BACKGROUND: Interscan variability of coronary arterial plaque volume and composition quantification with coronary computed tomographic angiography (CCTA), an important attribute when considering CCTA as a serial modality, has not been examined. OBJECTIVE: We sought to systematically determine intraobserver- and interobserver-interscan reproducibility of these measures. METHODS: Two blinded, experienced readers independently evaluated proximal coronary segments on CCTAs from 30 patients who underwent 2 scans within 200 days (median, 124 days; interquartile range, 49-155 days) without experiencing an interim acute coronary event. Readers recorded number of plaques and, in plaques that met a preset minimal length criterion, quantified total, calcified plaque (CP), and noncalcified plaque (NCP) volumes and percentage of total plaque volume occupied by NCP. RESULTS: Of 89 total segments studied, 36 contained detectable plaque, and 26 met criterion for quantification. Intraobserver, interobserver, and interscan agreements for normal segments were 100%. Intraobserver-interscan correlations of total, CP, and NCP volumes and percentage of NCP were excellent (r=0.93-0.97, P values<0.001). Interobserver-interscan correlations for all measures were also very good (r=0.81-0.96, P values<0.001). Variability in plaque volume quantification was significant, exceeding 60% of the averaged paired plaque volumes in the best-case scenario (interobserver-interscan CP volume). Quantification of percentage of NCP composition by volume was more consistent, with <24% variation in the worst-case scenario (interobserver-interscan). CONCLUSION: CCTA shows promise for quantifying serial coronary plaque change. Currently, the most robust measure seems to be percentage of plaque composition, rather than plaque volume. For smaller plaques, volume quantification remains challenging.
BACKGROUND: Interscan variability of coronary arterial plaque volume and composition quantification with coronary computed tomographic angiography (CCTA), an important attribute when considering CCTA as a serial modality, has not been examined. OBJECTIVE: We sought to systematically determine intraobserver- and interobserver-interscan reproducibility of these measures. METHODS: Two blinded, experienced readers independently evaluated proximal coronary segments on CCTAs from 30 patients who underwent 2 scans within 200 days (median, 124 days; interquartile range, 49-155 days) without experiencing an interim acute coronary event. Readers recorded number of plaques and, in plaques that met a preset minimal length criterion, quantified total, calcified plaque (CP), and noncalcified plaque (NCP) volumes and percentage of total plaque volume occupied by NCP. RESULTS: Of 89 total segments studied, 36 contained detectable plaque, and 26 met criterion for quantification. Intraobserver, interobserver, and interscan agreements for normal segments were 100%. Intraobserver-interscan correlations of total, CP, and NCP volumes and percentage of NCP were excellent (r=0.93-0.97, P values<0.001). Interobserver-interscan correlations for all measures were also very good (r=0.81-0.96, P values<0.001). Variability in plaque volume quantification was significant, exceeding 60% of the averaged paired plaque volumes in the best-case scenario (interobserver-interscan CP volume). Quantification of percentage of NCP composition by volume was more consistent, with <24% variation in the worst-case scenario (interobserver-interscan). CONCLUSION:CCTA shows promise for quantifying serial coronary plaque change. Currently, the most robust measure seems to be percentage of plaque composition, rather than plaque volume. For smaller plaques, volume quantification remains challenging.
Authors: Lauren A Baldassarre; Subha V Raman; James K Min; Jennifer H Mieres; Martha Gulati; Nanette K Wenger; Thomas H Marwick; Chiara Bucciarelli-Ducci; C Noel Bairey Merz; Dipti Itchhaporia; Keith C Ferdinand; Carl J Pepine; Mary Norine Walsh; Jagat Narula; Leslee J Shaw Journal: JACC Cardiovasc Imaging Date: 2016-04
Authors: Henry Chang; James K Min; Sunil V Rao; Manesh R Patel; Orlando P Simonetti; Giuseppe Ambrosio; Subha V Raman Journal: Circ Cardiovasc Imaging Date: 2012-07 Impact factor: 7.792
Authors: Rolf Symons; Justin Z Morris; Colin O Wu; Amir Pourmorteza; Mark A Ahlman; João A C Lima; Marcus Y Chen; Marissa Mallek; Veit Sandfort; David A Bluemke Journal: Radiology Date: 2016-09-16 Impact factor: 11.105
Authors: Kristian Altern Øvrehus; Mohamed Marwan; Hans Erik Bøtker; Stephan Achenbach; Bjarne Linde Nørgaard Journal: Int J Cardiovasc Imaging Date: 2011-05-29 Impact factor: 2.357
Authors: Annika Schuhbaeck; Damini Dey; Yuka Otaki; Piotr Slomka; Brian G Kral; Stephan Achenbach; Daniel S Berman; Elliott K Fishman; Shenghan Lai; Hong Lai Journal: Eur Radiol Date: 2014-06-25 Impact factor: 5.315