Semiautomated Evaluation of the Primary Motor Cortex in Patients with Amyotrophic Lateral Sclerosis at 3T

Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.

Distribution Indices of Magnetic Susceptibility Values in the Primary Motor Cortex Enable to Classify Patients with Amyotrophic Lateral Sclerosis

Quantitative Susceptibility Mapping (QSM) can measure iron concentration increase in the primary motor cortex (M1) of patients with Amyotrophic Lateral Sclerosis (ALS). However, such alteration is confined to only specific regions interested by upper motor neuron pathology; therefore, mean QSM values in the entire M1 have limited diagnostic accuracy in discriminating between ALS patients and control subjects. This study investigates the diagnostic accuracy of a broader set of M1 QSM distribution indices in classifying ALS patients and controls. Mean, standard deviation, skewness and kurtosis of M1 QSM values were used either individually or as combined predictors in support vector machines. The classification performance was compared to that obtained by the radiological assessment of T2* signal hypo-intensity of M1 in susceptibility-weighted MRI. The least informative index for the classification of ALS patients and controls was the subject’s mean QSM value in M1. The highest diagnostic performance was obtained when all the distribution indices of positive QSM values in M1 were considered, which yielded a diagnostic accuracy of 0.90, with sensitivity = 0.89 and specificity = 1. The radiological assessment of M1 yielded a diagnostic accuracy of 0.79, with sensitivity = 0.76 and specificity = 0.90. The joint evaluation of QSM distribution indices could support the clinical examination in ALS diagnosis and patient monitoring.

Iron-sensitive MR imaging of the primary motor cortex to differentiate hereditary spastic paraplegia from other motor neuron diseases

OBJECTIVES

Hereditary spastic paraplegia (HSP) is a group of genetic neurodegenerative diseases characterised by upper motor neuron (UMN) impairment of the lower limbs. The differential diagnosis with primary lateral sclerosis (PLS) and amyotrophic lateral sclerosis (ALS) can be challenging. As microglial iron accumulation was reported in the primary motor cortex (PMC) of ALS cases, here we assessed the radiological appearance of the PMC in a cohort of HSP patients using iron-sensitive MR imaging and compared the PMC findings among HSP, PLS, and ALS patients.

METHODS

We included 3-T MRI scans of 23 HSP patients, 7 PLS patients with lower limb onset, 8 ALS patients with lower limb and prevalent UMN onset (UMN-ALS), and 84 ALS patients with any other clinical picture. The PMC was visually rated on 3D T2*-weighted images as having normal signal intensity, mild hypointensity, or marked hypointensity, and differences in the frequency distribution of signal intensity among the diseases were investigated.

RESULTS

The marked hypointensity in the PMC was visible in 3/22 HSP patients (14%), 7/7 PLS patients (100%), 6/8 UMN-ALS patients (75%), and 35/84 ALS patients (42%). The frequency distribution of normal signal intensity, mild hypointensity, and marked hypointensity in HSP patients was different than that in PLS, UMN-ALS, and ALS patients (p < 0.01 in all cases).

CONCLUSIONS

Iron-sensitive imaging of the PMC could provide useful information in the diagnostic work - up of adult patients with a lower limb onset UMN syndrome, as the cortical hypointensity often seen in PLS and ALS cases is apparently rare in HSP patients.

KEY POINTS

• The T2* signal intensity of the primary motor cortex was investigated in patients with HSP, PLS with lower limb onset, and ALS with lower limb and prevalent UMN onset (UMN-ALS) using a clinical 3-T MRI sequence. • Most HSP patients had normal signal intensity in the primary motor cortex (86%); on the contrary, all the PLS and the majority of UMN-ALS patients (75%) had marked cortical hypointensity. • The T2*-weighted imaging of the primary motor cortex could provide useful information in the differential diagnosis of sporadic adult-onset UMN syndromes.

Motor cortical patterns of upper motor neuron pathology in amyotrophic lateral sclerosis: A 3 T MRI study with iron-sensitive sequences

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M1 regions associated with the body site of onset are frequently affected at MRI.

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The simultaneous involvement of both homologous M1 regions is frequent.

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The T2* hypointensity in non-contiguous M1 regions seems rare.

Background

Patterns of initiation and propagation of disease in Amyotrophic Lateral Sclerosis (ALS) are still partly unknown. Single or multiple foci of neurodegeneration followed by disease diffusion to contiguous or connected regions have been proposed as mechanisms underlying symptom occurrence. Here, we investigated cortical patterns of upper motor neuron (UMN) pathology in ALS using iron-sensitive MR imaging.

Methods

Signal intensity and magnetic susceptibility of the primary motor cortex (M1), which are associated with clinical UMN burden and neuroinflammation, were assessed in 78 ALS patients using respectively T2*-weighted images and Quantitative Susceptibility Maps. The signal intensity of the whole M1 and each of its functional regions was rated as normal or reduced, and the magnetic susceptibility of each M1 region was measured.

Results

The highest frequencies of T2* hypointensity were found in M1 regions associated with the body sites of symptom onset. Homologous M1 regions were both hypointense in 80–93 % of patients with cortical abnormalities, and magnetic susceptibility values measured in homologous M1 regions were strongly correlated with each other (ρ = 0.88; p < 0.0001). In some cases, the T2* hypointensity was detectable in two non-contiguous M1 regions but spared the cortex in between.

Conclusions

M1 regions associated with the body site of onset are frequently affected at imaging. The simultaneous involvement of both homologous M1 regions is frequent, followed by that of adjacent regions; the affection of non-contiguous regions, instead, seems rare. This type of cortical involvement suggests the interhemispheric connections as one of the preferential paths for the UMN pathology diffusion in ALS.

Enhancing the impact of Artificial Intelligence in Medicine: A joint AIFM-INFN Italian initiative for a dedicated cloud-based computing infrastructure

Artificial Intelligence (AI) techniques have been implemented in the field of Medical Imaging for more than forty years. Medical Physicists, Clinicians and Computer Scientists have been collaborating since the beginning to realize software solutions to enhance the informative content of medical images, including AI-based support systems for image interpretation. Despite the recent massive progress in this field due to the current emphasis on Radiomics, Machine Learning and Deep Learning, there are still some barriers to overcome before these tools are fully integrated into the clinical workflows to finally enable a precision medicine approach to patients' care. Nowadays, as Medical Imaging has entered the Big Data era, innovative solutions to efficiently deal with huge amounts of data and to exploit large and distributed computing resources are urgently needed. In the framework of a collaboration agreement between the Italian Association of Medical Physicists (AIFM) and the National Institute for Nuclear Physics (INFN), we propose a model of an intensive computing infrastructure, especially suited for training AI models, equipped with secure storage systems, compliant with data protection regulation, which will accelerate the development and extensive validation of AI-based solutions in the Medical Imaging field of research. This solution can be developed and made operational by Physicists and Computer Scientists working on complementary fields of research in Physics, such as High Energy Physics and Medical Physics, who have all the necessary skills to tailor the AI-technology to the needs of the Medical Imaging community and to shorten the pathway towards the clinical applicability of AI-based decision support systems.

Studying Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis with 7-T magnetic resonance

Ultra-high-field (UHF) magnetic resonance (MR) scanners, that is, equipment operating at static magnetic field of 7 tesla (7 T) and above, enable the acquisition of data with greatly improved signal-to-noise ratio with respect to conventional MR systems (e.g., scanners operating at 1.5 T and 3 T). The change in tissue relaxation times at UHF offers the opportunity to improve tissue contrast and depict features that were previously inaccessible. These potential advantages come, however, at a cost: in the majority of UHF-MR clinical protocols, potential drawbacks may include signal inhomogeneity, geometrical distortions, artifacts introduced by patient respiration, cardiac cycle, and motion. This article reviews the 7 T MR literature reporting the recent studies on the most widespread neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.

Corticospinal Tract and Related Grey Matter Morphometric Shape Analysis in ALS Phenotypes: A Fractal Dimension Study

A pathological hallmark of amyotrophic lateral sclerosis (ALS) is corticospinal tract (CST) degeneration resulting in upper motor neuron (UMN) dysfunction. No quantitative test is available to easily assess UMN pathways. Brain neuroimaging in ALS promises to potentially change this through identifying biomarkers of UMN dysfunction that may accelerate diagnosis and track disease progression. Fractal dimension (FD) has successfully been used to quantify brain grey matter (GM) and white matter (WM) shape complexity in various neurological disorders. Therefore, we investigated CST and whole brain GM and WM morphometric changes using FD analyses in ALS patients with different phenotypes. We hypothesized that FD would detect differences between ALS patients and neurologic controls and even between the ALS subgroups. Neuroimaging was performed in neurologic controls (n = 14), and ALS patients (n = 75). ALS patients were assigned into four groups based on their clinical or radiographic phenotypes. FD values were estimated for brain WM and GM structures. Patients with ALS and frontotemporal dementia (ALS-FTD) showed significantly higher CST FD values and lower primary motor and sensory cortex GM FD values compared to other ALS groups. No other group of ALS patients revealed significant FD value changes when compared to neurologic controls or with other ALS patient groups. These findings support a more severe disease process in ALS-FTD patients compared to other ALS patient groups. FD value measures may be a sensitive index to evaluate GM and WM (including CST) degeneration in ALS patients.

Clinically Applicable Quantitative Magnetic Resonance Morphologic Measurements of Grey Matter Changes in the Human Brain

(1) Purpose: Quantitative magnetic resonance imaging (qMRI) measurements can be used to sensitively estimate brain morphological alterations and may support clinical diagnosis of neurodegenerative diseases (ND). We aimed to establish a normative reference database for a clinical applicable quantitative MR morphologic measurement on neurodegenerative changes in patients; (2) Methods: Healthy subjects (HCs, n = 120) with an evenly distribution between 21 to 70 years and amyotrophic lateral sclerosis (ALS) patients (n = 11, mean age = 52.45 ± 6.80 years), as an example of ND patients, underwent magnetic resonance imaging (MRI) examinations under routine diagnostic conditions. Regional cortical thickness (rCTh) in 68 regions of interest (ROIs) and subcortical grey matter volume (SGMV) in 14 ROIs were determined from all subjects by using Computational Anatomy Toolbox. Those derived from HCs were analyzed to determine age-related differences and subsequently used as reference to estimate ALS-related alterations; (3) Results: In HCs, the rCTh (in 49/68 regions) and the SGMV (in 9/14 regions) in elderly subjects were less than those in younger subjects and exhibited negative linear correlations to age (p < 0.0007 for rCTh and p < 0.004 for SGMV). In comparison to age- and sex-matched HCs, the ALS patients revealed significant decreases of rCTh in eight ROIs, majorly located in frontal and temporal lobes; (4) Conclusion: The present study proves an overall grey matter decline with normal ageing as reported previously. The provided reference may be used for detection of grey matter alterations in neurodegenerative diseases that are not apparent in standard MR scans, indicating the potential of using qMRI as an add-on diagnostic tool in a clinical setting.

Genetic Convergence Brings Clarity to the Enigmatic Red Line in ALS

Amyotrophic lateral sclerosis (ALS) is an aggressive neurodegenerative disorder that orchestrates an attack on the motor nervous system that is unrelenting. Recent discoveries into the pathogenic consequences of repeat expansions in C9ORF72, which are the most common genetic cause of ALS, combined with the identification of new genetic mutations are providing novel insight into the underlying mechanism(s) that cause ALS. In particular, the myriad of functions linked to ALS-associated genes have collectively implicated four main pathways in disease pathogenesis, including RNA metabolism and translational biology; protein quality control; cytoskeletal integrity and trafficking; and mitochondrial function and transport. Through the identification of common disease mechanisms on which multiple ALS genes converge, key targets for potential therapeutic intervention are highlighted.

MRI cortical feature of bulbar impairment in patients with amyotrophic lateral sclerosis

The decline of voluntary bulbar functions such as speech and swallowing are among the clinical manifestations of amyotrophic lateral sclerosis (ALS) influencing a worst prognosis. Differential diagnosis between the contribution of upper motor neuron (UMN) and lower motor neuron degeneration to the bulbar impairment is often hard. Thinning and T2* hypointensity of the primary motor cortex have been recently suggested as possible MRI markers of UMN impairment in ALS patients, but little research has purposely targeted the orofacial region of the primary motor cortex (fM1). With the aim of finding an MRI marker of UMN impairment responsible for bulbar dysfunction, we investigated the T2* signal intensity of fM1 and the relationship with bulbar impairment in ALS patients. Fifty-five ALS patients were examined with 3 T MRI. Their fM1 was evaluated both qualitatively in terms of T2* signal intensity and quantitatively by measuring its magnetic susceptibility with Quantitative Susceptibility Mapping (QSM). Bulbar functions were assessed clinically, by neurological examination and using the items 1–3 of the ALSFRS-R, and with neurophysiological tests.

The marked hypointensity of fM1 was detected in 25% of ALS patients, including all patients with bulbar onset, and was 74% sensitive, 100% specific and 91% accurate in diagnosing functional bulbar impairment. Such hypointensity involved the middle and ventral part of fM1 and was usually visible in both hemispheres. The magnetic susceptibility was significantly higher in patients with marked fM1 hypointensity than in the other patients (p ≤ .001).

The relationship with clinical and neurophysiological data suggests that such feature could be a marker of UMN degeneration for voluntary bulbar functions.

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T2* hypointensity was assessed in the orofacial region of M1 (fM1) of ALS patients.

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All ALS patients with marked T2* hypointensity of fM1 had bulbar impairment (BI).

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The marked T2* hypointensity of fM1 was 91% accurate in diagnosing BI.

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fM1 hypointensity can be a marker of upper motor neuron degeneration causing BI.

Imaging Biomarkers for the Diagnosis and Prognosis of Neurodegenerative Diseases. The Example of Amyotrophic Lateral Sclerosis

The term amyotrophic lateral sclerosis (ALS) comprises a heterogeneous group of fatal neurodegenerative disorders of largely unknown etiology characterized by the upper motor neurons (UMN) and/or lower motor neurons (LMN) degeneration. The development of brain imaging biomarkers is essential to advance in the diagnosis, stratification and monitoring of ALS, both in the clinical practice and clinical trials. In this review, the characteristics of an optimal imaging biomarker and common pitfalls in biomarkers evaluation will be discussed. Moreover, the development and application of the most promising brain magnetic resonance (MR) imaging biomarkers will be reviewed. Finally, the integration of both qualitative and quantitative multimodal brain MR biomarkers in a structured report will be proposed as a support tool for ALS diagnosis and stratification.