Javier E Villanueva-Meyer1, David M Naeger2, Jesse L Courtier3, Michael D Hope4, Jack W Lambert3, John D MacKenzie3, Andrew S Phelps3. 1. Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, M-391, San Francisco, CA, 94143, USA. Javier.Villanueva-Meyer@ucsf.edu. 2. Thoracic Radiology Section, University of California San Francisco, San Francisco, CA, USA. 3. Pediatric Radiology Section, University of California San Francisco Benioff Children's Hospital, 1975 4th St C1758, San Francisco, CA, 94158, USA. 4. Thoracic Radiology Section, University of California San Francisco, Box 0628, 350 Parnassus Avenue, Room 307, San Francisco, CA, 94117, USA.
Abstract
PURPOSE: Computed tomography (CT) use in emergency departments represents a significant contribution to pediatric patients' exposure to ionizing radiation. Here, we evaluate whether ultralow-dose chest CT can be diagnostically adequate for other diagnoses and whether model-based iterative reconstruction (MBIR) can improve diagnostic adequacy compared to adaptive statistical iterative reconstruction (ASIR) at ultralow doses. METHODS: Twenty children underwent chest CTs: 10 standard-dose reconstructed with ASIR and 10 ultralow-dose reconstructed with ASIR and MBIR. Four radiologists assessed images for their adequacy to exclude five hypothetical diagnoses: foreign body, fracture, lung metastasis, pulmonary infection, and interstitial lung disease. Additionally, pairwise comparison for subjective image quality was used to compare ultralow-dose chest CT with ASIR and MBIR. Radiation dose and objective image noise measures were obtained. RESULTS: For exclusion of an airway foreign body, the adequacy of ultralow-dose CT was comparable to standard-dose (p = 0.6). For the remaining diagnoses, ultralow-dose CT was inferior to standard-dose (p = 0.03-<0.001). MBIR partially recovered the adequacy of ultralow-dose CT to exclude pulmonary infection (p = 0.017), but was suboptimal for the other diagnoses. Image noise was significantly lower with MBIR compared to ASIR in ultralow-dose CT (p < 0.001), although subjective preference showed only a slight advantage of MBIR (58 versus 42%). CONCLUSIONS: Ultralow-dose chest CT may be adequate for airway assessment, but suboptimal for the evaluation parenchymal lung disease. Although MBIR improves objective and subjective image quality, it does not completely restore the diagnostic adequacy of ultralow-dose CT when compared to standard-dose CT.
PURPOSE: Computed tomography (CT) use in emergency departments represents a significant contribution to pediatric patients' exposure to ionizing radiation. Here, we evaluate whether ultralow-dose chest CT can be diagnostically adequate for other diagnoses and whether model-based iterative reconstruction (MBIR) can improve diagnostic adequacy compared to adaptive statistical iterative reconstruction (ASIR) at ultralow doses. METHODS: Twenty children underwent chest CTs: 10 standard-dose reconstructed with ASIR and 10 ultralow-dose reconstructed with ASIR and MBIR. Four radiologists assessed images for their adequacy to exclude five hypothetical diagnoses: foreign body, fracture, lung metastasis, pulmonary infection, and interstitial lung disease. Additionally, pairwise comparison for subjective image quality was used to compare ultralow-dose chest CT with ASIR and MBIR. Radiation dose and objective image noise measures were obtained. RESULTS: For exclusion of an airway foreign body, the adequacy of ultralow-dose CT was comparable to standard-dose (p = 0.6). For the remaining diagnoses, ultralow-dose CT was inferior to standard-dose (p = 0.03-<0.001). MBIR partially recovered the adequacy of ultralow-dose CT to exclude pulmonary infection (p = 0.017), but was suboptimal for the other diagnoses. Image noise was significantly lower with MBIR compared to ASIR in ultralow-dose CT (p < 0.001), although subjective preference showed only a slight advantage of MBIR (58 versus 42%). CONCLUSIONS: Ultralow-dose chest CT may be adequate for airway assessment, but suboptimal for the evaluation parenchymal lung disease. Although MBIR improves objective and subjective image quality, it does not completely restore the diagnostic adequacy of ultralow-dose CT when compared to standard-dose CT.
Authors: Andrew S Phelps; David M Naeger; Jesse L Courtier; Jack W Lambert; Peter A Marcovici; Javier E Villanueva-Meyer; John D MacKenzie Journal: AJR Am J Roentgenol Date: 2015-01 Impact factor: 3.959
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