ArticleNeuroImage. Clinical2018
Baseline biomarkers of connectome disruption and atrophy predict future processing speed in early multiple sclerosis.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
23 citing papers in PubMed.
- Structural covariance analysis for neurodegenerative and neuroinflammatory brain disorders.Brain : a journal of neurology · 2025Review
- Conventional MRI-Based Structural Disconnection and Morphometric Similarity Networks and Their Clinical Correlates in Multiple Sclerosis.Neurology · 2025Article
- Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis.Biological psychiatry · 2024Article
- Article
- Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis.The Cochrane database of systematic reviews · 2023Review
- Mapping the relationship of white matter lesions to depression in multiple sclerosis.medRxiv : the preprint server for health sciences · 2023Article
- The sequence of regional structural disconnectivity due to multiple sclerosis lesions.Brain communications · 2023Article
- Correlations between hippocampal functional connectivity, structural changes, and clinical data in patients with relapsing-remitting multiple sclerosis: a case-control study using multimodal magnetic resonance imaging.Neural regeneration research · 2022Article
- Gray matter atrophy in relapsing-remitting multiple sclerosis is associated with white matter lesions in connecting fibers.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Article
- Disease correlates of rim lesions on quantitative susceptibility mapping in multiple sclerosis.Scientific reports · 2022Article
- Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study.NeuroImage. Clinical · 2022Article
- Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome.Frontiers in robotics and AI · 2022Article
- Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis.Journal of personalized medicine · 2021Review
- Structural disconnectivity from paramagnetic rim lesions is related to disability in multiple sclerosis.Brain and behavior · 2021Article
- Estimated connectivity networks outperform observed connectivity networks when classifying people with multiple sclerosis into disability groups.NeuroImage. Clinical · 2021Article
- Dynamic Functional Connectivity Better Predicts Disability Than Structural and Static Functional Connectivity in People With Multiple Sclerosis.Frontiers in neuroscience · 2021Article
- Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises.Biological psychiatry · 2020Review
- MRI biomarkers of disease progression in multiple sclerosis: old dog, new tricks?Quantitative imaging in medicine and surgery · 2020Article
- Structural brain networks and functional motor outcome after stroke-a prospective cohort study.Brain communications · 2020Article
- Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis.Frontiers in neurology · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The development of accurate prognoses in multiple sclerosis is difficult, as the disease is characterized by heterogeneous patterns of brain abnormalities that relate in an unclear way to future impairments. Here, we use a statistical modeling approach to determine if the baseline pattern of connectome disruption due to T2-FLAIR lesions could predict a patient's future processing speed, as measured using the Symbol Digits Modality Test scores. Imaging data, demographics and Symbol Digits Modality Test scores were collected from 61 early relapsing remitting multiple sclerosis patients. The Network Modification Tool was used to estimate damage to the connectome by quantifying white matter abnormalities' effects on 1) global network properties, 2) regional connectivity and 3) connectivity between pairs of regions. MS subjects showed significant improvement of processing speed between baseline and follow-up (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.