Cortical microstructure in the amyotrophic lateral sclerosis-frontotemporal dementia continuum

Neuroimaging correlates of domain-specific cognitive deficits in amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with frequent extra-motor involvement. In the present study, we investigated whether specific cognitive and behavioral deficits in ALS correlate with distinct extra-motor neurodegeneration patterns on brain MRI.

METHODS

We performed multimodal brain MRI and Edinburgh cognitive and behavioral ALS screen (ECAS) in 293 patients and 237 controls. Follow-up data were acquired from 171 patients with a median duration of 7.9 months. Domain-level cognitive scores from the ECAS were compared with grey and white matter MRI parameters. Interaction analyses between patients and controls were performed to explore whether correlates were specific to ALS, rather than related to normal aging. Follow-up data were used to assess changes of domain-associated brain structures over time.

RESULTS

Language impairment was significantly associated with (left predominant) frontal, temporal, parietal and subcortical grey matter neurodegeneration. Letter fluency with widespread cortical and subcortical grey matter involvement. Memory dysfunction with hippocampal and medial-temporal atrophy. Executive impairment was exclusively correlated with widespread white matter impairment. Visuospatial scores did not correlate with MRI parameters. Interaction analyses between patients and controls showed that most ECAS-MRI correlations were stronger in ALS than in controls (75.7% significant in grey matter, 52.7% in white matter). Longitudinal analyses showed that all grey matter structures associated with cognitive domains worsened over time while, for this study population, ECAS domain scores did not decline significantly.

CONCLUSIONS

MRI can capture the heterogeneity of cognitive and behavioral involvement in ALS and provides a useful longitudinal biomarker for progression of extra-motor neurodegeneration.

The spectrum of behavioral disorders in amyotrophic lateral sclerosis: current view

Behavioral disorders, with an average prevalence of 30-60% are important non-motor symptoms in amyotrophic lateral sclerosis (ALS) that have a negative impact on prognosis, management and quality of life, yet the underlying neurobiology is poorly understood. Among people with ALS, apathy, fatigue, anxiety, irritability and other behavioral symptoms are the most prominent, although less frequent than cognitive impairment. The present review explores the current understanding of behavioral changes in ALS with particular emphasis on our current knowledge about their structural and functional brain correlates, substantiating a multisystem degeneration with particular dysfunction of frontal-subcortical circuits and dysfunction of fronto-striatal, frontotemporal and other essential brain systems. The natural history of behavioral dysfunctions in ALS and their relationship to frontotemporal lobe degeneration (FTLD) are not fully understood, although they form a clinical continuum, suggesting a differential vulnerability of non-motor brain networks, ALS being considered a brain network disorder. An assessment of risks or the early detection of brain connectivity signatures before structural changes may be helpful in investigating the pathophysiological mechanisms of behavioral impairment in ALS. Treatment of both ALS and co-morbid behavioral disorders is a multidisciplinary task, but whereas no causal or disease-modifying therapies for ALS are available, symptomatic treatment of a variety of behavioral symptoms plays a pivotal role in patient care, although the management of behavioral symptoms in clinical care still remains limited.

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.

Current potential diagnostic biomarkers of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) currently lacks the useful diagnostic biomarkers. The current diagnosis of ALS is mainly depended on the clinical manifestations, which contributes to the diagnostic delay and be difficult to make the accurate diagnosis at the early stage of ALS, and hinders the clinical early therapeutics. The more and more pathogenesis of ALS are found at the last 30 years, including excitotoxicity, the oxidative stress, the mitochondrial dysfunction, neuroinflammation, the altered energy metabolism, the RNA misprocessing and the most recent neuroimaging findings. The findings of these pathogenesis bring the new clues for searching the diagnostic biomarkers of ALS. At present, a large number of relevant studies about the diagnostic biomarkers are underway. The ALS pathogenesis related to the diagnostic biomarkers might lessen the diagnostic reliance on the clinical manifestations. Among them, the cortical altered signatures of ALS patients derived from both structural and functional magnetic resonance imaging and the emerging proteomic biomarkers of neuronal loss and glial activation in the cerebrospinal fluid as well as the potential biomarkers in blood, serum, urine, and saliva are leading a new phase of biomarkers. Here, we reviewed these current potential diagnostic biomarkers of ALS.

Spatial and temporal patterns of cortical mean diffusivity in Alzheimer's disease and suspected non-Alzheimer's disease pathophysiology

INTRODUCTION

The spatial and temporal patterns of cortical mean diffusivity (cMD), as well as its association with Alzheimer's disease (AD) and suspected non-Alzheimer's pathophysiology (SNAP), are not yet fully understood.

METHODS

We compared baseline (n = 617) and longitudinal changes (n = 421) of cMD, cortical thickness, and gray matter volume and their relations to vascular risk factors, amyloid beta (Aβ), and tau positron emission tomography (PET), and longitudinal cognitive decline in Aβ PET negative and positive older adults.

RESULTS

cMD increases were more sensitive to detecting brain structural alterations than cortical thinning and gray matter atrophy. Tau-related cMD increases partially mediated Aβ-related cognitive decline in AD, whereas vascular disease-related increased cMD levels substantially mediated age-related cognitive decline in SNAP.

DISCUSSION

These findings revealed the dynamic changes of microstructural and macrostructural indicators and their associations with AD and SNAP, providing novel insights into understanding upstream and downstream events of cMD in neurodegenerative disease.

HIGHLIGHTS

Cortical mean diffusivity (cMD) was more sensitive to detecting structural changes than macrostructural factors. Tau-related cMD increases partially mediated amyloid beta-related cognitive decline in Alzheimer's disease (AD). White matter hyperintensity-related higher cMD mainly explained the age-related cognitive decline in suspected non-Alzheimer's pathophysiology (SNAP). cMD may assist in tracking earlier neurodegenerative signs in AD and SNAP.

Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study

Background

Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity.

Methods

This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R.

Results

In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05).

Conclusions

The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.

Cortical Macro- and Microstructural Changes in Parkinson's Disease with Probable Rapid Eye Movement Sleep Behavior Disorder

BACKGROUND

Evidence regarding cortical atrophy patterns in Parkinson's disease (PD) with probable rapid eye movement sleep behavior disorder (RBD) (PD-pRBD) remains scarce. Cortical mean diffusivity (cMD), as a novel imaging biomarker highly sensitive to detecting cortical microstructural changes in different neurodegenerative diseases, has not been investigated in PD-pRBD yet.

OBJECTIVES

The aim was to investigate cMD as a sensitive measure to identify subtle cortical microstructural changes in PD-pRBD and its relationship with cortical thickness (CTh).

METHODS

Twenty-two PD-pRBD, 31 PD without probable RBD (PD-nonpRBD), and 28 healthy controls (HC) were assessed using 3D T1-weighted and diffusion-weighted magnetic resonance imaging on a 3-T scanner and neuropsychological testing. Measures of cortical brain changes were obtained through cMD and CTh. Two-class group comparisons of a general linear model were performed (P < 0.05). Cohen's d effect size for both approaches was computed.

RESULTS

PD-pRBD patients showed higher cMD than PD-nonpRBD patients in the left superior temporal, superior frontal, and precentral gyri, precuneus cortex, as well as in the right middle frontal and postcentral gyri and paracentral lobule (d > 0.8), whereas CTh did not detect significant differences. PD-pRBD patients also showed increased bilateral posterior cMD in comparison with HCs (d > 0.8). These results partially overlapped with CTh results (0.5 < d < 0.8). PD-nonpRBD patients showed no differences in cMD when compared with HCs but showed cortical thinning in the left fusiform gyrus and lateral occipital cortex bilaterally (d > 0.5).

CONCLUSIONS

cMD may be more sensitive than CTh displaying significant cortico-structural differences between PD subgroups, indicating this imaging biomarker's utility in studying early cortical changes in PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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

Background

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

Methods

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

Results

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

Conclusion

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

Structural and Functional Brain Network Connectivity at Different King's Stages in Patients With Amyotrophic Lateral Sclerosis

BACKGROUND AND OBJECTIVES

There is currently no validated disease-stage biomarker for amyotrophic lateral sclerosis (ALS). The identification of quantitative and reproducible markers of disease stratification in ALS is fundamental for study design definition and inclusion of homogenous patient cohorts into clinical trials. Our aim was to assess the rearrangements of structural and functional brain connectivity underlying the clinical stages of ALS, to suggest objective, reproducible measures provided by MRI connectomics mirroring disease staging.

METHODS

In this observational study, patients with ALS and healthy controls (HCs) underwent clinical evaluation and brain MRI on a 3T scanner. Patients were classified into 4 groups, according to the King's staging system. Structural and functional brain connectivity matrices were obtained using diffusion tensor and resting-state fMRI data, respectively. Whole-brain network-based statistics (NBS) analysis and comparisons of intraregional and inter-regional connectivity values using analysis of covariance models were performed between groups. Correlations between MRI and clinical/cognitive measures were tested using Pearson coefficient.

RESULTS

One hundred four patients with ALS and 61 age-matched and sex-matched HCs were included. NBS and regional connectivity analyses demonstrated a progressive decrease of intranetwork and internetwork structural connectivity of sensorimotor regions at increasing ALS stages in our cohort, compared with HCs. By contrast, functional connectivity showed divergent patterns between King's stages 3 (increase in basal ganglia and temporal circuits [p = 0.04 and p = 0.05, respectively]) and 4 (frontotemporal decrease [p = 0.03]), suggesting a complex interplay between opposite phenomena in late stages of the disease. Intraregional sensorimotor structural connectivity was correlated with ALS Functional Rating Scale-revised (ALSFRS-r) score (r = 0.31, p < 0.001) and upper motor neuron burden (r = -0.25, p = 0.01). Inter-regional frontal-sensorimotor structural connectivity was also correlated with ALSFRS-r (r = 0.24, p = 0.02). No correlations with cognitive measures were found.

DISCUSSION

MRI of the brain allows to demonstrate and quantify increasing disruption of structural connectivity involving the sensorimotor networks in ALS, mirroring disease stages. Frontotemporal functional disconnection seems to characterize only advanced disease phases. Our findings support the utility of MRI connectomics to stratify patients and stage brain pathology in ALS in a reproducible way, which may mirror clinical progression.

Association of cortical and subcortical microstructure with disease severity: impact on cognitive decline and language impairments in frontotemporal lobar degeneration

BACKGROUND

Cortical and subcortical microstructural modifications are critical to understanding the pathogenic changes in frontotemporal lobar degeneration (FTLD) subtypes. In this study, we investigated cortical and subcortical microstructure underlying cognitive and language impairments across behavioral variant of frontotemporal dementia (bvFTD), semantic variant of primary progressive aphasia (svPPA), and nonfluent variant of primary progressive aphasia (nfvPPA) subtypes.

METHODS

The current study characterized 170 individuals with 3 T MRI structural and diffusion-weighted imaging sequences as portion of the Frontotemporal Lobar Degeneration Neuroimaging Initiative study: 41 bvFTD, 35 nfvPPA, 34 svPPA, and 60 age-matched cognitively unimpaired controls. To determine the severity of the disease, clinical dementia rating plus national Alzheimer's coordinating center behavior and language domains sum of boxes scores were used; other clinical measures, including the Boston naming test and verbal fluency test, were also evaluated. We computed surface-based cortical thickness and cortical and subcortical microstructural metrics using tract-based spatial statistics and explored their relationships with clinical and cognitive assessments.

RESULTS

Compared with controls, those with FTLD showed substantial cortical mean diffusivity alterations extending outside the regions with cortical thinning. Tract-based spatial statistics revealed that anomalies in subcortical white matter diffusion were widely distributed across the frontotemporal and parietal areas. Patients with bvFTD, nfvPPA, and svPPA exhibited distinct patterns of cortical and subcortical microstructural abnormalities, which appeared to correlate with disease severity, and separate dimensions of language functions.

CONCLUSIONS

Our findings imply that cortical and subcortical microstructures may serve as sensitive biomarkers for the investigation of neurodegeneration-associated microstructural alterations in FTLD subtypes. Flowchart of the study design (see materials and methods for detailed description).

Cortical microstructure in primary progressive aphasia: a multicenter study

BACKGROUND

Cortical mean diffusivity is a novel imaging metric sensitive to early changes in neurodegenerative syndromes. Higher cortical mean diffusivity values reflect microstructural disorganization and have been proposed as a sensitive biomarker that might antedate macroscopic cortical changes. We aimed to test the hypothesis that cortical mean diffusivity is more sensitive than cortical thickness to detect cortical changes in primary progressive aphasia (PPA).

METHODS

In this multicenter, case-control study, we recruited 120 patients with PPA (52 non-fluent, 31 semantic, and 32 logopenic variants; and 5 GRN-related PPA) as well as 89 controls from three centers. The 3-Tesla MRI protocol included structural and diffusion-weighted sequences. Disease severity was assessed with the Clinical Dementia Rating scale. Cortical thickness and cortical mean diffusivity were computed using a surface-based approach.

RESULTS

The comparison between each PPA variant and controls revealed cortical mean diffusivity increases and cortical thinning in overlapping regions, reflecting the canonical loci of neurodegeneration of each variant. Importantly, cortical mean diffusivity increases also expanded to other PPA-related areas and correlated with disease severity in all PPA groups. Cortical mean diffusivity was also increased in patients with very mild PPA when only minimal cortical thinning was observed and showed a good correlation with measures of disease severity.

CONCLUSIONS

Cortical mean diffusivity shows promise as a sensitive biomarker for the study of the neurodegeneration-related microstructural changes in PPA.

Amyotrophic Lateral Sclerosis-Frontotemporal Dementia: Shared and Divergent Neural Correlates Across the Clinical Spectrum

BACKGROUND AND OBJECTIVES

A significant overlap between amyotrophic lateral sclerosis (ALS) and behavioral variant of frontotemporal dementia (bvFTD) has been observed at clinical, genetic, and pathologic levels. Within this continuum of presentations, the presence of mild cognitive or behavioral symptoms in patients with ALS has been consistently reported, although it is unclear whether this is to be considered a distinct phenotype or rather a natural evolution of ALS. Here, we used mathematical modeling of MRI connectomic data to decipher common and divergent neural correlates across the ALS-frontotemporal dementia (FTD) spectrum.

METHODS

We included 83 patients with ALS, 35 patients with bvFTD, and 61 healthy controls, who underwent clinical, cognitive, and MRI assessments. Patients with ALS were classified according to the revised Strong criteria into 54 ALS with only motor deficits (ALS-cn), 21 ALS with cognitive or behavioral involvement (ALS-ci/bi), and 8 ALS with bvFTD (ALS-FTD). First, we assessed the functional and structural connectivity patterns across the ALS-FTD spectrum. Second, we investigated whether and where MRI connectivity alterations of patients with ALS with any degree of cognitive impairment (i.e., ALS-ci/bi and ALS-FTD) resembled more the pattern of damage of one (ALS-cn) or the other end (bvFTD) of the spectrum, moving from group-level to single-subject analysis.

RESULTS

As compared with controls, extensive structural and functional disruption of the frontotemporal and parietal networks characterized bvFTD (bvFTD-like pattern), while a more focal structural damage within the sensorimotor-basal ganglia areas characterized ALS-cn (ALS-cn-like pattern). ALS-ci/bi patients demonstrated an ALS-cn-like pattern of structural damage, diverging from ALS-cn with similar motor impairment for the presence of enhanced functional connectivity within sensorimotor areas and decreased functional connectivity within the bvFTD-like pattern. On the other hand, patients with ALS-FTD resembled both structurally and functionally the bvFTD-like pattern of damage with, in addition, the structural ALS-cn-like damage in the motor areas.

DISCUSSION

Our findings suggest a maladaptive role of functional rearrangements in ALS-ci/bi concomitantly with similar structural alterations compared to ALS-cn, supporting the hypothesis that ALS-ci/bi might be considered as a phenotypic variant of ALS, rather than a consequence of disease worsening.

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.

Low Fluctuation of Symptoms May Delay Diagnosis of Myasthenia Gravis: A Case Series

Introduction

Myasthenia gravis is an autoimmune disorder affecting neuromuscular transmission, and its hallmark is fluctuating muscular weakness affecting the ocular, bulbar, respiratory, or limb muscles. Our objective is to highlight the difficulties encountered in diagnosing this disorder in patients lacking this characteristic phenomenon.

Methods

Three cases of patients presenting with progressive weakness of bulbar and ocular muscles, in whom a lack of fluctuation delayed the diagnosis of myasthenia gravis, are described.

Results

Amyotrophic lateral sclerosis was considered in two of the patients, while cavernous sinus thrombosis was initially diagnosed in the third. Electrodiagnostic, pharmacologic, and serologic testing ultimately established the diagnosis of myasthenia gravis.

Conclusion

While the typical clinical pattern of myasthenia gravis is well known and easily recognizable, there are cases when the diagnosis, and thus the treatment, is delayed because of low or absent fluctuation of symptoms. The acknowledgment of this probably underestimated presentation is important for expeditious management.

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.

Intracortical surface-based MR diffusivity to investigate neurologic and psychiatric disorders: a review

Diffusion tensor imaging (DTI) allows the quantification of water diffusivity within the cerebral cortex. Alterations in cortical mean diffusivity (MD) have been suggested to reflect microstructural damage. Interestingly, microstructural changes can be detected in the absence of macrostructural alterations such as cortical thinning or gray matter volume loss. However, volume-based neuroimaging techniques for the study of cortical MD have shown some limitations in terms of intersubject registration, partial volume correction, and smoothing artifacts. In this review, we summarize how a surface-based approach for the assessment of intracortical MD has not only overcome these technical limitations, but also provided important contributions to the fields of neurology and psychiatry. Since its proposal in 2018, the use of this neuroimaging technique has revealed cortical microstructural alterations in a wide range of clinical contexts, including Alzheimer's disease, Parkinson's disease, schizophrenia, Huntington's disease, multiple sclerosis, amyotrophic lateral sclerosis, and primary progressive aphasia. In most cases, the detection of early intracortical MD alterations preceded the identification of macrostructural changes. Importantly, microstructural damage significantly correlated with cognitive performance and biomarker measures, suggesting a potential role for its use in clinical trials as a sensitive imaging marker of neurodegeneration. Given that DTI is a widely available imaging modality, these encouraging results motivate further research using this novel neuroimaging metric in other clinical contexts. Overall, this technique has shed light into the key role of early cortical degeneration in many diseases where cortical involvement was previously thought to have limited clinical and biological significance.

Frontotemporal Pathology in Motor Neuron Disease Phenotypes: Insights From Neuroimaging

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

Regional grey matter microstructural changes and volume loss according to disease duration in multiple sclerosis patients

The spatio-temporal characteristics of grey matter (GM) impairment in multiple sclerosis (MS) are poorly understood. We used a new surface-based diffusion MRI processing tool to investigate regional modifications of microstructure, and we quantified volume loss in GM in a cohort of patients with MS classified into three groups according to disease duration. Additionally, we investigated the relationship between GM changes with disease severity. We studied 54 healthy controls and 247 MS patients classified regarding disease duration: MS1 (less than 5 years, n = 67); MS2 (5–15 years, n = 107); and MS3 (more than15 years, n = 73). We compared GM mean diffusivity (MD), fractional anisotropy (FA) and volume between groups, and estimated their clinical associations. Regional modifications in diffusion measures (MD and FA) and volume did not overlap early in the disease, and became widespread in later phases. We found higher MD in MS1 group, mainly in the temporal cortex, and volume reduction in deep GM and left precuneus. Additional MD changes were evident in cingulate and occipital cortices in the MS2 group, coupled to volume reductions in deep GM and parietal and frontal poles. Changes in MD and volume extended to more than 80% of regions in MS3 group. Conversely, increments in FA, with very low effect size, were observed in the parietal cortex and thalamus in MS1 and MS2 groups, and extended to the frontal lobe in the later group. MD and GM changes were associated with white matter lesion load and with physical and cognitive disability. Microstructural integrity loss and atrophy present differential spatial predominance early in MS and accrual over time, probably due to distinct pathogenic mechanisms that underlie tissue damage.

Cognitive dysfunction in amyotrophic lateral sclerosis: can we predict it?

Background and aim

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the degeneration of both upper and lower motoneurons in the brain and spinal cord leading to motor and extra-motor symptoms. Although traditionally considered a pure motor disease, recent evidences suggest that ALS is a multisystem disorder. Neuropsychological alterations, in fact, are observed in more than 50% of patients: while executive dysfunctions have been firstly identified, alterations in verbal fluency, behavior, and pragmatic and social cognition have also been described. Detecting and monitoring ALS cognitive and behavioral impairment even at early disease stages is likely to have staging and prognostic implications, and it may impact the enrollment in future clinical trials. During the last 10 years, humoral, radiological, neurophysiological, and genetic biomarkers have been reported in ALS, and some of them seem to potentially correlate to cognitive and behavioral impairment of patients. In this review, we sought to give an up-to-date state of the art of neuropsychological alterations in ALS: we will describe tests used to detect cognitive and behavioral impairment, and we will focus on promising non-invasive biomarkers to detect pre-clinical cognitive decline.

Conclusions

To date, the research on humoral, radiological, neurophysiological, and genetic correlates of neuropsychological alterations is at the early stage, and no conclusive longitudinal data have been published. Further and longitudinal studies on easily accessible and quantifiable biomarkers are needed to clarify the time course and the evolution of cognitive and behavioral impairments of ALS patients.

Cortical microstructural correlates of plasma neurofilament light chain in Huntington's disease

INTRODUCTION

Huntington's disease (HD) is a severe neurodegenerative disorder with no effective treatment. Minimally-invasive biomarkers such as blood neurofilament light chain (NfL) in HD are therefore needed to quantitatively characterize neuronal loss. NfL levels in HD are known to correlate with disease progression and striatal atrophy, but whether they also reflect cortical degeneration remains elusive.

METHODS

In a sample of 35 HD patients, we characterized the cortical macro (cortical thickness) and microstructural (increased intracortical diffusivity) correlates of plasma NfL levels. We further investigated whether NfL-related cortical alterations correlated with clinical indicators of disease progression.

RESULTS

Increased plasma NfL levels in HD reflected posterior-cortical microstructural degeneration, but not reduced cortical thickness (p < 0.05, corrected). Importantly, these imaging alterations correlated, in turn, with more severe motor, cognitive and behavioral symptoms.

CONCLUSION

Plasma NfL levels may be useful for tracking clinically-meaningful cortical deterioration in HD. Additionally, our results further reinforce the role of intracortical diffusivity as a valuable imaging indicator in movement disorders.

Association of cortical microstructure with amyloid-β and tau: impact on cognitive decline, neurodegeneration, and clinical progression in older adults

Noninvasive biomarkers of early neuronal injury may help identify cognitively normal individuals at risk of developing Alzheimer's disease (AD). A recent diffusion-weighted imaging (DWI) method allows assessing cortical microstructure via cortical mean diffusivity (cMD), suggested to be more sensitive than macrostructural neurodegeneration. Here, we aimed to investigate the association of cMD with amyloid-β and tau pathology in older adults, and whether cMD predicts longitudinal cognitive decline, neurodegeneration and clinical progression. The study sample comprised n = 196 cognitively normal older adults (mean[SD] 72.5 [9.4] years; 114 women [58.2%]) from the Harvard Aging Brain Study. At baseline, all participants underwent structural MRI, DWI, ¹¹C-Pittsburgh compound-B-PET, ¹⁸F-flortaucipir-PET imaging, and cognitive assessments. Longitudinal measures of Preclinical Alzheimer Cognitive Composite-5 were available for n = 186 individuals over 3.72 (1.96)-year follow-up. Prospective clinical follow-up was available for n = 163 individuals over 3.2 (1.7) years. Surface-based image analysis assessed vertex-wise relationships between cMD, global amyloid-β, and entorhinal and inferior-temporal tau. Multivariable regression, mixed effects models and Cox proportional hazards regression assessed longitudinal cognition, brain structural changes and clinical progression. Tau, but not amyloid-β, was positively associated with cMD in AD-vulnerable regions. Correcting for baseline demographics and cognition, increased cMD predicted steeper cognitive decline, which remained significant after correcting for amyloid-β, thickness, and entorhinal tau; there was a synergistic interaction between cMD and both amyloid-β and tau on cognitive slope. Regional cMD predicted hippocampal atrophy rate, independently from amyloid-β, tau, and thickness. Elevated cMD predicted progression to mild cognitive impairment. Cortical microstructure is a noninvasive biomarker that independently predicts subsequent cognitive decline, neurodegeneration and clinical progression, suggesting utility in clinical trials.