(Sunday, 7/29/2018) 3:00 PM - 3:30 PM
Room: Exhibit Hall | Forum 8
Purpose: The purpose of this study was to compare pediatric body CT doses from CAREkV and our institution’s weight-based manual techniques.
Methods: Using Radimetrics, 289 pediatric body CT examinations (abd/pel and chest) performed on Siemens Definition (with CAREkV) and 474 performed on Siemens Sensation (manual kV selection) , were collected for analysis. Along with patients CTDIvol, water Equivalent diameter, effective diameter, kVp, QR mAs and average effective mAs values were collected for all examinations. To investigate differences between CARE kV and manual kV selection, 37 patients, 17 abd/pel and 20 chest, performed on Definition were selected and their ED used to choose corresponding patients with similar ED performed on Sensation scanners. Differences in terms of kV, QR mAs, and average mAs were studied.
Results: As expected using CAREkV reduced CTDIvol by more than 40% as compared to using manual technique. Out of 74 selected studies (37 from each scanner with very similar sizes); in 50% of the studied cases, CAREkV selected a different kV than our weight-based technique. From these 50%, CAREkV selected a higher kV in 65% of the cases as compared to manual technique. For all studied patients scanned on Sensation scanners, the average effective mAs was larger as compared to the Quality Reference mAs. Only 20% of the patients scanned on the Definition scanners had higher average mAs values as compared to their Quality Reference mAs.
Conclusion: The increased CTDIvol for patients scanned on Sensation scanners appears to be mostly due to the smaller patient size reference, rather than the selection of a higher kV. Sensation series have two patient size references (25 and 70 kg), whereas Definition series have a single reference. Almost 50% of the patients scanned on Sensation weighted less than 25 kg, however, their average effective mAs was larger than their QR mAs.
Funding Support, Disclosures, and Conflict of Interest: Michael McNitt-Gray, Ph.D Departmental master research agreement, Siemens Health
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