Clinical validation of an automated vessel-segmentation software of the extracranial-carotid arteries based on 3D-MRA: A prospective study

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

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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 and Schroth, Gerhard

ISSN:

0150-9861

ISBN:

18707758

Publisher:

Elsevier Masson

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 15:01

Last Modified:

08 Jun 2016 10:44

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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