ArticleJournal of neurointerventional surgery2022
Diagnostic performance of an algorithm for automated large vessel occlusion detection on CT angiography.
Article in Journal of neurointerventional surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 42 citations in OpenAlex.
- Time Since Stroke Onset, Quantitative Collateral Score, and Functional Outcome After Endovascular Treatment for Acute Ischemic Stroke.Neurology · 2022Trial
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- Current State of the Clinical Applications of Artificial Intelligence in Stroke: A Literature Review.Brain sciences · 2026Review
- Validity of intracerebral haemorrhage volume assessment: comparison of fully automated segmentation analysis with manual ABC/2 and semi-automated measurement.European stroke journal · 2026Article
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- AI-Based Automated Quantification of Arterial Stenosis in Head and Neck CT Angiography: A Comparison with Manual Measurements from Digital Subtraction Angiography and CT Angiography.Clinical neuroradiology · 2025Article
- CT perfusion enhances accuracy of intracranial occlusion detection in acute stroke: effect of specialty and experience level.Neuroradiology · 2025Article
- Artificial intelligence assisted detection of large vessel occlusion on CT angiography in acute stroke patients: a multi-reader multi-case study.BJR artificial intelligence · 2025Article
- Generalizable self-supervised learning for brain CTA in acute stroke.Computers in biology and medicine · 2025Article
- Spatial resolution enhancement using deep learning improves chest disease diagnosis based on thick slice CT.NPJ digital medicine · 2024Article
- Enhancing Stroke Recognition: A Comparative Analysis of Balance and Eyes-Face, Arms, Speech, Time (BE-FAST) and Face, Arms, Speech, Time (FAST) in Identifying Posterior Circulation Strokes.Journal of clinical medicine · 2024Article
- Study on the clinical value of computed tomography angiography in the diagnosis of aortic aneurysm.Journal of cardiothoracic surgery · 2024Article
- A self-supervised learning approach for registration agnostic imaging models with 3D brain CTA.iScience · 2024Article
- Article
- Automated identification of thrombectomy amenable vessel occlusion on computed tomography angiography using deep learning.Frontiers in neurology · 2024Article
- Deep learning-assisted diagnosis of large vessel occlusion in acute ischemic stroke based on four-dimensional computed tomography angiography.Frontiers in neuroscience · 2024Article
- Performance of deep learning-based autodetection of arterial stenosis on head and neck CT angiography: an independent external validation study.La Radiologia medica · 2023Article
- AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation.Heliyon · 2023Article
- Artificial Intelligence and Machine Learning in the Diagnosis and Management of Stroke: A Narrative Review of United States Food and Drug Administration-Approved Technologies.Journal of clinical medicine · 2023Review
- Spatial CT perfusion data helpful in automatically locating vessel occlusions for acute ischemic stroke patients.Frontiers in neurology · 2023Article
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Authors and funding
16 authors at 8 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMachine learning algorithms hold the potential to contribute to fast and accurate detection of large vessel occlusion (LVO) in patients with suspected acute ischemic stroke. We assessed the diagnostic performance of an automated LVO detection algorithm on CT angiography (CTA).
methodsData from the MR CLEAN Registry and PRESTO were used including patients with and without LVO. CTA data were analyzed by the algorithm for detection and localization of LVO (intracranial internal carotid artery (ICA)/ICA terminus (ICA-T), M1, or M2). Assessments done by expert neuroradiologists were used as reference. Diagnostic performance was assessed for detection of LVO and per occlusion location by means of sensitivity, specificity, and area under the curve (AUC).
resultsWe analyzed CTAs of 1110 patients from the MR CLEAN Registry (median age (IQR) 71 years (60-80); 584 men; 1110 with LVO) and of 646 patients from PRESTO (median age (IQR) 73 years (62-82); 358 men; 141 with and 505 without LVO). For detection of LVO, the algorithm yielded a sensitivity of 89% in the MR CLEAN Registry and a sensitivity of 72%, specificity of 78%, and AUC of 0.75 in PRESTO. Sensitivity per occlusion location was 88% for ICA/ICA-T, 94% for M1, and 72% for M2 occlusion in the MR CLEAN Registry, and 80% for ICA/ICA-T, 95% for M1, and 49% for M2 occlusion in PRESTO.
conclusionThe algorithm provided a high detection rate for proximal LVO, but performance varied significantly by occlusion location. Detection of M2 occlusion needs further improvement.
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