Procedure for optimal implementation of automatic tube potential selection in pediatric CT to reduce radiation dose and improve workflow. Issue 2 (18th December 2020) - Browne, Jacinta E.; Bruesewitz, Michael R.; Thomas, Vrieze; Thomas, Kristen B.; Hull, Nathan C.; McCollough, Cynthia H.; Yu, Lifeng
Abstract: It is important to employ radiation dose reduction techniques in pediatric computed tomography (CT) to reduce potential risks of radiation‐induced malignancy. Automatic tube potential (kV) selection tools have been developed and become available on many CT scanners, which select the optimum kV based on the patient size and clinical task to improve the radiation dose efficiency. However, its use in pediatric CT has been mostly empirical, following manufacturer's default recommendation without solid demonstration for quality improvement. This study aimed to implement an automatic tube potential tool (CAREkV, Siemens Healthcare) into routine pediatric CT practice, using the "Plan‐Do‐Study‐Act" quality improvement process, in place of an existing kV/mAs technique chart. The design of this quality improvement project involved Plan‐Do‐Study‐Act stages. P lan and D o stages identified the criteria for optimal automatic kV selection; a range of phantoms representing typical pediatric groups were scanned on a dual‐source 128‐slice scanner using a fast‐pitch scanning mode. The identified CAREkV settings were implemented into the CT protocol and evaluated after a 6‐month period. In the S tudy stage, an objective evaluation of the image metrics and radiation dose for two similar patient cohorts using CAREkV and the technique‐chart, respectively, were compared. The kV selected, image quality and radiation dose determined by CAREkV were comparable to those obtained while using the technique‐chart. The CAREkV was successfully implemented into our pediatric abdominopelvic CT practice. By utilizing the " PDSA " process optimal image quality and radiation dose reduction were achieved with an automatic kV selection tool to improve CT workflow.