ArticleEuropean radiology2023
Prediction of new cerebral ischemic lesion after carotid artery stenting: a high-resolution vessel wall MRI-based radiomics analysis.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Spectral CT parameters of perivascular adipose tissue as non-invasive biomarkers for identifying symptomatic carotid atherosclerosis.Insights into imaging · 2026Article
- Development and interpretation of a dual-energy CT-based deep learning radiomics model for predicting new cerebral ischemic lesions after carotid artery stenting: a multicenter study.European radiology · 2026Article
- Prediction of PD-1 Expression and Outcomes of Combined Therapy in Hepatocellular Carcinoma: an MRI-Based Radiomics Approach.Journal of imaging informatics in medicine · 2026Article
- A clinical-radiomics nomogram based on multisequence MRI for predicting intraoperative vertebral artery injury in patients with primary cervical spine tumor: a diagnostic study.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 · 2026Article
- Carotid atherosclerotic plaque vulnerability assessment from angiography-derived radial wall strain validated by MRI.Scientific reports · 2025Article
- Predicting periprocedural complications risk in intracranial angioplasty and stenting from integrated high-resolution vessel wall imaging radiomics and clinical characteristics.Neuroradiology · 2025Article
- Non-alcoholic fatty liver disease is a strong predictor of carotid high-risk plaques as assessed by high-resolution magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2025Article
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Authors and funding
10 authors at 6 institutions in 3 countries.
Funding
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Abstract
objectivesCarotid artery stenting (CAS) is an established treatment for local stenosis. The most common complication is new ipsilateral ischemic lesions (NIILs). This study aimed to develop models considering lesion morphological and compositional features, and radiomics to predict NIILs. MATERIALS AND
methodsOne hundred and forty-six patients who underwent brain MRI and high-resolution vessel wall MR imaging (hrVWI) before and after CAS were retrospectively recruited. Lumen and outer wall boundaries were segmented on hrVWI as well as atherosclerotic components. A traditional model was constructed with patient clinical information, and lesion morphological and compositional features. Least absolute shrinkage and selection operator algorithm was performed to determine key radiomics features for reconstructing a radiomics model. The model in predicting NIILs was trained and its performance was tested.
resultsSixty-one patients were NIIL-positive and eighty-five negative. Volume percentage of intraplaque hemorrhage (IPH) and patients' clinical presentation (symptomatic/asymptomatic) were risk factors of NIILs. The traditional model considering these two features achieved an area under the curve (AUC) of 0.778 and 0.777 in the training and test cohorts, respectively. Twenty-two key radiomics features were identified and the model based on these features achieved an AUC of 0.885 and 0.801 in the two cohorts. The AUCs of the combined model considering IPH volume percentage, clinical presentation, and radiomics features were 0.893 and 0.842 in the training and test cohort respectively.
conclusionsCompared with traditional features (clinical and compositional features), the combination of traditional and radiomics features improved the power in predicting NIILs after CAS. KEY POINTS: • Volume percentage of IPH and symptomatic events were independent risk factors of new ipsilateral ischemic lesions (NIILs). • Radiomics features derived from carotid artery high-resolution vessel wall imaging had great potential in predicting NIILs after CAS. • The combination model with radiomics and traditional features further improved the diagnostic performance than traditional features alone.
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