Abstract
Purpose: To evaluate the effect of automated tube voltage selection (ATVS) on radiation dose at computed tomography (CT) worldwide encompassing all body regions and types of CT examinations. Materials and Methods: No patient information was accessed;therefore, institutional review board approval was not sought. Data from 86 centers across the world were analyzed. All CT interactions were automatically collected and transmitted to the CT vendor during two 6-week periods immediately before and 2 weeks after implementation of ATVS. A total of 164 323 unique CT studies were analyzed. Studies were categorized by body region and type of examination. Tube voltage and volume CT dose index (CTDIvol) were compared between examinations performed with ATVS and those performed before ATVS implementation. Descriptive statistical methods and multilevel linear regression models were used for analysis. Results: Across all types of CT examinations and body regions, CTDIvol was 14.7% lower in examinations performed with ATVS (n = 30 313) than in those performed before ATVS implementation (n = 79 275). Relative reductions in mean CTDIvol were most notable for temporal bone CT (-56.1%), peripheral runoff CT angiography (-48.6%), CT of the paranasal sinus (-39.6%), cerebral or carotid CT angiography (-36.4%), coronary CT angiography (-25.1%), and head CT (-23.9%). An increase in mean CTDIvol was observed for renal stone protocols (26.2%) and thoracic or lumbar spine examinations (6.6%). In the multilevel model with fixed effects ATVS and examination type, and the interaction of these variables and the random effect country, a significant influence on CTDIvol for all fixed efects was revealed (ATVS, P = .0031;examination type, P < .0001;interaction term, P < .0001). Conclusion: ATVS significantly reduces radiation dose across most, but not all, body regions and types of CT examinations. (C) RSNA, 2015
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 0033-8419 |
Sprache: | Englisch |
Dokumenten ID: | 45914 |
Datum der Veröffentlichung auf Open Access LMU: | 27. Apr. 2018, 08:09 |
Letzte Änderungen: | 04. Nov. 2020, 13:22 |