ArticleNPJ digital medicine2023
A real-world clinical validation for AI-based MRI monitoring in multiple sclerosis.
Article in NPJ digital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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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.
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.
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Who cites it
24 citing papers in PubMed, 45 citations in OpenAlex.
- Artificial intelligence in central nervous system autoimmune diseases: from clinical decision support to mechanistic discovery and translation.EMBO molecular medicine · 2026Review
- Spinal cord imaging in multiple sclerosis: from diagnosis to disease progression.Journal of neurology · 2026Review
- Degenerative cervical myelopathy diagnosis: applicability of artificial intelligence-enhanced modalities in a systematic review and meta-analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Review
- Artificial Intelligence That Changes Clinical Neurology Practice: Translating Algorithms Into Actionable Care.Journal of clinical neurology (Seoul, Korea) · 2026Review
- Mechanistic Insights into the Role of Artificial Intelligence and Machine Learning in the Diagnosis and Management of Multiple Sclerosis.Pathophysiology : the official journal of the International Society for Pathophysiology · 2026Review
- Comparison of Three Automated Measurements of Ventricular Volumes of the Brain.Journal of imaging informatics in medicine · 2026Article
- Multiple sclerosis and the limits of classical autoimmune theory.Frontiers in immunology · 2026Review
- Combined magnetic resonance imaging and serum analysis reveals distinct multiple sclerosis types.Brain : a journal of neurology · 2025Article
- Prospective clinical evaluation of automatic lesion assessment in patients with multiple sclerosis.Neuroradiology · 2025Article
- The Serum Lipid Profile of Relapsing Multiple Sclerosis Differs Reproducibly From Healthy Controls.Journal of neurochemistry · 2025Article
- User requirements for quantitative radiological reports in multiple sclerosis.European radiology · 2025Article
- Detecting New Lesions Using a Large Language Model: Applications in Real-World Multiple Sclerosis Datasets.Annals of neurology · 2025Article
- Evolution of Chronic Lesion Tissue in Relapsing-Remitting Patients With Multiple Sclerosis: An Association With Disease Progression.Neurology(R) neuroimmunology & neuroinflammation · 2025Article
- Enabling new insights from old scans by repurposing clinical MRI archives for multiple sclerosis research.Nature communications · 2025Article
- Associations of high-sensitivity C-reactive protein with neuropsychological outcomes and cerebral white matter hyperintensities in older adults at risk of dementia.Brain, behavior, & immunity - health · 2025Article
- Artificial intelligence in autoimmune diseases: a bibliometric exploration of the past two decades.Frontiers in immunology · 2025Review
- The role of AI for MRI-analysis in multiple sclerosis-A brief overview.Frontiers in artificial intelligence · 2025Review
- Depicting multiple sclerosis disease course using lesion parenchymal fraction: a quantified expression of the topographical model of multiple sclerosis.Brain communications · 2025Article
- Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging.Neuroimaging clinics of North America · 2024Review
- Changes in MRI Workflow of Multiple Sclerosis after Introduction of an AI-Software: A Qualitative Study.Healthcare (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
25 authors at 10 institutions in 5 countries.
Funding
Abstract
Modern management of MS targets No Evidence of Disease Activity (NEDA): no clinical relapses, no magnetic resonance imaging (MRI) disease activity and no disability worsening. While MRI is the principal tool available to neurologists for monitoring clinically silent MS disease activity and, where appropriate, escalating treatment, standard radiology reports are qualitative and may be insensitive to the development of new or enlarging lesions. Existing quantitative neuroimaging tools lack adequate clinical validation. In 397 multi-center MRI scan pairs acquired in routine practice, we demonstrate superior case-level sensitivity of a clinically integrated AI-based tool over standard radiology reports (93.3% vs 58.3%), relative to a consensus ground truth, with minimal loss of specificity. We also demonstrate equivalence of the AI-tool with a core clinical trial imaging lab for lesion activity and quantitative brain volumetric measures, including percentage brain volume loss (PBVC), an accepted biomarker of neurodegeneration in MS (mean PBVC -0.32% vs -0.36%, respectively), whereas even severe atrophy (>0.8% loss) was not appreciated in radiology reports. Finally, the AI-tool additionally embeds a clinically meaningful, experiential comparator that returns a relevant MS patient centile for lesion burden, revealing, in our cohort, inconsistencies in qualitative descriptors used in radiology reports. AI-based image quantitation enhances the accuracy of, and value-adds to, qualitative radiology reporting. Scaled deployment of these tools will open a path to precision management for patients with MS.
Identifiers
What OpenQuestion holds
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.