Guzman, R; Lovblad, K O; Altrichter, S; Remonda, L; de Koning, P; Andres, R H; El-Koussy, M; Kelly, M E; Reiber, J H C; Schroth, G; Oswald, H; Barth, A (2008). Clinical validation of an automated vessel-segmentation software of the extracranial-carotid arteries based on 3D-MRA: A prospective study. Journal of neuroradiology, 35(5), pp. 278-285. Issy-les-Moulineaux (F): Elsevier Masson 10.1016/j.neurad.2008.07.001
Full text not available from this repository.OBJECTIVES: To determine the accuracy of automated vessel-segmentation software for vessel-diameter measurements based on three-dimensional contrast-enhanced magnetic resonance angiography (3D-MRA). METHOD: In 10 patients with high-grade carotid stenosis, automated measurements of both carotid arteries were obtained with 3D-MRA by two independent investigators and compared with manual measurements obtained by digital subtraction angiography (DSA) and 2D maximum-intensity projection (2D-MIP) based on MRA and duplex ultrasonography (US). In 42 patients undergoing carotid endarterectomy (CEA), intraoperative measurements (IOP) were compared with postoperative 3D-MRA and US. RESULTS: Mean interoperator variability was 8% for measurements by DSA and 11% by 2D-MIP, but there was no interoperator variability with the automated 3D-MRA analysis. Good correlations were found between DSA (standard of reference), manual 2D-MIP (rP=0.6) and automated 3D-MRA (rP=0.8). Excellent correlations were found between IOP, 3D-MRA (rP=0.93) and US (rP=0.83). CONCLUSION: Automated 3D-MRA-based vessel segmentation and quantification result in accurate measurements of extracerebral-vessel dimensions.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology |
UniBE Contributor: |
El-Koussy, Marwan, Schroth, Gerhard |
ISSN: |
0150-9861 |
ISBN: |
18707758 |
Publisher: |
Elsevier Masson |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 15:01 |
Last Modified: |
05 Dec 2022 14:19 |
Publisher DOI: |
10.1016/j.neurad.2008.07.001 |
PubMed ID: |
18707758 |
Web of Science ID: |
000261970400005 |
URI: |
https://boris.unibe.ch/id/eprint/26686 (FactScience: 84258) |
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