Zhonghua Sun1, Abdulrahman Marzouq D Almutairi. 1. Discipline of Medical Imaging, Department of Imaging and Applied Physics, Curtin University of Technology, Perth, WA, Australia. z.sun@curtin.edu.au
Abstract
PURPOSE: The aim of this study was to perform a meta-analysis of the diagnostic accuracy of 64-slice CT angiography for the detection of coronary in-stent restenosis in patients treated with coronary stents when compared to conventional coronary angiography. MATERIALS AND METHODS: A search of PUBMED/MEDLINE, ProQuest and Cochrane library databases for English literature was performed. Only studies comparing 64-slice CT angiography with conventional coronary angiography for the detection of coronary in-stent restenosis (more than 50% stenosis) were included for analysis. Sensitivity and specificity estimates pooled across studies were tested using a fixed effects model. RESULTS: Fourteen studies met selection criteria for inclusion in the analysis. The mean value of assessable stents was 89%. Prevalence of in-stent restenosis following coronary stenting was 20% among these studies. Pooled estimates of the sensitivity and specificity of overall 64-slice CT angiography for the detection of coronary in-stent restenosis was 90% (95% CI: 86%, 94%) and 91% (95% CI: 90%, 93%), respectively, based on the evaluation of assessable stents. Diagnostic value of 64-slice CT angiography was found to decrease significantly when the analysis was performed with inclusion of nonassessable segments in five studies, with pooled sensitivity and specificity being 79% (95% CI: 68%, 88%) and 81% (95% CI: 77%, 84%). Stent diameter is the main factor affecting the diagnostic value of 64-slice CT angiography. CONCLUSION: Our results showed that 64-slice CT angiography has high diagnostic value (both sensitivity and specificity) for detection of coronary in-stent restenosis based on assessable segments when compared to conventional coronary angiography. Copyright (c) 2008 Elsevier Ireland Ltd. All rights reserved.
PURPOSE: The aim of this study was to perform a meta-analysis of the diagnostic accuracy of 64-slice CT angiography for the detection of coronary in-stent restenosis in patients treated with coronary stents when compared to conventional coronary angiography. MATERIALS AND METHODS: A search of PUBMED/MEDLINE, ProQuest and Cochrane library databases for English literature was performed. Only studies comparing 64-slice CT angiography with conventional coronary angiography for the detection of coronary in-stent restenosis (more than 50% stenosis) were included for analysis. Sensitivity and specificity estimates pooled across studies were tested using a fixed effects model. RESULTS: Fourteen studies met selection criteria for inclusion in the analysis. The mean value of assessable stents was 89%. Prevalence of in-stent restenosis following coronary stenting was 20% among these studies. Pooled estimates of the sensitivity and specificity of overall 64-slice CT angiography for the detection of coronary in-stent restenosis was 90% (95% CI: 86%, 94%) and 91% (95% CI: 90%, 93%), respectively, based on the evaluation of assessable stents. Diagnostic value of 64-slice CT angiography was found to decrease significantly when the analysis was performed with inclusion of nonassessable segments in five studies, with pooled sensitivity and specificity being 79% (95% CI: 68%, 88%) and 81% (95% CI: 77%, 84%). Stent diameter is the main factor affecting the diagnostic value of 64-slice CT angiography. CONCLUSION: Our results showed that 64-slice CT angiography has high diagnostic value (both sensitivity and specificity) for detection of coronary in-stent restenosis based on assessable segments when compared to conventional coronary angiography. Copyright (c) 2008 Elsevier Ireland Ltd. All rights reserved.
Authors: Ullrich Ebersberger; Francesco Tricarico; U Joseph Schoepf; Philipp Blanke; J Reid Spears; Garrett W Rowe; William T Halligan; Thomas Henzler; Fabian Bamberg; Alexander W Leber; Ellen Hoffmann; Paul Apfaltrer Journal: Eur Radiol Date: 2012-07-10 Impact factor: 5.315
Authors: Tobias Gassenmaier; Nils Petri; Thomas Allmendinger; Thomas Flohr; David Maintz; Wolfram Voelker; Thorsten A Bley Journal: Eur Radiol Date: 2014-07-21 Impact factor: 5.315
Authors: Jason R Sims; Nandan S Anavekar; Krishnaswamy Chandrasekaran; James M Steckelberg; Walter R Wilson; Bernard J Gersh; Larry M Baddour; Daniel C DeSimone Journal: Int J Cardiovasc Imaging Date: 2018-02-15 Impact factor: 2.357