Functional connectivity changes and their relationship with clinical disability and white matter integrity in patients with relapsing-remitting multiple sclerosis

Background and objective: To define the pathological substrate underlying disability in multiple sclerosis by evaluating the relationship of resting-state functional connectivity with microstructural brain damage, as assessed by diffusion tensor maging, and clinical impairments. Methods: Thirty relapsing–remitting patients and 24 controls underwent 3T-MRI; motor abilities were evaluated by using measures of walking speed, hand dexterity and balance capability, while information processing speed was evaluated by a paced auditory serial addiction task. Independent component analysis and tract-based spatial statistics were applied to RS-fMRI and diffusion tensor imaging data using FSL software. Group differences, after dual regression, and clinical correlations were modelled with GeneralLinear-Model and corrected for multiple comparisons. Results: Patients showed decreased functional connectivity in 5 of 11 resting-state-networks (cerebellar, executive-control, medial-visual, basal ganglia and sensorimotor), changes in inter-network correlations and widespread white matter microstructural damage. In multiple sclerosis, corpus callosum microstructural damage positively correlated with functional connectivity in cerebellar and auditory networks. Moreover, functional connectivity within the medial-visual network inversely correlated with information processing speed. White matter widespread microstructural damage inversely correlated with both the paced auditory serial addiction task and hand dexterity. Conclusions: Despite the within-network functional connectivity decrease and the widespread microstructural damage, the inter-network functional connectivity changes suggest a global brain functional rearrangement in multiple sclerosis. The correlation between functional connectivity alterations and callosal damage uncovers a link between functional and structural connectivity. Finally, functional connectivity abnormalities affect information processing speed rather than motor abilities

Setting a research agenda for progressive multiple sclerosis: The International Collaborative on Progressive MS

Despite significant progress in the development of therapies for relapsing MS, progressive MS remains comparatively disappointing. Our objective, in this paper, is to review the current challenges in developing therapies for progressive MS and identify key priority areas for research. A collaborative was convened by volunteer and staff leaders from several MS societies with the mission to expedite the development of effective disease-modifying and symptom management therapies for progressive forms of multiple sclerosis. Through a series of scientific and strategic planning meetings, the collaborative identified and developed new perspectives on five key priority areas for research: experimental models, identification and validation of targets and repurposing opportunities, proof-of-concept clinical trial strategies, clinical outcome measures, and symptom management and rehabilitation. Our conclusions, tackling the impediments in developing therapies for progressive MS will require an integrated, multi-disciplinary approach to enable effective translation of research into therapies for progressive MS. Engagement of the MS research community through an international effort is needed to address and fund these research priorities with the ultimate goal of expediting the development of disease-modifying and symptom-relief treatments for progressive MS

The role of fMRI in the assessment of neuroplasticity in MS: a systematic review

Neuroplasticity, which is the ability of the brain to adapt to internal and external environmental changes, physiologically occurs during growth and in response to damage. The brain's response to damage is of particular interest in multiple sclerosis, a chronic disease characterized by inflammatory and neurodegenerative damage to the central nervous system. Functional MRI (fMRI) is a tool that allows functional changes related to the disease and to its evolution to be studied in vivo. Several studies have shown that abnormal brain recruitment during the execution of a task starts in the early phases of multiple sclerosis. The increased functional activation during a specific task observed has been interpreted mainly as a mechanism of adaptive plasticity designed to contrast the increase in tissue damage. More recent fMRI studies, which have focused on the activity of brain regions at rest, have yielded nonunivocal results, suggesting that changes in functional brain connections represent mechanisms of either adaptive or maladaptive plasticity. The few longitudinal studies available to date on disease evolution have also yielded discrepant results that are likely to depend on the clinical features considered and the length of the follow-up. Lastly, fMRI has been used in interventional studies to investigate plastic changes induced by pharmacological therapy or rehabilitation, though whether such changes represent a surrogate of neuroplasticity remains unclear. The aim of this paper is to systematically review the existing literature in order to provide an overall description of both the neuroplastic process itself and the evolution in the use of fMRI techniques as a means of assessing neuroplasticity. The quantitative and qualitative approach adopted here ensures an objective analysis of published, peer-reviewed research and yields an overview of up-to-date knowledge

Neural indicators of fatigue in chronic diseases : A systematic review of MRI studies

The authors would like to thank the Sir Jules Thorn Charitable Trust for their financial support.Peer reviewedPublisher PD

Backward Walking: A Novel Marker Of Fall Risk, Cognitive Dysfunction, And Myelin Damage In Persons With Multiple Sclerosis

Multiple sclerosis (MS) is a progressive, neurologic disease of the central nervous system that causes debilitating motor, sensory and cognitive impairments. As a result, persons with MS are at an increased risk for falls and falls represent a serious public health concern for the MS population. The current clinical measures used to assess fall risk in MS patients lack sensitivity and predictive validity for falls and are limited in their ability to capture to multiple functional domains (i.e., motor, sensory, cognitive and pathological domains) that are impaired by MS. Backward walking sensitively detects falls in the elderly and other neurologic diseases. However, backward walking and falls has never been explored in the MS population and the underlying reasons as to why backward walking sensitively detects falls remains unknown. Identification of a quick, simply and clinically feasible fall risk measures related to multiple functions impacted by MS and related to fall risk, which can detect falls before they occur is critical for fall prevention and timely and targeted intervention. Therefore, this dissertation examines backward walking as a novel marker of fall risk and its cognitive and pathological underpinnings to support its clinical utility. Our results indicate that backward walking is a sensitive marker of fall risk in the MS population, regardless of co-morbid cognitive deficits, and that examining underlying brain regions likely to contribute to backward walking performance including the corticospinal tract, corpus callosum and cerebellum, with neuroimaging tools sensitive to myelin (i.e., Myelin Water Imaging) demonstrate potential to identify underlying mechanisms of backward walking performance in the MS population. This work is the critical first step in establishing backward walking as a sensitive marker of fall risk for the MS population and leads the way to more personalized fall prevention therapies and interventions to improve clinical outcomes and decrease fall rates in the MS population

Subtyping relapsing–remitting multiple sclerosis using structural MRI

Background and purpose: Subtyping relapsing–remitting multiple sclerosis (RRMS) patients may help predict disease progression and triage patients for treatment. We aimed to subtype RRMS patients by structural MRI and investigate their clinical significances. / Methods: 155 relapse-remitting MS (RRMS) and 210 healthy controls (HC) were retrospectively enrolled with structural 3DT1, diffusion tensor imaging (DTI) and resting-state functional MRI. Z scores of cortical and deep gray matter volumes (CGMV and DGMV) and white matter fractional anisotropy (WM-FA) in RRMS patients were calculated based on means and standard deviations of HC. We defined RRMS as “normal” (− 2 < z scores of both GMV and WM-FA), DGM (z scores of DGMV < − 2), and DGM-plus types (z scores of DGMV and [CGMV or WM-FA] < − 2) according to combinations of z scores compared to HC. Expanded disability status scale (EDSS), cognitive and functional MRI measurements, and conversion rate to secondary progressive MS (SPMS) at 5-year follow-up were compared between subtypes. / Results: 77 (49.7%) patients were “normal” type, 37 (23.9%) patients were DGM type and 34 (21.9%) patients were DGM-plus type. 7 (4.5%) patients who were not categorized into the above types were excluded. DGM-plus type had the highest EDSS. Both DGM and DGM-plus types had more severe cognitive impairment than “normal” type. Only DGM-plus type showed decreased functional MRI measures compared to HC. A higher conversion ratio to SPMS in DGM-plus type (55%) was identified compared to “normal” type (14%, p < 0.001) and DGM type (20%, p = 0.005). / Conclusion: Three MRI-subtypes of RRMS were identified with distinct clinical and imaging features and different prognosis

Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation

Machine learning-based imaging diagnostics has recently reached or even superseded the level of clinical experts in several clinical domains. However, classification decisions of a trained machine learning system are typically non-transparent, a major hindrance for clinical integration, error tracking or knowledge discovery. In this study, we present a transparent deep learning framework relying on convolutional neural networks (CNNs) and layer-wise relevance propagation (LRP) for diagnosing multiple sclerosis (MS). MS is commonly diagnosed utilizing a combination of clinical presentation and conventional magnetic resonance imaging (MRI), specifically the occurrence and presentation of white matter lesions in T2-weighted images. We hypothesized that using LRP in a naive predictive model would enable us to uncover relevant image features that a trained CNN uses for decision-making. Since imaging markers in MS are well-established this would enable us to validate the respective CNN model. First, we pre-trained a CNN on MRI data from the Alzheimer's Disease Neuroimaging Initiative (n = 921), afterwards specializing the CNN to discriminate between MS patients and healthy controls (n = 147). Using LRP, we then produced a heatmap for each subject in the holdout set depicting the voxel-wise relevance for a particular classification decision. The resulting CNN model resulted in a balanced accuracy of 87.04% and an area under the curve of 96.08% in a receiver operating characteristic curve. The subsequent LRP visualization revealed that the CNN model focuses indeed on individual lesions, but also incorporates additional information such as lesion location, non-lesional white matter or gray matter areas such as the thalamus, which are established conventional and advanced MRI markers in MS. We conclude that LRP and the proposed framework have the capability to make diagnostic decisions of..

Understanding cognitive dysfunction in secondary progressive multiple sclerosis using functional and structural MRI

This thesis concerns a 2 year follow-up study of people with secondary progressive multiple sclerosis (SPMS). I investigate: (1) cognitive performance of SPMS and changes over time, (2) the classification of cognitive impairment and predictors of this, (3) mechanisms underlying the SPMS phenotype with and without cognitive impairment using functional and structural MRI. The literature has highlighted the input of executive dysfunction in the cognitive profile of SPMS over and above that seen in other multiple sclerosis (MS) phenotypes. I looked at cognitive performance in SPMS, and predictors of this in this pure SPMS cohort study. I found that being employed, having higher IQ, more premorbid leisure interests, and higher qualifications mitigate against negative cognitive outcomes in SPMS. Additionally, anxiety, even when not reaching clinically diagnostic levels, impacts on tests of information processing speed, verbal working memory, and executive function in SPMS. The symbol digit modality test (SDMT) at baseline is predicted by MS lower limb disability outcome measures; the Expanded Disability Status Scale (EDSS) and timed 25 foot walk (T25FW) which emphasises the role of the SDMT as an adjunctive measure of clinical disability prediction in studies. I show that decline on the SDMT at follow-up is purely predicted by cognitive measures of information processing speed and working memory at either timepoint, supporting, and furthering, the evidence for the SDMT as a sentinel assessment of cognitive performance in SPMS. These findings inform future longitudinal cognitive studies in SPMS, particularly with regards to the importance of tests of executive function, and important associations with clinical outcomes in a highly disabled cohort. I also considered the threshold for classifying cognitive impairment, and its implications. There is marked heterogeneity in these thresholds due to the lack of current consensus on a diagnostic criteria. Using a higher threshold for cognitive impairment in my studies strengthened the associations with clinically relevant outcomes. Additionally, unemployment showed the greatest association with cognitive impairment regardless of criteria used. I found that assessments of information processing speed, verbal memory, and executive function had the greatest input to cognitive impairment in SPMS. These findings indicate the importance of these cognitive domains and demographic factors when evaluating cognitive status in SPMS. These results will guide the international consensus on how best to measure cognitive impairment in SPMS, and in MS more broadly. Posterior and deep resting state networks (RSNs) have been shown to be altered in resting state functional MRI (rs-fMRI) studies of progressive MS phenotypes. I confirm this using functional connectivity (FC) and highlight that this is mainly in terms of cognitive RSNs in SPMS versus healthy controls using a global rs-fMRI analysis technique. Additionally, with cognitive impairment in SPMS, I show that there are key attentional RSN FC reductions. I further highlight the importance of more stringent classification criteria of cognitive impairment to allow for more detailed evaluation of dynamic FC changes, that are missed when using a lenient criteria. Over time, the development of cognitive impairment in SPMS from a preserved state appears to relate to reduced FC in working memory, posterior default mode (DMN) and visual RSNs, and increased FC in the executive control, and more anterior DMN hubs at baseline. Therefore, alterations in posterior cognitive and executive RSNs may inform cognitive status in SPMS. These results provide, to my knowledge, the first longitudinal rs-fMRI study of cognitive status in SPMS. Regional grey matter atrophy has been shown to be greater in SPMS then in other MS phenotypes. I found that SPMS cognitive impairment is associated with grey matter volume, cortical grey matter volume, and deep grey matter and regional deep grey matter atrophy. I also highlighted that proportionally, within the cerebellum, there are greater percentage changes in FC versus volume in those with SPMS with cognitive impairment versus in SPMS overall. These findings therefore show the importance of deeper grey matter atrophy in SPMS underlying cognitive impairment, and indicate the need for a longitudinal study of rs-fMRI and regional grey matter MRI metrics to understand the interplay of underlying mechanisms in more detail

Cognitive alterations in Multiple Sclerosis patients: diagnostic, prognostic, and rehabilitation aspects

Cognitive impairment is frequent in most patients with Multiple Sclerosis (MS) and affects several cognitive domains, having a significant impact on their quality of life and on their personal, social and work dimensions. An early and comprehensive neuropsychological assessment may provide relevant diagnostic, prognostic, and rehabilitative implications. The first chapter highlights the diagnostic and the prognostic aspects, with the description of a multicentric project, conducted in collaboration with MS centers of Bergamo, Montichiari, and Modena, in which were included newly-diagnosed MS patients and were evaluated their neurological, neuropsychological, neuroradiological and bioumoral outcomes. Results of this project have allowed the preparation of several sub-studies with important results: the first study highlighted how MS patients at the time of diagnosis, even in the absence of an evident cognitive impairment as clinically defined, are characterized by slight cognitive alterations as compared to healthy controls, both considering global cognitive functioning level and also specific cognitive domains. The second study has allowed the identification of two biomarkers present in the cerebrospinal fluid that are associated with cognitive alterations: the first (LIGHT) is associated with the inflammatory phase of the disease, while the second (parvalbumin) is associated with the neurodegenerative phase of the disease and also correlates with cortical thinning and physical disability, moreover with a stronger association compared to the one found with the level of neurofilament light chain (NF-L, a well-known biomarker of neurodegeneration). The third study has allowed to describe the predictive role of some inflammatory cytokines in the cerebrospinal fluid (CXCL13, CXCL12, IFNγ, TNF, TWEAK, LIGHT, sCD163) in discriminating, since the time of diagnosis, those MS patients that were more likely to develop neurologic and neuroradiologic worsening after 4-years follow-up. The second chapter addresses the importance of assessing MS patients not only with the classical neuropsychological tests but also with experimental paradigms. The first study, conducted in collaboration with the University of Florence and the University of Padua, investigated the phenomena of false memories, using a paradigm that induces memory distortions due to the strong connection between words associated with a same semantic category. Results showed that MS patients were not characterized by the expected memory distortions, probably due to weak association between nodes that compose semantic memory, because of neurodegenerative events. The second study, conducted in collaboration with the Kessler Foundation (West Orange, NJ, USA), focused on social cognition abilities: in a group of MS patients without evidence of cognitive impairment as traditionally defined was observed a performance significantly lower compared to healthy controls in tests of facial emotion recognition, theory of mind, and empathy. Moreover, it was demonstrated that these social cognition alterations were correlated specifically with the cortical lesions volume in both the amygdalae of MS patients, while no significant correlation was found with other measures of brain damage included in the study (cortical thickness and cortical lesion load in all the cerebral cortex). The third and last chapter focuses on the rehabilitative aspects, showing results from a study carried at the Buffalo Neuroimaging Analysis Center (Buffalo, NY, USA) on a group of MS patients that performed a cognitive training by using a telerehabilitation approach. The project aimed to identify neurological, psychological and neuroradiological variables able to characterize patients that can benefit more from the rehabilitation. Results showed that a relapsing-remitting disease phenotype (as compared with progressive patients), a higher personality trait of conscientiousness, a higher gray matter volume, a lower tract disruption in a network centered on precuneus and posterior cingulate, and a higher deviation in functional brain connectivity compared to healthy controls, play a key role to achieve a greater cognitive amelioration after the rehabilitative treatment