OBJECTIVES: To systematically assess inter-technique and inter-/intra-reader variability of coronary CT angiography (CTA) to measure plaque burden compared with intravascular ultrasound (IVUS) and to determine whether iterative reconstruction algorithms affect variability. METHODS: IVUS and CTA data were acquired from nine human coronary arteries ex vivo. CT images were reconstructed using filtered back projection (FBPR) and iterative reconstruction algorithms: adaptive-statistical (ASIR) and model-based (MBIR). After co-registration of 284 cross-sections between IVUS and CTA, two readers manually delineated the cross-sectional plaque area in all images presented in random order. RESULTS: Average plaque burden by IVUS was 63.7 ± 10.7% and correlated significantly with all CTA measurements (r = 0.45-0.52; P < 0.001), while CTA overestimated the burden by 10 ± 10%. There were no significant differences among FBPR, ASIR and MBIR (P > 0.05). Increased overestimation was associated with smaller plaques, eccentricity and calcification (P < 0.001). Reproducibility of plaque burden by CTA and IVUS datasets was excellent with a low mean intra-/inter-reader variability of <1/<4% for CTA and <0.5/<1% for IVUS respectively (P < 0.05) with no significant difference between CT reconstruction algorithms (P > 0.05). CONCLUSION: In ex vivo coronary arteries, plaque burden by coronary CTA had extremely low inter-/intra-reader variability and correlated significantly with IVUS measurements. Accuracy as well as reader reliability were independent of CT image reconstruction algorithm. KEY POINTS: • IVUS is deemed the gold standard in-vivo coronary plaque assessment • But coronary CT angiography findings correlate strongly with IVUS results • Coronary CT angiography now allows plaque quantification close to IVUS • Iterative image reconstruction algorithms do not alter accuracy or reproducibility • Plaque quantification is more challenging in smaller eccentric calcified lesions.
OBJECTIVES: To systematically assess inter-technique and inter-/intra-reader variability of coronary CT angiography (CTA) to measure plaque burden compared with intravascular ultrasound (IVUS) and to determine whether iterative reconstruction algorithms affect variability. METHODS: IVUS and CTA data were acquired from nine human coronary arteries ex vivo. CT images were reconstructed using filtered back projection (FBPR) and iterative reconstruction algorithms: adaptive-statistical (ASIR) and model-based (MBIR). After co-registration of 284 cross-sections between IVUS and CTA, two readers manually delineated the cross-sectional plaque area in all images presented in random order. RESULTS: Average plaque burden by IVUS was 63.7 ± 10.7% and correlated significantly with all CTA measurements (r = 0.45-0.52; P < 0.001), while CTA overestimated the burden by 10 ± 10%. There were no significant differences among FBPR, ASIR and MBIR (P > 0.05). Increased overestimation was associated with smaller plaques, eccentricity and calcification (P < 0.001). Reproducibility of plaque burden by CTA and IVUS datasets was excellent with a low mean intra-/inter-reader variability of <1/<4% for CTA and <0.5/<1% for IVUS respectively (P < 0.05) with no significant difference between CT reconstruction algorithms (P > 0.05). CONCLUSION: In ex vivo coronary arteries, plaque burden by coronary CTA had extremely low inter-/intra-reader variability and correlated significantly with IVUS measurements. Accuracy as well as reader reliability were independent of CT image reconstruction algorithm. KEY POINTS: • IVUS is deemed the gold standard in-vivo coronary plaque assessment • But coronary CT angiography findings correlate strongly with IVUS results • Coronary CT angiography now allows plaque quantification close to IVUS • Iterative image reconstruction algorithms do not alter accuracy or reproducibility • Plaque quantification is more challenging in smaller eccentric calcified lesions.
Authors: G S Mintz; S E Nissen; W D Anderson; S R Bailey; R Erbel; P J Fitzgerald; F J Pinto; K Rosenfield; R J Siegel; E M Tuzcu; P G Yock Journal: J Am Coll Cardiol Date: 2001-04 Impact factor: 24.094
Authors: Priyanka Prakash; Mannudeep K Kalra; Avinash K Kambadakone; Homer Pien; Jiang Hsieh; Michael A Blake; Dushyant V Sahani Journal: Invest Radiol Date: 2010-04 Impact factor: 6.016
Authors: Y J Liu; P P Zhu; B Chen; J Y Wang; Q X Yuan; W X Huang; H Shu; E R Li; X S Liu; K Zhang; H Ming; Z Y Wu Journal: Phys Med Biol Date: 2007-05-22 Impact factor: 3.609
Authors: Sebastian Leschka; Sara Seitun; Matthias Dettmer; Stephan Baumüller; Paul Stolzmann; Robert Goetti; Hans Scheffel; Gudrun Feuchtner; Kathrin Wunnicke; Simon Wildermuth; Christian Oehlschlegel; Borut Marincek; Wolfram Jochum; Hatem Alkadhi Journal: J Cardiovasc Comput Tomogr Date: 2010-06-08
Authors: Michael Schmid; Stephan Achenbach; Dieter Ropers; Sei Komatsu; Ulrike Ropers; Werner G Daniel; Tobias Pflederer Journal: Am J Cardiol Date: 2007-12-21 Impact factor: 2.778
Authors: Stefan B Puchner; Maros Ferencik; Mihaly Karolyi; Synho Do; Pal Maurovich-Horvat; Hans-Ulrich Kauczor; Udo Hoffmann; Christopher L Schlett Journal: Int J Cardiovasc Imaging Date: 2013-08-30 Impact factor: 2.357
Authors: Lei Zhao; Fabian Plank; Moritz Kummann; Philipp Burghard; Andrea Klauser; Wolfgang Dichtl; Gudrun Feuchtner Journal: Cardiovasc Diagn Ther Date: 2015-04
Authors: Ryo Nakazato; Aryeh Shalev; Joon-Hyung Doh; Bon-Kwon Koo; Damini Dey; Daniel S Berman; James K Min Journal: Eur Radiol Date: 2013-04-04 Impact factor: 5.315
Authors: Stefan B Puchner; Maros Ferencik; Pal Maurovich-Horvat; Masataka Nakano; Fumiyuki Otsuka; Hans-Ulrich Kauczor; Renu Virmani; Udo Hoffmann; Christopher L Schlett Journal: Eur Radiol Date: 2014-09-03 Impact factor: 5.315
Authors: Annemarie M den Harder; Martin J Willemink; Ronald L A W Bleys; Pim A de Jong; Ricardo P J Budde; Arnold M R Schilham; Tim Leiner Journal: Int J Cardiovasc Imaging Date: 2014-05-03 Impact factor: 2.357
Authors: Márton Kolossváry; Júlia Karády; Yasuka Kikuchi; Alexander Ivanov; Christopher L Schlett; Michael T Lu; Borek Foldyna; Béla Merkely; Hugo J Aerts; Udo Hoffmann; Pál Maurovich-Horvat Journal: Radiology Date: 2019-08-06 Impact factor: 11.105