ArticleAJNR. American journal of neuroradiology2019
Determinants of Deep Gray Matter Atrophy in Multiple Sclerosis: A Multimodal MRI Study.
Article in AJNR. American journal of neuroradiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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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
35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.
- Quantitative Susceptibility Mapping Values Quantification in Deep Gray Matter Structures for Relapsing-Remitting Multiple Sclerosis: A Systematic Review and Meta-Analysis.Brain and behavior · 2024Pooled it
- Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis.NeuroImage. Clinical · 2024Pooled it
- Nucleus-specific thalamic volumes and retinal thickness in pediatric-onset multiple sclerosis: a cross-sectional study.European journal of pediatrics · 2026Article
- Insights From Quantitative Susceptibility Mapping: An Umbrella Review of Multiple Sclerosis.Health science reports · 2026Review
- Microstructure-informed deep learning improves thalamic atrophy segmentation and clinical associations in multiple sclerosis and related neuroimmunological diseases.NeuroImage. Clinical · 2026Article
- Nomograms integrating cortical morphometric metrics with 3D multi-parametric MRI radiomics for predicting disability progression and cognitive worsening in relapsing-remitting multiple sclerosis: a multi-center validation study.Journal of neurology · 2025Article
- Quantitative Susceptibility Mapping of Deep Grey Matter in MS: Association With Clinical Scores and Brain Volume Measures.Brain and behavior · 2025Article
- Grey matter atrophy patterns of mobility shared across older adults with and without multiple sclerosis.Journal of neurology · 2025Article
- Neurological disability and brain grey matter atrophy in primary progressive multiple sclerosis are determined by microstructural lesional changes, but not by lesion load.Journal of neurology · 2025Article
- Thalamic iron in multiple sclerosis: Waning support for the early-rise late-decline hypothesis.NeuroImage. Clinical · 2025Article
- Impact of processing and analysis methodology on thalamic susceptibility assessment in multiple sclerosis.PloS one · 2025Article
- Leveraging hand-crafted radiomics on multicenter FLAIR MRI for predicting disability worsening in people with multiple sclerosis.Frontiers in neuroscience · 2025Article
- Automated Quantitative Susceptibility and Morphometry MR Study: Feasibility and Interrelation Between Clinical Score, Lesion Load, Deep Grey Matter and Normal-Appearing White Matter in Multiple Sclerosis.Diagnostics (Basel, Switzerland) · 2024Article
- The role of 7 T MRI to assess atrophy of the subcortical deep gray matter in relapsing-remitting multiple sclerosis.Journal of neurology · 2024Article
- Causal relationships of grey matter structures in multiple sclerosis and neuromyelitis optica spectrum disorder: insights from Mendelian randomization.Brain communications · 2024Article
- Clinical correlates of R1 relaxometry and magnetic susceptibility changes in multiple sclerosis: a multi-parameter quantitative MRI study of brain iron and myelin.European radiology · 2023Article
- Unmet needs and gaps in the identification of secondary progression in multiple sclerosis: a Southern Italy healthcare professionals' perspective.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023Review
- Accounting for uncertainty in training data to improve machine learning performance in predicting new disease activity in early multiple sclerosis.Frontiers in neurology · 2023Article
- Iron deposition in multiple sclerosis: overall load or distribution alteration?European radiology experimental · 2022Article
- Tissue damage detected by quantitative gradient echo MRI correlates with clinical progression in non-relapsing progressive MS.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Article
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Authors and funding
14 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeDeep gray matter involvement is a consistent feature in multiple sclerosis. The aim of this study was to evaluate the relationship between different deep gray matter alterations and the development of subcortical atrophy, as well as to investigate the possible different substrates of volume loss between phenotypes. MATERIALS AND
methodsSeventy-seven patients with MS (52 with relapsing-remitting and 25 with progressive MS) and 41 healthy controls were enrolled in this cross-sectional study. MR imaging investigation included volumetric, DTI, PWI and Quantitative Susceptibility Mapping analyses. Deep gray matter structures were automatically segmented to obtain volumes and mean values for each MR imaging metric in the thalamus, caudate, putamen, and globus pallidus. Between-group differences were probed by ANCOVA analyses, while the contribution of different MR imaging metrics to deep gray matter atrophy was investigated via hierarchic multiple linear regression models.
resultsPatients with MS showed a multifaceted involvement of the thalamus and basal ganglia, with significant atrophy of all deep gray matter structures (
conclusionsOur study confirms the diffuse involvement of deep gray matter in MS, demonstrating a different behavior between MS phenotypes, with subcortical GM atrophy mainly determined by global WM lesion burden in patients with relapsing-remitting MS, while local microstructural damage and susceptibility changes mainly accounted for the development of deep gray matter volume loss in patients with progressive MS.
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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.