ArticleInterventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences2021
e-ASPECTS software improves interobserver agreement and accuracy of interpretation of aspects score.
Article in Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Software with artificial intelligence-derived algorithms for analysing CT brain scans in people with a suspected acute stroke: a systematic review and cost-effectiveness analysis.Health technology assessment (Winchester, England) · 2024Pooled it
- Implementation of an AI-supported decision-making tool in a high-volume stroke system with routine perfusion imaging.European stroke journal · 2026Article
- Artificial Intelligence in Ischemic Stroke Lesion Segmentation: A Narrative Review of Deep Learning Methods, Clinical Utility, and Future Directions.Journal of imaging informatics in medicine · 2026Review
- Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on automated Alberta stroke program early CT score- evaluation.Neuroradiology · 2026Article
- Characterizing the effects of noncontrast head CT reconstruction kernel and slice thickness parameters on the performance of an automated AI algorithm in the evaluation of ischemic stroke.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Article
- Performance of an artificial intelligence tool for multi-step acute stroke imaging: A multicenter diagnostic study.European journal of radiology open · 2025Article
- Human Readers versus AI-Based Systems in ASPECTS Scoring for Acute Ischemic Stroke: A Systematic Review and Meta-Analysis with Region-Specific Guidance.ASIDE internal medicine · 2025Article
- Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT.Stroke and vascular neurology · 2025Article
- Prospective Evaluation of Artificial Intelligence Imaging Support Software for Acute Ischemic Stroke in the Mayo Clinic Telestroke Network.Mayo Clinic proceedings. Innovations, quality & outcomes · 2025Article
- Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.AJNR. American journal of neuroradiology · 2025Article
- Assessing the eligibility of Brainomix e-ASPECTS for acute stroke imaging.Frontiers in neuroinformatics · 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
- Automatically quantified follow-up imaging biomarkers predict clinical outcomes after acute ischemic stroke.Frontiers in neurology · 2025Article
- Real-world evaluation of Brainomix e-Stroke software.Stroke and vascular neurology · 2024Article
- APIS: a paired CT-MRI dataset for ischemic stroke segmentation - methods and challenges.Scientific reports · 2024Article
- Automated ASPECTS calculation may equal the performance of experienced clinicians: a machine learning study based on a large cohort.European radiology · 2024Article
- Deep Learned Segmentations of Inflammation for Novel ⁹⁹Diagnostics (Basel, Switzerland) · 2023Article
- Deep Learning Applied to Intracranial Hemorrhage Detection.Journal of imaging · 2023Article
- Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study.Frontiers in neurology · 2023Article
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18 authors.
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Abstract
introductionThere is increased interest in the use of artificial intelligence-based (AI) software packages in the evaluation of neuroimaging studies for acute ischemic stroke. We studied whether, compared to standard image interpretation without AI, Brainomix e-ASPECTS software improved interobserver agreement and accuracy in detecting ASPECTS regions affected in anterior circulation LVO.
methodsWe included 60 consecutive patients with anterior circulation LVO who had TICI 3 revascularization within 60 minutes of their baseline CT. A total of 16 readers, including senior neuroradiologists, junior neuroradiologists and vascular neurologists participated. Readers interpreted CT scans on independent workstations and assessed final ASPECTS and evaluated whether each individual ASPECTS region was affected. Two months later, readers again evaluated the CT scans, but with assistance of e-ASPECTS software. We assessed interclass correlation coefficient for total ASPECTS and interobserver agreement with Fleiss' Kappa for each ASPECTS region with and without assistance of the e-ASPECTS. We also assessed accuracy for the readers with and without e-ASPECTS assistance. In our assessment of accuracy, ground truth was the 24 hour CT in this cohort of patients who had prompt and complete revascularization.
resultsInterclass correlation coefficient for total ASPECTS without e-ASPECTS assistance was 0.395, indicating fair agreement compared, to 0.574 with e-ASPECTS assistance, indicating good agreement (P < 0.01). There was significant improvement in inter-rater agreement with e-ASPECTS assistance for each individual region with the exception of M6 and caudate. The e-ASPECTS software had higher accuracy than the overall cohort of readers (with and without e-ASPECTS assistance) for every region except the caudate.
conclusionsUse of Brainomix e-ASPECTS software resulted in significant improvements in inter-rater agreement and accuracy of ASPECTS score evaluation in a large group of neuroradiologists and neurologists. e-ASPECTS software was more predictive of final infarct/ASPECTS than the overall group interpreting the CT scans with and without e-ASPECTS assistance.
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