Yonsei Med J.  2015 Jan;56(1):253-261. 10.3349/ymj.2015.56.1.253.

Quantitative Analysis of the Effect of Iterative Reconstruction Using a Phantom: Determining the Appropriate Blending Percentage

• Kim HG
• Chung YE
• Lee YH
• Choi JY
• Park MS
• Kim MJ
• Kim KW

• KMID: 2352814
• DOI: http://doi.org/10.3349/ymj.2015.56.1.253

Abstract

PURPOSE
To investigate the optimal blending percentage of adaptive statistical iterative reconstruction (ASIR) in a reduced radiation dose while preserving a degree of image quality and texture that is similar to that of standard-dose computed tomography (CT).
MATERIALS AND METHODS
The CT performance phantom was scanned with standard and dose reduction protocols including reduced mAs or kVp. Image quality parameters including noise, spatial, and low-contrast resolution, as well as image texture, were quantitatively evaluated after applying various blending percentages of ASIR. The optimal blending percentage of ASIR that preserved image quality and texture compared to standard dose CT was investigated in each radiation dose reduction protocol.
RESULTS
As the percentage of ASIR increased, noise and spatial-resolution decreased, whereas low-contrast resolution increased. In the texture analysis, an increasing percentage of ASIR resulted in an increase of angular second moment, inverse difference moment, and correlation and in a decrease of contrast and entropy. The 20% and 40% dose reduction protocols with 20% and 40% ASIR blending, respectively, resulted in an optimal quality of images with preservation of the image texture.
CONCLUSION
Blending the 40% ASIR to the 40% reduced tube-current product can maximize radiation dose reduction and preserve adequate image quality and texture.

Keyword

CT Image quality; iterative reconstruction; filtered back projection; radiation dose reduction; texture analysis

MeSH Terms

*Algorithms
Artifacts
Contrast Media/diagnostic use
Humans
*Phantoms, Imaging
Radiation Dosage
Radiographic Image Interpretation, Computer-Assisted/*methods
Signal-To-Noise Ratio
Tomography, X-Ray Computed
Contrast Media

Figure

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  Fig. 1 American Association of Physicists in Medicine (AAPM) CT performance phantom. Selected blocks from the AAPM phantom were used to quantify noise (A), spatial resolution (B), low-contrast resolution, and texture (C).

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  Fig. 2 Schematic graph of a HU graph drawn by the linear HU difference between five holes of the same size. HU, Hounsfield unit.

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  Fig. 3 Noise (standard deviation of CT numbers) of different acquisition protocols according to increasing ASIR percentage. The reference line shows the acceptable noise value of 7. If the value is <7, the quality of image is considered acceptable. ASIR, adaptive statistical iterative reconstruction.

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  Fig. 4 Average HU differences between the peaks and valleys are shown according to increasing ASIR percentage. A difference of at least 30 HU needed to be met for optimal quality in terms of spatial resolution (A). Two graphs of the 150-mAs acquisition protocol with ASIR 100% (B) and 40% (C) are shown. HU, Hounsfield unit; ASIR, adaptive statistical iterative reconstruction.

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  Fig. 5 Contrast to noise ratio that was obtained to quantify low-contrast resolution according to an increase in the percentage of ASIR. The reference line indicates a value of 1.63, which was defined as the lowest acceptable limit. ASIR, adaptive statistical iterative reconstruction.

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  Fig. 6 Texture analysis graphs showing five different texture features according to an increase in the percentage of ASIR: angular second moment (A), inverse different moment (B), correlation (C), contrast (D), and entropy (E). The reference line of each graph shows the value of standard images.

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