BACKGROUND: Sixteen-slice multi-detector computed tomography (MDCT) permits reliable noninvasive detection of significant coronary stenosis based on qualitative visual assessment. The purpose of this study was to determine the accuracy of MDCT to quantify the degree of coronary stenosis as compared to quantitative coronary angiography (QCA) using two different reconstruction methods. METHODS: We studied 69 coronary artery lesions from 38 consecutive patients that underwent 16-slice MDCT as a part of research study, which enrolled consecutive subjects scheduled for clinically indicated invasive coronary angiography. Nine coronary artery lesions with motion artifacts, heavily calcified plaques or stents were excluded from the analysis. The degree of stenosis was calculated by two independent readers non-blinded to the location of the stenosis, but blinded to the results of the QCA. MDCT luminal diameters were measured in cross-sectional multi-planar reformatted (CS-MPR) images created perpendicular to the centerline of the vessel and in 5 mm thin-slab maximum intensity projections (MIP) parallel to the long axis of the vessel. Both MDCT methods were compared against QCA. RESULTS: The mean degree of stenosis as measured by MDCT was closely correlated to QCA for both methods (CS-MPR versus QCA: 61 +/- 23% versus 64 +/- 29%; r2 = 0.83, p < 0.001 and MIP versus QCA: 64 +/- 22% versus 64 +/- 29%; r2 = 0.84, p < 0.001 for MIP. Bland-Altman analysis demonstrated a negative bias of the degree of stenosis of -2.8 +/- 12% using CS-MPR and a minimally positive bias of 0.6 +/- 12% for MIP. In stratified analysis for lesion severity (mild, 0-40%; moderate, 41-70% or severe, > 70%) the agreement between both CS-MPR and MIP was high when compared to QCA (kappa = 0.74 and 0.71, respectively). CONCLUSION: Multi-detector spiral CT permits accurate quantitative assessment of the degree of coronary stenosis in selected data sets of sufficient quality using both cross-sectional and longitudinal vessel reconstructions.
BACKGROUND: Sixteen-slice multi-detector computed tomography (MDCT) permits reliable noninvasive detection of significant coronary stenosis based on qualitative visual assessment. The purpose of this study was to determine the accuracy of MDCT to quantify the degree of coronary stenosis as compared to quantitative coronary angiography (QCA) using two different reconstruction methods. METHODS: We studied 69 coronary artery lesions from 38 consecutive patients that underwent 16-slice MDCT as a part of research study, which enrolled consecutive subjects scheduled for clinically indicated invasive coronary angiography. Nine coronary artery lesions with motion artifacts, heavily calcified plaques or stents were excluded from the analysis. The degree of stenosis was calculated by two independent readers non-blinded to the location of the stenosis, but blinded to the results of the QCA. MDCT luminal diameters were measured in cross-sectional multi-planar reformatted (CS-MPR) images created perpendicular to the centerline of the vessel and in 5 mm thin-slab maximum intensity projections (MIP) parallel to the long axis of the vessel. Both MDCT methods were compared against QCA. RESULTS: The mean degree of stenosis as measured by MDCT was closely correlated to QCA for both methods (CS-MPR versus QCA: 61 +/- 23% versus 64 +/- 29%; r2 = 0.83, p < 0.001 and MIP versus QCA: 64 +/- 22% versus 64 +/- 29%; r2 = 0.84, p < 0.001 for MIP. Bland-Altman analysis demonstrated a negative bias of the degree of stenosis of -2.8 +/- 12% using CS-MPR and a minimally positive bias of 0.6 +/- 12% for MIP. In stratified analysis for lesion severity (mild, 0-40%; moderate, 41-70% or severe, > 70%) the agreement between both CS-MPR and MIP was high when compared to QCA (kappa = 0.74 and 0.71, respectively). CONCLUSION: Multi-detector spiral CT permits accurate quantitative assessment of the degree of coronary stenosis in selected data sets of sufficient quality using both cross-sectional and longitudinal vessel reconstructions.
Authors: Filippo Cademartiri; Erica Maffei; Anselmo Alessandro Palumbo; Roberto Malagò; Ludovico La Grutta; W Bob Meiijboom; Annachiara Aldrovandi; Michele Fusaro; Luigi Vignali; Alberto Menozzi; Valerio Brambilla; Paolo Coruzzi; Massimo Midiri; Miles A Kirchin; Nico R A Mollet; Gabriel P Krestin Journal: Eur Radiol Date: 2007-10-13 Impact factor: 5.315
Authors: Lars Husmann; Oliver Gaemperli; Tiziano Schepis; Hans Scheffel; Ines Valenta; Tobias Hoefflinghaus; Paul Stolzmann; Lotus Desbiolles; Bernhard A Herzog; Sebastian Leschka; Borut Marincek; Hatem Alkadhi; Philipp A Kaufmann Journal: Int J Cardiovasc Imaging Date: 2008-06-19 Impact factor: 2.357
Authors: M Francone; I Carbone; A Napoli; E Algeri; H Grazhdani; R Lezoche; F Mirabelli; C Gaudio; F A Calabrese; C Catalano; R Passariello Journal: Radiol Med Date: 2007-12-13 Impact factor: 3.469
Authors: Tej Sheth; Craig Butler; Benjamin Chow; M T V Chan; Ayesha Mitha; Peter Nagele; Vikas Tandon; Lori Stewart; Michelle Graham; G Y S Choi; T Kisten; P K Woodard; Andrew Crean; Y F Abdul Aziz; G Karthikeyan; C K Chow; W Szczeklik; M Markobrada; T Mastracci; P J Devereaux Journal: BMJ Open Date: 2012-07-31 Impact factor: 2.692