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Radiology. 2006 Jun;239(3):768-76.

CT colonography: influence of 3D viewing and polyp candidate features on interpretation with computer-aided detection.

Author information

  • 1Department of Radiology, Stanford University Medical Center, James H. Clark Center, 318 Campus Dr, Room S324, Stanford, CA 94305-5450, and Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA. rshi@stanford.edu

Abstract

PURPOSE:

To retrospectively determine if three-dimensional (3D) viewing improves radiologists' accuracy in classifying true-positive (TP) and false-positive (FP) polyp candidates identified with computer-aided detection (CAD) and to determine candidate polyp features that are associated with classification accuracy, with known polyps serving as the reference standard.

MATERIALS AND METHODS:

Institutional review board approval and informed consent were obtained; this study was HIPAA compliant. Forty-seven computed tomographic (CT) colonography data sets were obtained in 26 men and 10 women (age range, 42-76 years). Four radiologists classified 705 polyp candidates (53 TP candidates, 652 FP candidates) identified with CAD; initially, only two-dimensional images were used, but these were later supplemented with 3D rendering. Another radiologist unblinded to colonoscopy findings characterized the features of each candidate, assessed colon distention and preparation, and defined the true nature of FP candidates. Receiver operating characteristic curves were used to compare readers' performance, and repeated-measures analysis of variance was used to test features that affect interpretation.

RESULTS:

Use of 3D viewing improved classification accuracy for three readers and increased the area under the receiver operating characteristic curve to 0.96-0.97 (P<.001). For TP candidates, maximum polyp width (P=.038), polyp height (P=.019), and preparation (P=.004) significantly affected accuracy. For FP candidates, colonic segment (P=.007), attenuation (P<.001), surface smoothness (P<.001), distention (P=.034), preparation (P<.001), and true nature of candidate lesions (P<.001) significantly affected accuracy.

CONCLUSION:

Use of 3D viewing increases reader accuracy in the classification of polyp candidates identified with CAD. Polyp size and examination quality are significantly associated with accuracy.

Copyright (c) RSNA, 2006.

PMID:
16714460
[PubMed - indexed for MEDLINE]
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