(Tuesday, 7/16/2019) 1:15 PM - 1:45 PM
Room: Exhibit Hall | Forum 9
Purpose: To develop and evaluate the performance of profile-based auto kV selection with respect to radiation dose and image quality on Revolution Apex (GE Healthcare, Waukesha, WI) (kV Assist 2.0) and compare to the performance of kV Assist currently on Revolution CT (GE Healthcare, Waukesha, WI) (kV Assist 1.0).
Methods: Five different sized anthropomorphic phantoms (water equivalent diameters [Dw]: 22.0, 24.8, 27.7, 31.2, and 33.6 cm) were used. A gated thoracic CT angiography protocol was used. Reference settings for kV Assist 1.0 were 120 kV, 20 noise index (NI), and 1.25mm slice thickness. Reference settings for kV Assist 2.0 were 100 kV, 27 NI, and 1.25mm slice thickness.Phantoms were scanned on each scanner at the reference kV/NI and the kV/NI determined by the kV Assist algorithms. Contrast-to-noise ratio (CNR) was calculated. A radiologist evaluated all image sets using 5-point Likert scales for overall image quality (3=Good dose/IQ trade-off, representing the best score on this scale) and noise texture (5=Excellent) and a 3-point Likert scale for diagnostic acceptability (3=Acceptable).
Results: kV values selected by kV Assist 2.0 were lower than kV Assist 1.0 for four of the five phantoms, resulting in maximum and average CTDIvol reductions of 40.3% and 14.4%. CNR improved for kV Assist 2.0 for four of the five phantoms, with maximum and average CNR increases of 18.2% and 6.5%. The average overall IQ, noise texture, and diagnostic acceptability scores were 3.2, 3.2, and 2.8 for kV Assist 1.0 and 3.0, 4.0, and 2.8 for kV Assist 2.0.
Conclusion: Profile-based kV Assist on Revolution Apex may allow lower kV selection, lower or similar radiation dose, and improved image quality compared to the previous generation of kV Assist currently on Revolution CT.
Keywords
Taxonomy
IM- CT: General (Most aspects)
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