Article ID Journal Published Year Pages File Type
504743 Computerized Medical Imaging and Graphics 2006 6 Pages PDF
Abstract

We aimed to compare the time efficiency of three visualization methods in CT colonography and to identify the colonic factors influencing the time for interpretation.Twenty CT colonographic examinations were prospectively analysed. Three reading methods were adopted: method 1, primary 2D analysis with the use of virtual endoscopy as problem solver, method 2, primary standard virtual endoscopy with semiautomatic navigation through the colon and use of 2D images as problem solver; method 3, primary virtual endoscopy with automatic navigation and the use of 2D images as problem solver.In method 1, time for 2D analysis ranged between 6 and 18 min (mean 12) for evaluation of both supine and prone decubitus with a synchronization method. In method 2, time for 3D manual navigation in supine plus prone ranged between 9 and 24 min (mean 17).In method 3, time for automated navigation ranged between 6 and 20 min (mean 12) for evaluation of both supine and prone decubitus. A statistically significant difference was found between time efficiency of methods 1 and 2 (p=0.009, t-test, unequal variances). Methods 2 and 3 showed a tendency to significant differences (p=0.054, t-test, unequal variances).Faecal or fluid residuals were reported as major drawbacks in 3D navigations, requiring constant correlation with 2D images; tortuous folds influenced mostly the 2D analysis; diverticula were reported as influencing factor in all three methods.No differences in sensitivity and specificity were observed between the three viewing methods.The 3D semiautomatic navigation method* tended to increase the time for interpretation in almost all cases. There is, in particular, greatest time efficiency for 2D analysis as compared with 3D manual analysis. Two-dimensional and automated 3D navigation reading have comparable time efficiencies in a routine clinical setting.

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Physical Sciences and Engineering Computer Science Computer Science Applications
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