A E Mirro1, S L Brady2, R A Kaufman3. 1. From the Department of Biomedical Engineering (A.E.M.), Washington University, St. Louis, Missouri Department of Diagnostic Imaging (A.E.M. S.L.B., R.A.K.), St Jude Children's Research Hospital, Memphis, Tennessee. 2. Department of Diagnostic Imaging (A.E.M. S.L.B., R.A.K.), St Jude Children's Research Hospital, Memphis, Tennessee. samuel.brady@stjude.org. 3. Department of Diagnostic Imaging (A.E.M. S.L.B., R.A.K.), St Jude Children's Research Hospital, Memphis, Tennessee.
Abstract
BACKGROUND AND PURPOSE: A statistical iterative reconstruction algorithm provides an effective approach to reduce patient dose by compensating for increased image noise in CT due to reduced radiation output. However, after a point, the degree to which a statistical iterative algorithm is used for image reconstruction changes the image appearance. Our aim was to determine the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population while maintaining similar appearance and level of image noise in the reconstructed image. MATERIALS AND METHODS: Select head examinations (brain, orbits, sinus, maxilla, and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction were compared for image quality with the original filtered back-projection reconstructed protocols in a phantom by using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio, and spatial resolution. Dose-reduction estimates were based on CT dose index values. Patient volume CT dose index and image noise magnitude were assessed in 737 pre- and post-dose-reduced examinations. RESULTS: Image noise texture was acceptable for up to 60% adaptive statistical iterative reconstruction for the soft reconstruction kernel (at both 100 and 120 kV[peak]) and up to 40% adaptive statistical iterative reconstruction for the standard reconstruction kernel. Implementation of 40% and 60% adaptive statistical iterative reconstruction led to an average reduction in the volume CT dose index of 43% for brain, 41% for orbit, 30% for maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years of age, while maintaining an average noise magnitude difference of 0.1% (range, -3% to 5%), improving the contrast-to-noise ratio of low-contrast soft-tissue targets and the spatial resolution of high-contrast bony anatomy, compared with filtered back-projection. CONCLUSIONS: The methodology in this study demonstrates maximizing patient dose reduction and maintaining image quality by using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examinations.
BACKGROUND AND PURPOSE: A statistical iterative reconstruction algorithm provides an effective approach to reduce patient dose by compensating for increased image noise in CT due to reduced radiation output. However, after a point, the degree to which a statistical iterative algorithm is used for image reconstruction changes the image appearance. Our aim was to determine the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population while maintaining similar appearance and level of image noise in the reconstructed image. MATERIALS AND METHODS: Select head examinations (brain, orbits, sinus, maxilla, and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction were compared for image quality with the original filtered back-projection reconstructed protocols in a phantom by using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio, and spatial resolution. Dose-reduction estimates were based on CT dose index values. Patient volume CT dose index and image noise magnitude were assessed in 737 pre- and post-dose-reduced examinations. RESULTS: Image noise texture was acceptable for up to 60% adaptive statistical iterative reconstruction for the soft reconstruction kernel (at both 100 and 120 kV[peak]) and up to 40% adaptive statistical iterative reconstruction for the standard reconstruction kernel. Implementation of 40% and 60% adaptive statistical iterative reconstruction led to an average reduction in the volume CT dose index of 43% for brain, 41% for orbit, 30% for maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years of age, while maintaining an average noise magnitude difference of 0.1% (range, -3% to 5%), improving the contrast-to-noise ratio of low-contrast soft-tissue targets and the spatial resolution of high-contrast bony anatomy, compared with filtered back-projection. CONCLUSIONS: The methodology in this study demonstrates maximizing patient dose reduction and maintaining image quality by using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examinations.
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