Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis. (22nd April 2012)

• Record Type: Journal Article
• Authors: Stefanini, Matteo; Gaspari, Eleonora; Boi, Luca; Del Giudice, Costantino; Mastrangeli, Roberta; Nucera, Francesca; Simonetti, Giovanni
• Other Names: Minar Erich Academic Editor.
• Is Part Of: International journal of vascular medicine. Volume 2012(2012)
• Publication Date: 2012-04-22
• Subjects: Blood-vessels -- Diseases -- Periodicals; 616.13005
• DOI: 10.1155/2012/928638
• Languages: English
• ISSNs: 2090-2824

Abstract

Abstract : Purpose . To correlate ultrasonographic peak systolic velocity (US-PSV) and 64-row multidetector computed tomography angiography (MDCTA) with advanced vessel analysis (AVA) software in the quantification of 50–70% carotid artery stenosis. Materials and methods . 199 consecutive patients (247 arteries) with internal carotid artery (ICA) or third proximal bifurcation stenosis. Each patient was studied by duplex US (DUS) and 64-row MDCTA with AVA software. Results . DUS showed PSV measurements less than 125 cm/s in 51 carotid stenosis and a value greater than this in 196 arteries. 64-row MDCTA AVA software showed a grade of stenosis less than 50% in 42 carotid arteries while a greater 70% was found in 4 carotid arteries; then, carotid arteries with stenosis percentage between 50% and 70% were 201. Linear regression analysis showed a good linear correlation (r = 0.88 ) between MDCTA-AVA software percentage stenosis and PSV: between 50% grade of stenosis and PSV value corresponding to 133, 6 cm/sec and between 70% stenosis and PSV value corresponding to 268 cm/sec. The sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV) of this analysis were 93%, 82%, 97%, 75%, respectively. Conclusion . Linear correlation between PSV data and grade of stenosis from 50% to 70% obtained with 64-row MDCTA AVA software. Main PSV value corresponding to 50% and 70% grade of stenosis at AVA analysis.