title: Polyp size measurement at CT colonography: what do we know and what do we need to know?
abstract: Polyp size is a critical biomarker for clinical management. Larger polyps have a greater likelihood of being or of becoming an adenocarcinoma. To balance the referral rate for polypectomy against the risk of leaving potential cancers in situ, sizes of 6 and 10 mm are increasingly being discussed as critical thresholds for clinical decision making (immediate polypectomy versus polyp surveillance) and have been incorporated into the consensus CT Colonography Reporting and Data System (C-RADS). Polyp size measurement at optical colonoscopy, pathologic examination, and computed tomographic (CT) colonography has been studied extensively but the reported precision, accuracy, and relative sizes have been highly variable. Sizes measured at CT colonography tend to lie between those measured at optical colonoscopy and pathologic evaluation. The size measurements are subject to a variety of sources of error associated with image acquisition, display, and interpretation, such as partial volume averaging, two- versus three-dimensional displays, and observer variability. This review summarizes current best practices for polyp size measurement, describes the role of automated size measurement software, discusses how to manage the measurement uncertainties, and identifies areas requiring further research.
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bldg 10, Room 1C368X, MSC 1182, Bethesda, MD 20892-1182, USA. rms@nih.gov
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Summers
mesh_terms: D003111:Colonic Polyps / Q000000981:diagnostic imaging* / Q000473:pathology; D023881:Colonography, Computed Tomographic; D003113:Colonoscopy; D015179:Colorectal Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D006801:Humans; D021621:Imaging, Three-Dimensional; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results