ArticleFrontiers in neurology2023
Identifying vulnerable plaques: A 3D carotid plaque radiomics model based on HRMRI.
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 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence diagnostic performance in image-based vulnerable carotid plaque detection: a systematic review and meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Radiomics and ischemic stroke research: bibliometric insights and visual trends (2004-2024).Frontiers in neurology · 2025Pooled it
- Development of a recurrence risk prediction model for intracranial atherosclerotic stroke using HR-VWI combined with radiomics.Neuroradiology · 2026Article
- Plaque-level machine-learning prediction of carotid plaque vulnerability on computed tomography angiography.Neuroradiology · 2026Article
- Feasibility Exploration of High-Resolution MRI Plaque Features for Assessing Outcomes of Intracranial Angioplasty and Stenting in Ischemic Stroke Patients.Revista de neurologia · 2025Article
- Application of Artificial Intelligence in Vulnerable Carotid Atherosclerotic Plaque Assessment-A Scoping Review.Medicina (Kaunas, Lithuania) · 2025Article
- Classification of carotid artery plaques: promising alternative methods to computed tomography angiography through radiomics approach using neck non-contrast computed tomography.Quantitative imaging in medicine and surgery · 2025Article
- Combining Computational Fluid Dynamics, Structural Analysis, and Machine Learning to Predict Cerebrovascular Events: A Mild ML Approach.Diagnostics (Basel, Switzerland) · 2024Article
- Quality assessment of radiomics models in carotid plaque: a systematic review.Quantitative imaging in medicine and surgery · 2024Review
- Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque.Frontiers in neurology · 2024Article
- Characteristics and evaluation of atherosclerotic plaques: an overview of state-of-the-art techniques.Frontiers in neurology · 2023Review
- Controversies in the management of asymptomatic carotid stenosis: from best medical therapy to a redefinition of surgical indications.Frontiers in neurologyReview
- A radiomics-based approach with automated segmentation for identifying symptomatic basilar artery plaques in acute stroke.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Background: Identification of vulnerable carotid plaque is important for the treatment and prevention of stroke. In previous studies, plaque vulnerability was assessed qualitatively. We aimed to develop a 3D carotid plaque radiomics model based on high-resolution magnetic resonance imaging (HRMRI) to quantitatively identify vulnerable plaques. Methods: Ninety patients with carotid atherosclerosis who underwent HRMRI were randomized into training and test cohorts. Using the radiological characteristics of carotid plaques, a traditional model was constructed. A 3D carotid plaque radiomics model was constructed using the radiomics features of 3D T Results: 48 patients (53.33%) were symptomatic and 42 (46.67%) were asymptomatic. The traditional model was constructed using intraplaque hemorrhage, plaque enhancement, wall remodeling pattern, and lumen stenosis, and it provided an area under the curve (AUC) of 0.816 vs. 0.778 in the training and testing sets. In the two cohorts, the 3D carotid plaque radiomics model and the combined model had an AUC of 0.915 vs. 0.835 and 0.957 vs. 0.864, respectively. In the training set, both the radiomics model and the combination model outperformed the traditional model, but there was no significant difference between the radiomics model and the combined model. Conclusions: HRMRI-based 3D carotid radiomics models can improve the precision of detecting vulnerable carotid plaques, consequently improving risk classification and clinical decision-making in patients with carotid stenosis.
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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 Socratic graph.