Neurite density is reduced in the presymptomatic phase of C9orf72 disease

Premorbid brain structure influences risk of amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a disease of the motor network associated with brain structure and functional connectivity alterations that are implicated in disease progression. Whether such changes have a causal role in ALS, fitting with a postulated influence of premorbid cerebral architecture on the phenotypes associated with neurodegenerative disorders is not known.

METHODS

This study considered causal effects and shared genetic risk of 2240 structural and functional MRI brain scan imaging-derived phenotypes (IDPs) on ALS using two sample Mendelian randomisation, with putative associations further examined with extensive sensitivity analysis. Shared genetic predisposition between IDPs and ALS was explored using genetic correlation analysis.

RESULTS

Increased white matter volume in the cerebral hemispheres was causally associated with ALS. Weaker causal associations were observed for brain stem grey matter volume, parieto-occipital white matter surface and volume of the left thalamic ventral anterior nucleus. Genetic correlation was observed between ALS and intracellular volume fraction and isotropic free water volume fraction within the posterior limb of the internal capsule.

CONCLUSIONS

This study provides evidence that premorbid brain structure, in particular white matter volume, contributes to the risk of ALS.

Data-driven modelling of neurodegenerative disease progression: thinking outside the black box

Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.

Neurite orientation dispersion and density imaging quantifies microstructural impairment in the thalamus and its connectivity in amyotrophic lateral sclerosis

AIMS

To evaluate microstructural impairment in the thalamus and thalamocortical connectivity using neurite orientation dispersion and density imaging (NODDI) in amyotrophic lateral sclerosis (ALS).

METHODS

This study included 47 healthy controls and 43 ALS patients, whose structural and diffusion-weighted data were collected. We used state-of-the-art parallel transport tractography to identify thalamocortical pathways in individual spaces. Thalamus was then parcellated into six subregions based on its connectivity pattern with the priori defined cortical (i.e., prefrontal/motor/somatosensory/temporal/posterior-parietal/occipital) regions. For each of the thalamic and cortical subregions and thalamo-cortical tracts, we compared the following NODDI metrics between groups: orientation dispersion index (ODI), neurite density index (NDI), and isotropic volume fraction (ISO). We also used these metrics to conduct receiver operating characteristic curve (ROC) analyses and Spearman correlation.

RESULTS

In ALS patients, we found decreased ODI and increased ISO in the thalamic subregion connecting the left motor cortex and other extramotor (e.g., somatosensory and occipital) cortex (Bonferroni-corrected p < 0.05). NDI decreased in the bilateral thalamo-motor and thalamo-somatosensory tracts and in the right thalamo-posterior-parietal and thalamo-occipital tracts (Bonferroni-corrected p < 0.05). NDI reduction in the bilateral thalamo-motor tract (p = 0.017 and 0.009) and left thalamo-somatosensory tract (p = 0.029) was correlated with disease severity. In thalamo-cortical tracts, NDI yielded a higher effect size during between-group comparisons and a greater area under ROC (p < 0.05) compared with conventional diffusion tensor imaging metrics.

CONCLUSIONS

Microstructural impairment in the thalamus and thalamocortical connectivity is the hallmark of ALS. NODDI improved the detection of disrupted thalamo-cortical connectivity in ALS.

Biomarkers in amyotrophic lateral sclerosis: current status and future prospects

Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG-magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Presymptomatic grey matter alterations in ALS kindreds: a computational neuroimaging study of asymptomatic C9orf72 and SOD1 mutation carriers

BACKGROUND

The characterisation of presymptomatic disease-burden patterns in asymptomatic mutation carriers has a dual academic and clinical relevance. The understanding of disease propagation mechanisms is of considerable conceptual interests, and defining the optimal time of pharmacological intervention is essential for improved clinical trial outcomes.

METHODS

In a prospective, multimodal neuroimaging study, 22 asymptomatic C9orf72 GGGGCC hexanucleotide repeat carriers, 13 asymptomatic subjects with SOD1, and 54 "gene-negative" ALS kindreds were enrolled. Cortical and subcortical grey matter alterations were systematically appraised using volumetric, morphometric, vertex, and cortical thickness analyses. Using a Bayesian approach, the thalamus and amygdala were further parcellated into specific nuclei and the hippocampus was segmented into anatomically defined subfields.

RESULTS

Asymptomatic GGGGCC hexanucleotide repeat carriers in C9orf72 exhibited early subcortical changes with the preferential involvement of the pulvinar and mediodorsal regions of the thalamus, as well as the lateral aspect of the hippocampus. Volumetric approaches, morphometric methods, and vertex analyses were anatomically consistent in capturing focal subcortical changes in asymptomatic C9orf72 hexanucleotide repeat expansion carriers. SOD1 mutation carriers did not exhibit significant subcortical grey matter alterations. In our study, none of the two asymptomatic cohorts exhibited cortical grey matter alterations on either cortical thickness or morphometric analyses.

DISCUSSION

The presymptomatic radiological signature of C9orf72 is associated with selective thalamic and focal hippocampal degeneration which may be readily detectable before cortical grey matter changes ensue. Our findings confirm selective subcortical grey matter involvement early in the course of C9orf72-associated neurodegeneration.

Dynamic structural remodeling of the human visual system prompted by bilateral retinal gene therapy

The impact of changes in visual input on neuronal circuitry is complex and much of our knowledge on human brain plasticity of the visual systems comes from animal studies. Reinstating vision in a group of patients with low vision through retinal gene therapy creates a unique opportunity to dynamically study the underlying process responsible for brain plasticity. Historically, increases in the axonal myelination of the visual pathway has been the biomarker for brain plasticity. Here, we demonstrate that to reach the long-term effects of myelination increase, the human brain may undergo demyelination as part of a plasticity process. The maximum change in dendritic arborization of the primary visual cortex and the neurite density along the geniculostriate tracks occurred at three months (3MO) post intervention, in line with timing for the peak changes in postnatal synaptogenesis within the visual cortex reported in animal studies. The maximum change at 3MO for both the gray and white matter significantly correlated with patients' clinical responses to light stimulations called full field sensitivity threshold (FST). Our results shed a new light on the underlying process of brain plasticity by challenging the concept of increase myelination being the hallmark of brain plasticity and instead reinforcing the idea of signal speed optimization as a dynamic process for brain plasticity.

Longitudinal Effects of Asymptomatic C9orf72 Carriership on Brain Morphology

OBJECTIVE

We investigated effects of C9orf72 repeat expansion and gene expression on longitudinal cerebral changes before symptom onset.

METHODS

We enrolled 79 asymptomatic family members (AFMs) from 9 families with C9orf72 repeat expansion. Twenty-eight AFMs carried the mutation (C9+). Participants had up to 3 magnetic resonance imaging (MRI) scans, after which we compared motor cortex and motor tracts between C9+ and C9- AFMs using mixed effects models, incorporating kinship to correct for familial relations and lessen effects of other genetic factors. We also compared cortical, subcortical, cerebellar, and connectome structural measurements in a hypothesis-free analysis. We correlated regional C9orf72 expression in donor brains with the pattern of cortical thinning in C9+ AFMs using meta-regression. For comparison, we included 42 C9+ and 439 C9- patients with amyotrophic lateral sclerosis (ALS) in this analysis.

RESULTS

C9+ AFM motor cortex had less gyrification and was thinner than in C9- AFMs, without differences in motor tracts. Whole brain analysis revealed thinner cortex and less gyrification in parietal, occipital, and temporal regions, smaller thalami and right hippocampus, and affected frontotemporal connections. Thinning of bilateral precentral, precuneus, and left superior parietal cortex was faster in C9+ than in C9- AFMs. Higher C9orf72 expression correlated with thinner cortex in both C9+ AFMs and C9+ ALS patients.

INTERPRETATION

In asymptomatic C9orf72 repeat expansion carriers, brain MRI reveals widespread features suggestive of impaired neurodevelopment, along with faster decline of motor and parietal cortex than found in normal aging. C9orf72 expression might play a role in cortical development, and consequently explain the specific brain abnormalities of mutation carriers. ANN NEUROL 2022.

Cerebellar pathology in motor neuron disease: neuroplasticity and neurodegeneration

Amyotrophic lateral sclerosis is a relentlessly progressive multi-system condition. The clinical picture is dominated by upper and lower motor neuron degeneration, but extra-motor pathology is increasingly recognized, including cerebellar pathology. Post-mortem and neuroimaging studies primarily focus on the characterization of supratentorial disease, despite emerging evidence of cerebellar degeneration in amyotrophic lateral sclerosis. Cardinal clinical features of amyotrophic lateral sclerosis, such as dysarthria, dysphagia, cognitive and behavioral deficits, saccade abnormalities, gait impairment, respiratory weakness and pseudobulbar affect are likely to be exacerbated by co-existing cerebellar pathology. This review summarizes in vivo and post mortem evidence for cerebellar degeneration in amyotrophic lateral sclerosis. Structural imaging studies consistently capture cerebellar grey matter volume reductions, diffusivity studies readily detect both intra-cerebellar and cerebellar peduncle white matter alterations and functional imaging studies commonly report increased functional connectivity with supratentorial regions. Increased functional connectivity is commonly interpreted as evidence of neuroplasticity representing compensatory processes despite the lack of post-mortem validation. There is a scarcity of post-mortem studies focusing on cerebellar alterations, but these detect pTDP-43 in cerebellar nuclei. Cerebellar pathology is an overlooked facet of neurodegeneration in amyotrophic lateral sclerosis despite its contribution to a multitude of clinical symptoms, widespread connectivity to spinal and supratentorial regions and putative role in compensating for the degeneration of primary motor regions.

Pre-symptomatic radiological changes in frontotemporal dementia: propagation characteristics, predictive value and implications for clinical trials

Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3-141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1-8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.

Early and progressive dysfunction revealed by in vivo neurite imaging in the rNLS8 TDP-43 mouse model of ALS

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Are neurite density and dispersion altered in amyotropic lateral sclerosis (ALS)?

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Both measures are affected in the rNLS8 TDP-43 mouse model of ALS.

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Diffusion tensor imaging metrics were also affected.

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Group-wise changes were observed early in the disease course.

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Together these diffusion imaging metrics may aid in the timelier diagnosis of ALS.

Amyotrophic lateral sclerosis (ALS) is characterized by transactive response DNA-binding protein 43 (TDP-43) pathology, progressive loss of motor neurons and muscle dysfunction. Symptom onset can be insidious and diagnosis challenging. Conventional neuroimaging is used to exclude ALS mimics, however more advanced neuroimaging techniques may facilitate an earlier diagnosis. Here, we investigate the potential for neurite orientation dispersion and density imaging and diffusion tensor imaging (DTI) to detect microstructural changes in an experimental model of ALS with neuronal doxycycline (Dox)-suppressible overexpression of human TDP-43 (hTDP-43). In vivo diffusion-weighted imaging (DWI) was acquired 1- and 3- weeks following the initiation of hTDP-43 expression (post-Dox) to investigate whether neurite density imaging (NDI) and orientation dispersion imaging (ODI) are affected early in this preclinical model of ALS and if so, how these metrics compare to those derived from the diffusion tensor. Tract-based spatial statistics at 1-week post-Dox, i.e. very early in the disease stage, demonstrated increased NDI in TDP-43 mice but no change in ODI or DTI metrics. At 3-weeks post-Dox, a reduced pattern of increased NDI was observed along with widespread increases in ODI, and decreased fractional anisotropy (FA), apparent diffusion coefficient (ADC) and axial diffusivity (AD). A hypothesis driven analysis of the bilateral corticospinal tracts demonstrated that at 1-week post-Dox, ODI was significantly increased caudally but decreased in the motor cortex of TDP-43 mice. Decreased cortical ODI had normalized by 3-weeks post-Dox and only significant increases were observed. A similar, but inverse pattern in FA was also observed. Together, these results suggest a non-monotonic relationship between DWI metrics and pathophysiological progression with TDP-43 mice exhibiting significantly altered diffusion metrics consistent with early inflammation followed by progressive axonal degeneration. Importantly, significant group-wise changes were observed in the earliest stages of disease when subtle pathology may be more elusive to traditional structural imaging techniques.

Characterizing Sensorimotor-Related Area Abnormalities in Amyotrophic Lateral Sclerosis: An Intravoxel Incoherent Motion Magnetic Resonance Imaging Study

RATIONALE AND OBJECTIVES

To investigate the microperfusion and water molecule diffusion alterations in sensorimotor-related areas in amyotrophic lateral sclerosis (ALS) using intravoxel incoherent motion (IVIM) magnetic resonance imaging.

MATERIALS AND METHODS

IVIM data were obtained from 43 ALS patients and 31 controls. This study employed the revised ALS Functional Rating Scale (ALSFRS-R) in evaluating disease severity. IVIM-derived metrics were calculated, including diffusion coefficient (D), pseudo-diffusion coefficient, and perfusion fraction. Conventional apparent diffusion coefficient was also computed. Atlas-based analysis was conducted to detect between-group difference in these metrics in sensorimotor-related gray/white matter areas. Spearman correlation analysis was employed to establish correlation between various metrics and ALSFRS-R.

RESULTS

ALS patients had perfusion fraction (× 10^-3) reduction in the left presupplementary motor area (60.72 ± 16.15 vs. 71.15 ± 12.98, p = 0.016), right presupplementary motor area (61.35 ± 17.02 vs. 72.18 ± 14.22, p = 0.016), left supplementary motor area (55.73 ± 12.29 vs. 64.12 ± 9.17, p = 0.015), and right supplementary motor area (56.53 ± 11.93 vs. 63.67 ± 10.03, p = 0.020). Patients showed D (× 10^-6 mm²/s) increase in a white matter tract projecting to the right ventral premotor cortex (714.20 ± 39.75 vs. 691.01 ± 24.53, p = 0.034). A negative correlation between D of right ventral premotor cortex tract and ALSFRS-R score was observed (r = -0.316, p = 0.039).

CONCLUSION

These findings suggest aberrant microperfusion and water molecule diffusion in the sensorimotor-related areas in ALS patients, which are associated with motor impairment in ALS.

White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation

BACKGROUND

Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets.

METHODS

To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data.

RESULTS

The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics.

CONCLUSIONS

Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.

Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means

Neurite orientation dispersion and density imaging (NODDI) estimates microstructural properties of brain tissue relating to the organisation and processing capacity of neurites, which are essential elements for neuronal communication. Descriptive statistics of NODDI tissue metrics are commonly analyzed in regions-of-interest (ROI) to identify brain-phenotype associations. Here, the conventional method to calculate the ROI mean weights all voxels equally. However, this produces biased estimates in the presence of CSF partial volume. This study introduces the tissue-weighted mean, which calculates the mean NODDI metric across the tissue within an ROI, utilising the tissue fraction estimate from NODDI to reduce estimation bias. We demonstrate the proposed mean in a study of white matter abnormalities in young onset Alzheimer's disease (YOAD). Results show the conventional mean induces significant bias that correlates with CSF partial volume, primarily affecting periventricular regions and more so in YOAD subjects than in healthy controls. Due to the differential extent of bias between healthy controls and YOAD subjects, the conventional mean under- or over-estimated the effect size for group differences in many ROIs. This demonstrates the importance of using the correct estimation procedure when inferring group differences in studies where the extent of CSF partial volume differs between groups. These findings are robust across different acquisition and processing conditions. Bias persists in ROIs at higher image resolution, as demonstrated using data obtained from the third phase of the Alzheimer's disease neuroimaging initiative (ADNI); and when performing ROI analysis in template space. This suggests that conventional ROI means of NODDI metrics are biased estimates under most contemporary experimental conditions, the correction of which requires the proposed tissue-weighted mean. The tissue-weighted mean produces accurate estimates of ROI means and group differences when ROIs contain voxels with CSF partial volume. In addition to NODDI, the technique can be applied to other multi-compartment models that account for CSF partial volume, such as the free water elimination method. We expect the technique to help generate new insights into normal and abnormal variation in tissue microstructure of regions typically confounded by CSF partial volume, such as those in individuals with larger ventricles due to atrophy associated with neurodegenerative disease.

The strength of corticomotoneuronal drive underlies ALS split phenotypes and reflects early upper motor neuron dysfunction

BACKGROUND

Split phenotypes, (split hand, elbow, leg, and foot), are probably unique to ALS, and are characterized by having a shared peripheral input of both affected and unaffected muscles. This implies an anatomical origin rostral to the spinal cord, primarily within the cerebral cortex. Therefore, split phenotypes are a potential marker of ALS upper motor neuron pathology. However, to date, reports documenting upper motor neuron dysfunction in split phenotypes have been limited to using transcranial magnetic stimulation and cortical threshold tracking techniques. Here, we consider several other potential methodologies that could confirm a primary upper motor neuron pathology in split phenotypes.

METHODS

We review the potential of: 1. measuring the compound excitatory post-synaptic potential recorded from a single activated motor unit, 2. cortical-muscular coherence, and 3. new advanced modalities of neuroimaging (high-resolution imaging protocols, ultra-high field MRI platforms [7T], and novel Non-Gaussian diffusion models).

CONCLUSIONS

We propose that muscles involved in split phenotypes are those functionally involved in the human motor repertoire used particularly in complex activities. Their anterior horn cells receive the strongest corticomotoneuronal input. This is also true of the weakest muscles that are the earliest to be affected in ALS. Descriptions of split hand in non-ALS cases and proposals that peripheral nerve or muscle dysfunction may be causative are contentious. Only a few carefully controlled cases of each form of split phenotype, using upper motor neuron directed methodologies, are necessary to prove our postulate.

Biomarkers for C9orf7-ALS in Symptomatic and Pre-symptomatic Patients: State-of-the-art in the New Era of Clinical Trials

The development of new possible treatments for C9orf72-related ALS and the possibility of early identification of subjects genetically at risk of developing the disease is creating a critical need for biomarkers to track neurodegeneration that could be used as outcome measures in clinical trials. Current candidate biomarkers in C9orf72-ALS include neuropsychology tests, imaging, electrophysiology as well as different circulating biomarkers. Neuropsychology tests show early executive and verbal function involvement both in symptomatic and asymptomatic mutation carriers. At brain MRI, C9orf72-ALS patients present diffuse white and grey matter degeneration, which are already identified up to 20 years before symptom onset and that seem to be slowly progressive over time, while regions of altered connectivity at fMRI and of hypometabolism at [¹⁸F]FDG PET have been described as well. At the same time, spinal cord MRI has also shown progressive decrease of FA in the cortico-spinal tract over time. On the side of wet biomarkers, neurofilament proteins are increased both in the CSF and serum just before symptom onset and tend to slowly increase over time, while poly(GP) protein can be detected in the CSF and probably used as target engagement marker in clinical trials.

Brain structural abnormalities in the preclinical stage of Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3): evaluation by MRI morphometry, diffusion tensor imaging and neurite orientation dispersion and density imaging

OBJECTIVE

To investigate whether neurite orientation dispersion and density imaging (NODDI) could provide the added value for detecting brain microstructural alterations in the preclinical stage of Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3) compared with MRI morphometry and diffusion tensor imaging (DTI).

METHODS

Twenty preclinical MJD/SCA3 patients and 21 healthy controls were enrolled. Three b values DWI and 3D T1-weighted images were acquired at 3.0 T. Tract-based spatial statistics (TBSS) approach was used to investigate the white matter (WM) alterations in the DTI metrics and NODDI metrics. Gray matter-based spatial statistics (GBSS) approach was used to investigate the grey matter (GM) alterations in the NODDI metrics. Voxel-based morphometry (VBM) approach was performed on the 3D T1-weighted images. The relationship between the cytosine-adenine-guanine (CAG) repeat length and brain microstructural alterations of preclinical MJD/SCA3 was identified.

RESULTS

Compared with healthy controls, the preclinical MJD/SCA3 patients showed decreased FA and NDI as well as increased MD, AD, and RD in the WM of cerebellum and brainstem (corrected P < 0.05), and decreased NDI in the GM of cerebellar vermis (corrected P < 0.05). The CAG repeat length in preclinical MJD/SCA3 patients was negatively correlated with the reduced FA and NDI of the infratentorial WM and the reduced NDI of the cerebellum, and positively with the increased MD and RD of the infratentorial WM.

CONCLUSIONS

NOODI can provide novel quantitative microstructural changes in MJD/SCA3 carriers, expanding our understanding of the gray and white matter (axons and dendrites) degeneration in this frequent ataxia syndrome.

White matter microstructural impairments in amyotrophic lateral sclerosis: A mean apparent propagator MRI study

Background

White matter (WM) impairment is a hallmark of amyotrophic lateral sclerosis (ALS). This study evaluated the capacity of mean apparent propagator magnetic resonance imaging (MAP-MRI) for detecting ALS-related WM alterations.

Methods

Diffusion images were obtained from 52 ALS patients and 51 controls. MAP-derived indices [return-to-origin/-axis/-plane probability (RTOP/RTAP/RTPP) and non-Gaussianity (NG)/perpendicular/parallel NG (NG_⊥/NG_||)] were computed. Measures from diffusion tensor/kurtosis imaging (DTI/DKI) and neurite orientation dispersion and density imaging (NODDI) were also obtained. Voxel-wise analysis (VBA) was performed to determine differences in these parameters. Relationship between MAP parameters and disease severity (assessed by the revised ALS Functional Rating Scale (ALSFRS-R)) was evaluated by Pearson’s correlation analysis in a voxel-wise way. ALS patients were further divided into two subgroups: 29 with limb-only involvement and 23 with both bulbar and limb involvement. Subgroup analysis was then conducted to investigate diffusion parameter differences related to bulbar impairment.

Results

The VBA (with threshold of P < 0.05 after family-wise error correction (FWE)) showed that ALS patients had significantly decreased RTOP/RTAP/RTPP and NG/ NG_⊥/NG_|| in a set of WM areas, including the bilateral precentral gyrus, corona radiata, posterior limb of internal capsule, midbrain, middle corpus callosum, anterior corpus callosum, parahippocampal gyrus, and medulla. MAP-MRI had the capacity to capture WM damage in ALS, which was higher than DTI and similar to DKI/NODDI. RTOP/RTAP/NG/NG_⊥/NG_|| parameters, especially in the bilateral posterior limb of internal capsule and middle corpus callosum, were significantly correlated with ALSFRS-R (with threshold of FWE-corrected P < 0.05). The VBA (with FWE-corrected P < 0.05) revealed the significant RTAP reduction in subgroup with both bulbar and limb involvement, compared with those with limb-only involvement.

Conclusions

Microstructural impairments in corticospinal tract and corpus callosum represent the consistent characteristic of ALS. MAP-MRI could provide alternative measures depicting ALS-related WM alterations, complementary to the common diffusion imaging methods.

Pathological neural networks and artificial neural networks in ALS: diagnostic classification based on pathognomonic neuroimaging features

The description of group-level, genotype- and phenotype-associated imaging traits is academically important, but the practical demands of clinical neurology centre on the accurate classification of individual patients into clinically relevant diagnostic, prognostic and phenotypic categories. Similarly, pharmaceutical trials require the precision stratification of participants based on quantitative measures. A single-centre study was conducted with a uniform imaging protocol to test the accuracy of an artificial neural network classification scheme on a cohort of 378 participants composed of patients with ALS, healthy subjects and disease controls. A comprehensive panel of cerebral volumetric measures, cortical indices and white matter integrity values were systematically retrieved from each participant and fed into a multilayer perceptron model. Data were partitioned into training and testing and receiver-operating characteristic curves were generated for the three study-groups. Area under the curve values were 0.930 for patients with ALS, 0.958 for disease controls, and 0.931 for healthy controls relying on all input imaging variables. The ranking of variables by classification importance revealed that white matter metrics were far more relevant than grey matter indices to classify single subjects. The model was further tested in a subset of patients scanned within 6 weeks of their diagnosis and an AUC of 0.915 was achieved. Our study indicates that individual subjects may be accurately categorised into diagnostic groups in an observer-independent classification framework based on multiparametric, spatially registered radiology data. The development and validation of viable computational models to interpret single imaging datasets are urgently required for a variety of clinical and clinical trial applications.

Evaluation and categorisation of individual patients based on white matter profiles: Single-patient diffusion data interpretation in neurodegeneration

The majority of radiology studies in neurodegenerative conditions infer group-level imaging traits from group comparisons. While this strategy is helpful to define phenotype-specific imaging signatures for academic use, the meaningful interpretation of single scans of individual subjects is more important in everyday clinical practice. Accordingly, we present a computational method to evaluate individual subject diffusion tensor data to highlight white matter integrity alterations. Fifty white matter tracts were quantitatively evaluated in 132 patients with amyotrophic lateral sclerosis (ALS) with respect to normative values from 100 healthy subjects. Fractional anisotropy and radial diffusivity alterations were assessed individually in each patient. The approach was validated against standard tract-based spatial statistics and further scrutinised by the assessment of 78 additional data sets with a blinded diagnosis. Our z-score-based approach readily detected white matter degeneration in individual ALS patients and helped to categorise single subjects with a 'blinded diagnosis' as likely 'ALS' or 'control'. The group-level inferences from the z-score-based approach were analogous to the standard TBSS output maps. The benefit of the z-score-based strategy is that it enables the interpretation of single DTI datasets as well as the comparison of study groups. Outputs can be summarised either visually by highlighting the affected tracts, or, listing the affected tracts in a text file with reference to normative data, making it particularly useful for clinical applications. While individual diffusion data cannot be visually appraised, our approach provides a viable framework for single-subject imaging data interpretation.

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.

The imaging signature of C9orf72 hexanucleotide repeat expansions: implications for clinical trials and therapy development

While C9orf72-specific imaging signatures have been proposed by both ALS and FTD research groups and considerable presymptomatic alterations have also been confirmed in young mutation carriers, considerable inconsistencies exist in the literature. Accordingly, a systematic review of C9orf72-imaging studies has been performed to identify consensus findings, stereotyped shortcomings, and unique contributions to outline future directions. A formal literature review was conducted according to the STROBE guidelines. All identified papers were individually reviewed for sample size, choice of controls, study design, imaging modalities, statistical models, clinical profiling, and identified genotype-associated pathological patterns. A total of 74 imaging papers were systematically reviewed. ALS patients with GGGGCC repeat expansions exhibit relatively limited motor cortex involvement and widespread extra-motor pathology. C9orf72 positive FTD patients often show preferential posterior involvement. Reports of thalamic involvement are relatively consistent across the various phenotypes. Asymptomatic hexanucleotide repeat carriers often exhibit structural and functional changes decades prior to symptom onset. Common shortcomings included sample size limitations, lack of disease-controls, limited clinical profiling, lack of genetic testing in healthy controls, and absence of post mortem validation. There is a striking paucity of longitudinal studies and existing presymptomatic studies have not evaluated the predictive value of radiological changes with regard to age of onset and phenoconversion. With the advent of antisense oligonucleotide therapies, the meticulous characterisation of C9orf72-associated changes has gained practical relevance. Neuroimaging offers non-invasive biomarkers for future clinical trials, presymptomatic ascertainment, diagnostic and prognostic applications.

The presymptomatic phase of amyotrophic lateral sclerosis: are we merely scratching the surface?

Presymptomatic studies in ALS have consistently captured considerable disease burden long before symptom manifestation and contributed important academic insights. With the emergence of genotype-specific therapies, however, there is a pressing need to address practical objectives such as the estimation of age of symptom onset, phenotypic prediction, informing the optimal timing of pharmacological intervention, and identifying a core panel of biomarkers which may detect response to therapy. Existing presymptomatic studies in ALS have adopted striking different study designs, relied on a variety of control groups, used divergent imaging and electrophysiology methods, and focused on different genotypes and demographic groups. We have performed a systematic review of existing presymptomatic studies in ALS to identify common themes, stereotyped shortcomings, and key learning points for future studies. Existing presymptomatic studies in ALS often suffer from sample size limitations, lack of disease controls and rarely follow their cohort until symptom manifestation. As the characterisation of presymptomatic processes in ALS serves a multitude of academic and clinical purposes, the careful review of existing studies offers important lessons for future initiatives.

Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) have a strong clinical, genetic and pathological overlap. This review focuses on the current understanding of structural, functional and molecular neuroimaging signatures of genetic FTD and ALS. We overview quantitative neuroimaging studies on the most common genes associated with FTD (MAPT, GRN), ALS (SOD1), and both (C9orf72), and summarize visual observations of images reported in the rarer genes (CHMP2B, TARDBP, FUS, OPTN, VCP, UBQLN2, SQSTM1, TREM2, CHCHD10, TBK1).

NODDI in clinical research

Diffusion MRI (dMRI) has proven to be a useful imaging approach for both clinical diagnosis and research investigating the microstructures of nervous tissues, and it has helped us to better understand the neurophysiological mechanisms of many diseases. Though diffusion tensor imaging (DTI) has long been the default tool to analyze dMRI data in clinical research, acquisition with stronger diffusion weightings beyond the DTI regimen is now possible with modern clinical scanners, potentially enabling even more detailed characterization of tissue microstructures. To take advantage of such data, neurite orientation dispersion and density imaging (NODDI) has been proposed as a way to relate the dMRI signal to tissue features via biophysically inspired modeling. The number of reports demonstrating the potential clinical utility of NODDI is rapidly increasing. At the same time, the pitfalls and limitations of NODDI, and general challenges in microstructure modeling, are becoming increasingly recognized by clinicians. dMRI microstructure modeling is a rapidly evolving field with great promise, where people from different scientific backgrounds, such as physics, medicine, biology, neuroscience, and statistics, are collaborating to build novel tools that contribute to improving human healthcare. Here, we review the applications of NODDI in clinical research and discuss future perspectives for investigations toward the implementation of dMRI microstructure imaging in clinical practice.

Longitudinal changes in resting state networks in early presymptomatic carriers of C9orf72 expansions

Previous cross-sectional imaging studies found differences in brain structure and in resting state networks between presymptomatic carriers of mutations in C9orf72 (C9+) and healthy controls. We carried out a prospective longitudinal study of clinical and resting state functional imaging in a cohort of 15 presymptomatic C9+ carriers to determine whether differences in resting state connectivity prior to developing symptoms reflect static developmental differences or ongoing low-grade degenerative changes. Presymptomatic C9+ carriers were scanned at baseline with follow-up scanning at 6- and 18-months and compared to a cohort of 14 healthy controls scanned longitudinally. Resting state networks associated with manifest disease were visualized by comparing 27 symptomatic C9+ carriers to 34 healthy controls. Motor, salience, thalamic, and speech production networks were visualized using a seed-based analysis. Neurofilament light chain was measured in serum obtained at the time of the scans. Neither clinical measures of motor, cognitive, and behavioral function nor neurofilament levels changed over follow-up in presymptomatic C9+ carriers. In thalamic networks, there was a reduction in connectivity in presymptomatic carriers at all timepoints with a constant difference compared to healthy controls. In contrast, precuneus/posterior cingulate regions exhibited declining functional connectivity compared to controls over the 18-month follow-up, particularly in motor networks. These were regions that also exhibited reduced functional connectivity in symptomatic C9+ carriers. Reduced connectivity over time also occurred in small regions of frontal and temporal cortex within salience and thalamic networks in presymptomatic C9+ carriers. A few areas of increased connectivity occurred, including cortex near the motor seed and within the speech production network. Overall, changes in functional connectivity over time favor the explanation of ongoing low-grade alterations in presymptomatic C9+ carriers in most networks, with the exception of thalamic networks where functional connectivity reductions were stable over time. The loss of connectivity to parietal cortex regions in several different networks may be a distinct feature of C9orf72-related degeneration. Longitudinal studies of carriers who phenoconvert will be important to determine the prognostic significance of presymptomatic functional connectivity alterations.

Amygdala pathology in amyotrophic lateral sclerosis and primary lateral sclerosis

Temporal lobe studies in motor neuron disease overwhelmingly focus on white matter alterations and cortical grey matter atrophy. Reports on amygdala involvement are conflicting and the amygdala is typically evaluated as single structure despite consisting of several functionally and cytologically distinct nuclei. A prospective, single-centre, neuroimaging study was undertaken to comprehensively characterise amygdala pathology in 100 genetically-stratified ALS patients, 33 patients with PLS and 117 healthy controls. The amygdala was segmented into groups of nuclei using a Bayesian parcellation algorithm based on a probabilistic atlas and shape deformations were additionally assessed by vertex analyses. The accessory basal nucleus (p = .021) and the cortical nucleus (p = .022) showed significant volume reductions in C9orf72 negative ALS patients compared to controls. The lateral nucleus (p = .043) and the cortico-amygdaloid transition (p = .024) were preferentially affected in C9orf72 hexanucleotide carriers. A trend of total volume reduction was identified in C9orf72 positive ALS patients (p = .055) which was also captured in inferior-medial shape deformations on vertex analyses. Our findings highlight that the amygdala is affected in ALS and our study demonstrates the selective involvement of specific nuclei as opposed to global atrophy. The genotype-specific patterns of amygdala involvement identified by this study are consistent with the growing literature of extra-motor clinical features. Mesial temporal lobe pathology in ALS is not limited to hippocampal pathology but, as a key hub of the limbic system, the amygdala is also affected in ALS.

Assessing neuraxial microstructural changes in a transgenic mouse model of early stage Amyotrophic Lateral Sclerosis by ultra-high field MRI and diffusion tensor metrics

OBJECTIVE

Cell structural changes are one of the main features observed during the development of amyotrophic lateral sclerosis (ALS). In this work, we propose the use of diffusion tensor imaging (DTI) metrics to assess specific ultrastructural changes in the central nervous system during the early neurodegenerative stages of ALS.

METHODS

Ultra-high field MRI and DTI data at 17.6T were obtained from fixed, excised mouse brains, and spinal cords from ALS (G93A-SOD1) mice.

RESULTS

Changes in fractional anisotropy (FA) and linear, planar, and spherical anisotropy ratios (CL, CP, and CS, respectively) of the diffusion eigenvalues were measured in white matter (WM) and gray matter (GM) areas associated with early axonal degenerative processes (in both the brain and the spinal cord). Specifically, in WM structures (corpus callosum, corticospinal tract, and spinal cord funiculi) as the disease progressed, FA, CL, and CP values decreased, whereas CS values increased. In GM structures (prefrontal cortex, hippocampus, and central spinal cord) FA and CP decreased, whereas the CL and CS values were unchanged or slightly smaller. Histological studies of a fluorescent mice model (YFP, G93A-SOD1 mouse) corroborated the early alterations in neuronal morphology and axonal connectivity measured by DTI.

CONCLUSIONS

Changes in diffusion tensor shape were observed in this animal model at the early, nonsymptomatic stages of ALS. Further studies of CL, CP, and CS as imaging biomarkers should be undertaken to refine this neuroimaging tool for future clinical use in the detection of the early stages of 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.

Different CSF protein profiles in amyotrophic lateral sclerosis and frontotemporal dementia with C9orf72 hexanucleotide repeat expansion

OBJECTIVES

The hexanucleotide repeat expansion in the C9orf72 gene is the most common mutation associated with amyotrophic lateral sclerosis (C9-ALS) and frontotemporal dementia (C9-FTD). Until now, it is unknown which factors define whether C9orf72 mutation carriers develop ALS or FTD. Our aim was to identify protein biomarker candidates in the cerebrospinal fluid (CSF) which differentiate between C9-ALS and C9-FTD and might be indicative for the outcome of the mutation.

METHODS

We compared the CSF proteome of 16 C9-ALS and 8 C9-FTD patients and 11 asymptomatic C9orf72 mutation carriers (CAR) by isobaric tags for relative and absolute quantitation. Eleven biomarker candidates were selected from the pool of differentially regulated proteins for further validation by multiple reaction monitoring and single-molecule array in a larger cohort (n=156).

RESULTS

In total, 2095 CSF proteins were identified and 236 proteins were significantly different in C9-ALS versus C9-FTD including neurofilament medium polypeptide (NEFM) and chitotriosidase-1 (CHIT1). Eight candidates were successfully validated including significantly increased ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1) levels in C9-ALS compared with C9-FTD and controls and decreased neuronal pentraxin receptor (NPTXR) levels in C9-FTD versus CAR.

CONCLUSIONS

This study presents a deep proteomic CSF analysis of C9-ALS versus C9-FTD patients. As a proof of concept, we observed higher NEFM and CHIT1 CSF levels in C9-ALS. In addition, we also show clear upregulation of UCHL1 in C9-ALS and downregulation of NPTXR in C9-FTD. Significant differences in UCHL1 CSF levels may explain diverging ubiquitination and autophagy processes and NPTXR levels might reflect different synapses organisation processes.

Detection of Glioblastoma Subclinical Recurrence Using Serial Diffusion Tensor Imaging

Glioblastoma is an aggressive brain tumor with a propensity for intracranial recurrence. We hypothesized that tumors can be visualized with diffusion tensor imaging (DTI) before they are detected on anatomical magnetic resonance (MR) images. We retrospectively analyzed serial MR images from 30 patients, including the DTI and T1-weighted images at recurrence, at 2 months and 4 months before recurrence, and at 1 month after radiation therapy. The diffusion maps and T1 images were deformably registered longitudinally. The recurrent tumor was manually segmented on the T1-weighted image and then applied to the diffusion maps at each time point to collect mean FA, diffusivities, and neurite density index (NDI) values, respectively. Group analysis of variance showed significant changes in FA (p = 0.01) and NDI (p = 0.0015) over time. Pairwise t tests also revealed that FA and NDI at 2 months before recurrence were 11.2% and 6.4% lower than those at 1 month after radiation therapy (p < 0.05), respectively. Changes in FA and NDI were observed 2 months before recurrence, suggesting that progressive microstructural changes and neurite density loss may be detectable before tumor detection in anatomical MR images. FA and NDI may serve as non-contrast MR-based biomarkers for detecting subclinical tumors.

MR Biomarkers of Degenerative Brain Disorders Derived From Diffusion Imaging

The incidence of neurodegenerative diseases has shown an increasing trend. These conditions typically cause progressive functional disability. Identification of robust biomarkers of neurodegenerative diseases is a key imperative to facilitate early identification of the pathological features and to foster a better understanding of the pathogenetic mechanisms of individual diseases. Diffusion tensor imaging (DTI) is the most widely used diffusion MRI technique for assessment of neurodegenerative diseases. The DTI parameters are promising biomarkers for evaluation of microstructural changes; however, some limitations of DTI restrict its wider clinical use. New diffusion MRI techniques, such as diffusion kurtosis imaging (DKI), bi-tensor DTI, and neurite orientation density and dispersion imaging (NODDI) have been demonstrated to provide value addition to DTI for evaluation of neurodegenerative diseases. In this review article, we summarize the key technical aspects and provide an overview of the current state of knowledge regarding the role of DKI, bi-tensor DTI, and NODDI as biomarkers of microstructural changes in representative neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1620-1636.

Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study

OBJECTIVE

C9orf72 hexanucleotide repeats expansions account for almost half of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases. Recent imaging studies in asymptomatic C9orf72 carriers have demonstrated cerebral white (WM) and gray matter (GM) degeneration before the age of 40 years. The objective of this study was to characterize cervical spinal cord (SC) changes in asymptomatic C9orf72 hexanucleotide carriers.

METHODS

Seventy-two asymptomatic individuals were enrolled in a prospective study of first-degree relatives of ALS and FTD patients carrying the c9orf72 hexanucleotide expansion. Forty of them carried the pathogenic mutation (C9⁺ ). Each subject underwent quantitative cervical cord imaging. Structural GM and WM metrics and diffusivity parameters were evaluated at baseline and 18 months later. Data were analyzed in C9⁺ and C9^- subgroups, and C9⁺ subjects were further stratified by age.

RESULTS

At baseline, significant WM atrophy was detected at each cervical vertebral level in C9⁺ subjects older than 40 years without associated changes in GM and diffusion tensor imaging parameters. At 18-month follow-up, WM atrophy was accompanied by significant corticospinal tract (CST) fractional anisotropy (FA) reductions. Intriguingly, asymptomatic C9⁺ subjects older than 40 years with family history of ALS (as opposed to FTD) also exhibited significant CST FA reduction at baseline.

INTERPRETATION

Cervical SC imaging detects WM atrophy exclusively in C9⁺ subjects older than 40 years, and progressive CST FA reductions can be identified on 18-month follow-up. Cervical SC magnetic resonance imaging readily captures presymptomatic pathological changes and disease propagation in c9orf72-associated conditions. ANN NEUROL 2019;86:158-167.

Prodromal and Early bvFTD: Evaluating Clinical Features and Current Biomarkers

Despite the current diagnostic criteria, early diagnostics of behavioral variant of frontotemporal dementia (bvFTD) has remained challenging. Patients with bvFTD often present with misleading psychiatric phenotype, and, on the other hand, impairment in memory functions have increasingly been reported. However, impaired episodic memory is currently considered as an exclusion criterion for bvFTD. Single biofluid-based or imaging biomarkers do not currently provide sufficient sensitivity or specificity for early bvFTD diagnosis at single-subject level, although studies have suggested improved accuracy with different biomarker combinations. In this mini review, we evaluate the core clinical features of early bvFTD and summarize the most potential imaging and fluid biomarkers for bvFTD diagnostics.

An update on genetic frontotemporal dementia

Frontotemporal dementia (FTD) is a highly heritable group of neurodegenerative disorders, with around 30% of patients having a strong family history. The majority of that heritability is accounted for by autosomal dominant mutations in the chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), and microtubule-associated protein tau (MAPT) genes, with mutations more rarely seen in a number of other genes. This review will discuss the recent updates in the field of genetic FTD. Age at symptom onset in genetic FTD is variable with recently identified genetic modifiers including TMEM106B (in GRN carriers particularly) and a polymorphism at a locus containing two overlapping genes LOC101929163 and C6orf10 (in C9orf72 carriers). Behavioural variant FTD (bvFTD) is the most common diagnosis in each of the genetic groups, although in C9orf72 carriers amyotrophic lateral sclerosis either alone, or with bvFTD, is also common. An atypical neuropsychiatric presentation is also seen in C9orf72 carriers and family members of carriers are at greater risk of psychiatric disorders including schizophrenia and autistic spectrum disorders. Large natural history studies of presymptomatic genetic FTD are now underway both in Europe/Canada (GENFI—the Genetic FTD Initiative) and in the US (ARTFL/LEFFTDS study), collaborating together under the banner of the FTD Prevention Initiative (FPI). These studies are taking forward the validation of cognitive, imaging and fluid biomarkers that aim to robustly measure disease onset, staging and progression in genetic FTD. Grey matter changes on MRI and hypometabolism on FDG-PET are seen at least 10 years before symptom onset with white matter abnormalities seen earlier, but the pattern and exact timing of changes differ between different genetic groups. In contrast, tau PET has yet to show promise in genetic FTD. Three key fluid biomarkers have been identified so far that are likely to be helpful in clinical trials—CSF or blood neurofilament light chain levels (in all groups), CSF or blood progranulin levels (in GRN carriers) and CSF poly(GP) dipeptide repeat protein levels (in C9orf72 carriers). Increased knowledge about genetic FTD has led to more clinical presymptomatic genetic testing but this has not yet been mirrored in the development of either an accepted FTD-specific testing protocol or provision of appropriate psychological support mechanisms for those living through the at-risk phase. This will become even more relevant as disease-modifying therapy trials start in each of the genetic groups over the next few years.

Spinal Cord Imaging in Amyotrophic Lateral Sclerosis: Historical Concepts-Novel Techniques

Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease with no effective disease modifying therapies at present. Spinal cord degeneration is a hallmark feature of ALS, highlighted in the earliest descriptions of the disease by Lockhart Clarke and Jean-Martin Charcot. The anterior horns and corticospinal tracts are invariably affected in ALS, but up to recently it has been notoriously challenging to detect and characterize spinal pathology in vivo. With recent technological advances, spinal imaging now offers unique opportunities to appraise lower motor neuron degeneration, sensory involvement, metabolic alterations, and interneuron pathology in ALS. Quantitative spinal imaging in ALS has now been used in cross-sectional and longitudinal study designs, applied to presymptomatic mutation carriers, and utilized in machine learning applications. Despite its enormous clinical and academic potential, a number of physiological, technological, and methodological challenges limit the routine use of computational spinal imaging in ALS. In this review, we provide a comprehensive overview of emerging spinal cord imaging methods and discuss their advantages, drawbacks, and biomarker potential in clinical applications, clinical trial settings, monitoring, and prognostic roles.

Tracking a Fast-Moving Disease: Longitudinal Markers, Monitoring, and Clinical Trial Endpoints in ALS

Amyotrophic lateral sclerosis (ALS) encompasses a heterogeneous group of phenotypes with different progression rates, varying degree of extra-motor involvement and divergent progression patterns. The natural history of ALS is increasingly evaluated by large, multi-time point longitudinal studies, many of which now incorporate presymptomatic and post-mortem assessments. These studies not only have the potential to characterize patterns of anatomical propagation, molecular mechanisms of disease spread, but also to identify pragmatic monitoring markers. Sensitive markers of progressive neurodegenerative change are indispensable for clinical trials and individualized patient care. Biofluid markers, neuroimaging indices, electrophysiological markers, rating scales, questionnaires, and other disease-specific instruments have divergent sensitivity profiles. The discussion of candidate monitoring markers in ALS has a dual academic and clinical relevance, and is particularly timely given the increasing number of pharmacological trials. The objective of this paper is to provide a comprehensive and critical review of longitudinal studies in ALS, focusing on the sensitivity profile of established and emerging monitoring markers.

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

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