (DTI) findings in these patients. Aims This study was done to identify white matter tracts that have reduced fractional anisotropy (FA) in motor neuron disease (MND) patients using tract-based spatial statistics and to correlate FA values with Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) score. Settings and Design A case-control study in a tertiary care hospital. Materials and Methods We did DTI sequence (20 gradient directions, b -value 1,000) in 15 MND patients (10 men and 5 women; mean age: 46.5 ± 16.5 years; 11 amyotrophic lateral sclerosis [ALS], 2 monomelic amyotrophy, 1 progressive muscular atrophy, and 1 bulbar ALS) and 15 age- and sex-matched controls. The data set from each subject was postprocessed using FSL downloaded from the FMRIB Software Library, Oxford, United Kingdom (http://www.fmrib.ox.ac.uk/fsl). Statistical Analysis The statistical permutation tool "randomize" with 5,000 permutations was used to identify voxels that were different between the patient data set and the control data set. Mean FA values of these voxels were obtained separately for each tract as per "JHU white-matter tractography atlas." SPSS was used to look to correlate tract-wise mean FA value with ALSFRS-R score. Results We found clusters of reduced FA values in multiple tracts in the brain of patients with MND. Receiver operating characteristic curves plotted for individual tracts, showed that bilateral corticospinal tract, bilateral anterior thalamic radiation, bilateral uncinate fasciculus, and right superior longitudinal fasciculus were the best discriminators (area under the curve > 0.8, p < 0.01). FA values did not correlate with ALFRS-R severity score. Conclusion In MND patients, not only the motor tracts, but several nonmotor association tracts are additionally affected, reflecting nonmotor pathological processes in ALS.

Progressive Neurochemical Abnormalities in Cognitive and Motor Subgroups of Amyotrophic Lateral Sclerosis: A Prospective Multicenter Study

OBJECTIVE

To evaluate progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) by assessing alterations in N-acetylaspartate (NAA) ratios in the motor and prefrontal cortex within clinical subgroups of ALS.

METHODS

Seventy-six patients with ALS and 59 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium. Participants underwent serial clinical evaluations and magnetic resonance spectroscopy at baseline and 4 and 8 months using a harmonized protocol across 5 centers. NAA ratios were quantified in the motor cortex and prefrontal cortex. Patients were stratified into subgroups based on disease progression rate, upper motor neuron (UMN) signs, and cognitive status. Linear mixed models were used for baseline and longitudinal comparisons of NAA metabolite ratios.

RESULTS

Patients with ALS had reduced NAA ratios in the motor cortex at baseline (p < 0.001). Ratios were lower in those with more rapid disease progression and greater UMN signs (p < 0.05). A longitudinal decline in NAA ratios was observed in the motor cortex in the rapidly progressing (p < 0.01) and high UMN burden (p < 0.01) cohorts. The severity of UMN signs did not change significantly over time. NAA ratios were reduced in the prefrontal cortex only in cognitively impaired patients (p < 0.05); prefrontal cortex metabolites did not change over time.

CONCLUSIONS

Progressive degeneration of the motor cortex in ALS is associated with more aggressive clinical presentations. These findings provide biological evidence of variable spatial and temporal cerebral degeneration linked to the disease heterogeneity of ALS. The use of standardized imaging protocols may have a role in clinical trials for patient selection or subgrouping.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that MRS NAA metabolite ratios of the motor cortex are associated with more rapid disease progression and greater UMN signs in patients with ALS.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02405182.

How to Arrange Follow-Up Time-Intervals for Longitudinal Brain MRI Studies in Neurodegenerative Diseases

Background

Longitudinal brain MRI monitoring in neurodegeneration potentially provides substantial insights into the temporal dynamics of the underlying biological process, but is time- and cost-intensive and may be a burden to patients with disabling neurological diseases. Thus, the conceptualization of follow-up time-intervals in longitudinal MRI studies is an essential challenge and substantial for the results. The objective of this work is to discuss the association of time-intervals and the results of longitudinal trends in the frequently used design of one baseline and two follow-up scans.

Methods

Different analytical approaches for calculating the linear trend of longitudinal parameters were studied in simulations including their performance of dealing with outliers; these simulations were based on the longitudinal striatum atrophy in MRI data of Huntington’s disease patients, detected by atlas-based volumetry (ABV).

Results

For the design of one baseline and two follow-up visits, the simulations with outliers revealed optimum results for identical time-intervals between baseline and follow-up scans. However, identical time-intervals between the three acquisitions lead to the paradox that, depending on the fit method, the first follow-up scan results do not influence the final results of a linear trend analysis.

Conclusions

This theoretical study analyses how the design of longitudinal imaging studies with one baseline and two follow-up visits influences the results. Suggestions for the analysis of longitudinal trends are provided.

Brainstem Involvement in Amyotrophic Lateral Sclerosis: A Combined Structural and Diffusion Tensor MRI Analysis

Introduction

The brainstem is an important component in the pathology of amyotrophic lateral sclerosis (ALS). Although neuroimaging studies have shown multiple structural changes in ALS patients, few studies have investigated structural alterations in the brainstem. Herein, we compared the brainstem structure between patients with ALS and healthy controls.

Methods

A total of 33 patients with ALS and 33 healthy controls were recruited in this study. T1-weighted and diffusion tensor imaging (DTI) were acquired on a 3 Tesla magnetic resonance imaging (3T MRI) scanner. Volumetric and vertex-wised approaches were implemented to assess the differences in the brainstem’s morphological features between the two groups. An atlas-based region of interest (ROI) analysis was performed to compare the white matter integrity of the brainstem between the two groups. Additionally, a correlation analysis was used to evaluate the relationship between ALS clinical characteristics and structural features.

Results

Volumetric analyses showed no significant difference in the subregion volume of the brainstem between ALS patients and healthy controls. In the shape analyses, ALS patients had a local abnormal surface contraction in the ventral medulla oblongata and ventral pons. Compared with healthy controls, ALS patients showed significantly lower fractional anisotropy (FA) in the left corticospinal tract (CST) and bilateral frontopontine tracts (FPT) at the brainstem level, and higher radial diffusivity (RD) in bilateral CST and left FPT at the brainstem level by ROI analysis in DTI. Correlation analysis showed that disease severity was positively associated with FA in left CST and left FPT.

Conclusion

These findings suggest that the brainstem in ALS suffers atrophy, and degenerative processes in the brainstem may reflect disease severity in ALS. These findings may be helpful for further understanding of potential neural mechanisms in ALS.

Segmental involvement of the corpus callosum in C9orf72-associated ALS: a tract of interest-based DTI study

Background:

C9orf72 hexanucleotide repeat expansions are associated with widespread cerebral alterations, including white matter alterations. However, there is lack of information on changes in commissure fibres. Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of regional brain alterations at the group level. The objective of this study was to investigate the structural connectivity of the corpus callosum (CC) in ALS patients with C9orf72 expansions.

Methods:

DTI-based white matter mapping was performed by a hypothesis-guided tractwise analysis of fractional anisotropy (FA) maps for 25 ALS patients with C9orf72 expansion versus 25 matched healthy controls. Furthermore, a comparison with a patient control group of 25 sporadic ALS patients was performed. DTI-based tracts that originate from callosal sub-areas I to V were identified and correlated with clinical data.

Results:

The analysis of white matter integrity demonstrated regional FA reductions for tracts of the callosal areas II and III for ALS patients with C9orf72 expansions while FA reductions in sporadic ALS patients were observed only for tracts of the callosal area III; these reductions were correlated with clinical parameters.

Conclusion:

The tract-of-interest-based analysis showed a microstructural callosal involvement pattern in C9orf72-associated ALS that included the motor segment III together with frontal callosal connections, as an imaging signature of the C9orf72-associated overlap of motor neuron disease and frontotemporal pathology.

Oligodendrocyte Dysfunction in Amyotrophic Lateral Sclerosis: Mechanisms and Therapeutic Perspectives

Myelin is the lipid-rich structure formed by oligodendrocytes (OLs) that wraps the axons in multilayered sheaths, assuring protection, efficient saltatory signal conduction and metabolic support to neurons. In the last few years, the impact of OL dysfunction and myelin damage has progressively received more attention and is now considered to be a major contributing factor to neurodegeneration in several neurological diseases, including amyotrophic lateral sclerosis (ALS). Upon OL injury, oligodendrocyte precursor cells (OPCs) of adult nervous tissue sustain the generation of new OLs for myelin reconstitution, but this spontaneous regeneration process fails to successfully counteract myelin damage. Of note, the functions of OPCs exceed the formation and repair of myelin, and also involve the trophic support to axons and the capability to exert an immunomodulatory role, which are particularly relevant in the context of neurodegeneration. In this review, we deeply analyze the impact of dysfunctional OLs in ALS pathogenesis. The possible mechanisms underlying OL degeneration, defective OPC maturation, and impairment in energy supply to motor neurons (MNs) have also been examined to provide insights on future therapeutic interventions. On this basis, we discuss the potential therapeutic utility in ALS of several molecules, based on their remyelinating potential or capability to enhance energy metabolism.

Detection of White Matter Ultrastructural Changes for Amyotrophic Lateral Sclerosis Characterization: A Diagnostic Study from Dti-Derived Data

In amyotrophic lateral sclerosis (ALS), magnetic resonance imaging (MRI) allows investigation at the microstructural level, employing techniques able to reveal white matter changes. In the current study, a diffusion tensor imaging (DTI) analysis, with a collection of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) indexes, was performed in ALS patients to correlate geno- and phenotype features with MRI data, to investigate an in-vivo correlation of different neuropathological patterns. All patients who underwent the MR-DTI analysis were retrospectively recruited. MRI scan was collected within three months from diagnosis. FA and ADC values were collected in corpus callosum (CC), corona radiata (CR), cerebral peduncle (CR), cerebellar peduncle (CbP) and corticospinal tract at posterior limb of internal capsule (CST). DTI analysis performed in the whole ALS cohort revealed significant FA reduction and ADC increase in all selected regions, as widespread changes. Moreover, we observed a higher value of FA in rCR in bulbar patients. A positive correlation between ALS Functional Rating Scale-Revised and FA in rCP was evident. In consideration of the non-invasiveness, the reliability and the easy reproducibility of the method, we believe that brain MRI with DTI analyses may represent a valid tool usable as a diagnostic marker in ALS.

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.

Fiber-specific white matter reductions in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the loss of both upper and lower motor neurons. Studies using metrics derived from the diffusion tensor model have documented decreased fractional anisotropy (FA) and increased mean diffusivity in the corticospinal tract (CST) and the corpus callosum (CC) in ALS. These studies, however, only focused on microstructural white matter (WM) changes, while the macrostructural alterations of WM tracts in ALS remain unknown. Moreover, studies conducted based on the diffusion tensor model cannot provide information related to specific fiber bundles and fail to clarify which biological characteristics are changing. Using a novel fixel-based analytical method that can characterize the fiber density (FD) and the fiber-bundle cross-section (FC), this study investigated both microstructural and macrostructural changes in the WM in a large cohort of patients with ALS (N = 60) compared with demographically matched healthy controls (N = 60). Compared with healthy controls, we found decreased FD, FC and fiber density and cross-section (FDC, a combined measure of the FD and FC) values in the bilateral CST and the middle posterior body of the CC in patients with ALS, suggesting not only microstructural but also macrostructural abnormalities in these fiber bundles. Additionally, we found that the mean FD and FDC values in the bilateral CST were positively correlated with the revised ALS Functional Rating Scale, indicating that these two indices may serve as potential markers for assessing the clinical severity of ALS. Thus, these findings provide initial evidence for the existence of microstructural and macrostructural abnormalities of the fiber bundles in ALS.

In vivo histopathological staging in C9orf72-associated ALS: A tract of interest DTI study

BACKGROUND

Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of brain alterations at the group level according to a neuropathological staging system.

OBJECTIVE

The study was designed to investigate the in vivo staging in ALS patients with the C9orf72 expansion and potential differences to ALS patients with the SOD1 mutation.

METHODS

DTI-based white matter mapping was performed both by an unbiased voxel-wise statistical comparison and by a hypothesis-guided tract-wise analysis of fractional anisotropy (FA) maps according to the ALS-staging pattern for 27 ALS patients with C9orf72 expansion vs 15 ALS patients with SOD1 mutation vs 32 matched healthy controls. Clinical and neuropsychological data were acquired and correlated to DTI data.

RESULTS

The analysis of white matter integrity demonstrated regional FA reductions along the CST and also in frontal and prefrontal brain areas according to the proposed propagation pattern for the ALS patients with C9orf72 expansion and sporadic patients. This pattern could not be identified for the SOD1 mutation at the group level. In contrast, in the tract-specific analysis according to the neuropathological ALS-staging pattern, C9orf72 expansion ALS patients showed significant alterations of ALS-related tract systems similar to sporadic patients.

CONCLUSIONS

The DTI study including the tract-of-interest-based analysis showed a microstructural corticoefferent involvement pattern according to the staging scheme in C9orf72-associated ALS patients but not in the SOD1 mutation.