Korean J Radiol.  2017 Dec;18(6):881-887. 10.3348/kjr.2017.18.6.881.

Effect of a Novel Intracycle Motion Correction Algorithm on Dual-Energy Spectral Coronary CT Angiography: A Study with Pulsating Coronary Artery Phantom at High Heart Rates

Affiliations
  • 1Imaging Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang 830011, China. wenyaliu2002@yahoo.com
  • 2CT Imaging Research Center, GE Healthcare, Beijing 100176, China.

Abstract


OBJECTIVE
Using a pulsating coronary artery phantom at high heart rate settings, we investigated the efficacy of a motion correction algorithm (MCA) to improve the image quality in dual-energy spectral coronary CT angiography (CCTA).
MATERIALS AND METHODS
Coronary flow phantoms were scanned at heart rates of 60-100 beats/min at 10-beats/min increments, using dual-energy spectral CT mode. Virtual monochromatic images were reconstructed from 50 to 90 keV at 10-keV increments. Two blinded observers assessed image quality using a 4-point Likert Scale (1 = non-diagnostic, 4 = excellent) and the fraction of interpretable segments using MCA versus conventional algorithm (CA). Comparison of variables was performed with the Wilcoxon rank sum test and McNemar test.
RESULTS
At heart rates of 70, 80, 90, and 100 beats/min, images with MCA were rated as higher image scores compared to those with CA on monochromatic levels of 50, 60, and 70 keV (each p < 0.05). Meanwhile, at a heart rate of 90 beats/min, image interpretability was improved by MCA at a monochromatic level of 60 keV (p < 0.05) and 70 keV (p < 0.05). At a heart rate of 100 beats/min, image interpretability was improved by MCA at monochromatic levels of 50 keV (from 69.4% to 86.1%, p < 0.05), 60 keV (from 55.6% to 83.3%, p < 0.05) and 70 keV (from 33.3% to 69.3%, p < 0.05).
CONCLUSION
Low-keV monochromatic images combined with MCA improves image quality and image interpretability in CCTAs at high heart rates.

Keyword

Motion correction algorithm; Spectral imaging; Coronary arteries; Tomography, X-ray computed

MeSH Terms

*Algorithms
Computed Tomography Angiography/instrumentation/*methods
Coronary Vessels/*diagnostic imaging/physiology
Heart Rate/*physiology
Humans
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results

Figure

  • Fig. 1 Pulsating coronary artery phantom and segmentations of vessels. A. Pulsating coronary artery phantom. B. Volume rending images demonstrate segmentations of vessels.

  • Fig. 2 Comparison of image score and 95% confidence interval (CI) between MCA and CA at heart rates of 70, 80, 90, and 100 bpm, at different monochromatic levels. A. Comparison of image quality score (95% CI) between MCA and CA at heart rate of 70 bpm. B. Comparison of image quality score (95% CI) between MCA and CA at heart rate of 80 bpm. C. Comparison of image quality score (95% CI) between MCA and CA at heart rate of 90 bpm. D. Comparison of image quality score (95% CI) between MCA and CA at heart rate of 100 bpm. *0.05, †p < 0.01. bpm = beats/minute, CA = conventional algorithm, MCA = motion correction algorithm

  • Fig. 3 Comparison of phantom axial images after CA and MCA at different keV levels at heart rate of 90 bpm.


Cited by  2 articles

Optimal Monochromatic Imaging of Spectral Computed Tomography Potentially Improves the Quality of Hepatic Vascular Imaging
Xiao-Ping Yin, Bu-Lang Gao, Cai-Ying Li, Huan Zhou, Liang Zhao, Ya-Ting Zheng, Yong-Xia Zhao
Korean J Radiol. 2018;19(4):578-584.    doi: 10.3348/kjr.2018.19.4.578.

Influence of Heart Rate and Innovative Motion-Correction Algorithm on Coronary Artery Image Quality and Measurement Accuracy Using 256-Detector Row Computed Tomography Scanner: Phantom Study
Jeong Bin Park, Yeon Joo Jeong, Geewon Lee, Nam Kyung Lee, Jin You Kim, Ji Won Lee
Korean J Radiol. 2019;20(1):94-101.    doi: 10.3348/kjr.2018.0251.


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