Carotid artery stenosis: performance of advanced vessel analysis software in evaluating CTA.

Abstract

OBJECTIVES:

The aim of this study was to evaluate time efficiency and diagnostic reproducibility of an advanced vessel analysis software for diagnosis of carotid artery stenosis.

MATERIAL AND METHODS:

40 patients with suspected carotid artery stenosis received head and neck DE-CTA as part of their pre-interventional workup. Acquired data were evaluated by 2 independent radiologists. Stenosis grading was performed by MPR eyeballing with freely adjustable MPRs and with a preliminary prototype of the meanwhile available client-server and advanced visualization software syngo.via CT Vascular (Siemens Healthcare, Erlangen, Germany). Stenoses were graded according to the following 5 categories: I: 0%, II: 1-50%, III: 51-69%, IV: 70-99% and V: total occlusion. Furthermore, time to diagnosis for each carotid artery was recorded.

RESULTS:

Both readers achieved very good specificity values and good respectively very good sensitivity values without significant differences between both reading methods. Furthermore, there was a very good correlation between both readers for both reading methods without significant differences (kappa value: standard image interpretation k=0.809; advanced vessel analysis software k=0.863). Using advanced vessel analysis software resulted in a significant time saving (p<0.0001) for both readers. Time to diagnosis could be decreased by approximately 55%.

CONCLUSIONS:

Advanced vessel analysis application CT Vascular of the new imaging software syngo.via (Siemens Healthcare, Forchheim, Germany) provides a high rate of reproducibility in assessment of carotid artery stenosis. Furthermore a significant time saving in comparison to standard image interpretation is achievable.

• Authors: Ilias Tsiflikas, Christina Biermann, Christoph Thomas, Dominik Ketelsen, Claus D Claussen, Martin Heuschmid
• Journal: European journal of radiology (Eur J Radiol) Vol. 81 Issue 9 Pg. 2255-9 (Sep 2012) ISSN: 1872-7727 [Electronic] Ireland
• PMID: 21930358 (Publication Type: Journal Article)
• Copyright: Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Topics

• Algorithms
• Angiography (methods)
• Carotid Stenosis (diagnostic imaging)
• Humans
• Observer Variation
• Pattern Recognition, Automated (methods)
• Radiographic Image Enhancement (methods)
• Radiographic Image Interpretation, Computer-Assisted (methods)
• Reproducibility of Results
• Sensitivity and Specificity
• Software
• Software Validation
• Tomography, X-Ray Computed (methods)