Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study

Mapping motor and extra-motor gray and white matter changes in ALS: a comprehensive review of MRI insights

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor neurons, yet with substantial clinical variability. Furthermore, beyond motor symptoms, ALS patients also show non-motor features, reflecting its classification as a multi-system disorder. The identification of reliable biomarkers is a critical challenge for improving diagnosis, tracking disease progression, and predicting patient outcomes. This review explores macro- and microstructural alterations in ALS, focusing on gray matter (GM) and white matter (WM) as observed through Magnetic Resonance Imaging (MRI). This approach synthesizes not only the expected involvement of motor areas but also highlights emerging evidence that these changes extend to extra-motor areas, such as the frontal and temporal lobes, underscoring the complex pathophysiology of ALS. The review emphasizes the potential of MRI as a non-invasive tool to provide new biomarkers by assessing both GM and WM integrity, a key advancement in ALS research. Additionally, it addresses existing discrepancies in findings and stresses the need for standardized imaging protocols. It also highlights the role of multi-modal MRI approaches in deepening our understanding of ALS pathology, emphasizing the importance of combining structural and diffusion MRI techniques to offer more comprehensive insights into ALS progression, ultimately advancing the potential for personalized treatment strategies and improving patient outcomes.

Brain neurovascular coupling in amyotrophic lateral sclerosis: Correlations with disease progression and cognitive impairment

BACKGROUND AND PURPOSE

'Neurovascular coupling' (NVC) alterations, assessing the interplay between local cerebral perfusion and neural activity within a given brain region or network, may reflect neurovascular unit impairment in amyotrophic lateral sclerosis (ALS). The aim was to explore NVC as a correlation between the functional connectivity and cerebral blood flow within the large-scale resting-state functional magnetic resonance imaging brain networks in a sample of ALS patients compared to healthy controls (HCs).

METHODS

Forty-eight ALS patients (30 males; mean age 60.64 ± 9.62 years) and 32 HC subjects (14 males; mean age 55.06 ± 16 years) were enrolled and underwent 3 T magnetic resonance imaging. ALS patients were screened by clinical and neuropsychological scales and were retrospectively classified as very fast progressors (VFPs), fast progressors and slow progressors (SPs).

RESULTS

Neurovascular coupling reduction within the default mode network (DMN) (p = 0.005) was revealed in ALS patients compared to HCs, observing, for this network, significant NVC differences between VFP and SP groups. Receiver operating characteristic curve analysis showed that impaired NVC in the DMN at baseline best discriminated VFPs and SPs (area under the curve 75%). Significant correlations were found between NVC and the executive (r = 0.40, p = 0.01), memory (r = 0.32, p = 0.04), visuospatial ability (r = 0.40, p = 0.01) and non-ALS-specific (r = 0.40, p = 0.01) subscores of the Edinburgh Cognitive and Behavioural ALS Screen.

CONCLUSIONS

The reduction of brain NVC in the DMN may reflect largely distributed abnormalities of the neurovascular unit. NVC alterations in the DMN could play a role in anticipating a faster clinical progression in ALS patients, aiding patient selection and monitoring during clinical trials.

T1-weighted MRI texture analysis in amyotrophic lateral sclerosis patients stratified by the D50 progression model

Amyotrophic lateral sclerosis, a progressive neurodegenerative disease, presents challenges in predicting individual disease trajectories due to its heterogeneous nature. This study explores the application of texture analysis on T1-weighted MRI in patients with amyotrophic lateral sclerosis, stratified by the D50 disease progression model. The D50 model, which offers a more nuanced representation of disease progression than traditional linear metrics, calculates the sigmoidal curve of functional decline and provides independent quantifications of disease aggressiveness and accumulation. In this research, a representative cohort of 116 patients with amyotrophic lateral sclerosis was studied using the D50 model and texture analysis on MRI images. Texture analysis, a technique used for quantifying voxel intensity patterns in MRI images, was employed to discern alterations in brain tissue associated with amyotrophic lateral sclerosis. This study examined alterations of the texture feature autocorrelation across sub-groups of patients based on disease accumulation, aggressiveness and the first site of onset, as well as in direct regressions with accumulation/aggressiveness. The findings revealed distinct patterns of the texture-derived autocorrelation in grey and white matter, increase in bilateral corticospinal tract, right hippocampus and left temporal pole as well as widespread decrease within motor and extra-motor brain regions, of patients stratified based on their disease accumulation. Autocorrelation alterations in grey and white matter, in clusters within the left cingulate gyrus white matter, brainstem, left cerebellar tonsil grey matter and right inferior fronto-occipital fasciculus, were also negatively associated with disease accumulation in regression analysis. Otherwise, disease aggressiveness correlated with only two small clusters, within the right superior temporal gyrus and right posterior division of the cingulate gyrus white matter. The findings suggest that texture analysis could serve as a potential biomarker for disease stage in amyotrophic lateral sclerosis, with potential for quick assessment based on using T1-weighted images.

Altered spreading of fast aperiodic brain waves relates to disease duration in Amyotrophic Lateral Sclerosis

OBJECTIVE

To test the hypothesis that patients affected by Amyotrophic Lateral Sclerosis (ALS) show an altered spatio-temporal spreading of neuronal avalanches in the brain, and that this may related to the clinical picture.

METHODS

We obtained the source-reconstructed magnetoencephalography (MEG) signals from thirty-six ALS patients and forty-two healthy controls. Then, we used the construct of the avalanche transition matrix (ATM) and the corresponding network parameter nodal strength to quantify the changes in each region, since this parameter provides key information about which brain regions are mostly involved in the spreading avalanches.

RESULTS

ALS patients presented higher values of the nodal strength in both cortical and sub-cortical brain areas. This parameter correlated directly with disease duration.

CONCLUSIONS

In this work, we provide a deeper characterization of neuronal avalanches propagation in ALS, describing their spatio-temporal trajectories and identifying the brain regions most likely to be involved in the process. This makes it possible to recognize the brain areas that take part in the pathogenic mechanisms of ALS. Furthermore, the nodal strength of the involved regions correlates directly with disease duration.

SIGNIFICANCE

Our results corroborate the clinical relevance of aperiodic, fast large-scale brain activity as a biomarker of microscopic changes induced by neurophysiological processes.

Potential of neuroimaging as a biomarker in amyotrophic lateral sclerosis: from structure to metabolism

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by motor neuron degeneration. The development of ALS involves metabolite alterations leading to tissue lesions in the nervous system. Recent advances in neuroimaging have significantly improved our understanding of the underlying pathophysiology of ALS, with findings supporting the corticoefferent axonal disease progression theory. Current studies on neuroimaging in ALS have demonstrated inconsistencies, which may be due to small sample sizes, insufficient statistical power, overinterpretation of findings, and the inherent heterogeneity of ALS. Deriving meaningful conclusions solely from individual imaging metrics in ALS studies remains challenging, and integrating multimodal imaging techniques shows promise for detecting valuable ALS biomarkers. In addition to giving an overview of the principles and techniques of different neuroimaging modalities, this review describes the potential of neuroimaging biomarkers in the diagnosis and prognostication of ALS. We provide an insight into the underlying pathology, highlighting the need for standardized protocols and multicenter collaborations to advance ALS research.

M1/precuneus ratio as a surrogate marker of upper motor neuron sign in ALS

OBJECTIVE

To investigate whether primary motor cortex (M1) volume measured with an automated approach in MRI reflects upper motor neuron dysfunction and whether it can serve as a potential diagnostic and/or disease-tracking biomarker for amyotrophic lateral sclerosis (ALS).

METHODS

In this retrospective study, we enrolled 95 subjects, including 33 possible or laboratory supported probable ALS, 26 probable or definite ALS (Prob/Def), 2 primary lateral sclerosis patients, 8 progressive muscular atrophy patients, 19 normal controls (NC) and 7 ALS patients having a second structural MRI scan. Some subjects also underwent functional MRI. We calculated M1, primary sensory cortex, precuneus volumes, and total gray matter volume (TGMV) with FreeSurfer. The sensorimotor network (SMN) was identified using independent component analysis.

RESULTS

The M1/precuneus ratio showed a significant difference between the NC and Prob/Def groups (p < 0.05). The diagnostic accuracy of the M1/precuneus ratio was moderate for distinguishing Prob/Def from NC (cutoff = 1.00, sensitivity = 0.42, specificity = 0.90). Two of eight cases without upper motor neuron dysfunction could be diagnosed with ALS using M1/precuneus ratio as a surrogate marker. A negative correlation between M1/precuneus ratio and functional activity was found in Brodmann area 6 in the SMN in all subjects. TGMV tended to decrease with disease progression (p = 0.04).

INTERPRETATION

The M1/precuneus volume ratio, associated with the SMN, may have potential as a surrogate biomarker of upper motor neuron dysfunction in ALS. Furthermore, TGMV may serve as an ALS disease-tracking biomarker.

Yield of EEG features as markers of disease severity in amyotrophic lateral sclerosis: a pilot study

OBJECTIVE

To clarify the role of electroencephalography (EEG) as a promising marker of severity in amyotrophic lateral sclerosis (ALS). We characterized the brain spatio-temporal patterns activity at rest by means of both spectral band powers and EEG microstates and correlated these features with clinical scores.

METHODS

Eyes closed EEG was acquired in 15 patients with ALS and spectral band power was calculated in frequency bands, defined on the basis of individual alpha frequency (IAF): delta-theta band (1-7 Hz); low alpha (IAF - 2 Hz - IAF); high alpha (IAF - IAF + 2 Hz); beta (13 - 25 Hz). EEG microstate metrics (duration, occurrence, and coverage) were also evaluated. Spectral band powers and microstate metrics were correlated with several clinical scores of disabilities and disease progression. As a control group, 15 healthy volunteers were enrolled.

RESULTS

The beta-band power in motor/frontal regions was higher in patients with higher disease burden, negatively correlated with clinical severity scores and positively correlated with disease progression. Overall microstate duration was longer and microstate occurrence was lower in patients than in controls. Longer duration was correlated with a worse clinical status.

CONCLUSIONS

Our results showed that beta-band power and microstate metrics may be good candidates of disease severity in ALS. Increased beta and longer microstate duration in clinically worse patients suggest a possible impairment of both motor and non-motor network activities to fast modify their status. This can be interpreted as an attempt in ALS patients to compensate the disability but resulting in an ineffective and probably maladaptive behavior.

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

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

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

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

Background

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

Materials and Methods

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

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

Results

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

Discussions

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

Cortico-striatal functional connectivity and cerebral small vessel disease: Contribution to mild Parkinsonian signs

BACKGROUND AND PURPOSE

Mild Parkinsonian signs (MPS) are common in older adults. We hypothesized that MPS are associated with lower functional connectivity (FC) in dopamine-dependent cortico-striatal networks, and these associations vary with white matter hyperintensity (WMH), a risk factor for MPS.

METHODS

We examined resting-state functional MRI in 266 participants (mean age 83; 57% female; 41% African American) with data on MPS (Unified Parkinson's Disease Rating Scale), demographics, cognition, muscle-skeletal, and cardiometabolic health. FC between cortex and striatum was examined separately for sensorimotor, executive, and limbic functional subregions. Logistic regression tested the association of FC in each network with MPS, adjusted for covariates. Interactions of FC by WMH were tested; and analyses were repeated stratified by WMH above/below the median.

RESULTS

Compared to those without MPS, those with MPS had lower cortico-striatal FC in the left executive network (adjusted odds ratio [95% confidence interval], p-value: 0.188 [0.043, 0.824], .027). The interaction with WMH was p = .064; left executive FC was inversely associated with MPS for high WMH (0.077 [0.010, 0.599], .014) but not low WMH participants (1.245 [0.128, 12.132], .850).

CONCLUSIONS

MPS appear related to lower executive network FC, robust to adjustment for other risk factors, and stronger for those with higher burden of WMH. Future longitudinal studies should examine the interplay between cerebral small vessel disease and connectivity influencing MPS.

Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Between-sex variability of resting state functional brain networks in amyotrophic lateral sclerosis (ALS)

The organization of brain functional connectivity (FC) has been shown to differ between sexes. Amyotrophic lateral sclerosis (ALS) is characterized by sexual dimorphism, showing sex-specific trends in site of onset, phenotypes, and prognosis. Here, we explored resting state (RS) FC differences within major large-scale functional networks between women and men in a sample of ALS patients, in comparison to healthy controls (HCs). A group-level independent component analysis (ICA) was performed on RS-fMRI time-series enabling spatial and spectral analyses of large-scale RS FC networks in 45 patients with ALS (20 F; 25 M) and 31 HCs (15 F; 16 M) with a focus on sex-related differences. A whole-brain voxel-based morphometry (VBM) was also performed to highlight atrophy differences. Between-sex comparisons showed: decreased FC in the right middle frontal gyrus and in the precuneus within the default mode network (DMN), in affected men compared to affected women; decreased FC in the right post-central gyrus (sensorimotor network), in the right inferior parietal gyrus (right fronto-parietal network) and increased FC in the anterior cingulate cortex and right insula (salience network), in both affected and non-affected men compared to women. When comparing affected men to affected women, VBM analysis revealed atrophy in men in the right lateral occipital cortex. Our results suggest that in ALS sex-related trends of brain functional and structural changes are more heavily represented in DMN and in the occipital cortex, suggesting that sex is an additional dimension of functional and structural heterogeneity in ALS.