ArticleQuantitative imaging in medicine and surgery2023
Predictors of hyperperfusion syndrome after stent implantation in symptomatic intracranial atherosclerotic stenosis.
Article in Quantitative imaging in medicine and surgery, 2023. 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, 7 citations in OpenAlex.
- Postoperative perfusion volume on territorial arterial spin labeling provides an exploratory risk signal for cerebrovascular autoregulation failure after moyamoya revascularization: a prospective physiological study.Frontiers in physiology · 2026Article
- Recanalization of atherosclerotic stenosis and occlusion of intracranial vertebrobasilar artery.IBRO neuroscience reports · 2025Review
- Machine Learning-Based Classification of Anterior Circulation Cerebral Infarction Using Computational Fluid Dynamics and CT Perfusion Metrics.Brain sciences · 2025Article
- Elucidating the benefit of drug-eluting stent for symptomatic intracranial atherosclerotic stenosis: Meta-analysis of randomized controlled trials.Surgical neurology international · 2025Review
- Semi-automatic computed tomography angiography quantification assessment is an alternative method to digital subtraction angiography in intracranial stenosis: a multicenter study.Quantitative imaging in medicine and surgery · 2024Article
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hyperperfusion syndrome (HPS) is a serious complication after stent implantation in symptomatic intracranial atherosclerotic stenosis (ICAS). This study aims to explore the predictive value of preprocedural computed tomography perfusion (CTP) for HPS after intracranial stenting. Methods: In this retrospective case-control study we collected data from consecutive patients from June 2012 to September 2019 who underwent stent implantation due to severe symptomatic ICAS. Patients who underwent CTP before the procedure were enrolled. CTP was postprocessed using the automated RAPID software to assess the preoperative cerebral perfusion. According to the presence or absence of HPS, the patients were classified into two groups: the HPS group and the non-HPS group. The baseline data, lesion characteristics, and preoperative CTP parameters between the two groups were compared. The receiver operating characteristic (ROC) curve analysis was performed to determine the optimal predictor of HPS. Results: Among the 170 eligible patients, 6 patients (3.53%) had HPS, including 3 who presented with intracranial hemorrhages (ICHs), 1 who had dysphoria, 1 who had delirium, and 1 who had a headache. There were no significant differences in baseline and lesion characteristics between the HPS and non-HPS groups. Compared with the non-HPS group, the HPS group had a significantly higher volume of time-to-maximum (T Conclusions: T
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