Region-based supine-prone correspondence for the reduction of false-positive CAD polyp candidates in CT colonography.
OBJECTIVE
Radiologists often compare the supine and prone data sets of a patient to confirm potential polyp findings in computed tomographic (CT) colonography (CTC). We developed a new automated method that uses region-based supine-prone correspondence for the reduction of false-positive (FP) polyp candidates in computer-aided detection (CAD) for CTC.


METHODS
Up to six anatomic landmarks are established by use of the extracted region of the colonic lumen. A region-growing scheme with distance calculations is used to divide the colonic lumen into overlapping segments that match in the supine and prone data sets. Polyp candidates detected by means of a CAD scheme are eliminated in colonic segments that have sufficient diagnostic quality and contain polyp candidates in only one of the data sets of a patient. The method was evaluated with 121 CTC cases, including 42 polyps of 5 mm or greater in 28 patients, obtained by use of single- and multidetector CT scanners with standard pre-colonoscopy cleansing.


RESULTS
Complete or partial correspondence was established in 71% of cases. Based on a leave-one-patient-out evaluation, application of the method reduced 19% of FP results reported by our CAD scheme at a 90.5% by-polyp detection sensitivity, without loss of any true-positive results. The resulting CAD scheme yielded 2.4 FP results per patient, on average, with the use of the correspondence method, whereas it yielded 3.0 FP results per patient without the use of the method.


CONCLUSIONS
The correspondence method is potentially useful for improving the specificity of CAD in CTC.
Näppi
Janne
J
Department of Radiology, The University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637, USA. jnappi@partners.org
Okamura
Akihiko
A
Frimmel
Hans
H
Dachman
Abraham
A
Yoshida
Hiroyuki
H
D003111:Colonic Polyps / Q000000981:diagnostic imaging*; D023881:Colonography, Computed Tomographic / Q000379:methods*; D005189:False Positive Reactions; D006801:Humans; D010363:Pattern Recognition, Automated; D016684:Prone Position / Q000502:physiology*; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D016683:Supine Position / Q000502:physiology*