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Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis
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)...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3346995/ https://www.ncbi.nlm.nih.gov/pubmed/22577554 http://dx.doi.org/10.1155/2012/928638 |
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author | Stefanini, Matteo Gaspari, Eleonora Boi, Luca Del Giudice, Costantino Mastrangeli, Roberta Nucera, Francesca Simonetti, Giovanni |
author_facet | Stefanini, Matteo Gaspari, Eleonora Boi, Luca Del Giudice, Costantino Mastrangeli, Roberta Nucera, Francesca Simonetti, Giovanni |
author_sort | Stefanini, Matteo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3346995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-33469952012-05-10 Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis Stefanini, Matteo Gaspari, Eleonora Boi, Luca Del Giudice, Costantino Mastrangeli, Roberta Nucera, Francesca Simonetti, Giovanni Int J Vasc Med Research Article 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. Hindawi Publishing Corporation 2012 2012-04-22 /pmc/articles/PMC3346995/ /pubmed/22577554 http://dx.doi.org/10.1155/2012/928638 Text en Copyright © 2012 Matteo Stefanini et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Stefanini, Matteo Gaspari, Eleonora Boi, Luca Del Giudice, Costantino Mastrangeli, Roberta Nucera, Francesca Simonetti, Giovanni Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis |
title | Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis |
title_full | Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis |
title_fullStr | Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis |
title_full_unstemmed | Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis |
title_short | Correlation between US-PSV and 64-Row MDCTA with Advanced Vessel Analysis in the Quantification of 50–70% Carotid Artery Stenosis |
title_sort | correlation between us-psv and 64-row mdcta with advanced vessel analysis in the quantification of 50–70% carotid artery stenosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3346995/ https://www.ncbi.nlm.nih.gov/pubmed/22577554 http://dx.doi.org/10.1155/2012/928638 |
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