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J Cardiovasc Comput Tomogr. 2014 Mar-Apr;8(2):115-23. doi: 10.1016/j.jcct.2013.12.010. Epub 2014 Jan 12.

Value of knowledge-based iterative model reconstruction in low-kV 256-slice coronary CT angiography.

Author information

1
Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto-shi, Kumamoto, 860-8556, Japan.
2
Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto-shi, Kumamoto, 860-8556, Japan. Electronic address: utsunomi@kumamoto-u.ac.jp.
3
Medical Physics, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan.
4
CT Clinical Science, Philips Electronics, Tokyo, Japan.
5
Diagnostic Radiology and eCardiovascular Medicine, Kumamoto Chuo Hospital, Kumamoto, Japan.
6
Cardiovascular Medicine, Kumamoto Chuo Hospital, Kumamoto, Japan.

Abstract

BACKGROUND:

Most current iterative reconstruction algorithms for CT imaging are a mixture of iterative reconstruction and filtered back projection. The value of "fully" iterative reconstruction in coronary CT angiography remains poorly understood.

OBJECTIVE:

We aimed to assess the value of the knowledge-based iterative model reconstruction (IMR) algorithm on the qualitative and quantitative image quality at 256-slice cardiac CT.

METHODS:

We enrolled 21 patients (mean age: 69 ± 11 years) who underwent retrospectively ECG gated coronary CT anhgiography at 100 kVp tube voltage. Images were reconstructed with the filtered back projection (FBP), hybrid iterative reconstruction (IR), and IMR algorithms. CT attenuation and the contrast-to-noise ratio (CNR) of the coronary arteries were calculated. With the use of a 4-point scale, 2 reviewers visually evaluated the coronary arteries and cardiac structures.

RESULTS:

The mean CT attenuation of the proximal coronary arteries was 369.3 ± 73.6 HU, 363.9 ± 75.3 HU, and 363.3 ± 74.5 HU, respectively, for FBP, hybrid IR, and IMR and was not significantly different. The image noise of the proximal coronary arteries was significantly lower with IMR (11.3 ± 2.8 HU) than FBP (51.9 ± 12.9 HU) and hybrid IR (23.2 ± 5.2 HU). The mean CNR of the proximal coronary arteries was 9.4 ± 2.4, 20.2 ± 4.7, and 41.8 ± 9.5 with FBP, hybrid IR and IMR, respectively; it was significantly higher with IMR. The best subjective image quality for coronary vessels was obtained with IMR (proximal vessels: FBP, 2.6 ± 0.5; hybrid IR, 3.4 ± 0.5; IMR, 3.8 ± 0.4; distal vessels: FBP, 2.3 ± 0.5; hybrid IR. 3.1 ± 0.5; IMR, 3.7 ± 0.5). IMR also yielded the best visualization for cardiac systems, that is myocardium and heart valves.

CONCLUSION:

The novel knowledge-based IMR algorithm yields significantly improved CNR and better subjective image quality of coronary vessels and cardiac systems with reliable CT number measurements for cardiac CT imaging.

TRIAL REGISTRATION:

ClinicalTrials.gov NCT01896674.

KEYWORDS:

Cardiac CT; Coronary artery; Iterative model reconstruction; Low tube voltage; Multidetector CT

PMID:
24661824
DOI:
10.1016/j.jcct.2013.12.010
[Indexed for MEDLINE]
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