title: Context-specific method for detection of soft-tissue lesions in non-cathartic low-dose dual-energy CT colonography.
abstract: In computed tomographic colonography (CTC), orally administered fecal-tagging agents can be used to indicate residual feces and fluid that could otherwise hide or imitate lesions on CTC images of the colon. Although the use of fecal tagging improves the detection accuracy of CTC, it can introduce image artifacts that may cause lesions that are covered by fecal tagging to have a different visual appearance than those not covered by fecal tagging. This can distort the values of image-based computational features, thereby reducing the accuracy of computer-aided detection (CADe). We developed a context-specific method that performs the detection of lesions separately on lumen regions covered by air and on those covered by fecal tagging, thereby facilitating the optimization of detection parameters separately for these regions and their detected lesion candidates to improve the detection accuracy of CADe. For pilot evaluation, the method was integrated into a dual-energy CADe (DE-CADe) scheme and evaluated by use of leave-one-patient-out evaluation on 66 clinical non-cathartic low-dose dual-energy CTC (DE-CTC) cases that were acquired at a low effective radiation dose and reconstructed by use of iterative image reconstruction. There were 22 colonoscopy-confirmed lesions ≥6 mm in size in 21 patients. The DE-CADe scheme detected 96% of the lesions at a median of 6 FP detections per patient. These preliminary results indicate that the use of context-specific detection can yield high detection accuracy of CADe in non-cathartic low-dose DE-CTC examinations.
authors.affiliation: 3D Imaging Research, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon Street, Suite 400C, Boston, MA 02114, USA.
authors.forename: Janne J
authors.initials: JJ
authors.lastname: Näppi
authors.affiliation: Institute for Cancer Research and Treatment, Strada Provinciale 142, IT-10060 Candiolo, Turin, Italy.
authors.forename: Daniele
authors.initials: D
authors.lastname: Regge
authors.affiliation: 3D Imaging Research, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon Street, Suite 400C, Boston, MA 02114, USA.
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Yoshida
keywords: Computer-aided detection; dual-energy CT; false-positive reduction; noncathartic preparation; polyp detection; virtual colonoscopy