J Korean Soc Radiol.  2016 May;74(5):291-298. 10.3348/jksr.2016.74.5.291.

Coronary Stent on Coronary CT Angiography: Assessment with Model-Based Iterative Reconstruction Technique

• Lee E
• Kim YK
• Chun EJ
• Choi SI

• KMID: 2164824
• DOI: http://doi.org/10.3348/jksr.2016.74.5.291

Abstract

PURPOSE
To assess the performance of model-based iterative reconstruction (MBIR) technique for evaluation of coronary artery stents on coronary CT angiography (CCTA).
MATERIALS AND METHODS
Twenty-two patients with coronary stent implantation who underwent CCTA were retrospectively enrolled for comparison of image quality between filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR) and MBIR. In each data set, image noise was measured as the standard deviation of the measured attenuation units within circular regions of interest in the ascending aorta (AA) and left main coronary artery (LM). To objectively assess the noise and blooming artifacts in coronary stent, we additionally measured the standard deviation of the measured attenuation and intra-luminal stent diameters of total 35 stents with dedicated software.
RESULTS
All image noise measured in the AA (all p < 0.001), LM (p < 0.001, p = 0.001) and coronary stent (all p < 0.001) were significantly lower with MBIR in comparison to those with FBP or ASIR. Intraluminal stent diameter was significantly higher with MBIR, as compared with ASIR or FBP (p < 0.001, p = 0.001).
CONCLUSION
MBIR can reduce image noise and blooming artifact from the stent, leading to better in-stent assessment in patients with coronary artery stent.

MeSH Terms

Angiography*
Aorta
Artifacts
Coronary Vessels
Dataset
Humans
Image Processing, Computer-Assisted
Noise
Retrospective Studies
Stents*

Figure

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  Fig. 1 Image noise measured in the ascending aorta is significantly lower by MBIR, as compared to ASIR and FBP (all p < 0.001). AA = ascending aorta, ASIR = adaptive statistical iterative reconstruction, FBP = filtered back projection, HU = Hounsfield units, MBIR = model-based iterative reconstruction

• 

  Fig. 2 Image noise measured in the left main coronary artery is significantly lower by MBIR, as compared to ASIR and FBP (p < 0.001, p = 0.001). ASIR = adaptive statistical iterative reconstruction, FBP = filtered back projection, HU = Hounsfield units, LM = left main coronary artery, MBIR = model-based iterative reconstruction

• 

  Fig. 3 Straight view of curved MPR images with FBP (A), ASIR (B), and MBIR (C) technique. Curved MPR images with FBP (D), ASIR (E), and MBIR (F) technique. Note the reduction of noise and blooming artifact in coronary stent is better on images with MBIR (C, F) than those with ASIR (B, E) and FBP (A, D). ASIR = adaptive statistical iterative reconstruction, FBP = filtered back projection, MBIR = model-based iterative reconstruction, MPR = multi-planar reconstruction

• 

  Fig. 4 Image noise measured in the stent is significantly lower by MBIR, as compared to ASIR and FBP (all p < 0.001). ASIR = adaptive statistical iterative reconstruction, FBP = filtered back projection, HU = Hounsfield units, MBIR = model-based iterative reconstruction

• 

  Fig. 5 In-stent diameters are significantly higher by MBIR, as compared to ASIR and FBP, which means that the reduction of blooming artifact is better by MBIR (p < 0.001, p = 0.001) than ASIR and FBP. ASIR = adaptive statistical iterative reconstruction, FBP = filtered back projection, HU = Hounsfield units, MBIR = model-based iterative reconstruction

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