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Erschienen in:
01.06.2013 | Computed Tomography
Iterative reconstruction techniques for computed tomography part 2: initial results in dose reduction and image quality
Erschienen in: European Radiology | Ausgabe 6/2013
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Objectives
To present the results of a systematic literature search aimed at determining to what extent the radiation dose can be reduced with iterative reconstruction (IR) for cardiopulmonary and body imaging with computed tomography (CT) in the clinical setting and what the effects on image quality are with IR versus filtered back-projection (FBP) and to provide recommendations for future research on IR.
Methods
We searched Medline and Embase from January 2006 to January 2012 and included original research papers concerning IR for CT.
Results
The systematic search yielded 380 articles. Forty-nine relevant studies were included. These studies concerned: the chest(n = 26), abdomen(n = 16), both chest and abdomen(n = 1), head(n = 4), spine(n = 1), and no specific area (n = 1). IR reduced noise and artefacts, and it improved subjective and objective image quality compared to FBP at the same dose. Conversely, low-dose IR and normal-dose FBP showed similar noise, artefacts, and subjective and objective image quality. Reported dose reductions ranged from 23 to 76 % compared to locally used default FBP settings. However, IR has not yet been investigated for ultra-low-dose acquisitions with clinical diagnosis and accuracy as endpoints.
Conclusion
Benefits of IR include improved subjective and objective image quality as well as radiation dose reduction while preserving image quality. Future studies need to address the value of IR in ultra-low-dose CT with clinically relevant endpoints.
Key Points
• Iterative reconstruction improves image quality of CT images at equal acquisition parameters.
• IR preserves image quality compared to normal-dose filtered back-projection.
• The reduced radiation dose made possible by IR is advantageous for patients.
• IR has not yet been investigated with clinical diagnosis and accuracy as endpoints.