A CT imaging-based prediction model of functional outcome and benefit of endovascular thrombectomy for ischemic stroke

Question The predictive value of baseline CT imaging for the prediction of functional outcome and benefit of EVT for anterior LVO stroke is uncertain. Findings Discrimination of a model based on CT imaging alone is substantial, but can further be improved by the addition of limited clinical characteristics. Clinical relevance Baseline CT imaging holds considerable predictive value with regard to functional outcome and treatment benefit. The addition of limited clinical information is needed to achieve predictive performance similar to an established prediction model.

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Publication Details

Journal
European Radiology
Published
2026-01-14
DOI
https://doi.org/10.1007/s00330-025-12207-7
Primary Topic
Acute Ischemic Stroke Management
Type
article
Field-Weighted Citation Impact
0.00

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article

A CT imaging-based prediction model of functional outcome and benefit of endovascular thrombectomy for ischemic stroke

S Brown, Joachim Fladt, Sven P. R. Luijten, Adam Marcus et al.
European Radiology
Acute Ischemic Stroke Management
article

A CT imaging-based prediction model of functional outcome and benefit of endovascular thrombectomy for ischemic stroke

S Brown, Joachim Fladt, Sven P. R. Luijten, Adam Marcus, K Muir, Fouzi Bala, Bijoy K. Menon, Philip White, Mayank Goyal, Serge Bracard, F. Guillemin, Daniel Bos, Ibrahim Alhabli, Jeffrey Saver, Hester F. Lingsma, Faysal Benali, Aad van der Lugt, Charles BLM Majoie, Aravind Ganesh, Peter J. Mitchell, Tudor G. Jovin, Daniel Rueckert, Theo van Walsum, Diederik WJ Dippel, Paul Bentley, Michael D. Hill
article en

Abstract

Question The predictive value of baseline CT imaging for the prediction of functional outcome and benefit of EVT for anterior LVO stroke is uncertain. Findings Discrimination of a model based on CT imaging alone is substantial, but can further be improved by the addition of limited clinical characteristics. Clinical relevance Baseline CT imaging holds considerable predictive value with regard to functional outcome and treatment benefit. The addition of limited clinical information is needed to achieve predictive performance similar to an established prediction model.

European Radiology
Université de Tours (FR), Altair Engineering (United States) (US), The Royal Melbourne Hospital (AU), Inserm (FR), University of California, Los Angeles (US), The University of Melbourne (AU), University of Calgary (CA), Newcastle upon Tyne Hospitals NHS Foundation Trust (GB), Erasmus MC (NL), TUM Klinikum (DE), Maastricht University (NL), O'Brien Institute (AU), Centre Hospitalier Universitaire de Tours (FR), Centre d’Investigation Clinique Innovation Technologique de Nancy (FR), Newcastle upon Tyne Hospital (GB), NIHR Newcastle Biomedical Research Centre (GB), University of Pittsburgh Medical Center (US), Amsterdam University Medical Centers (NL), AZ Sint-Blasius (BE), Queen Elizabeth University Hospital (GB), Imperial College London (GB), Technical University of Munich (DE), University of Glasgow (GB), Newcastle University (GB), University of Amsterdam (NL), Université de Lorraine (FR)
University of Pittsburgh, Université de Lorraine, Amsterdam University Medical Centers, Newcastle University, University of Glasgow, Institut National de la Santé et de la Recherche Médicale, Universiteit van Amsterdam, Newcastle upon Tyne Hospitals NHS Foundation Trust, Fakultet Medicinskih Nauka, Univerziteta U Kragujevcu, University of California, Los Angeles, Medical Center, University of Pittsburgh, Faculty of Medical Sciences, Newcastle University, Erasmus Universitair Medisch Centrum Rotterdam
Reduced inequalities
Openalex Percentile: Top 88%
Acute Ischemic Stroke Management
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