Fully automated three-dimensional detection of polyps in fecal-tagging CT colonography.
OBJECTIVE
The presence of opacified materials presents several technical challenges for automated detection of polyps in fecal-tagging computed tomography colonography (ftCTC), such as pseudo-enhancement and the distortion of the density, size, and shape of the observed lesions. We developed a fully automated computer-aided detection (CAD) scheme that addresses these issues in automated detection of polyps in ftCTC.


METHODS
Pseudo-enhancement was minimized by use of an adaptive density correction (ADC) method. The presence of tagging was minimized by use of an adaptive density mapping (ADM) method. We also developed a new method for automated extraction of the colonic wall within air-filled and tagged regions. The ADC and ADM parameters were optimized by use of an anthropomorphic phantom. The CAD scheme was evaluated with 32+32 cases from two types of clinical ftCTC databases. The cases in database I had full cathartic cleansing and 40 polyps > or =6 mm, and the cases in database II had reduced cathartic cleansing and 44 polyps > or =6 mm. The by-polyp detection performance of the CAD scheme was evaluated by use of a leave-one-patient-out method with five features, and the results were compared with those of a conventional CAD scheme by use of free-response receiver operating characteristic curves.


RESULTS
The CAD scheme detected 95% and 86% of the polyps > or =6 mm with 3.6 and 4.2 false positives per scan on average in databases I and II, respectively. For polyps > or =10 mm, the detection sensitivity was 94% in database I (with one missed hyperplastic polyp) and 100% in database II at the same false-positive rate. The detection sensitivity of the new CAD scheme was approximately 20% higher than that of the conventional CAD scheme.


CONCLUSIONS
The results show that the CAD scheme developed in this study resolves the technical challenges introduced by fecal tagging, is applicable to a variety of colon preparation regimens, and provides a performance superior to that of conventional CAD schemes.
Näppi
Janne
J
Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St., Suite 400C Boston, MA 02114, USA. jnappi@partners.org
Yoshida
Hiroyuki
H
D003111:Colonic Polyps / Q000000981:diagnostic imaging*; D023881:Colonography, Computed Tomographic / Q000379:methods*; D003936:Diagnosis, Computer-Assisted; D005189:False Positive Reactions; D005243:Feces; D006801:Humans; D021621:Imaging, Three-Dimensional; D019047:Phantoms, Imaging; D012372:ROC Curve; D012680:Sensitivity and Specificity