Trial reportTranslational stroke research2022
Relation of Carotid Plaque Features Detected with Ultrasonography-Based Radiomics to Clinical Symptoms.
Trial report in Translational stroke research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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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
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- 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-based machine learning atherosclerotic carotid artery disease in ultrasound: systematic review with meta-analysis of RQS.Journal of ultrasound · 2025Pooled it
- Application of the Carotid Plaque-RADS Classification System in Ultrasound: Inter- and Intra-Observer Agreement Analysis and Learning Curve Analysis.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2026Article
- Dual-modal ultrasound radiomics model enhances identification of symptomatic carotid plaque: a multicenter retrospective study.The international journal of cardiovascular imaging · 2026Article
- Identification of histological carotid plaque vulnerability by CT angiography using perivascular adipose tissue radiomics signature.Insights into imaging · 2026Article
- Integrated proteomics and metabolomics analyses reveal potential molecular signatures of rabbit atherosclerotic plaques.International journal of cardiology. Heart & vasculature · 2025Article
- Lipid-related radiomics of low-echo carotid plaques is associated with diabetic stroke and non-diabetic coronary heart disease.The international journal of cardiovascular imaging · 2025Article
- Contrast-enhanced carotid ultrasound improves vulnerable plaque detection in acute central retinal artery occlusion: a propensity score-matched study.Frontiers in cardiovascular medicine · 2025Article
- Molecular Imaging of Fibroblast Activation in Rabbit Atherosclerotic Plaques: a Preclinical PET/CT Study.Molecular imaging and biology · 2024Article
- Quality assessment of radiomics models in carotid plaque: a systematic review.Quantitative imaging in medicine and surgery · 2024Review
- A deep learning model for carotid plaques detection based on CTA images: a two stepwise early-stage clinical validation study.Frontiers in neurology · 2024Article
- Computed tomography angiography-based radiomics model to identify high-risk carotid plaques.Quantitative imaging in medicine and surgery · 2023Article
- Identifying vulnerable plaques: A 3D carotid plaque radiomics model based on HRMRI.Frontiers in neurology · 2023Article
- Article
- Radiomics and artificial neural networks modelling for identification of high-risk carotid plaques.Frontiers in cardiovascular medicine · 2023Article
- Computed tomography angiography-based radiomics model for predicting carotid atherosclerotic plaque vulnerability.Frontiers in neurology · 2023Article
- Advances in Noninvasive Carotid Wall Imaging with Ultrasound: A Narrative Review.Journal of clinical medicine · 2022Review
- Letter to Relation of Carotid Plaque Features Detected with Ultrasonography‑Based Radiomics to Clinical Symptoms.Translational stroke research · 2022Article
- Prediction of Carotid In-Stent Restenosis by Computed Tomography Angiography Carotid Plaque-Based Radiomics.Journal of clinical medicine · 2022Article
- A Radiomics Approach to Assess High Risk Carotid Plaques: A Non-invasive Imaging Biomarker, Retrospective Study.Frontiers in neurology · 2022Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Carotid plaque is one of the predominant causes of stroke. We sought to build a nomogram using ultrasonography (US)-based radiomics and clinical features for identification of symptomatic carotid plaques. We prospectively enrolled 548 patients (mean age ± standard deviation, 63 ± 10 years; 373 men) were randomly divided into training and test cohorts. Clinical and conventional US features of carotid plaques were used to generate a clinical and conventional US model. US-based radiomics model was constructed by extracting radiomics features from grayscale and strain elasticity images. Multivariate logistic regression was performed using the radiomics scores together with clinical and conventional US data, and a final nomogram was subsequently developed. The performance of the final nomogram was assessed with respect to discrimination and clinical usefulness in the training of the test cohorts and contrast-enhanced US test cohort. All the radiomics scores were significantly higher in patients with symptomatic carotid plaques. The US-based radiomics model [area under the curve (AUC) = 0.930 and 0.922 for training and test cohorts, respectively] and final nomogram (AUC = 0.927 and 0.919, respectively) outperformed the clinical and conventional US model (AUC = 0.723 and 0.580, respectively). The decision curve analysis indicated that the final nomogram was clinically useful. In patients undergoing the contrast-enhanced US, the prevalence of plaque enhancement was higher in high-risk patients than in low-risk patients based on the final nomogram-score (P = 0.008). Nomogram has a high diagnostic performance for identification of symptomatic carotid plaques.
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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.