Semiautomated quantitation of carotid artery stenosis in Gadolinium-Bolus magnetic resonance angiography

Research output: Contribution to journalArticle

Abstract

Magnetic resonance angiography (MRA) has become the standard method for evaluation of carotid occlusive disease. Fast imaging methods combined with bolus intravenous injection of gadolinium contrast have improved the quality of these images. Nevertheless, the gold standard for evaluation was based on projection arterial angiography. The properties of these images are rather different. Whereas most previous evaluations of MRA have used visual assessment of images, we evaluate an algorithm in which a computer algorithm plays the primary role in defining arterial lumen margins, hence, disease. The accuracy of this semiautomated algorithm is shown to compare favorably with gold-standard arteriography in a series of 50 patients.

Original languageEnglish (US)
Pages (from-to)69-77
Number of pages9
JournalJournal of Digital Imaging
Volume15
Issue number2
DOIs
StatePublished - 2002

Fingerprint

Angiography
Gadolinium
Magnetic Resonance Angiography
Carotid Stenosis
Magnetic resonance
Intravenous Injections
Gold
Imaging techniques

Keywords

  • Carotid atherosclerosis
  • Magnetic resonance angiography
  • North American Symptomatic Carotid Endarterectomy Trial
  • Quantitation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Computer Vision and Pattern Recognition

Cite this

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AB - Magnetic resonance angiography (MRA) has become the standard method for evaluation of carotid occlusive disease. Fast imaging methods combined with bolus intravenous injection of gadolinium contrast have improved the quality of these images. Nevertheless, the gold standard for evaluation was based on projection arterial angiography. The properties of these images are rather different. Whereas most previous evaluations of MRA have used visual assessment of images, we evaluate an algorithm in which a computer algorithm plays the primary role in defining arterial lumen margins, hence, disease. The accuracy of this semiautomated algorithm is shown to compare favorably with gold-standard arteriography in a series of 50 patients.

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