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Quantification of uncertainty in the assessment of coronary plaque in CCTA through a dynamic cardiac phantom and 3D-printed plaque model.
- Source :
-
Journal of medical imaging (Bellingham, Wash.) [J Med Imaging (Bellingham)] 2018 Jan; Vol. 5 (1), pp. 013501. Date of Electronic Publication: 2018 Jan 17. - Publication Year :
- 2018
-
Abstract
- The purpose of this study was to develop a dynamic physical cardiac phantom with a realistic coronary plaque to investigate stenosis measurement accuracy under clinically relevant heart-rates. The coronary plaque model (5 mm diameter, 50% stenosis, and 32 mm long) was designed and 3D-printed with tissue equivalent materials (calcified plaque with iodine-enhanced lumen). Realistic cardiac motion was modeled by converting computational cardiac motion vectors into compression and rotation profiles executed by a commercial base cardiac phantom. The phantom was imaged on a dual-source CT system applying a retrospective gated coronary CT angiography (CCTA) protocol using synthesized motion-synchronized electrocardiogram (ECG) waveforms. Multiplanar reformatted images were reconstructed along vessel centerlines. Enhanced lumens were segmented by five independent operators. On average, stenosis measurement accuracy was 0.9% positively biased for the motion-free condition. Average measurement accuracy monotonically decreased from 0.9% positive bias for the motion-free condition to 18.5% negative bias at 90 beats per minute. Contrast-to-noise ratio, lumen circularity, and segmentation conformity also decreased monotonically with increasing heart-rate. These results demonstrate successful implementation of a base cardiac phantom with a 3D-printed coronary plaque model, relevant motion profile, and coordinated ECG waveform. They further show the utility of the model to ascertain metrics of CCTA accuracy and image quality under realistic plaque, motion, and acquisition conditions.
Details
- Language :
- English
- ISSN :
- 2329-4302
- Volume :
- 5
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of medical imaging (Bellingham, Wash.)
- Publication Type :
- Academic Journal
- Accession number :
- 29376102
- Full Text :
- https://doi.org/10.1117/1.JMI.5.1.013501