Abstract
Traditional filtered back projection (FBP) reconstruction methods have served the computed tomography (CT) community well for over 40 years. With the increased use of CT during the last decades, efforts to minimise patient exposure, while maintaining sufficient or improved image quality, have led to the development of model-based iterative reconstruction (MBIR) algorithms from several vendors. The usefulness of the advanced modeled iterative reconstruction (ADMIRE) (Siemens Healthineers) MBIR in abdominal CT is reviewed and its noise suppression and/or dose reduction possibilities explored. Quantitative and qualitative methods with phantom and human subjects were used. Assessment of the quality of phantom images will not always correlate positively with those of patient images, particularly at the higher strength of the ADMIRE algorithm. With few exceptions, ADMIRE Strength 3 typically allows for substantial noise reduction compared to FBP and hence to significant (≈30%) patient dose reductions. The size of the dose reductions depends on the diagnostic task.
Highlights
Modern computed tomography (CT) scanners are equipped with several dose reduction features such as tube current modulation, automatic tube voltage selection, filtration, dynamic shielding and postprocessing methods such as iterative reconstruction (IR)(1)
Noise reduction of approximately 10% per advanced modeled iterative reconstruction (ADMIRE) strength level was found to be significant when compared to filtered back projection (FBP)
The conclusion was that ADMIRE improved subjective and objective image quality when compared to FBP
Summary
Modern computed tomography (CT) scanners are equipped with several dose reduction features such as tube current modulation, automatic tube voltage selection, filtration, dynamic shielding and postprocessing methods such as iterative reconstruction (IR)(1). The faster realtime analytical reconstruction method filtered back projection (FBP), which has been the clinical standard for the past 40 years, has reached its limitation and does not allow for further dose reductions. The increasing use of CT in clinical practice and associated absorbed dose to the population have raised concerns about the adverse effects of ionising radiation. This has led to the introduction of several generations of vendor-specific IR algorithms between 2008 and 2015; their function and mechanism are based on the properties of the imaging system. The statistical/hybrid algorithms mainly reduce noise while the MBIR algorithms, in addition to their denoising properties, correct for image degrading effects by incorporating several geometric, optic and system models(1,2,4,5). The strengths and weaknesses of noise reduction strategies are discussed by Ehman et al(5) in their comprehensive overview and review of qualitative and quantitative tools used in evaluation of noise reduction techniques in abdominopelvic CT
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