ArticleAJNR. American journal of neuroradiology2025
Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.
Article in AJNR. American journal of neuroradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Noncontrast CT-based habitat analysis for differentiating hemorrhagic transformation from contrast extravasation after endovascular therapy of acute ischemic stroke.European radiology experimental · 2026Article
- Are AI Neuroimaging Models Ready for Clinical Use? A Systematic Methodological Review.Journal of clinical medicine · 2026Review
- Dual-Energy CT-Based Assessment of Thrombotic Heterogeneity for Predicting Stroke Source and Response to Machine Thrombectomy: A Step Toward Visualization Thrombus Treatment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Delta radiomics modeling based on CTP for predicting hemorrhagic transformation after intravenous thrombolysis in acute cerebral infarction: an 8-year retrospective pilot study.Frontiers in neurology · 2025Article
- Rapid prediction of hemorrhagic transformation after endovascular thrombectomy: a multimodal model in patients with post-thrombectomy cerebral hyperdensities.Frontiers in neurologyArticle
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10 authors.
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Abstract
background and purposeClinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study aimed to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large-vessel occlusion (AIS-LVO). MATERIALS AND
methodsA total of 156 eligible patients with AIS-LVO in Center I from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training (
resultsClinical blood glucose and the maximum cross-sectional area on CT were associated with the HT or non-HT of the HDA according to multivariate logistic regression analyses (
conclusionsThe combined model based on radiomics had the best performance, indicating that radiomics features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.
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