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  • Title: Introduction of an effective method for the optimization of CT protocols using iterative reconstruction algorithms: comparison with patient data.
    Author: Kordolaimi SD, Saradeas I, Ploussi A, Pantos I, Argentos S, Efstathopoulos EP.
    Journal: AJR Am J Roentgenol; 2014 Oct; 203(4):W434-9. PubMed ID: 25247973.
    Abstract:
    OBJECTIVE: The purpose of this study is to introduce an efficient method for the optimization of iterative reconstruction CT protocols based on phantom image analysis and the comparison of obtained results with actual patient data. MATERIALS AND METHODS: We considered chest, abdomen, and pelvis CT examinations before the installation of an iterative reconstruction algorithm (iDose4) to define the exposure parameters used in clinical routine with filtered back projection (FBP). The body area of a CT phantom was subsequently scanned with various tube voltages and tube currents-exposure time products, and acquired data were reconstructed with FBP and different levels of iDose4. The contrast-to-noise ratio (CNR) for FBP with the original exposure parameters was calculated to define the minimum acceptable CNR value for each tube voltage. Then, an optimum tube current-exposure time products for each tube voltage and level of iterative reconstruction was estimated. We also compared findings derived by the phantom with real patient data by assessing dosimetric and image quality indexes from a patient cohort scanned with exposure parameters gradually adjusted during 1 year of adoption of iDose4. RESULTS: By use of the proposed phantom method, dose reduction up to 75% was achievable, whereas for an intermediate level of iteration (level 4), the dose reduction ranged between 50% and 60%, depending on the tube voltage. For comparison, with the gradual adjustment of exposure settings, the corresponding dose reduction for the same level of iteration was about 35%. CONCLUSION: The proposed method provides rapid and efficient optimization of CT protocols and could be used as the first step in the optimization process.
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