Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study
- Authors
- Choi, Se Young; Ahn, Seung H.; Choi, Jae D.; Kim, Jung H.; Lee, Byoung-Il; Kim, Jeong-In; Park, Sung Bin
- Issue Date
- Feb-2016
- Publisher
- BRITISH INST RADIOLOGY
- Citation
- BRITISH JOURNAL OF RADIOLOGY, v.89, no.1058
- Journal Title
- BRITISH JOURNAL OF RADIOLOGY
- Volume
- 89
- Number
- 1058
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/8649
- DOI
- 10.1259/bjr.20150527
- ISSN
- 0007-1285
1748-880X
- Abstract
- Objective: The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses. Methods: A 5x5x5 mm(3) uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80kV) and 4 current-time products (100, 70, 30 and 15mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5-7) and knowledge-based IMR (soft-tissue Levels 1-3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed. Results: The effective doses ranged from 0.095 to 2.621mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs. Conclusion: At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment. Advances in knowledge: Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients.
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