QUANTITATIVE CHARACTERIZATION OF COLOR DOPPLER IMAGES - REPRODUCIBILITY, ACCURACY, AND LIMITATIONS

Citation
S. Delorme et al., QUANTITATIVE CHARACTERIZATION OF COLOR DOPPLER IMAGES - REPRODUCIBILITY, ACCURACY, AND LIMITATIONS, Journal of clinical ultrasound, 23(9), 1995, pp. 537-550
Citations number
25
Categorie Soggetti
Radiology,Nuclear Medicine & Medical Imaging",Acoustics
ISSN journal
00912751
Volume
23
Issue
9
Year of publication
1995
Pages
537 - 550
Database
ISI
SICI code
0091-2751(1995)23:9<537:QCOCDI>2.0.ZU;2-3
Abstract
A computer-based quantitative analysis for color Doppler images of com plex vascular formations is presented. The red-green-blue-signal from an Acuson XP10 is frame-grabbed and digitized. By matching each image pixel with the color bar, color pixels are identified and assigned to the corresponding flow velocity (color value). Data analysis consists of delineation of a region of interest and calculation of the relative number of color pixels in this region (color pixel density) as well a s the mean color value. The mean color value was compared to flow velo cities in a flow phantom. The thyroid and carotid artery in a voluntee r were repeatedly examined by a single examiner to assess intra-observ er variability. The thyroids in five healthy controls were examined by three experienced physicians to assess the extent of inter-observer v ariability and observer bias. The correlation between the mean color v alue and flow velocity ranged from 0.94 to 0.96 for a range of velocit ies determined by pulse repetition frequency. The average deviation of the mean color value from the flow velocity was 22% to 41%, depending on the selected pulse repetition frequency (range of deviations, - 46 % to + 66%). Flow velocity was underestimated with inadequately low pu lse repetition frequency, or inadequately high reject threshold. An ov erestimation occurred with inadequately high pulse repetition frequenc y. The highest intra-observer variability was 22% (relative standard d eviation) for the color pixel density, and 9.1% for the mean color val ue. The inter-observer variation was approximately 30% for the color p ixel density, and 20% for the mean color value. In conclusion, compute r assisted image analysis permits an objective description of color Do ppler images. However, the user must be aware that image acquisition u nder in vivo conditions as well as physical and instrumental factors m ay considerably influence the results. (C) 1995 John Wiley & Sons, Inc .