Advanced imaging tools to investigate multiple sclerosis pathology

Quantitative susceptibility mapping of the normal-appearing white matter as a potential new marker of disability progression in multiple sclerosis

OBJECTIVES

To investigate the normal-appearing white matter (NAWM) susceptibility in a cohort of newly diagnosed multiple sclerosis (MS) patients and to evaluate possible correlations between NAWM susceptibility and disability progression.

METHODS

Fifty-nine patients with a diagnosis of MS (n = 53) or clinically isolated syndrome (CIS) (n = 6) were recruited and followed up. All participants underwent neurological examination, blood sampling for serum neurofilament light chain (sNfL) level assessment, lumbar puncture for the quantification of cerebrospinal fluid (CSF) β-amyloid1-42 (Aβ) levels, and brain MRI. T2-weighted scans were used to quantify white matter (WM) lesion loads. For each scan, we derived the NAWM volume fraction and the WM lesion volume fraction. Quantitative susceptibility mapping (QSM) of the NAWM was calculated using the susceptibility tensor imaging (STI) suite. Susceptibility maps were computed with the STAR algorithm.

RESULTS

Primary progressive patients (n = 9) showed a higher mean susceptibility value in the NAWM than relapsing-remitting (n = 44) and CIS (n = 6) (p = 0.01 and p = 0.02). Patients with a higher susceptibility in the NAWM showed increased sNfL concentration (ρ = 0.38, p = 0.004) and lower CSF Aβ levels (ρ = -0.34, p = 0.009). Mean NAWM susceptibility turned out to be a predictor of the expanded disability status scale (EDSS) worsening at follow-up (β = 0.41, t = 2.66, p = 0.01) and of the MS severity scale (MSSS) (β = 0.38, t = 2.43, p = 0.019).

CONCLUSIONS

QSM in the NAWM seems to predict the EDSS increment over time. This finding might provide evidence on the role of QSM in identifying patients with an increased risk of early disability progression.

KEY POINTS

• NAWM-QSM is higher in PPMS patients than in RRMS. • NAWM-QSM seems to be a predictor of EDSS worsening over time. • Patients with higher NAWM-QSM show increased sNfL concentration and lower CSF Aβ levels.

Early remission in multiple sclerosis is linked to altered coherence of the Cerebellar Network

BACKGROUND

The development of permanent disability in multiple sclerosis (MS) is highly variable among patients, and the exact mechanisms that contribute to this disability remain unknown.

METHODS

Following the idea that the brain has intrinsic network organization, we investigated changes of functional networks in MS patients to identify possible links between network reorganization and remission from clinical episodes in MS. Eighteen relapsing-remitting MS patients (RRMS) in their first clinical manifestation underwent resting-state functional MRI and again during remission. We used ten template networks, identified from independent component analysis, to compare changes in network coherence for each patient compared to those of 44 healthy controls from the Human Connectome Project test-retest dataset (two-sample t-test of pre-post differences). Combining a binomial test with Monte Carlo procedures, we tested four models of how functional coherence might change between the first clinical episode and remission: a network can change its coherence (a) with itself ("one-with-self"), (b) with another network ("one-with-other"), or (c) with a set of other networks ("one-with-many"), or (d) multiple networks can change their coherence with respect to one common network ("many-with-one").

RESULTS

We found evidence supporting two of these hypotheses: coherence decreased between the Executive Control Network and several other networks ("one-with-many" hypothesis), and a set of networks altered their coherence with the Cerebellar Network ("many-with-one" hypothesis).

CONCLUSION

Given the unexpected commonality of the Cerebellar Network's altered coherence with other networks (a finding present in more than 70% of the patients, despite their clinical heterogeneity), we conclude that remission in MS may result from learning processes mediated by the Cerebellar Network.

Gray Matter Matters: A Longitudinal Magnetic Resonance Voxel-Based Morphometry Study of Primary Progressive Multiple Sclerosis

Background: Multiple Sclerosis (MS) lesions in white matter (WM) are easily detected with conventional MRI which induce inflammation thereby generating contrast. WM lesions do not consistently explain the extent of clinical disability, cognitive impairment, or the source of an exacerbation. Gray matter (GM) structures including the cerebral cortex and various deep nuclei are known to be affected early in Primary Progressive Multiple Sclerosis (PPMS) and drive disease progression, disability, fatigue, and cognitive dysfunction. However, little is known about how rapidly GM lesions develop and accumulate over time.

Objective: The purpose of this study is to analyze the degree and rate of progression in 25 patients with PPMS using voxel-based automated volumetric quantitation.

Methods: This is a retrospective single-center study which includes a cohort of 25 patients with PPMS scanned utilizing NeuroQuant® 3 dimensional voxel-based morphometry (3D VBM) automated analysis and database and restudied after a period of ~1 year (11–14 months). Comparisons with normative data were acquired for whole brain, forebrain parenchyma, cortical GM, hippocampus, thalamus, superior and inferior lateral ventricles. GM volume changes were correlated with their clinical motor and cognitive scores using Extended Disability Status Scales (EDSS) and Montreal Cognitive Assessments (MoCA).

Results: Steep reductions occurred in cerebral cortical GM and deep GM nuclei volumes which correlated with each patient's clinical and cognitive impairment. The median observed percentile volume losses were statistically significant compared with the 50th percentile for each GM component. Longitudinal assessments of an unselected sample of one dozen patients involved in the PPMS study showed prominent losses occurring mainly in cortical GM and hippocampus which were reflected in their EDSS and MoCA. The longitudinal results were compared with a similar sample of patients having Relapsing MS (RMS) whose GM values were largely in normal range, annualized volume GM changes were much less, while WM hyperintensities were in abnormal range in half the unselected cases.

Conclusions: Knowledge of the degree and rapidity with which cortical atrophy and deep GM volume loss develops clarifies the source of progressive cognitive and clinical decline in PPMS.

Calgary Normative Study: design of a prospective longitudinal study to characterise potential quantitative MR biomarkers of neurodegeneration over the adult lifespan

INTRODUCTION

A number of MRI methods have been proposed to be useful, quantitative biomarkers of neurodegeneration in ageing. The Calgary Normative Study (CNS) is an ongoing single-centre, prospective, longitudinal study that seeks to develop, test and assess quantitative magnetic resonance (MR) methods as potential biomarkers of neurodegeneration. The CNS has three objectives: first and foremost, to evaluate and characterise the dependence of the selected quantitative neuroimaging biomarkers on age over the adult lifespan; second, to evaluate the precision, variability and repeatability of quantitative neuroimaging biomarkers as part of biomarker validation providing proof-of-concept and proof-of-principle; and third, provide a shared repository of normative data for comparison to various disease cohorts.

METHODS AND ANALYSIS

Quantitative MR mapping of the brain including longitudinal relaxation time (T1), transverse relaxation time (T2), T2*, magnetic susceptibility (QSM), diffusion and perfusion measurements, as well as morphological assessments are performed. The Montreal Cognitive Assessment (MoCA) and a brief, self-report medical history will be collected. Mixed regression models will be used to characterise changes in quantitative MR biomarker measures over the adult lifespan. In this report, we describe the study design, strategies to recruit and perform changes to the acquisition protocol from inception to 31 December 2018, planned statistical approach and data sharing procedures for the study.

ETHICS AND DISSEMINATION

Participants provide signed informed consent. Changes in quantitative MR biomarkers measured over the adult lifespan as well as estimates of measurement variance and repeatability will be disseminated through peer-reviewed scientific publication.

Chronic inflammation in multiple sclerosis - seeing what was always there

Activation of innate immune cells and other compartmentalized inflammatory cells in the brains and spinal cords of people with relapsing-remitting multiple sclerosis (MS) and progressive MS has been well described histopathologically. However, conventional clinical MRI is largely insensitive to this inflammatory activity. The past two decades have seen the introduction of quantitative dynamic MRI scanning with contrast agents that are sensitive to the reduction in blood-brain barrier integrity associated with inflammation and to the trafficking of inflammatory myeloid cells. New MRI imaging sequences provide improved contrast for better detection of grey matter lesions. Quantitative lesion volume measures and magnetic resonance susceptibility imaging are sensitive to the activity of macrophages in the rims of white matter lesions. PET and magnetic resonance spectroscopy methods can also be used to detect contributions from innate immune activation in the brain and spinal cord. Some of these advanced research imaging methods for visualization of chronic inflammation are practical for relatively routine clinical applications. Observations made with the use of these techniques suggest ways of stratifying patients with MS to improve their care. The imaging methods also provide new tools to support the development of therapies for chronic inflammation in MS.

Molecular imaging of multiple sclerosis: from the clinical demand to novel radiotracers

BACKGROUND

Brain PET imaging with different tracers is mainly clinically used in the field of neurodegenerative diseases and brain tumors. In recent years, the potential usefulness of PET has also gained attention in the field of MS. In fact, MS is a complex disease and several processes can be selected as a target for PET imaging. The use of PET with several different tracers has been mainly evaluated in the research setting to investigate disease pathophysiology (i.e. phenotypes, monitoring of progression) or to explore its use a surrogate end-point in clinical trials.

RESULTS

We have reviewed PET imaging studies in MS in humans and animal models. Tracers have been grouped according to their pathophysiological targets (ie. tracers for myelin kinetic, neuroinflammation, and neurodegeneration). The emerging clinical indication for brain PET imaging in the differential diagnosis of suspected tumefactive demyelinated plaques as well as the clinical potential provided by PET images in view of the recent introduction of PET/MR technology are also addressed.

CONCLUSION

While several preclinical and fewer clinical studies have shown results, full-scale clinical development programs are needed to translate molecular imaging technologies into a clinical reality that could ideally fit into current precision medicine perspectives.

A Novel Classification Method using Effective Neural Network and Quantitative Magnetization Transfer Imaging of Brain White Matter in Relapsing Remitting Multiple Sclerosis

BACKGROUND

Quantitative Magnetization Transfer Imaging (QMTI) is often used to quantify the myelin content in multiple sclerosis (MS) lesions and normal appearing brain tissues. Also, automated classifiers such as artificial neural networks (ANNs) can significantly improve the identification and classification processes of MS clinical datasets.

OBJECTIVE

We classified patients with relapsing-remitting multiple sclerosis (RRMS) from healthy subjects using QMTI and T1 longitudinal relaxation time data of brain white matter, then the performance of three ANN-based classifiers have been investigated.

MATERIALS AND METHODS

The input features of ANN algorithms, including multilayer perceptron (MLP), radial basis function (RBF) and ensemble neural networks based on Akaike information criterion (ENN-AIC) were extracted in the form of QMTI and T1 mean values from parametric maps. The ANNs quantitative performance is measured by the standard evaluation of confusion matrix criteria.

RESULTS

The results indicate that ENN-AIC-based classification method has achieved 90% accuracy, 92% sensitivity and 86% precision compared to other ANN models. NPV, FPR and FDR values were found to be 0.933, 0.125 and 0.133, respectively, according to the proposed ENN-AIC model. A graphical representation of how to track actual data by the predictive values derived from ANN algorithms, was also presented.

CONCLUSION

It has been demonstrated that ENN-AIC as an effective neural network improves the quality of classification results compared to MLP and RBF.In addition, this research provides a new direction to classify a large amount of quantitative MRI data that can help the physician in a correct MS diagnosis.

A Novel Classification Method using Effective Neural Network and Quantitative Magnetization Transfer Imaging of Brain White Matter in Relapsing Remitting Multiple Sclerosis

Background

Quantitative Magnetization Transfer Imaging (QMTI) is often used to quantify the myelin content in multiple sclerosis (MS) lesions and normal appearing brain tissues. Also, automated classifiers such as artificial neural networks (ANNs) can significantly improve the identification and classification processes of MS clinical datasets.

Objective

We classified patients with relapsing-remitting multiple sclerosis (RRMS) from healthy subjects using QMTI and T1 longitudinal relaxation time data of brain white matter, then the performance of three ANN-based classifiers have been investigated.

Materials and Methods

The input features of ANN algorithms, including multilayer perceptron (MLP), radial basis function (RBF) and ensemble neural networks based on Akaike information criterion (ENN-AIC) were extracted in the form of QMTI and T1 mean values from parametric maps. The ANNs quantitative performance is measured by the standard evaluation of confusion matrix criteria.

Results

The results indicate that ENN-AIC-based classification method has achieved 90% accuracy, 92% sensitivity and 86% precision compared to other ANN models. NPV, FPR and FDR values were found to be 0.933, 0.125 and 0.133, respectively, according to the proposed ENN-AIC model. A graphical representation of how to track actual data by the predictive values derived from ANN algorithms, was also presented.

Conclusion

It has been demonstrated that ENN-AIC as an effective neural network improves the quality of classification results compared to MLP and RBF.In addition, this research provides a new direction to classify a large amount of quantitative MRI data that can help the physician in a correct MS diagnosis.

Amyloid PET as a marker of normal-appearing white matter early damage in multiple sclerosis: correlation with CSF β-amyloid levels and brain volumes

PURPOSE

The disease course of multiple sclerosis (MS) is unpredictable, and reliable prognostic biomarkers are needed. Positron emission tomography (PET) with β-amyloid tracers is a promising tool for evaluating white matter (WM) damage and repair. Our aim was to investigate amyloid uptake in damaged (DWM) and normal-appearing WM (NAWM) of MS patients, and to evaluate possible correlations between cerebrospinal fluid (CSF) β-amyloid_1-42 (Aβ) levels, amyloid tracer uptake, and brain volumes.

METHODS

Twelve MS patients were recruited and divided according to their disease activity into active and non-active groups. All participants underwent neurological examination, neuropsychological testing, lumbar puncture, brain magnetic resonance (MRI) imaging, and ¹⁸F-florbetapir PET. Aβ levels were determined in CSF samples from all patients. MRI and PET images were co-registered, and mean standardized uptake values (SUV) were calculated for each patient in the NAWM and in the DWM. To calculate brain volumes, brain segmentation was performed using statistical parametric mapping software. Nonparametric statistical analyses for between-group comparisons and regression analyses were conducted.

RESULTS

We found a lower SUV in DWM compared to NAWM (p < 0.001) in all patients. Decreased NAWM-SUV was observed in the active compared to non-active group (p < 0.05). Considering only active patients, NAWM volume correlated with NAWM-SUV (p = 0.01). Interestingly, CSF Aβ concentration was a predictor of both NAWM-SUV (r = 0.79; p = 0.01) and NAWM volume (r = 0.81, p = 0.01).

CONCLUSIONS

The correlation between CSF Aβ levels and NAWM-SUV suggests that the predictive role of β-amyloid may be linked to early myelin damage and may reflect disease activity and clinical progression.

Molecular and Metabolic Imaging in Multiple Sclerosis

Multiple sclerosis is a multifactorial disease with heterogeneous pathogenetic mechanisms, which deserve to be studied to evaluate new possible targets for treatments and improve patient management. MR spectroscopy and PET allow assessing in vivo the molecular and metabolic mechanisms underlying the pathogenesis of multiple sclerosis. This article focuses on the relationship between these imaging techniques and the biologic and chemical pathways leading to multiple sclerosis pathology and its clinical features. Future directions of research are also presented.

Imaging outcome measures for progressive multiple sclerosis trials

Imaging markers that are reliable, reproducible and sensitive to neurodegenerative changes in progressive multiple sclerosis (MS) can enhance the development of new medications with a neuroprotective mode-of-action. Accordingly, in recent years, a considerable number of imaging biomarkers have been included in phase 2 and 3 clinical trials in primary and secondary progressive MS. Brain lesion count and volume are markers of inflammation and demyelination and are important outcomes even in progressive MS trials. Brain and, more recently, spinal cord atrophy are gaining relevance, considering their strong association with disability accrual; ongoing improvements in analysis methods will enhance their applicability in clinical trials, especially for cord atrophy. Advanced magnetic resonance imaging (MRI) techniques (e.g. magnetization transfer ratio (MTR), diffusion tensor imaging (DTI), spectroscopy) have been included in few trials so far and hold promise for the future, as they can reflect specific pathological changes targeted by neuroprotective treatments. Positron emission tomography (PET) and optical coherence tomography have yet to be included. Applications, limitations and future perspectives of these techniques in clinical trials in progressive MS are discussed, with emphasis on measurement sensitivity, reliability and sample size calculation.

Gray and White Matter Demyelination and Remyelination Detected with Multimodal Quantitative MRI Analysis at 11.7T in a Chronic Mouse Model of Multiple Sclerosis

Myelin is a component of the nervous system that is disrupted in multiple sclerosis, resulting in neuro-axonal degeneration. The longitudinal effect of chronic cuprizone-induced demyelination was investigated in the cerebral gray and white matter of treated mice and the spontaneous remyelination upon treatment interruption. Multimodal Magnetic Resonance Imaging and a Cryoprobe were used at 11.7T to measure signal intensity ratios, T₂ values and diffusion metrics. The results showed significant and reversible modifications in white matter and gray matter regions such as in the rostral and caudal corpus callosum, the external capsule, the cerebellar peduncles, the caudate putamen, the thalamus, and the somatosensory cortex of treated mice. T₂ and radial diffusivity metrics appeared to be more sensitive than fractional anisotropy, axial diffusivity or mean diffusivity to detect those cuprizone-induced changes. In the gray matter, only signal and T₂ metrics and not diffusion metrics were sensitive to detect any changes. Immunohistochemical qualitative assessments in the same regions confirmed demyelination and remyelination processes. These multimodal data will provide better understanding of the dynamics of cuprizone-induced de- and remyelination in white and gray matter structures, and will be the basis to test therapies in experimental models.

Precision Medicine in Multiple Sclerosis: Future of PET Imaging of Inflammation and Reactive Astrocytes

Non-invasive molecular imaging techniques can enhance diagnosis to achieve successful treatment, as well as reveal underlying pathogenic mechanisms in disorders such as multiple sclerosis (MS). The cooperation of advanced multimodal imaging techniques and increased knowledge of the MS disease mechanism allows both monitoring of neuronal network and therapeutic outcome as well as the tools to discover novel therapeutic targets. Diverse imaging modalities provide reliable diagnostic and prognostic platforms to better achieve precision medicine. Traditionally, magnetic resonance imaging (MRI) has been considered the golden standard in MS research and diagnosis. However, positron emission tomography (PET) imaging can provide functional information of molecular biology in detail even prior to anatomic changes, allowing close follow up of disease progression and treatment response. The recent findings support three major neuroinflammation components in MS: astrogliosis, cytokine elevation, and significant changes in specific proteins, which offer a great variety of specific targets for imaging purposes. Regardless of the fact that imaging of astrocyte function is still a young field and in need for development of suitable imaging ligands, recent studies have shown that inflammation and astrocyte activation are related to progression of MS. MS is a complex disease, which requires understanding of disease mechanisms for successful treatment. PET is a precise non-invasive imaging method for biochemical functions and has potential to enhance early and accurate diagnosis for precision therapy of MS. In this review we focus on modulation of different receptor systems and inflammatory aspect of MS, especially on activation of glial cells, and summarize the recent findings of PET imaging in MS and present the most potent targets for new biomarkers with the main focus on experimental MS research.