Predicting haemodialysis arteriovenous fistula outcomes using computational fluid dynamics and ferumoxytol-enhanced MRI.
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| Title: | Predicting haemodialysis arteriovenous fistula outcomes using computational fluid dynamics and ferumoxytol-enhanced MRI. |
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| Authors: | Ker R; Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK., Hyde-Linaker G; Department of Biomedical Engineering, University of Strathclyde, Glasgow, UK., Hall Barrientos P; Imaging Centre of Excellence, Queen Elizabeth University Hospital, Glasgow, UK., Kingsmore DB; Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK.; School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK., Stoumpos S; Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK.; School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK., Kazakidi A; Department of Biomedical Engineering, University of Strathclyde, Glasgow, UK. |
| Source: | The journal of vascular access [J Vasc Access] 2026 May; Vol. 27 (3), pp. 1219-1228. Date of Electronic Publication: 2025 Dec 07. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Sage Publications Country of Publication: United States NLM ID: 100940729 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1724-6032 (Electronic) Linking ISSN: 11297298 NLM ISO Abbreviation: J Vasc Access Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1724-6032 |
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| DOI: | 10.1177/11297298251395144 |
