Hostname: page-component-848d4c4894-ndmmz Total loading time: 0 Render date: 2024-06-02T02:24:51.062Z Has data issue: false hasContentIssue false
  • English
  • Français

NASCET Percent Stenosis Semi-Automated Versus Manual Measurement on CTA

Published online by Cambridge University Press:  02 December 2014

Kevin Lian ,
Jeremy H. White ,
Eric S. Bartlett ,
Aditya Bharatha ,
Richard I. Aviv ,
Allan J. Fox  and
Sean P. Symons
Kevin Lian
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
Jeremy H. White
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
Eric S. Bartlett
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
Aditya Bharatha
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
Richard I. Aviv
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
Allan J. Fox
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
Sean P. Symons*
Affiliation:
Division of Neuroradiology, Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
*
Division of Neuroradiology, Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, AG31D, Toronto, Ontario, Canada, M4N 3M5. Email: sean.symons@sunnybrook.ca
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Purpose:

To compare North American Symptomatic Carotid Endarterectomy Trial (NASCET) stenosis values and NASCET grade categorization (mild, moderate, severe) of semi-automated vessel analysis software versus manual measurements on computed tomography angiography (CTA).

Methods:

There were four observers. Two independently analyzed 81 carotid artery CTAs using semi-automated vessel analysis software according to a blinded protocol. The software measured the narrowest stenosis in millimeters (mm), distal internal carotid artery (ICA) in mm, and calculated percent stenosis based on NASCET criteria. One of these two observers performed this task twice on each carotid, the second analysis was delayed two months in order to mitigate recall bias. Two other observers manually measured the narrowest stenosis in mm, distal ICA in mm, and calculated NASCET percent stenosis in a blinded fashion. The calculated NASCET stenoses were categorized into mild, moderate, or severe. Chi square and analysis of variance (ANOVA) were used to test for statistical differences.

Results:

ANOVA did not find a statistically significant difference in the mean percent stenosis when comparing the two manual measurements, the two semi-automated measurements, and the repeat semi-automated. Chi square demonstrated that the distribution of grades of stenosis were statistically different (p<0.05) between the manual and semiautomated grades. Semi-automated vessel analysis tended to underestimate the degree of stenosis compared to manual measurement.

Conclusion:

The mean percentage stenosis determined by semi-automated vessel analysis is not significantly different from manual measurement. However, when the data is categorized into mild, moderate and severe stenosis, there is a significant difference between semi-automated and manual measurements. The semi-automated software tends to underestimate the stenosis grade compared to manual measurement.

Type
Research Article
Information
Canadian Journal of Neurological Sciences , Volume 39 , Issue 3 , May 2012 , pp. 343 - 346
Copyright
Copyright © The Canadian Journal of Neurological 2012

References

1North American Symptomatic Carotid Endarterectomy Trial Collaborators. Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis. N Engl J Med. 1991;325:445–53.Google Scholar
2Rothwell, PM, Eliasziw, M, Gutnikov, SA, et al.Analysis of pooled data from the randomized controlled trials of endarterectomy for symptomatic carotid stenosis. Lancet. 2003;361(9352):107–16.Google Scholar
3Levinson, MM, Rodriguez, DI.Endarterectomy for preventing stroke in symptomatic and asymptomatic carotid stenosis: review of clinical trials and recommendations for surgical therapy. Heart Surg Forum. 1999;2(2):147–68.Google Scholar
4Bartlett, ES, Walters, TD, Symons, SP, et al.Quantification of carotid stenosis on CT angiography. Am J Neuroradiol. 2006;27(1):13–19.Google Scholar
5Anderson, GB, Ashforth, R, Steinke, DE, et al.CT angiography for the detection and characterization of carotid artery bifurcation disease. Stroke. 2000;31(9):2168–74.Google Scholar
6Randoux, B, Marro, B, Koskas, F, et al.Carotid artery stenosis: prospective comparison of CT, three-dimensional gadolinium-enhanced MR, and conventional angiography. Radiology. 2001;220(1):179–85.CrossRefGoogle ScholarPubMed
7Leclerc, X, Godefroy, O, Pruvo, JP, et al.Computed tomographic angiography for the evaluation of carotid artery stenosis. Stroke. 1995;26(9):1577–81.Google Scholar
8Zhang, Z, Berg, M, Ikonen, A, et al.Carotid stenosis degree in CT angiography: assessment based on luminal area versus luminal diameter measurements. Eur Radiol. 2005;15(11):2359–65.CrossRefGoogle ScholarPubMed
9Zhang, Z, Berg, MH, Ikonen, AE, et al.Carotid artery stenosis: reproducibility of automated 3D CT angiography analysis method. Eur Radiol. 2004;14(4):665–72.CrossRefGoogle ScholarPubMed
10Silvennoinen, HM, Ikonen, S, Soinne, L, et al.CT angiographic analysis of carotid artery stenosis: comparison of manual assessment, semiautomatic vessel analysis, and digital subtraction angiography. Am J Neuroradiol. 2007;28(1):97–103.Google ScholarPubMed
11White, JR, Bartlett, ES, Bharatha, A, et al.Reproducibility of semiautomated measurement of carotid stenosis on CTA. Can J Neuro Sci. 2010;37(4):498–503.Google Scholar
12Fox, AJ, Eliasziw, M, Rothwell, PM, et al.Identification, prognosis, and management of patients with carotid artery near occlusion. Am J Neuroradiol. 2005;26(8):2086–94.Google ScholarPubMed
13Fox, AJ.How to measure carotid stenosis. Radiology. 1993;186(2):316–18.CrossRefGoogle ScholarPubMed
14Dix, JE, McNulty, BJ, Kalimes, DF.Frequency and significance of a small distal ICA in carotid stenosis. Am J Neuroradiol. 1998;19(7):1215–18.Google Scholar
15Bartlett, ES, Walters, TD, Symons, SP, et al.Diagnosing carotid stenosis near-occlusion by using CT angiography. Am J Neuroradiol. 2006;27(3):632–7.Google Scholar
16Bucek, RA, Puchner, S, Kanitsar, A, et al.Automated CTA quantification of internal carotid artery stenosis: a pilot trial. J Endovasc Ther. 2007;14:70–6.Google Scholar