Background: Rapid identification of large vessel occlusion (LVO) in acute ischemic stroke (AIS) is essential for reperfusion therapy. Screening tools, including Artificial Intelligence (AI) based algorithms, have been developed to accelerate detection but rely heavily on pre-test LVO prevalence. This study aimed to review LVO prevalence across clinical contexts and analyze its impact on AI-algorithm performance.
View Article and Find Full Text PDFIntroduction: Neutral results from trials assessing mechanical thrombectomy (MT) for medium/distal vessel occlusions (MDVO) suggest the need for better selection criteria in these patients. Tortuous vascular anatomies may negatively influence MT efficacy and safety.
Patients And Methods: Consecutive patients with middle cerebral artery (MCA)-MDVO (M2/M3) who underwent MT at our center between January 2017 and September 2024 were included.
Purpose: This study explores a multi-modal deep learning approach that integrates pre-intervention neuroimaging and clinical data to predict endovascular therapy (EVT) outcomes in acute ischemic stroke patients. To this end, consecutive stroke patients undergoing EVT were included in the study, including patients with suspected Intracranial Atherosclerosis-related Large Vessel Occlusion ICAD-LVO and other refractory occlusions.
Methods: A retrospective, single-center cohort of patients with anterior circulation LVO who underwent EVT between 2017-2023 was analyzed.
Interv Neuroradiol
March 2024
Background: Symptomatic carotid artery stenosis is a significant contributor to ischemic strokes. Carotid artery stenting (CAS) is usually indicated for secondary stroke prevention. This study evaluates the safety and efficacy of CAS performed within a short time frame from symptom onset.
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