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Six iterative reconstruction algorithms in brain CT: a phantom study on image quality at different radiation dose levels
Authors:A L?ve  M-L Olsson  R Siemund  F St?lhammar  I M Bj?rkman-Burtscher  M S?derberg
Institution:1.Department of Neuroradiology, Skåne University Hospital, Lund University, Lund, Sweden;2.Medical Radiation Physics Malmö, Skåne University Hospital, Lund University, Lund, Sweden;3.Lund University Bioimaging Centre, Lund University, Lund, Sweden
Abstract:

Objective:

To evaluate the image quality produced by six different iterative reconstruction (IR) algorithms in four CT systems in the setting of brain CT, using different radiation dose levels and iterative image optimisation levels.

Methods:

An image quality phantom, supplied with a bone mimicking annulus, was examined using four CT systems from different vendors and four radiation dose levels. Acquisitions were reconstructed using conventional filtered back-projection (FBP), three levels of statistical IR and, when available, a model-based IR algorithm. The evaluated image quality parameters were CT numbers, uniformity, noise, noise-power spectra, low-contrast resolution and spatial resolution.

Results:

Compared with FBP, noise reduction was achieved by all six IR algorithms at all radiation dose levels, with further improvement seen at higher IR levels. Noise-power spectra revealed changes in noise distribution relative to the FBP for most statistical IR algorithms, especially the two model-based IR algorithms. Compared with FBP, variable degrees of improvements were seen in both objective and subjective low-contrast resolutions for all IR algorithms. Spatial resolution was improved with both model-based IR algorithms and one of the statistical IR algorithms.

Conclusion:

The four statistical IR algorithms evaluated in the study all improved the general image quality compared with FBP, with improvement seen for most or all evaluated quality criteria. Further improvement was achieved with one of the model-based IR algorithms.

Advances in knowledge:

The six evaluated IR algorithms all improve the image quality in brain CT but show different strengths and weaknesses.Iterative reconstruction (IR) algorithms are one of the most recent advances in CT. Since the introduction of the first IR algorithm in 2008 1], multiple clinical studies have shown the potential of such algorithms to improve the image quality and allow for the reduction of radiation dose while maintaining diagnostic acceptability 27].Although all IR algorithms perform iterative image optimisation at some point in the CT image generation process, there are considerable technical differences between the available IR solutions. Furthermore, some vendors even offer more than one type of IR algorithm in their product range. Although detailed mechanisms of the current algorithms remain undisclosed, they can be classified into two basic categories 8,9] (
AlgorithmAcronymVendor
Statistical iterative optimisation
 ASIRAdaptive Statistical Iterative ReconstructionGE Healthcare, Milwaukee, MI
 iDOSE4Product name, not acronymPhilips Medical Systems, Best, Netherlands
 SAFIRESinogram Affirmed Iterative ReconstructionSiemens Healthcare, Forchheim, Germany
 AIDR 3DAdaptive Iterative Dose Reduction 3DToshiba Medical Systems, Tokyo, Japan
Model-based iterative optimisation
 VeoProduct name, not acronymGE Healthcare
 IMRIterative Model ReconstructionPhilips Medical Systems
Open in a separate windowWith a few exceptions 10,11], studies on IR from the literature have compared IR algorithms with filtered back-projection (FBP) reconstruction from the same vendor. As the IR algorithms can be expected to have different strengths and weaknesses, side-by-side assessment of their performance should be of interest. Such evaluation is best carried out in a phantom under standardised conditions.The purpose of this phantom study was to objectively and subjectively evaluate the image quality produced by six different IR algorithms in four CT systems from different vendors, using a variety of radiation dose levels and iterative image optimisation levels. The study was designed to simulate the demanding conditions of brain CT, with emphasis on noise and low-contrast resolution.
Keywords:
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