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Proceedings Paper

Quantification of the uncertainty in coronary CTA plaque measurements using dynamic cardiac phantom and 3D-printed plaque models
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Paper Abstract

The purpose of this study was to quantify the accuracy of coronary computed tomography angiography (CTA) stenosis measurements using newly developed physical coronary plaque models attached to a base dynamic cardiac phantom (Shelley Medical DHP-01). Coronary plaque models (5 mm diameter, 50% stenosis, and 32 mm long) were designed and 3D-printed with tissue equivalent materials (calcified plaque with iodine enhanced lumen). Realistic cardiac motion was achieved by fitting known cardiac motion vectors to left ventricle volume-time curves to create synchronized heart motion profiles executed by the base cardiac phantom. Realistic coronary CTA acquisition was accomplished by synthesizing corresponding ECG waveforms for gating and reconstruction purposes. All scans were acquired using a retrospective gating technique on a dual-source CT system (Siemens SOMATOM FLASH) with 75ms temporal resolution. Multi-planar reformatted images were reconstructed along vessel centerlines and the enhanced lumens were manually segmented by 5 independent operators. On average, the stenosis measurement accuracy was 0.9% positive bias for the motion free condition (0 bpm). The measurement accuracy monotonically decreased to 18.5% negative bias at 90 bpm. Contrast-tonoise (CNR), vessel circularity, and segmentation conformity also decreased monotonically with increasing heart rate. These results demonstrate successful implementation of the base cardiac phantom with 3D-printed coronary plaque models, adjustable motion profiles, and coordinated ECG waveforms. They further show the utility of the model to ascertain metrics of coronary CT accuracy and image quality under a variety of plaque, motion, and acquisition conditions.

Paper Details

Date Published: 9 March 2017
PDF: 10 pages
Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101325E (9 March 2017); doi: 10.1117/12.2255592
Show Author Affiliations
Taylor Richards, Carl E. Ravin Advanced Imaging Labs., Duke Univ. (United States)
Gregory M. Sturgeon, Carl E. Ravin Advanced Imaging Labs., Duke Univ. (United States)
Juan Carlos Ramirez-Giraldo, Siemens Medical Solutions USA Inc. (United States)
Geoffrey Rubin, Duke Univ. Health System (United States)
Paul Segars, Carl E. Ravin Advanced Imaging Labs., Duke Univ. (United States)
Duke Univ. Health System (United States)
Ehsan Samei, Carl E. Ravin Advanced Imaging Labs., Duke Univ. (United States)
Duke Univ. Health System (United States)

Published in SPIE Proceedings Vol. 10132:
Medical Imaging 2017: Physics of Medical Imaging
Thomas G. Flohr; Joseph Y. Lo; Taly Gilat Schmidt, Editor(s)

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