Padmavathi Sundaram | Search PubMed

PubMed2006

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

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.

Adult↗

PubMed2003

CT colonography: does improved z resolution help computer-aided polyp detection?

Multislice helical CT offers several retrospective choices of longitudinal (z) resolution at a given detector collimation setting. We sought to determine the effect of z resolution on the performance of a computer-aided colonic polyp detector, since a human reader and a computer-aided polyp detector may have optimal performances at different z resolutions. We ran a computer-aided polyp detection algorithm on phantom data sets as well as data obtained from a single patient. All data were reconstructed at various slice thicknesses ranging from 1.25 to 10 mm. We studied the performance of the detector at various ranges of polyp sizes using free-response receiver-operating characteristic analyses. We also studied contrast-to-noise ratios (CNR) as a function of slice thickness and polyp size. For the phantom data, reducing the slice thickness from 5 to 1.25 mm improves sensitivity from 84.5% to 98.3% (all polyps), from 61.4% to 95.5% (polyps in the range [0, 5) mm) and from 97.7% to 100% (polyps in the range [5, 10) mm) at a false positive rate of 20 per data set. For polyps larger than 10 mm, there is no significant improvement in detection sensitivity when slice thickness is reduced. CNRs showed expected behavior with slice thickness and polyp size, but in all cases remained high (> 4). The results for the patient data followed similar patterns to that of the phantom case. Thus we conclude that for this detector, the optimal slice thickness is dependent upon the size of the smallest polyps to be detected. For detection of polyps 10 mm and larger, reconstruction of 5 mm sections may be sufficient. Further study is required to generalize these results to a broader population of patients scanned on different scanners.

Colon↗