ArticleEuropean radiology2021
Comparison of automated and manual DWI-ASPECTS in acute ischemic stroke: total and region-specific assessment.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- Refined AI-ASPECTS with modified atlas and lesion-load thresholds: advancing acute ischemic stroke imaging and prognostic prediction.BMC medicine · 2026Article
- Automated quantification of the Alberta Stroke Programme Early CT Score (ASPECTS) and infarct core on diffusion-weighted imaging in acute ischaemic stroke: multi-centre validation and severity stratification.Brain communications · 2026Article
- Controversies in Treatment Methodologies in Cerebrovascular Surgery.Advances and technical standards in neurosurgery · 2026Review
- Clinical and neuroimaging insights into childhood arterial ischemic stroke of different ages.Frontiers in neurology · 2025Article
- Voxel level dense prediction of acute stroke territory in DWI using deep learning segmentation models and image enhancement strategies.Japanese journal of radiology · 2024Article
- Correlation between DWI-ASPECTS Score, Ischemic Stroke Volume on DWI, Clinical Severity and Short-Term Prognosis: A Single-Center Study.Brain sciences · 2024Article
- Artificial Intelligence in Stroke Imaging: A Comprehensive Review.The Eurasian journal of medicine · 2023Article
- Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study.Insights into imaging · 2022Article
- Machine learning in gastrointestinal surgery.Surgery today · 2022Review
- CT angiography-based radiomics as a tool for carotid plaque characterization: a pilot study.La Radiologia medica · 2022Article
- Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review.BioMed research international · 2022Review
- Study on the dynamic change law and correlation between CT imaging manifestations and cellular immunity of 2019 novel coronavirus disease.Japanese journal of radiology · 2020Article
- COVID-19 pneumonia: infection control protocol inside computed tomography suites.Japanese journal of radiology · 2020Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveTo compare the DWI-Alberta Stroke Program Early Computed Tomography Score calculated by a deep learning-based automatic software tool (eDWI-ASPECTS) with the neuroradiologists' evaluation for the acute stroke, with emphasis on its performance on 10 individual ASPECTS regions, and to determine the reasons for inconsistencies between eDWI-ASPECTS and neuroradiologists' evaluation.
methodsThis retrospective study included patients with middle cerebral artery stroke who underwent MRI from 2010 to 2019. All scans were evaluated by eDWI-ASPECTS and two independent neuroradiologists (with 15 and 5 years of experience in stroke study). Inter-rater agreement and agreement between manual vs. automated methods for total and each region were evaluated by calculating Kendall's tau-b, intraclass correlation coefficient (ICC), and kappa coefficient.
resultsIn total, 309 patients met our study criteria. For total ASPECTS, eDWI-ASPECTS and manual raters had a strong positive correlation (Kendall's tau-b = 0.827 for junior raters vs. eDWI-ASPECTS; Kendall's tau-b = 0.870 for inter-raters; Kendall's tau-b = 0.848 for senior raters vs. eDWI-ASPECTS) and excellent agreement (ICC = 0.923 for junior raters and automated scores; ICC = 0.954 for inter-raters; ICC = 0.939 for senior raters and automated scores). Agreement was different for individual ASPECTS regions. All regions except for M5 region (κ = 0.216 for junior raters and automated scores), internal capsule (κ = 0.525 for junior raters and automated scores), and caudate (κ = 0.586 for senior raters and automated scores) showed good to excellent concordance.
conclusionThe eDWI-ASPECTS performed equally well as senior neuroradiologists' evaluation, although interference by uncertain scoring rules and midline shift resulted in poor to moderate consistency in the M5, internal capsule, and caudate nucleus regions. KEY POINTS: • The eDWI-ASPECTS based on deep learning perform equally well as senior neuroradiologists' evaluations. • Among the individual ASPECTS regions, the M5, internal capsule, and caudate regions mainly affected the overall consistency. • Uncertain scoring rules and midline shift are the main reasons for regional inconsistency.
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