ReviewThe Lancet. Neurology2016
MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines.
Review in The Lancet. Neurology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 359 papers, 7 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
359 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Expert Panel Consensus Guidelines of the German Society of Neuroradiology on the Use of Magnetic Resonance Imaging in the Diagnosis and Monitoring of Multiple Sclerosis.Clinical neuroradiology · 2026Guideline
- Natalizumab and Tyruko (natalizumab biosimilar) for treating highly active relapsing-remitting multiple sclerosis after at least one disease-modifying therapy: a systematic review and economic model.Health technology assessment (Winchester, England) · 2026Pooled it
- Magnetic Resonance Imaging-Based Artificial Intelligence in Predicting Prostate Cancer Biochemical Recurrence: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Characteristics of MRI lesions in AQP4 antibody-positive NMOSD, MOGAD, and multiple sclerosis: a systematic review and meta-analysis.Journal of neurology · 2025Pooled it
- Clinical outcomes after switching from fingolimod to B-cell-depleting therapies in multiple sclerosis: systematic review and meta-analysis.Journal of neurology · 2025Pooled it
- The coincidence of multiple sclerosis and primary vasculitis; from the bench of pathology to the bedside of treatment: a systematic review of case reports.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Pooled it
- Diagnostic effectiveness of deep learning-based MRI in predicting multiple sclerosis: A meta-analysis.Neurosciences (Riyadh, Saudi Arabia) · 2024Pooled it
- Optic Nerve Lesion Length at the Acute Phase of Optic Neuritis Is Predictive of Retinal Neuronal Loss.Neurology(R) neuroimmunology & neuroinflammation · 2022Trial
- Sex- and age-specific associations ofAnnals of medicine · 2026Article
- Divergent Trends in Relapse Activity and Relapse-Independent Progression Over Two Decades in Multiple Sclerosis.Neurology and therapy · 2026Article
- Exploring the Type 4 Cerebrospinal Fluid Oligoclonal Band Pattern: Clinical and Paraclinical Features with Diagnostic Implications.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- An Explainable Multi-Scale Deep Learning Framework for Multi-Class Brain MRI Classification.Diagnostics (Basel, Switzerland) · 2026Article
- Whole anterior visual pathway segmentation from high-resolution MRI using artificial intelligence.European radiology experimental · 2026Article
- Deep learning-based neuroanatomical profiling reveals population-specific brain changes in multiple sclerosis: a large-scale Middle Eastern study.BMC medical imaging · 2026Observational
- From Phenotypes to Spectrum: Rethinking RRMS, SPMS and PPMS in the Era of PIRA-A Framework Integrating PIRA, Smouldering-Associated Worsening, and Neurologic Reserve to Facilitate Earlier Recognition of Progression.Neurology international · 2026Review
- Multiplexed magnetic resonance imaging.Nature · 2026Article
- Advancing clinical trial readiness in white matter disease and related dementias: key steps for future research progress.GeroScience · 2026Article
- Reliability of a convolutional neural network in segmenting multiple sclerosis lesions from MRI: Impact of data augmentation, image modality and tolerance with U-Net architecture.PLOS digital health · 2026Article
- Visualizing cortical laminar architecture in the living human brain using next-generation ultra-high-gradient diffusion MRI.Communications biology · 2026Article
- UNISELF: A unified network with instance normalization and self-ensembled lesion fusion for multiple sclerosis lesion segmentation.Medical image analysis · 2026Article
299 more citing papers are in PubMed but not listed here.
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Authors and funding
17 authors.
Funding
Abstract
In patients presenting with a clinically isolated syndrome, MRI can support and substitute clinical information in the diagnosis of multiple sclerosis by showing disease dissemination in space and time and by helping to exclude disorders that can mimic multiple sclerosis. MRI criteria were first included in the diagnostic work-up for multiple sclerosis in 2001, and since then several modifications to the criteria have been proposed in an attempt to simplify lesion-count models for showing disease dissemination in space, change the timing of MRI scanning to show dissemination in time, and increase the value of spinal cord imaging. Since the last update of these criteria, new data on the use of MRI to establish dissemination in space and time have become available, and MRI technology has improved. State-of-the-art MRI findings in these patients were discussed in a MAGNIMS workshop, the goal of which was to provide an evidence-based and expert-opinion consensus on proposed modifications to MRI criteria for the diagnosis of multiple sclerosis.
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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.