ArticleNeuroradiology2018
Automated ASPECT rating: comparison between the Frontier ASPECT Score software and the Brainomix software.
Article in Neuroradiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 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
- Clinical evaluation of a deep-learning model for automatic scoring of the Alberta stroke program early CT score on non-contrast CT.Journal of neurointerventional surgery · 2023Trial
- Clinical evaluation of an automated Alberta Stroke Program Early Computed Tomography Score (ASPECTS)-scoring system.Quantitative imaging in medicine and surgery · 2026Article
- Cerebral ischemia detection using deep learning techniques.Health information science and systems · 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
- Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.AJNR. American journal of neuroradiology · 2025Article
- Non-Contrast Computed Tomography-Based Triage and Notification for Large Vessel Occlusion Stroke: A Before and After Study Utilizing Artificial Intelligence on Treatment Times and Outcomes.Journal of clinical medicine · 2025Article
- The e-STROKE Study: The Design of a Prospective Observational Multicentral Study.Journal of cardiovascular development and disease · 2025Article
- Assessing the eligibility of Brainomix e-ASPECTS for acute stroke imaging.Frontiers in neuroinformatics · 2025Article
- Real-world evaluation of Brainomix e-Stroke software.Stroke and vascular neurology · 2024Article
- Improving acute stroke assessment in non-enhanced computed tomography: automated tool for early ischemic lesion volume detection.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Artificial Intelligence in Stroke Imaging: A Comprehensive Review.The Eurasian journal of medicine · 2023Article
- Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach.Scientific reports · 2023Article
- Artificial Intelligence in Neuroradiology: A Review of Current Topics and Competition Challenges.Diagnostics (Basel, Switzerland) · 2023Review
- Automatic Alberta Stroke Program Early Computed Tomographic Scoring in patients with acute ischemic stroke using diffusion-weighted imaging.Medical & biological engineering & computing · 2023Article
- Performance of Automated ASPECTS Software and Value as a Computer-Aided Detection Tool.AJNR. American journal of neuroradiology · 2023Article
- Artificial Intelligence in Acute Ischemic Stroke Subtypes According to Toast Classification: A Comprehensive Narrative Review.Biomedicines · 2023Review
- Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease.Frontiers in human neuroscience · 2023Review
- Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study.Insights into imaging · 2022Article
- External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke.Annals of neurology · 2022Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeComputer-aided diagnosis (CAD) appears promising in early ischemic change detection computed tomography (CT). This study aimed to compare the performance of two new CAD systems (Frontier ASPECTS Prototype and Brainomix) with two experienced readers in selected patients with suspected acute ischemic stroke.
methodsRetrospectively, non-contrast brain CTs of 150 patients suspected for acute middle cerebral artery ischemia were analyzed with respect to ASPECTS first separately, than in consensus by two senior radiologists, and by use of Frontier and Brainomix. Besides the fully automatic Frontier and Brainomix readings (Frontier_1, Brainomix_1), readings adjusted for the affected brain side (known by CT angiography or clinical presentation, Frontier_2, Brainomix_2) were assessed. Statistical analysis was performed by intraclass correlation and Bland-Altman statistics.
resultsThe score-based ASPECTS readings of Brainomix_1, Brainomix_2, both radiologists, and the expert consensus reading correlated highly (r = 0.714 to 0.841; always p < 0.001), whereas Frontier_1 and Frontier_2 correlated only lowly or moderately with both radiologists, the expert consensus reading, and Brainomix (r = 0.471 to 0.680; always p < 0.001). Bland-Altman analysis revealed lower mean ASPECT difference and standard deviation of difference for Brainomix_2 (mean difference = -0.2; SD = 1.15) compared to Frontier_2 (mean difference = 1.2; SD = 1.76). Correlation of region-based ASPECTS reading with the expert consensus reading was moderate for Brainomix_2 (r = 0.534), but only low for Frontier_2 (r = 0283; always p < 0.001).
conclusionWe found high agreement in ASPECTS rating between both radiologists, expert consensus reading, and Brainomix, but only low to moderate agreement to Frontier.
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Registered trials
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