ArticleFrontiers in neurology2023
Predicting acute ischemic stroke using the revised Framingham stroke risk profile and multimodal magnetic resonance imaging.
Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Perfusion-weighted MRI patterns in neuropsychiatric systemic lupus erythematosus: a systematic review and meta-analysis.Neuroradiology · 2025Pooled it
- Integrated imaging assessment of large arteries, intracranial plaque, and cerebral small vessel disease to distinguish acute ischemic stroke from transient ischemic attack.Neuroradiology · 2026Article
- GRaph-based analysis for stroke prediction (GRASP): A multi-modal model for identifying first ischemic stroke in high-risk population using UK biobank.Computers in biology and medicine · 2026Article
- Diagnostic and prognostic value of combined adiponectin, D-dimer, and Framingham Stroke Profilein patients with isolated vertigo and concurrent cerebral infarction.American journal of translational research · 2026Article
- Prediction and Classification the Risk of Stroke Patients Using Machine Learning Techniques: A Retrospective Cross-Sectional Study.Health science reports · 2025Article
- Correlating stroke risk with non-invasive cerebrovascular perfusion dynamics using a portable speckle contrast optical spectroscopy laser device.Biomedical optics express · 2024Article
- Developing and Validating a Nomogram Model for Predicting Ischemic Stroke Risk.Journal of personalized medicine · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Patients with transient ischemic attacks (TIA) have a significant risk of developing acute ischemic strokes (AIS), emphasizing the critical need for hierarchical management. This study aims to develop a clinical-imaging model utilizing multimodal magnetic resonance imaging (mMRI) and the revised Framingham Stroke Risk Profile (FSRP) to predict AIS and achieve early secondary prevention. Methods: mMRI scans were conducted on patients with symptomatic intracranial atherosclerotic disease (ICAD) to assess vascular wall features and cerebral perfusion parameters. Based on diffusion-weighted imaging (DWI), patients were divided into two groups: TIA and AIS. Clinical data were evaluated to calculate the FSRP score. Differences in clinical and imaging characteristics between the groups were analyzed, and a predictive model for AIS probability in patients with ICAD was established. Results: A total of 112 TIA and AIS patients were included in the study. The results showed that the AIS group had higher proportions of FSRP-high risk, hyperhomocysteinemia, and higher value of low-density lipoprotein (LDL), standardized plaque index (SQI), and enhancement rate (ER) compared to the TIA group ( Conclusion: FSRP-high risk and high ER were confirmed as independent risk factors for AIS. The combined prediction model utilizing clinical and imaging markers effectively predicts stroke risk in symptomatic ICAD patients.
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