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  • Title: CT radiation dose and image quality optimization using a porcine model.
    Author: Zarb F, McEntee MF, Rainford L.
    Journal: Radiol Technol; 2013; 85(2):127-36. PubMed ID: 24255137.
    Abstract:
    PURPOSE: To evaluate potential radiation dose savings and resultant image quality effects with regard to optimization of commonly performed computed tomography (CT) studies derived from imaging a porcine (pig) model. METHODS: Imaging protocols for 4 clinical CT suites were developed based on the lowest milliamperage and kilovoltage, the highest pitch that could be set from current imaging protocol parameters, or both. This occurred before significant changes in noise, contrast, and spatial resolution were measured objectively on images produced from a quality assurance CT phantom. The current and derived phantom protocols were then applied to scan a porcine model for head, abdomen, and chest CT studies. Further optimized protocols were developed based on the same methodology as in the phantom study. The optimization achieved with respect to radiation dose and image quality was evaluated following data collection of radiation dose recordings and image quality review. Relative visual grading analysis of image quality criteria adapted from the European guidelines on radiology quality criteria for CT were used for studies completed with both the phantom-based or porcine-derived imaging protocols. RESULTS: In 5 out of 16 experimental combinations, the current clinical protocol was maintained. In 2 instances, the phantom protocol reduced radiation dose by 19% to 38%. In the remaining 9 instances, the optimization based on the porcine model further reduced radiation dose by 17% to 38%. CONCLUSION: The porcine model closely reflects anatomical structures in humans, allowing the grading of anatomical criteria as part of image quality review without radiation risks to human subjects. This study demonstrates that using a porcine model to evaluate CT optimization resulted in more radiation dose reduction than when imaging protocols were tested solely on quality assurance phantoms.
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