Parametric color coding of digital subtraction angiography.
OBJECTIVE
Color has been shown to facilitate both visual search and recognition tasks. It was our purpose to examine the impact of a color-coding algorithm on the interpretation of 2D-DSA acquisitions by experienced and inexperienced observers.


METHODS
Twenty-six 2D-DSA acquisitions obtained as part of routine clinical care from subjects with a variety of cerebrovascular disease processes were selected from an internal data base so as to include a variety of disease states (aneurysms, AVMs, fistulas, stenosis, occlusions, dissections, and tumors). Three experienced and 3 less experienced observers were each shown the acquisitions on a prerelease version of a commercially available double-monitor workstation (XWP, Siemens Healthcare). Acquisitions were presented first as a subtracted image series and then as a single composite color-coded image of the entire acquisition. Observers were then asked a series of questions designed to assess the value of the color-coded images for the following purposes: 1) to enhance their ability to make a diagnosis, 2) to have confidence in their diagnosis, 3) to plan a treatment, and 4) to judge the effect of a treatment. The results were analyzed by using 1-sample Wilcoxon tests.


RESULTS
Color-coded images enhanced the ease of evaluating treatment success in >40% of cases (P < .0001). They also had a statistically significant impact on treatment planning, making planning easier in >20% of the cases (P = .0069). In >20% of the examples, color-coding made diagnosis and treatment planning easier for all readers (P < .0001). Color-coding also increased the confidence of diagnosis compared with the use of DSA alone (P = .056). The impact of this was greater for the naïve readers than for the expert readers.


CONCLUSIONS
At no additional cost in x-ray dose or contrast medium, color-coding of DSA enhanced the conspicuity of findings on DSA images. It was particularly useful in situations in which there was a complex flow pattern and in evaluation of pre- and posttreatment acquisitions. Its full potential remains to be defined.
Strother
C M
CM
Department of Radiology, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin 53792, USA. strother@wisc.edu
Bender
F
F
Deuerling-Zheng
Y
Y
Royalty
K
K
Pulfer
K A
KA
Baumgart
J
J
Zellerhoff
M
M
Aagaard-Kienitz
B
B
Niemann
D B
DB
Lindstrom
M L
ML
D000328:Adult; D000465:Algorithms; D015901:Angiography, Digital Subtraction / Q000379:methods*; D003124:Colorimetry / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity