title: Green tagging in displaying color Doppler aliasing: a comparison to standard color mapping in renal artery stenosis.
abstract: To quantitatively assess the contrast-to-noise ratio (CNR) of green tagging and standard color flow images in displaying fast flow velocity, we retrospectively reviewed 20 cases of hemodynamically significant renal artery stenosis (RAS) detected by renal color Doppler ultrasound and confirmed with digital subtraction angiography. At the site of RAS, blood flow with high velocity that appeared as aliasing on color flow images was computationally analyzed with both green tagging and standard color mapping. To assess the difference in the CNR between normal background flow and the aliased signal as a function of visualizing aliasing between the two color mappings, we used GetColorpixels (Chongqing Medical University, Chongqing, China) to count the values in the color channels after segmenting color pixels from gray-scale pixels. We then calculated the CNR in each color channel-red, green, and blue (RGB)--in the aliasing region on green tagging and standard color mapping. The CNRs in the red, green and blue channels were 0.35 ± 0.44, 1.11 ± 0.41 and 0.51 ± 0.19, respectively, on standard color mapping, and 0.97 ± 0.80, 4.01 ± 1.36 and 0.64 ± 0.29, respectively, on green tagging. We used a single-factor analysis of variance and two-tailed t-test to assess the difference in CNR in each color channel between the two color mappings at the site of RAS. With these comparisons, there was no significant difference in the CNR in the red or blue channel between green tagging and standard color mapping (p > 0.05). However, there was a statistically significant difference in the CNR in the green channel between the two color mappings (p = 0.00019). Furthermore, the CNR measured in the green channel on the green tagging image was significantly higher than the CNRs in all other color channels on both color mapping images (p = 0.000). Hence, we conclude that green tagging has significantly higher visibility as a function of high-velocity flow than standard color mapping. The use of green tagging may improve the ability to detect RAS with color Doppler ultrasound.
authors.affiliation: Department of Radiology, New York-Presbyterian Hospital, Weill Cornell Medical College, New York, New York, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Gao
authors.forename: Kevin
authors.initials: K
authors.lastname: Mennitt
authors.forename: Lily
authors.initials: L
authors.lastname: Belfi
authors.forename: Yuan-Yi
authors.initials: YY
authors.lastname: Zheng
authors.forename: Zong
authors.initials: Z
authors.lastname: Chen
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Rubin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003116:Color; D003124:Colorimetry / Q000379:methods; D003196:Computer Graphics; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D012078:Renal Artery Obstruction / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018615:Ultrasonography, Doppler, Color / Q000379:methods*; D014584:User-Computer Interface
keywords: Color Doppler ultrasound; Contrast-to-noise ratio; Green tagging; Renal artery stenosis